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Sample records for advance prediction computer

  1. Advanced Computational Modeling Approaches for Shock Response Prediction

    Science.gov (United States)

    Derkevorkian, Armen; Kolaini, Ali R.; Peterson, Lee

    2015-01-01

    Motivation: (1) The activation of pyroshock devices such as explosives, separation nuts, pin-pullers, etc. produces high frequency transient structural response, typically from few tens of Hz to several hundreds of kHz. (2) Lack of reliable analytical tools makes the prediction of appropriate design and qualification test levels a challenge. (3) In the past few decades, several attempts have been made to develop methodologies that predict the structural responses to shock environments. (4) Currently, there is no validated approach that is viable to predict shock environments overt the full frequency range (i.e., 100 Hz to 10 kHz). Scope: (1) Model, analyze, and interpret space structural systems with complex interfaces and discontinuities, subjected to shock loads. (2) Assess the viability of a suite of numerical tools to simulate transient, non-linear solid mechanics and structural dynamics problems, such as shock wave propagation.

  2. Seismic Response Prediction of Buildings with Base Isolation Using Advanced Soft Computing Approaches

    Directory of Open Access Journals (Sweden)

    Mosbeh R. Kaloop

    2017-01-01

    Full Text Available Modeling response of structures under seismic loads is an important factor in Civil Engineering as it crucially affects the design and management of structures, especially for the high-risk areas. In this study, novel applications of advanced soft computing techniques are utilized for predicting the behavior of centrically braced frame (CBF buildings with lead-rubber bearing (LRB isolation system under ground motion effects. These techniques include least square support vector machine (LSSVM, wavelet neural networks (WNN, and adaptive neurofuzzy inference system (ANFIS along with wavelet denoising. The simulation of a 2D frame model and eight ground motions are considered in this study to evaluate the prediction models. The comparison results indicate that the least square support vector machine is superior to other techniques in estimating the behavior of smart structures.

  3. On the Predictability of Computer simulations: Advances in Verification and Validation

    KAUST Repository

    Prudhomme, Serge

    2014-01-06

    We will present recent advances on the topics of Verification and Validation in order to assess the reliability and predictability of computer simulations. The first part of the talk will focus on goal-oriented error estimation for nonlinear boundary-value problems and nonlinear quantities of interest, in which case the error representation consists of two contributions: 1) a first contribution, involving the residual and the solution of the linearized adjoint problem, which quantifies the discretization or modeling error; and 2) a second contribution, combining higher-order terms that describe the linearization error. The linearization error contribution is in general neglected with respect to the discretization or modeling error. However, when nonlinear effects are significant, it is unclear whether ignoring linearization effects may produce poor convergence of the adaptive process. The objective will be to show how both contributions can be estimated and employed in an adaptive scheme that simultaneously controls the two errors in a balanced manner. In the second part of the talk, we will present novel approach for calibration of model parameters. The proposed inverse problem not only involves the minimization of the misfit between experimental observables and their theoretical estimates, but also an objective function that takes into account some design goals on specific design scenarios. The method can be viewed as a regularization approach of the inverse problem, one, however, that best respects some design goals for which mathematical models are intended. The inverse problem is solved by a Bayesian method to account for uncertainties in the data. We will show that it shares the same structure as the deterministic problem that one would obtain by multi-objective optimization theory. The method is illustrated on an example of heat transfer in a two-dimensional fin. The proposed approach has the main benefit that it increases the confidence in predictive

  4. Development of Computational Capabilities to Predict the Corrosion Wastage of Boiler Tubes in Advanced Combustion Systems

    Energy Technology Data Exchange (ETDEWEB)

    Kung, Steven; Rapp, Robert

    2014-08-31

    coal-fired boilers resulting from the coexistence of sulfur and chlorine in the fuel. A new corrosion mechanism, i.e., “Active Sulfidation Corrosion Mechanism,” has been proposed to account for the accelerated corrosion wastage observed on the furnace walls of utility boilers burning coals containing sulfur and chlorine. In addition, a second corrosion mechanism, i.e., “Active Sulfide-to-Oxide Corrosion Mechanism,” has been identified to account for the rapid corrosion attack on superheaters and reheaters. Both of the newly discovered corrosion mechanisms involve the formation of iron chloride (FeCl2) vapor from iron sulfide (FeS) and HCl, followed by the decomposition of FeCl2 via self-sustaining cycling reactions. For higher alloys containing sufficient chromium, the attack on superheaters and reheaters is dominated by Hot Corrosion in the presence of a fused salt. Furthermore, two stages of the hot corrosion mechanism have been identified and characterized in detail. The initiation of hot corrosion attack induced by molten sulfate leads to Stage 1 “acidic” fluxing and re-precipitation of the protective scale formed initially on the deposit-covered alloy surfaces. Once the protective scale is penetrated, Stage 2 Hot Corrosion is initiated, which is dominated by “basic” fluxing and re-precipitation of the scale in the fused salt. Based on the extensive corrosion information generated from this project, corrosion modeling was performed using non-linear regression analysis. As a result of the modeling efforts, two predictive equations have been formulated, one for furnace walls and the other for superheaters and reheaters. These first-of-the-kind equations can be used to estimate the corrosion rates of boiler tubes based on coal chemistry, alloy compositions, and boiler operating conditions for advanced boiler systems.

  5. Advances in Computer Entertainment.

    NARCIS (Netherlands)

    Nijholt, Antinus; Romão, T.; Reidsma, Dennis; Unknown, [Unknown

    2012-01-01

    These are the proceedings of the 9th International Conference on Advances in Computer Entertainment ACE 2012). ACE has become the leading scientific forum for dissemination of cutting-edge research results in the area of entertainment computing. Interactive entertainment is one of the most vibrant

  6. Advances in Computer Entertainment.

    OpenAIRE

    Nijholt, Antinus; Romão, T.; Reidsma, Dennis; Unknown, [Unknown

    2012-01-01

    These are the proceedings of the 9th International Conference on Advances in Computer Entertainment ACE 2012). ACE has become the leading scientific forum for dissemination of cutting-edge research results in the area of entertainment computing. Interactive entertainment is one of the most vibrant areas of interest in modern society and is amongst the fastest growing industries in the world. ACE 2012 will bring together leading researchers and practitioners from academia and industry to prese...

  7. Surgical outcome prediction in patients with advanced ovarian cancer using computed tomography scans and intraoperative findings

    Directory of Open Access Journals (Sweden)

    Ha-Jeong Kim

    2014-09-01

    Conclusion: The combination of omental extension to the stomach or spleen and involvement of inguinal or pelvic lymph nodes in preoperative CT scans is considered predictive of suboptimal cytoreduction. These patients may be more appropriately treated with neoadjuvant chemotherapy followed by surgical cytoreduction.

  8. Advanced computers and simulation

    International Nuclear Information System (INIS)

    Ryne, R.D.

    1993-01-01

    Accelerator physicists today have access to computers that are far more powerful than those available just 10 years ago. In the early 1980's, desktop workstations performed less one million floating point operations per second (Mflops), and the realized performance of vector supercomputers was at best a few hundred Mflops. Today vector processing is available on the desktop, providing researchers with performance approaching 100 Mflops at a price that is measured in thousands of dollars. Furthermore, advances in Massively Parallel Processors (MPP) have made performance of over 10 gigaflops a reality, and around mid-decade MPPs are expected to be capable of teraflops performance. Along with advances in MPP hardware, researchers have also made significant progress in developing algorithms and software for MPPS. These changes have had, and will continue to have, a significant impact on the work of computational accelerator physicists. Now, instead of running particle simulations with just a few thousand particles, we can perform desktop simulations with tens of thousands of simulation particles, and calculations with well over 1 million particles are being performed on MPPs. In the area of computational electromagnetics, simulations that used to be performed only on vector supercomputers now run in several hours on desktop workstations, and researchers are hoping to perform simulations with over one billion mesh points on future MPPs. In this paper we will discuss the latest advances, and what can be expected in the near future, in hardware, software and applications codes for advanced simulation of particle accelerators

  9. Advanced computed tomographic anatomical and morphometric plaque analysis for prediction of fractional flow reserve in intermediate coronary lesions

    International Nuclear Information System (INIS)

    Opolski, Maksymilian P.; Kepka, Cezary; Achenbach, Stephan; Pregowski, Jerzy; Kruk, Mariusz; Staruch, Adam D.; Kadziela, Jacek; Ruzyllo, Witold; Witkowski, Adam

    2014-01-01

    Objective: To determine the application of advanced coronary computed tomography angiography (CCTA) plaque analysis for predicting invasive fractional flow reserve (FFR) in intermediate coronary lesions. Methods: Sixty-one patients with 71 single intermediate coronary lesions (≥50–80% stenosis) on CCTA prospectively underwent coronary angiography and FFR. Advanced anatomical and morphometric plaque analysis was performed based on CCTA data set to determine optimal criteria for significant flow impairment. A significant stenosis was defined as FFR ≤ 0.80. Results: FFR averaged 0.85 ± 0.09, and 19 lesions (27%) were functionally significant. FFR correlated with minimum lumen area (MLA) (r = 0.456, p < 0.001), minimum lumen diameter (MLD) (r = 0.326, p = 0.006), reference lumen diameter (RLD) (r = 0.245, p = 0.039), plaque burden (r = −0.313, p = 0.008), lumen area stenosis (r = −0.305, p = 0.01), lesion length (r = −0.692, p < 0.001), and plaque volume (r = −0.668, p < 0.001). There was no relationship between FFR and CCTA morphometric plaque parameters. By multivariate analysis the independent predictors of FFR were lesion length (beta = −0.581, p < 0.001), MLA (beta = 0.360, p = 0.041), and RLD (beta = −0.255, p = 0.036). The optimal cutoffs for lesion length, MLA, MLD, RLD, and lumen area stenosis were >18.5 mm, ≤3.0 mm 2 , ≤2.1 mm, ≤3.2 mm, and >69%, respectively (max. sensitivity: 100% for MLA, max. specificity: 79% for lumen area stenosis). Conclusions: CCTA predictors for FFR support the mathematical relationship between stenosis pressure drop and coronary flow. CCTA could prove to be a useful rule-out test for significant hemodynamic effects of intermediate coronary stenoses

  10. Seismic attributes and advanced computer algorithm to predict formation pore pressure: Qalibah formation of Northwest Saudi Arabia

    Science.gov (United States)

    Nour, Abdoulshakour M.

    Oil and gas exploration professionals have long recognized the importance of predicting pore pressure before drilling wells. Pre-drill pore pressure estimation not only helps with drilling wells safely but also aids in the determination of formation fluids migration and seal integrity. With respect to the hydrocarbon reservoirs, the appropriate drilling mud weight is directly related to the estimated pore pressure in the formation. If the mud weight is lower than the formation pressure, a blowout may occur, and conversely, if it is higher than the formation pressure, the formation may suffer irreparable damage due to the invasion of drilling fluids into the formation. A simple definition of pore pressure is the pressure of the pore fluids in excess of the hydrostatic pressure. In this thesis, I investigated the utility of advance computer algorithm called Support Vector Machine (SVM) to learn the pattern of high pore pressure regime, using seismic attributes such as Instantaneous phase, t*Attenuation, Cosine of Phase, Vp/Vs ratio, P-Impedance, Reflection Acoustic Impedance, Dominant frequency and one well attribute (Mud-Weigh) as the learning dataset. I applied this technique to the over pressured Qalibah formation of Northwest Saudi Arabia. The results of my research revealed that in the Qalibah formation of Northwest Saudi Arabia, the pore pressure trend can be predicted using SVM with seismic and well attributes as the learning dataset. I was able to show the pore pressure trend at any given point within the geographical extent of the 3D seismic data from which the seismic attributes were derived. In addition, my results surprisingly showed the subtle variation of pressure within the thick succession of shale units of the Qalibah formation.

  11. In-Service Design and Performance Prediction of Advanced Fusion Material Systems by Computational Modeling and Simulation

    International Nuclear Information System (INIS)

    G. R. Odette; G. E. Lucas

    2005-01-01

    This final report on ''In-Service Design and Performance Prediction of Advanced Fusion Material Systems by Computational Modeling and Simulation'' (DE-FG03-01ER54632) consists of a series of summaries of work that has been published, or presented at meetings, or both. It briefly describes results on the following topics: (1) A Transport and Fate Model for Helium and Helium Management; (2) Atomistic Studies of Point Defect Energetics, Dynamics and Interactions; (3) Multiscale Modeling of Fracture consisting of: (3a) A Micromechanical Model of the Master Curve (MC) Universal Fracture Toughness-Temperature Curve Relation, KJc(T - To), (3b) An Embrittlement DTo Prediction Model for the Irradiation Hardening Dominated Regime, (3c) Non-hardening Irradiation Assisted Thermal and Helium Embrittlement of 8Cr Tempered Martensitic Steels: Compilation and Analysis of Existing Data, (3d) A Model for the KJc(T) of a High Strength NFA MA957, (3e) Cracked Body Size and Geometry Effects of Measured and Effective Fracture Toughness-Model Based MC and To Evaluations of F82H and Eurofer 97, (3f) Size and Geometry Effects on the Effective Toughness of Cracked Fusion Structures; (4) Modeling the Multiscale Mechanics of Flow Localization-Ductility Loss in Irradiation Damaged BCC Alloys; and (5) A Universal Relation Between Indentation Hardness and True Stress-Strain Constitutive Behavior. Further details can be found in the cited references or presentations that generally can be accessed on the internet, or provided upon request to the authors. Finally, it is noted that this effort was integrated with our base program in fusion materials, also funded by the DOE OFES

  12. Advances in unconventional computing

    CERN Document Server

    2017-01-01

    The unconventional computing is a niche for interdisciplinary science, cross-bred of computer science, physics, mathematics, chemistry, electronic engineering, biology, material science and nanotechnology. The aims of this book are to uncover and exploit principles and mechanisms of information processing in and functional properties of physical, chemical and living systems to develop efficient algorithms, design optimal architectures and manufacture working prototypes of future and emergent computing devices. This first volume presents theoretical foundations of the future and emergent computing paradigms and architectures. The topics covered are computability, (non-)universality and complexity of computation; physics of computation, analog and quantum computing; reversible and asynchronous devices; cellular automata and other mathematical machines; P-systems and cellular computing; infinity and spatial computation; chemical and reservoir computing. The book is the encyclopedia, the first ever complete autho...

  13. Recent advances, and unresolved issues, in the application of computational modelling to the prediction of the biological effects of nanomaterials

    International Nuclear Information System (INIS)

    Winkler, David A.

    2016-01-01

    Nanomaterials research is one of the fastest growing contemporary research areas. The unprecedented properties of these materials have meant that they are being incorporated into products very quickly. Regulatory agencies are concerned they cannot assess the potential hazards of these materials adequately, as data on the biological properties of nanomaterials are still relatively limited and expensive to acquire. Computational modelling methods have much to offer in helping understand the mechanisms by which toxicity may occur, and in predicting the likelihood of adverse biological impacts of materials not yet tested experimentally. This paper reviews the progress these methods, particularly those QSAR-based, have made in understanding and predicting potentially adverse biological effects of nanomaterials, and also the limitations and pitfalls of these methods. - Highlights: • Nanomaterials regulators need good information to make good decisions. • Nanomaterials and their interactions with biology are very complex. • Computational methods use existing data to predict properties of new nanomaterials. • Statistical, data driven modelling methods have been successfully applied to this task. • Much more must be learnt before robust toolkits will be widely usable by regulators.

  14. Advances in physiological computing

    CERN Document Server

    Fairclough, Stephen H

    2014-01-01

    This edited collection will provide an overview of the field of physiological computing, i.e. the use of physiological signals as input for computer control. It will cover a breadth of current research, from brain-computer interfaces to telemedicine.

  15. Predicting epileptic seizures in advance.

    Directory of Open Access Journals (Sweden)

    Negin Moghim

    Full Text Available Epilepsy is the second most common neurological disorder, affecting 0.6-0.8% of the world's population. In this neurological disorder, abnormal activity of the brain causes seizures, the nature of which tend to be sudden. Antiepileptic Drugs (AEDs are used as long-term therapeutic solutions that control the condition. Of those treated with AEDs, 35% become resistant to medication. The unpredictable nature of seizures poses risks for the individual with epilepsy. It is clearly desirable to find more effective ways of preventing seizures for such patients. The automatic detection of oncoming seizures, before their actual onset, can facilitate timely intervention and hence minimize these risks. In addition, advance prediction of seizures can enrich our understanding of the epileptic brain. In this study, drawing on the body of work behind automatic seizure detection and prediction from digitised Invasive Electroencephalography (EEG data, a prediction algorithm, ASPPR (Advance Seizure Prediction via Pre-ictal Relabeling, is described. ASPPR facilitates the learning of predictive models targeted at recognizing patterns in EEG activity that are in a specific time window in advance of a seizure. It then exploits advanced machine learning coupled with the design and selection of appropriate features from EEG signals. Results, from evaluating ASPPR independently on 21 different patients, suggest that seizures for many patients can be predicted up to 20 minutes in advance of their onset. Compared to benchmark performance represented by a mean S1-Score (harmonic mean of Sensitivity and Specificity of 90.6% for predicting seizure onset between 0 and 5 minutes in advance, ASPPR achieves mean S1-Scores of: 96.30% for prediction between 1 and 6 minutes in advance, 96.13% for prediction between 8 and 13 minutes in advance, 94.5% for prediction between 14 and 19 minutes in advance, and 94.2% for prediction between 20 and 25 minutes in advance.

  16. Advanced Computer Typography.

    Science.gov (United States)

    1981-12-01

    side it necessary and IdentOf, bp block number) Cartography Typography C uter Graphics 20.VSsT RACT (Continueaon reverse aide It necessary -d Identif...material with graphic arts quality. There are several systems’ ’a which operate through the computer. The CTI system was designed especially for...cartography and typography is the HERA system. It was designed especially for the printing of difficult material such as chemical structures, electronic

  17. Standardized uptake value on positron emission tomography/computed tomography predicts prognosis in patients with locally advanced pancreatic cancer.

    Science.gov (United States)

    Wang, Si-Liang; Cao, Shuo; Sun, Yu-Nan; Wu, Rong; Chi, Feng; Tang, Mei-Yue; Jin, Xue-Ying; Chen, Xiao-Dong

    2015-10-01

    The aim of the present study was to investigate the use and value of maximum standardized uptake value (SUV max) on positron emission tomography/computed tomography (PET/CT) images as a prognostic marker for patients with locally advanced pancreatic cancer (LAPC). The medical records of all consecutive patients who underwent PET/CT examination in our institution were retrospectively reviewed. Inclusion criteria were histologically or cytologically proven LAPC. Patients with distant metastasis were excluded. For statistical analysis, the SUV max of primary pancreatic cancer was measured. Survival rates were calculated using the Kaplan-Meier method, and multivariable analysis was performed to determine the association of SUV max with overall survival (OS) and progression-free survival (PFS) using a Cox proportional hazards model. Between July 2006 and June 2013, 69 patients were enrolled in the present study. OS and PFS were 14.9 months [95% confidence interval (CI) 13.1-16.7] and 8.3 months (95% CI 7.1-9.5), respectively. A high SUV max (>5.5) was observed in 35 patients, who had significantly worse OS and PFS than the remaining patients with a low SUV max (P = 0.025 and P = 0.003). Univariate analysis showed that SUV max and tumor size were prognostic factors for OS, with a hazard ratio of 1.90 and 1.81, respectively. A high SUV max was an independent prognostic factor, with a hazard ratio of 1.89 (95% CI 1.015-3.519, P = 0.045). The present study suggests that increased SUV max is a predictor of poor prognosis in patients with LAPC.

  18. Texture analysis of advanced non-small cell lung cancer (NSCLC) on contrast-enhanced computed tomography: prediction of the response to the first-line chemotherapy

    International Nuclear Information System (INIS)

    Farina, Davide; Morassi, Mauro; Maroldi, Roberto; Roca, Elisa; Tassi, Gianfranco; Cavalleri, Giuseppe

    2013-01-01

    To assess whether tumour heterogeneity, quantified by texture analysis (TA) on contrast-enhanced computed tomography (CECT), can predict response to chemotherapy in advanced non-small cell lung cancer (NSCLC). Fifty-three CECT studies of patients with advanced NSCLC who had undergone first-line chemotherapy were retrospectively reviewed. Response to chemotherapy was evaluated according to RECIST1.1. Tumour uniformity was assessed by a TA method based on Laplacian of Gaussian filtering. The resulting parameters were correlated with treatment response and overall survival by multivariate analysis. Thirty-one out of 53 patients were non-responders and 22 were responders. Average overall survival was 13 months (4-35), minimum follow-up was 12 months. In the adenocarcinoma group (n = 31), the product of tumour uniformity and grey level (GL*U) was the unique independent variable correlating with treatment response. Dividing the GL*U (range 8.5-46.6) into tertiles, lesions belonging to the second and the third tertiles had an 8.3-fold higher probability of treatment response compared with those in the first tertile. No association between texture features and response to treatment was observed in the non-adenocarcinoma group (n = 22). GL*U did not correlate with overall survival. TA on CECT images in advanced lung adenocarcinoma provides an independent predictive indicator of response to first-line chemotherapy. (orig.)

  19. Laparoscopy and computed tomography imaging in advanced ovarian tumors: A roadmap for prediction of optimal cytoreductive surgery

    OpenAIRE

    Ahmed Samy El-Agwany

    2018-01-01

    Introduction: Comprehensive staging laparotomy and cytoreductive surgery followed by chemotherapy has been the standard of care in advanced ovarian cancer. Neoadjuvant chemotherapy is an alternative in inoperable advanced cases. To select patients amenable for successful cytoreduction, major determinants including CT imaging and laparoscopy could be of value. There is no general accepted model for selection and reproducibility of techniques are a major challenge due to different clinical prac...

  20. Advanced computations in plasma physics

    International Nuclear Information System (INIS)

    Tang, W.M.

    2002-01-01

    Scientific simulation in tandem with theory and experiment is an essential tool for understanding complex plasma behavior. In this paper we review recent progress and future directions for advanced simulations in magnetically confined plasmas with illustrative examples chosen from magnetic confinement research areas such as microturbulence, magnetohydrodynamics, magnetic reconnection, and others. Significant recent progress has been made in both particle and fluid simulations of fine-scale turbulence and large-scale dynamics, giving increasingly good agreement between experimental observations and computational modeling. This was made possible by innovative advances in analytic and computational methods for developing reduced descriptions of physics phenomena spanning widely disparate temporal and spatial scales together with access to powerful new computational resources. In particular, the fusion energy science community has made excellent progress in developing advanced codes for which computer run-time and problem size scale well with the number of processors on massively parallel machines (MPP's). A good example is the effective usage of the full power of multi-teraflop (multi-trillion floating point computations per second) MPP's to produce three-dimensional, general geometry, nonlinear particle simulations which have accelerated progress in understanding the nature of turbulence self-regulation by zonal flows. It should be emphasized that these calculations, which typically utilized billions of particles for thousands of time-steps, would not have been possible without access to powerful present generation MPP computers and the associated diagnostic and visualization capabilities. In general, results from advanced simulations provide great encouragement for being able to include increasingly realistic dynamics to enable deeper physics insights into plasmas in both natural and laboratory environments. The associated scientific excitement should serve to

  1. Center for Advanced Computational Technology

    Science.gov (United States)

    Noor, Ahmed K.

    2000-01-01

    The Center for Advanced Computational Technology (ACT) was established to serve as a focal point for diverse research activities pertaining to application of advanced computational technology to future aerospace systems. These activities include the use of numerical simulations, artificial intelligence methods, multimedia and synthetic environments, and computational intelligence, in the modeling, analysis, sensitivity studies, optimization, design and operation of future aerospace systems. The Center is located at NASA Langley and is an integral part of the School of Engineering and Applied Science of the University of Virginia. The Center has four specific objectives: 1) conduct innovative research on applications of advanced computational technology to aerospace systems; 2) act as pathfinder by demonstrating to the research community what can be done (high-potential, high-risk research); 3) help in identifying future directions of research in support of the aeronautical and space missions of the twenty-first century; and 4) help in the rapid transfer of research results to industry and in broadening awareness among researchers and engineers of the state-of-the-art in applications of advanced computational technology to the analysis, design prototyping and operations of aerospace and other high-performance engineering systems. In addition to research, Center activities include helping in the planning and coordination of the activities of a multi-center team of NASA and JPL researchers who are developing an intelligent synthesis environment for future aerospace systems; organizing workshops and national symposia; as well as writing state-of-the-art monographs and NASA special publications on timely topics.

  2. Recent advances in computational optimization

    CERN Document Server

    2013-01-01

    Optimization is part of our everyday life. We try to organize our work in a better way and optimization occurs in minimizing time and cost or the maximization of the profit, quality and efficiency. Also many real world problems arising in engineering, economics, medicine and other domains can be formulated as optimization tasks. This volume is a comprehensive collection of extended contributions from the Workshop on Computational Optimization. This book presents recent advances in computational optimization. The volume includes important real world problems like parameter settings for con- trolling processes in bioreactor, robot skin wiring, strip packing, project scheduling, tuning of PID controller and so on. Some of them can be solved by applying traditional numerical methods, but others need a huge amount of computational resources. For them it is shown that is appropriate to develop algorithms based on metaheuristic methods like evolutionary computation, ant colony optimization, constrain programming etc...

  3. International Conference on Advanced Computing

    CERN Document Server

    Patnaik, Srikanta

    2014-01-01

    This book is composed of the Proceedings of the International Conference on Advanced Computing, Networking, and Informatics (ICACNI 2013), held at Central Institute of Technology, Raipur, Chhattisgarh, India during June 14–16, 2013. The book records current research articles in the domain of computing, networking, and informatics. The book presents original research articles, case-studies, as well as review articles in the said field of study with emphasis on their implementation and practical application. Researchers, academicians, practitioners, and industry policy makers around the globe have contributed towards formation of this book with their valuable research submissions.

  4. Advances in embedded computer vision

    CERN Document Server

    Kisacanin, Branislav

    2014-01-01

    This illuminating collection offers a fresh look at the very latest advances in the field of embedded computer vision. Emerging areas covered by this comprehensive text/reference include the embedded realization of 3D vision technologies for a variety of applications, such as stereo cameras on mobile devices. Recent trends towards the development of small unmanned aerial vehicles (UAVs) with embedded image and video processing algorithms are also examined. The authoritative insights range from historical perspectives to future developments, reviewing embedded implementation, tools, technolog

  5. Advances in medical image computing.

    Science.gov (United States)

    Tolxdorff, T; Deserno, T M; Handels, H; Meinzer, H-P

    2009-01-01

    Medical image computing has become a key technology in high-tech applications in medicine and an ubiquitous part of modern imaging systems and the related processes of clinical diagnosis and intervention. Over the past years significant progress has been made in the field, both on methodological and on application level. Despite this progress there are still big challenges to meet in order to establish image processing routinely in health care. In this issue, selected contributions of the German Conference on Medical Image Processing (BVM) are assembled to present latest advances in the field of medical image computing. The winners of scientific awards of the German Conference on Medical Image Processing (BVM) 2008 were invited to submit a manuscript on their latest developments and results for possible publication in Methods of Information in Medicine. Finally, seven excellent papers were selected to describe important aspects of recent advances in the field of medical image processing. The selected papers give an impression of the breadth and heterogeneity of new developments. New methods for improved image segmentation, non-linear image registration and modeling of organs are presented together with applications of image analysis methods in different medical disciplines. Furthermore, state-of-the-art tools and techniques to support the development and evaluation of medical image processing systems in practice are described. The selected articles describe different aspects of the intense development in medical image computing. The image processing methods presented enable new insights into the patient's image data and have the future potential to improve medical diagnostics and patient treatment.

  6. Computational Design of Advanced Nuclear Fuels

    International Nuclear Information System (INIS)

    Savrasov, Sergey; Kotliar, Gabriel; Haule, Kristjan

    2014-01-01

    The objective of the project was to develop a method for theoretical understanding of nuclear fuel materials whose physical and thermophysical properties can be predicted from first principles using a novel dynamical mean field method for electronic structure calculations. We concentrated our study on uranium, plutonium, their oxides, nitrides, carbides, as well as some rare earth materials whose 4f eletrons provide a simplified framework for understanding complex behavior of the f electrons. We addressed the issues connected to the electronic structure, lattice instabilities, phonon and magnon dynamics as well as thermal conductivity. This allowed us to evaluate characteristics of advanced nuclear fuel systems using computer based simulations and avoid costly experiments.

  7. Advances in Computer Science and Engineering

    CERN Document Server

    Second International Conference on Advances in Computer Science and Engineering (CES 2012)

    2012-01-01

    This book includes the proceedings of the second International Conference on Advances in Computer Science and Engineering (CES 2012), which was held during January 13-14, 2012 in Sanya, China. The papers in these proceedings of CES 2012 focus on the researchers’ advanced works in their fields of Computer Science and Engineering mainly organized in four topics, (1) Software Engineering, (2) Intelligent Computing, (3) Computer Networks, and (4) Artificial Intelligence Software.

  8. Computer loss experience and predictions

    Science.gov (United States)

    Parker, Donn B.

    1996-03-01

    The types of losses organizations must anticipate have become more difficult to predict because of the eclectic nature of computers and the data communications and the decrease in news media reporting of computer-related losses as they become commonplace. Total business crime is conjectured to be decreasing in frequency and increasing in loss per case as a result of increasing computer use. Computer crimes are probably increasing, however, as their share of the decreasing business crime rate grows. Ultimately all business crime will involve computers in some way, and we could see a decline of both together. The important information security measures in high-loss business crime generally concern controls over authorized people engaged in unauthorized activities. Such controls include authentication of users, analysis of detailed audit records, unannounced audits, segregation of development and production systems and duties, shielding the viewing of screens, and security awareness and motivation controls in high-value transaction areas. Computer crimes that involve highly publicized intriguing computer misuse methods, such as privacy violations, radio frequency emanations eavesdropping, and computer viruses, have been reported in waves that periodically have saturated the news media during the past 20 years. We must be able to anticipate such highly publicized crimes and reduce the impact and embarrassment they cause. On the basis of our most recent experience, I propose nine new types of computer crime to be aware of: computer larceny (theft and burglary of small computers), automated hacking (use of computer programs to intrude), electronic data interchange fraud (business transaction fraud), Trojan bomb extortion and sabotage (code security inserted into others' systems that can be triggered to cause damage), LANarchy (unknown equipment in use), desktop forgery (computerized forgery and counterfeiting of documents), information anarchy (indiscriminate use of

  9. Advanced computer-based training

    Energy Technology Data Exchange (ETDEWEB)

    Fischer, H D; Martin, H D

    1987-05-01

    The paper presents new techniques of computer-based training for personnel of nuclear power plants. Training on full-scope simulators is further increased by use of dedicated computer-based equipment. An interactive communication system runs on a personal computer linked to a video disc; a part-task simulator runs on 32 bit process computers and shows two versions: as functional trainer or as on-line predictor with an interactive learning system (OPAL), which may be well-tailored to a specific nuclear power plant. The common goal of both develoments is the optimization of the cost-benefit ratio for training and equipment.

  10. Advanced computer-based training

    International Nuclear Information System (INIS)

    Fischer, H.D.; Martin, H.D.

    1987-01-01

    The paper presents new techniques of computer-based training for personnel of nuclear power plants. Training on full-scope simulators is further increased by use of dedicated computer-based equipment. An interactive communication system runs on a personal computer linked to a video disc; a part-task simulator runs on 32 bit process computers and shows two versions: as functional trainer or as on-line predictor with an interactive learning system (OPAL), which may be well-tailored to a specific nuclear power plant. The common goal of both develoments is the optimization of the cost-benefit ratio for training and equipment. (orig.) [de

  11. Advances in photonic reservoir computing

    Directory of Open Access Journals (Sweden)

    Van der Sande Guy

    2017-05-01

    Full Text Available We review a novel paradigm that has emerged in analogue neuromorphic optical computing. The goal is to implement a reservoir computer in optics, where information is encoded in the intensity and phase of the optical field. Reservoir computing is a bio-inspired approach especially suited for processing time-dependent information. The reservoir’s complex and high-dimensional transient response to the input signal is capable of universal computation. The reservoir does not need to be trained, which makes it very well suited for optics. As such, much of the promise of photonic reservoirs lies in their minimal hardware requirements, a tremendous advantage over other hardware-intensive neural network models. We review the two main approaches to optical reservoir computing: networks implemented with multiple discrete optical nodes and the continuous system of a single nonlinear device coupled to delayed feedback.

  12. Advances in photonic reservoir computing

    Science.gov (United States)

    Van der Sande, Guy; Brunner, Daniel; Soriano, Miguel C.

    2017-05-01

    We review a novel paradigm that has emerged in analogue neuromorphic optical computing. The goal is to implement a reservoir computer in optics, where information is encoded in the intensity and phase of the optical field. Reservoir computing is a bio-inspired approach especially suited for processing time-dependent information. The reservoir's complex and high-dimensional transient response to the input signal is capable of universal computation. The reservoir does not need to be trained, which makes it very well suited for optics. As such, much of the promise of photonic reservoirs lies in their minimal hardware requirements, a tremendous advantage over other hardware-intensive neural network models. We review the two main approaches to optical reservoir computing: networks implemented with multiple discrete optical nodes and the continuous system of a single nonlinear device coupled to delayed feedback.

  13. Advances in computational complexity theory

    CERN Document Server

    Cai, Jin-Yi

    1993-01-01

    This collection of recent papers on computational complexity theory grew out of activities during a special year at DIMACS. With contributions by some of the leading experts in the field, this book is of lasting value in this fast-moving field, providing expositions not found elsewhere. Although aimed primarily at researchers in complexity theory and graduate students in mathematics or computer science, the book is accessible to anyone with an undergraduate education in mathematics or computer science. By touching on some of the major topics in complexity theory, this book sheds light on this burgeoning area of research.

  14. Advanced in Computer Science and its Applications

    CERN Document Server

    Yen, Neil; Park, James; CSA 2013

    2014-01-01

    The theme of CSA is focused on the various aspects of computer science and its applications for advances in computer science and its applications and provides an opportunity for academic and industry professionals to discuss the latest issues and progress in the area of computer science and its applications. Therefore this book will be include the various theories and practical applications in computer science and its applications.

  15. Quantum chromodynamics with advanced computing

    International Nuclear Information System (INIS)

    Kronfeld, A S

    2008-01-01

    We survey results in lattice quantum chromodynamics from groups in the USQCD Collaboration. The main focus is on physics, but many aspects of the discussion are aimed at an audience of computational physicists

  16. International Conference on Advanced Computing for Innovation

    CERN Document Server

    Angelova, Galia; Agre, Gennady

    2016-01-01

    This volume is a selected collection of papers presented and discussed at the International Conference “Advanced Computing for Innovation (AComIn 2015)”. The Conference was held at 10th -11th of November, 2015 in Sofia, Bulgaria and was aimed at providing a forum for international scientific exchange between Central/Eastern Europe and the rest of the world on several fundamental topics of computational intelligence. The papers report innovative approaches and solutions in hot topics of computational intelligence – advanced computing, language and semantic technologies, signal and image processing, as well as optimization and intelligent control.

  17. Computational prediction of protein hot spot residues.

    Science.gov (United States)

    Morrow, John Kenneth; Zhang, Shuxing

    2012-01-01

    Most biological processes involve multiple proteins interacting with each other. It has been recently discovered that certain residues in these protein-protein interactions, which are called hot spots, contribute more significantly to binding affinity than others. Hot spot residues have unique and diverse energetic properties that make them challenging yet important targets in the modulation of protein-protein complexes. Design of therapeutic agents that interact with hot spot residues has proven to be a valid methodology in disrupting unwanted protein-protein interactions. Using biological methods to determine which residues are hot spots can be costly and time consuming. Recent advances in computational approaches to predict hot spots have incorporated a myriad of features, and have shown increasing predictive successes. Here we review the state of knowledge around protein-protein interactions, hot spots, and give an overview of multiple in silico prediction techniques of hot spot residues.

  18. Computational Prediction of Hot Spot Residues

    Science.gov (United States)

    Morrow, John Kenneth; Zhang, Shuxing

    2013-01-01

    Most biological processes involve multiple proteins interacting with each other. It has been recently discovered that certain residues in these protein-protein interactions, which are called hot spots, contribute more significantly to binding affinity than others. Hot spot residues have unique and diverse energetic properties that make them challenging yet important targets in the modulation of protein-protein complexes. Design of therapeutic agents that interact with hot spot residues has proven to be a valid methodology in disrupting unwanted protein-protein interactions. Using biological methods to determine which residues are hot spots can be costly and time consuming. Recent advances in computational approaches to predict hot spots have incorporated a myriad of features, and have shown increasing predictive successes. Here we review the state of knowledge around protein-protein interactions, hot spots, and give an overview of multiple in silico prediction techniques of hot spot residues. PMID:22316154

  19. Bringing Advanced Computational Techniques to Energy Research

    Energy Technology Data Exchange (ETDEWEB)

    Mitchell, Julie C

    2012-11-17

    Please find attached our final technical report for the BACTER Institute award. BACTER was created as a graduate and postdoctoral training program for the advancement of computational biology applied to questions of relevance to bioenergy research.

  20. Soft computing in advanced robotics

    CERN Document Server

    Kobayashi, Ichiro; Kim, Euntai

    2014-01-01

    Intelligent system and robotics are inevitably bound up; intelligent robots makes embodiment of system integration by using the intelligent systems. We can figure out that intelligent systems are to cell units, while intelligent robots are to body components. The two technologies have been synchronized in progress. Making leverage of the robotics and intelligent systems, applications cover boundlessly the range from our daily life to space station; manufacturing, healthcare, environment, energy, education, personal assistance, logistics. This book aims at presenting the research results in relevance with intelligent robotics technology. We propose to researchers and practitioners some methods to advance the intelligent systems and apply them to advanced robotics technology. This book consists of 10 contributions that feature mobile robots, robot emotion, electric power steering, multi-agent, fuzzy visual navigation, adaptive network-based fuzzy inference system, swarm EKF localization and inspection robot. Th...

  1. Time-Predictable Computer Architecture

    Directory of Open Access Journals (Sweden)

    Schoeberl Martin

    2009-01-01

    Full Text Available Today's general-purpose processors are optimized for maximum throughput. Real-time systems need a processor with both a reasonable and a known worst-case execution time (WCET. Features such as pipelines with instruction dependencies, caches, branch prediction, and out-of-order execution complicate WCET analysis and lead to very conservative estimates. In this paper, we evaluate the issues of current architectures with respect to WCET analysis. Then, we propose solutions for a time-predictable computer architecture. The proposed architecture is evaluated with implementation of some features in a Java processor. The resulting processor is a good target for WCET analysis and still performs well in the average case.

  2. Computer networks and advanced communications

    International Nuclear Information System (INIS)

    Koederitz, W.L.; Macon, B.S.

    1992-01-01

    One of the major methods for getting the most productivity and benefits from computer usage is networking. However, for those who are contemplating a change from stand-alone computers to a network system, the investigation of actual networks in use presents a paradox: network systems can be highly productive and beneficial; at the same time, these networks can create many complex, frustrating problems. The issue becomes a question of whether the benefits of networking are worth the extra effort and cost. In response to this issue, the authors review in this paper the implementation and management of an actual network in the LSU Petroleum Engineering Department. The network, which has been in operation for four years, is large and diverse (50 computers, 2 sites, PC's, UNIX RISC workstations, etc.). The benefits, costs, and method of operation of this network will be described, and an effort will be made to objectively weigh these elements from the point of view of the average computer user

  3. Preface (to: Advances in Computer Entertainment)

    NARCIS (Netherlands)

    Romão, Teresa; Nijholt, Antinus; Romão, Teresa; Reidsma, Dennis

    2012-01-01

    These are the proceedings of the 9th International Conference on Advances in Computer Entertainment ACE 2012). ACE has become the leading scientific forum for dissemination of cutting-edge research results in the area of entertainment computing. Interactive entertainment is one of the most vibrant

  4. Advance Trends in Soft Computing

    CERN Document Server

    Kreinovich, Vladik; Kacprzyk, Janusz; WCSC 2013

    2014-01-01

    This book is the proceedings of the 3rd World Conference on Soft Computing (WCSC), which was held in San Antonio, TX, USA, on December 16-18, 2013. It presents start-of-the-art theory and applications of soft computing together with an in-depth discussion of current and future challenges in the field, providing readers with a 360 degree view on soft computing. Topics range from fuzzy sets, to fuzzy logic, fuzzy mathematics, neuro-fuzzy systems, fuzzy control, decision making in fuzzy environments, image processing and many more. The book is dedicated to Lotfi A. Zadeh, a renowned specialist in signal analysis and control systems research who proposed the idea of fuzzy sets, in which an element may have a partial membership, in the early 1960s, followed by the idea of fuzzy logic, in which a statement can be true only to a certain degree, with degrees described by numbers in the interval [0,1]. The performance of fuzzy systems can often be improved with the help of optimization techniques, e.g. evolutionary co...

  5. Advances in randomized parallel computing

    CERN Document Server

    Rajasekaran, Sanguthevar

    1999-01-01

    The technique of randomization has been employed to solve numerous prob­ lems of computing both sequentially and in parallel. Examples of randomized algorithms that are asymptotically better than their deterministic counterparts in solving various fundamental problems abound. Randomized algorithms have the advantages of simplicity and better performance both in theory and often in practice. This book is a collection of articles written by renowned experts in the area of randomized parallel computing. A brief introduction to randomized algorithms In the aflalysis of algorithms, at least three different measures of performance can be used: the best case, the worst case, and the average case. Often, the average case run time of an algorithm is much smaller than the worst case. 2 For instance, the worst case run time of Hoare's quicksort is O(n ), whereas its average case run time is only O( n log n). The average case analysis is conducted with an assumption on the input space. The assumption made to arrive at t...

  6. PEMS. Advanced predictive emission monitoring

    Energy Technology Data Exchange (ETDEWEB)

    Sandvig Nielsen, J.

    2010-07-15

    In the project PEMS have been developed for boilers, internal combustion engines and gas turbines. The PEMS models have been developed using two principles: The one called ''first principles'' is based on thermo-kinetic modeling of the NO{sub x}-formation by modeling conditions (like temperature, pressure and residence time) in the reaction zones. The other one is data driven using artificial neural network (ANN) and includes no physical properties and no thermo-kinetic formulation. Models of first principles have been developed for gas turbines and gas engines. Data driven models have been developed for gas turbines, gas engines and boilers. The models have been tested on data from sites located in Denmark and the Middle East. Weel and Sandvig has conducted the on-site emission measurements used for development and testing the PEMS models. For gas turbines, both the ''first principles'' and the data driven models have performed excellent considering the ability to reproduce the emission levels of NO{sub x} according to the input variables used for calibration. Data driven models for boilers and gas engines have performed excellent as well. The rather comprehensive first principle model, developed for gas engines, did not perform as well in the prediction of NO{sub x}. Possible a more complex model formulation is required for internal combustion engines. In general, both model types have been validated on data extracted from the data set used for calibration. The data for validation have been selected randomly as individual samplings, and is scattered over the entire measuring campaign. For one natural gas engine a secondary measuring campaign was conducted half a year later than the campaign used for training the data driven model. In the meantime, this engine had been through a refurbishment that included new pistons, piston rings and cylinder linings and cleaning of the cylinder heads. Despite the refurbishment, the

  7. Advances and challenges in computational plasma science

    International Nuclear Information System (INIS)

    Tang, W M; Chan, V S

    2005-01-01

    Scientific simulation, which provides a natural bridge between theory and experiment, is an essential tool for understanding complex plasma behaviour. Recent advances in simulations of magnetically confined plasmas are reviewed in this paper, with illustrative examples, chosen from associated research areas such as microturbulence, magnetohydrodynamics and other topics. Progress has been stimulated, in particular, by the exponential growth of computer speed along with significant improvements in computer technology. The advances in both particle and fluid simulations of fine-scale turbulence and large-scale dynamics have produced increasingly good agreement between experimental observations and computational modelling. This was enabled by two key factors: (a) innovative advances in analytic and computational methods for developing reduced descriptions of physics phenomena spanning widely disparate temporal and spatial scales and (b) access to powerful new computational resources. Excellent progress has been made in developing codes for which computer run-time and problem-size scale well with the number of processors on massively parallel processors (MPPs). Examples include the effective usage of the full power of multi-teraflop (multi-trillion floating point computations per second) MPPs to produce three-dimensional, general geometry, nonlinear particle simulations that have accelerated advances in understanding the nature of turbulence self-regulation by zonal flows. These calculations, which typically utilized billions of particles for thousands of time-steps, would not have been possible without access to powerful present generation MPP computers and the associated diagnostic and visualization capabilities. In looking towards the future, the current results from advanced simulations provide great encouragement for being able to include increasingly realistic dynamics to enable deeper physics insights into plasmas in both natural and laboratory environments. This

  8. Computation of Asteroid Proper Elements: Recent Advances

    Science.gov (United States)

    Knežević, Z.

    2017-12-01

    The recent advances in computation of asteroid proper elements are briefly reviewed. Although not representing real breakthroughs in computation and stability assessment of proper elements, these advances can still be considered as important improvements offering solutions to some practical problems encountered in the past. The problem of getting unrealistic values of perihelion frequency for very low eccentricity orbits is solved by computing frequencies using the frequency-modified Fourier transform. The synthetic resonant proper elements adjusted to a given secular resonance helped to prove the existence of Astraea asteroid family. The preliminary assessment of stability with time of proper elements computed by means of the analytical theory provides a good indication of their poorer performance with respect to their synthetic counterparts, and advocates in favor of ceasing their regular maintenance; the final decision should, however, be taken on the basis of more comprehensive and reliable direct estimate of their individual and sample average deviations from constancy.

  9. Computational electromagnetics recent advances and engineering applications

    CERN Document Server

    2014-01-01

    Emerging Topics in Computational Electromagnetics in Computational Electromagnetics presents advances in Computational Electromagnetics. This book is designed to fill the existing gap in current CEM literature that only cover the conventional numerical techniques for solving traditional EM problems. The book examines new algorithms, and applications of these algorithms for solving problems of current interest that are not readily amenable to efficient treatment by using the existing techniques. The authors discuss solution techniques for problems arising in nanotechnology, bioEM, metamaterials, as well as multiscale problems. They present techniques that utilize recent advances in computer technology, such as parallel architectures, and the increasing need to solve large and complex problems in a time efficient manner by using highly scalable algorithms.

  10. Advances and Challenges in Computational Plasma Science

    International Nuclear Information System (INIS)

    Tang, W.M.; Chan, V.S.

    2005-01-01

    Scientific simulation, which provides a natural bridge between theory and experiment, is an essential tool for understanding complex plasma behavior. Recent advances in simulations of magnetically-confined plasmas are reviewed in this paper with illustrative examples chosen from associated research areas such as microturbulence, magnetohydrodynamics, and other topics. Progress has been stimulated in particular by the exponential growth of computer speed along with significant improvements in computer technology

  11. Preface (to: Advances in Computer Entertainment)

    OpenAIRE

    Romão, Teresa; Nijholt, Antinus; Romão, Teresa; Reidsma, Dennis

    2012-01-01

    These are the proceedings of the 9th International Conference on Advances in Computer Entertainment ACE 2012). ACE has become the leading scientific forum for dissemination of cutting-edge research results in the area of entertainment computing. Interactive entertainment is one of the most vibrant areas of interest in modern society and is amongst the fastest growing industries in the world. ACE 2012 will bring together leading researchers and practitioners from academia and industry to prese...

  12. Advanced computational electromagnetic methods and applications

    CERN Document Server

    Li, Wenxing; Elsherbeni, Atef; Rahmat-Samii, Yahya

    2015-01-01

    This new resource covers the latest developments in computational electromagnetic methods, with emphasis on cutting-edge applications. This book is designed to extend existing literature to the latest development in computational electromagnetic methods, which are of interest to readers in both academic and industrial areas. The topics include advanced techniques in MoM, FEM and FDTD, spectral domain method, GPU and Phi hardware acceleration, metamaterials, frequency and time domain integral equations, and statistics methods in bio-electromagnetics.

  13. Computational Intelligence Paradigms in Advanced Pattern Classification

    CERN Document Server

    Jain, Lakhmi

    2012-01-01

    This monograph presents selected areas of application of pattern recognition and classification approaches including handwriting recognition, medical image analysis and interpretation, development of cognitive systems for image computer understanding, moving object detection, advanced image filtration and intelligent multi-object labelling and classification. It is directed to the scientists, application engineers, professors, professors and students will find this book useful.

  14. The Anatomical Biological Value on Pretreatment (18)F-fluorodeoxyglucose Positron Emission Tomography Computed Tomography Predicts Response and Survival in Locally Advanced Head and Neck Cancer.

    Science.gov (United States)

    Ashamalla, Hani; Mattes, Malcolm; Guirguis, Adel; Zaidi, Arifa; Mokhtar, Bahaa; Tejwani, Ajay

    2014-05-01

    (18)F-fluorodeoxyglucose positron emission tomography/computed tomography (PET/CT) has become increasingly relevant in the staging of head and neck cancers, but its prognostic value is controversial. The objective of this study was to evaluate different PET/CT parameters for their ability to predict response to therapy and survival in patients treated for head and neck cancer. A total of 28 consecutive patients with a variety of newly diagnosed head and neck cancers underwent PET/CT scanning at our institution before initiating definitive radiation therapy. All underwent a posttreatment PET/CT to gauge tumor response. Pretreatment PET/CT parameters calculated include the standardized uptake value (SUV) and the anatomical biological value (ABV), which is the product of SUV and greatest tumor diameter. Maximum and mean values were studied for both SUV and ABV, and correlated with response rate and survival. The mean pretreatment tumor ABVmax decreased from 35.5 to 7.9 (P = 0.0001). Of the parameters tested, only pretreatment ABVmax was significantly different among those patients with a complete response (CR) and incomplete response (22.8 vs. 65, respectively, P = 0.021). This difference was maximized at a cut-off ABVmax of 30 and those patients with ABVmax < 30 were significantly more likely to have a CR compared to those with ABVmax of ≥ 30 (93.8% vs. 50%, respectively, P = 0.023). The 5-year overall survival was 80% compared to 36%, respectively, (P = 0.028). Multivariate analysis confirmed that ABVmax was an independent prognostic factor. Our data supports the use of PET/CT, and specifically ABVmax, as a prognostic factor in head and neck cancer. Patients who have an ABVmax ≥ 30 were more likely to have a poor outcome with chemoradiation alone, and a more aggressive trimodality approach may be indicated in these patients.

  15. Recent Advances in Predictive (Machine) Learning

    Energy Technology Data Exchange (ETDEWEB)

    Friedman, J

    2004-01-24

    Prediction involves estimating the unknown value of an attribute of a system under study given the values of other measured attributes. In prediction (machine) learning the prediction rule is derived from data consisting of previously solved cases. Most methods for predictive learning were originated many years ago at the dawn of the computer age. Recently two new techniques have emerged that have revitalized the field. These are support vector machines and boosted decision trees. This paper provides an introduction to these two new methods tracing their respective ancestral roots to standard kernel methods and ordinary decision trees.

  16. Predicting Career Advancement with Structural Equation Modelling

    Science.gov (United States)

    Heimler, Ronald; Rosenberg, Stuart; Morote, Elsa-Sofia

    2012-01-01

    Purpose: The purpose of this paper is to use the authors' prior findings concerning basic employability skills in order to determine which skills best predict career advancement potential. Design/methodology/approach: Utilizing survey responses of human resource managers, the employability skills showing the largest relationships to career…

  17. Scientific Discovery through Advanced Computing in Plasma Science

    Science.gov (United States)

    Tang, William

    2005-03-01

    Advanced computing is generally recognized to be an increasingly vital tool for accelerating progress in scientific research during the 21st Century. For example, the Department of Energy's ``Scientific Discovery through Advanced Computing'' (SciDAC) Program was motivated in large measure by the fact that formidable scientific challenges in its research portfolio could best be addressed by utilizing the combination of the rapid advances in super-computing technology together with the emergence of effective new algorithms and computational methodologies. The imperative is to translate such progress into corresponding increases in the performance of the scientific codes used to model complex physical systems such as those encountered in high temperature plasma research. If properly validated against experimental measurements and analytic benchmarks, these codes can provide reliable predictive capability for the behavior of a broad range of complex natural and engineered systems. This talk reviews recent progress and future directions for advanced simulations with some illustrative examples taken from the plasma science applications area. Significant recent progress has been made in both particle and fluid simulations of fine-scale turbulence and large-scale dynamics, giving increasingly good agreement between experimental observations and computational modeling. This was made possible by the combination of access to powerful new computational resources together with innovative advances in analytic and computational methods for developing reduced descriptions of physics phenomena spanning a huge range in time and space scales. In particular, the plasma science community has made excellent progress in developing advanced codes for which computer run-time and problem size scale well with the number of processors on massively parallel machines (MPP's). A good example is the effective usage of the full power of multi-teraflop (multi-trillion floating point computations

  18. Advances in computers improving the web

    CERN Document Server

    Zelkowitz, Marvin

    2010-01-01

    This is volume 78 of Advances in Computers. This series, which began publication in 1960, is the oldest continuously published anthology that chronicles the ever- changing information technology field. In these volumes we publish from 5 to 7 chapters, three times per year, that cover the latest changes to the design, development, use and implications of computer technology on society today.Covers the full breadth of innovations in hardware, software, theory, design, and applications.Many of the in-depth reviews have become standard references that continue to be of significant, lasting value i

  19. Advanced computational approaches to biomedical engineering

    CERN Document Server

    Saha, Punam K; Basu, Subhadip

    2014-01-01

    There has been rapid growth in biomedical engineering in recent decades, given advancements in medical imaging and physiological modelling and sensing systems, coupled with immense growth in computational and network technology, analytic approaches, visualization and virtual-reality, man-machine interaction and automation. Biomedical engineering involves applying engineering principles to the medical and biological sciences and it comprises several topics including biomedicine, medical imaging, physiological modelling and sensing, instrumentation, real-time systems, automation and control, sig

  20. Research Institute for Advanced Computer Science

    Science.gov (United States)

    Gross, Anthony R. (Technical Monitor); Leiner, Barry M.

    2000-01-01

    The Research Institute for Advanced Computer Science (RIACS) carries out basic research and technology development in computer science, in support of the National Aeronautics and Space Administration's missions. RIACS is located at the NASA Ames Research Center. It currently operates under a multiple year grant/cooperative agreement that began on October 1, 1997 and is up for renewal in the year 2002. Ames has been designated NASA's Center of Excellence in Information Technology. In this capacity, Ames is charged with the responsibility to build an Information Technology Research Program that is preeminent within NASA. RIACS serves as a bridge between NASA Ames and the academic community, and RIACS scientists and visitors work in close collaboration with NASA scientists. RIACS has the additional goal of broadening the base of researchers in these areas of importance to the nation's space and aeronautics enterprises. RIACS research focuses on the three cornerstones of information technology research necessary to meet the future challenges of NASA missions: (1) Automated Reasoning for Autonomous Systems. Techniques are being developed enabling spacecraft that will be self-guiding and self-correcting to the extent that they will require little or no human intervention. Such craft will be equipped to independently solve problems as they arise, and fulfill their missions with minimum direction from Earth; (2) Human-Centered Computing. Many NASA missions require synergy between humans and computers, with sophisticated computational aids amplifying human cognitive and perceptual abilities; (3) High Performance Computing and Networking. Advances in the performance of computing and networking continue to have major impact on a variety of NASA endeavors, ranging from modeling and simulation to data analysis of large datasets to collaborative engineering, planning and execution. In addition, RIACS collaborates with NASA scientists to apply information technology research to a

  1. Advanced Computational Methods in Bio-Mechanics.

    Science.gov (United States)

    Al Qahtani, Waleed M S; El-Anwar, Mohamed I

    2018-04-15

    A novel partnership between surgeons and machines, made possible by advances in computing and engineering technology, could overcome many of the limitations of traditional surgery. By extending surgeons' ability to plan and carry out surgical interventions more accurately and with fewer traumas, computer-integrated surgery (CIS) systems could help to improve clinical outcomes and the efficiency of healthcare delivery. CIS systems could have a similar impact on surgery to that long since realised in computer-integrated manufacturing. Mathematical modelling and computer simulation have proved tremendously successful in engineering. Computational mechanics has enabled technological developments in virtually every area of our lives. One of the greatest challenges for mechanists is to extend the success of computational mechanics to fields outside traditional engineering, in particular to biology, the biomedical sciences, and medicine. Biomechanics has significant potential for applications in orthopaedic industry, and the performance arts since skills needed for these activities are visibly related to the human musculoskeletal and nervous systems. Although biomechanics is widely used nowadays in the orthopaedic industry to design orthopaedic implants for human joints, dental parts, external fixations and other medical purposes, numerous researches funded by billions of dollars are still running to build a new future for sports and human healthcare in what is called biomechanics era.

  2. Predictive Models and Computational Embryology

    Science.gov (United States)

    EPA’s ‘virtual embryo’ project is building an integrative systems biology framework for predictive models of developmental toxicity. One schema involves a knowledge-driven adverse outcome pathway (AOP) framework utilizing information from public databases, standardized ontologies...

  3. Computational predictions of zinc oxide hollow structures

    Science.gov (United States)

    Tuoc, Vu Ngoc; Huan, Tran Doan; Thao, Nguyen Thi

    2018-03-01

    Nanoporous materials are emerging as potential candidates for a wide range of technological applications in environment, electronic, and optoelectronics, to name just a few. Within this active research area, experimental works are predominant while theoretical/computational prediction and study of these materials face some intrinsic challenges, one of them is how to predict porous structures. We propose a computationally and technically feasible approach for predicting zinc oxide structures with hollows at the nano scale. The designed zinc oxide hollow structures are studied with computations using the density functional tight binding and conventional density functional theory methods, revealing a variety of promising mechanical and electronic properties, which can potentially find future realistic applications.

  4. Advances of evolutionary computation methods and operators

    CERN Document Server

    Cuevas, Erik; Oliva Navarro, Diego Alberto

    2016-01-01

    The goal of this book is to present advances that discuss alternative Evolutionary Computation (EC) developments and non-conventional operators which have proved to be effective in the solution of several complex problems. The book has been structured so that each chapter can be read independently from the others. The book contains nine chapters with the following themes: 1) Introduction, 2) the Social Spider Optimization (SSO), 3) the States of Matter Search (SMS), 4) the collective animal behavior (CAB) algorithm, 5) the Allostatic Optimization (AO) method, 6) the Locust Search (LS) algorithm, 7) the Adaptive Population with Reduced Evaluations (APRE) method, 8) the multimodal CAB, 9) the constrained SSO method.

  5. ATCA for Machines-- Advanced Telecommunications Computing Architecture

    Energy Technology Data Exchange (ETDEWEB)

    Larsen, R.S.; /SLAC

    2008-04-22

    The Advanced Telecommunications Computing Architecture is a new industry open standard for electronics instrument modules and shelves being evaluated for the International Linear Collider (ILC). It is the first industrial standard designed for High Availability (HA). ILC availability simulations have shown clearly that the capabilities of ATCA are needed in order to achieve acceptable integrated luminosity. The ATCA architecture looks attractive for beam instruments and detector applications as well. This paper provides an overview of ongoing R&D including application of HA principles to power electronics systems.

  6. ATCA for Machines-- Advanced Telecommunications Computing Architecture

    International Nuclear Information System (INIS)

    Larsen, R

    2008-01-01

    The Advanced Telecommunications Computing Architecture is a new industry open standard for electronics instrument modules and shelves being evaluated for the International Linear Collider (ILC). It is the first industrial standard designed for High Availability (HA). ILC availability simulations have shown clearly that the capabilities of ATCA are needed in order to achieve acceptable integrated luminosity. The ATCA architecture looks attractive for beam instruments and detector applications as well. This paper provides an overview of ongoing R and D including application of HA principles to power electronics systems

  7. An introduction to NASA's advanced computing program: Integrated computing systems in advanced multichip modules

    Science.gov (United States)

    Fang, Wai-Chi; Alkalai, Leon

    1996-01-01

    Recent changes within NASA's space exploration program favor the design, implementation, and operation of low cost, lightweight, small and micro spacecraft with multiple launches per year. In order to meet the future needs of these missions with regard to the use of spacecraft microelectronics, NASA's advanced flight computing (AFC) program is currently considering industrial cooperation and advanced packaging architectures. In relation to this, the AFC program is reviewed, considering the design and implementation of NASA's AFC multichip module.

  8. Medical image computing for computer-supported diagnostics and therapy. Advances and perspectives.

    Science.gov (United States)

    Handels, H; Ehrhardt, J

    2009-01-01

    Medical image computing has become one of the most challenging fields in medical informatics. In image-based diagnostics of the future software assistance will become more and more important, and image analysis systems integrating advanced image computing methods are needed to extract quantitative image parameters to characterize the state and changes of image structures of interest (e.g. tumors, organs, vessels, bones etc.) in a reproducible and objective way. Furthermore, in the field of software-assisted and navigated surgery medical image computing methods play a key role and have opened up new perspectives for patient treatment. However, further developments are needed to increase the grade of automation, accuracy, reproducibility and robustness. Moreover, the systems developed have to be integrated into the clinical workflow. For the development of advanced image computing systems methods of different scientific fields have to be adapted and used in combination. The principal methodologies in medical image computing are the following: image segmentation, image registration, image analysis for quantification and computer assisted image interpretation, modeling and simulation as well as visualization and virtual reality. Especially, model-based image computing techniques open up new perspectives for prediction of organ changes and risk analysis of patients and will gain importance in diagnostic and therapy of the future. From a methodical point of view the authors identify the following future trends and perspectives in medical image computing: development of optimized application-specific systems and integration into the clinical workflow, enhanced computational models for image analysis and virtual reality training systems, integration of different image computing methods, further integration of multimodal image data and biosignals and advanced methods for 4D medical image computing. The development of image analysis systems for diagnostic support or

  9. Use of prediction equations to determine the accuracy of whole-body fat and fat-free mass and appendicular skeletal muscle mass measurements from a single abdominal image using computed tomography in advanced cancer patients.

    Science.gov (United States)

    Kilgour, Robert D; Cardiff, Katrina; Rosenthall, Leonard; Lucar, Enriqueta; Trutschnigg, Barbara; Vigano, Antonio

    2016-01-01

    Measurements of body composition using dual-energy X-ray absorptiometry (DXA) and single abdominal images from computed tomography (CT) in advanced cancer patients (ACP) have important diagnostic and prognostic value. The question arises as to whether CT scans can serve as surrogates for DXA in terms of whole-body fat-free mass (FFM), whole-body fat mass (FM), and appendicular skeletal muscle (ASM) mass. Predictive equations to estimate body composition for ACP from CT images have been proposed (Mourtzakis et al. 2008; Appl. Physiol. Nutr. Metabol. 33(5): 997-1006); however, these equations have yet to be validated in an independent cohort of ACP. Thus, this study evaluated the accuracy of these equations in estimating FFM, FM, and ASM mass using CT images at the level of the third lumbar vertebrae and compared these values with DXA measurements. FFM, FM, and ASM mass were estimated from the prediction equations proposed by Mourtzakis and colleagues (2008) using single abdominal CT images from 43 ACP and were compared with whole-body DXA scans using Spearman correlations and Bland-Altman analyses. Despite a moderate to high correlation between the actual (DXA) and predicted (CT) values for FM (rho = 0.93; p ≤ 0.001), FFM (rho = 0.78; p ≤ 0.001), and ASM mass (rho = 0.70; p ≤ 0.001), Bland-Altman analyses revealed large range-of-agreement differences between the 2 methods (29.39 kg for FFM, 15.47 kg for FM, and 3.99 kg for ASM mass). Based on the magnitude of these differences, we concluded that prediction equations using single abdominal CT images have poor accuracy, cannot be considered as surrogates for DXA, and may have limited clinical utility.

  10. International Conference on Computers and Advanced Technology in Education

    CERN Document Server

    Advanced Information Technology in Education

    2012-01-01

    The volume includes a set of selected papers extended and revised from the 2011 International Conference on Computers and Advanced Technology in Education. With the development of computers and advanced technology, the human social activities are changing basically. Education, especially the education reforms in different countries, has been experiencing the great help from the computers and advanced technology. Generally speaking, education is a field which needs more information, while the computers, advanced technology and internet are a good information provider. Also, with the aid of the computer and advanced technology, persons can make the education an effective combination. Therefore, computers and advanced technology should be regarded as an important media in the modern education. Volume Advanced Information Technology in Education is to provide a forum for researchers, educators, engineers, and government officials involved in the general areas of computers and advanced technology in education to d...

  11. Computational advances in transition phase analysis

    International Nuclear Information System (INIS)

    Morita, K.; Kondo, S.; Tobita, Y.; Shirakawa, N.; Brear, D.J.; Fischer, E.A.

    1994-01-01

    In this paper, historical perspective and recent advances are reviewed on computational technologies to evaluate a transition phase of core disruptive accidents in liquid-metal fast reactors. An analysis of the transition phase requires treatment of multi-phase multi-component thermohydraulics coupled with space- and energy-dependent neutron kinetics. Such a comprehensive modeling effort was initiated when the program of SIMMER-series computer code development was initiated in the late 1970s in the USA. Successful application of the latest SIMMER-II in USA, western Europe and Japan have proved its effectiveness, but, at the same time, several areas that require further research have been identified. Based on the experience and lessons learned during the SIMMER-II application through 1980s, a new project of SIMMER-III development is underway at the Power Reactor and Nuclear Fuel Development Corporation (PNC), Japan. The models and methods of SIMMER-III are briefly described with emphasis on recent advances in multi-phase multi-component fluid dynamics technologies and their expected implication on a future reliable transition phase analysis. (author)

  12. Advanced Simulation and Computing FY17 Implementation Plan, Version 0

    Energy Technology Data Exchange (ETDEWEB)

    McCoy, Michel [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Archer, Bill [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Hendrickson, Bruce [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Wade, Doug [National Nuclear Security Administration (NNSA), Washington, DC (United States). Office of Advanced Simulation and Computing and Institutional Research and Development; Hoang, Thuc [National Nuclear Security Administration (NNSA), Washington, DC (United States). Computational Systems and Software Environment

    2016-08-29

    The Stockpile Stewardship Program (SSP) is an integrated technical program for maintaining the safety, surety, and reliability of the U.S. nuclear stockpile. The SSP uses nuclear test data, computational modeling and simulation, and experimental facilities to advance understanding of nuclear weapons. It includes stockpile surveillance, experimental research, development and engineering programs, and an appropriately scaled production capability to support stockpile requirements. This integrated national program requires the continued use of experimental facilities and programs, and the computational capabilities to support these programs. The Advanced Simulation and Computing Program (ASC) is a cornerstone of the SSP, providing simulation capabilities and computational resources that support annual stockpile assessment and certification, study advanced nuclear weapons design and manufacturing processes, analyze accident scenarios and weapons aging, and provide the tools to enable stockpile Life Extension Programs (LEPs) and the resolution of Significant Finding Investigations (SFIs). This requires a balance of resource, including technical staff, hardware, simulation software, and computer science solutions. ASC is now focused on increasing predictive capabilities in a three-dimensional (3D) simulation environment while maintaining support to the SSP. The program continues to improve its unique tools for solving progressively more difficult stockpile problems (sufficient resolution, dimensionality, and scientific details), and quantifying critical margins and uncertainties. Resolving each issue requires increasingly difficult analyses because the aging process has progressively moved the stockpile further away from the original test base. Where possible, the program also enables the use of high performance computing (HPC) and simulation tools to address broader national security needs, such as foreign nuclear weapon assessments and counter nuclear terrorism.

  13. Transport modeling and advanced computer techniques

    International Nuclear Information System (INIS)

    Wiley, J.C.; Ross, D.W.; Miner, W.H. Jr.

    1988-11-01

    A workshop was held at the University of Texas in June 1988 to consider the current state of transport codes and whether improved user interfaces would make the codes more usable and accessible to the fusion community. Also considered was the possibility that a software standard could be devised to ease the exchange of routines between groups. It was noted that two of the major obstacles to exchanging routines now are the variety of geometrical representation and choices of units. While the workshop formulated no standards, it was generally agreed that good software engineering would aid in the exchange of routines, and that a continued exchange of ideas between groups would be worthwhile. It seems that before we begin to discuss software standards we should review the current state of computer technology --- both hardware and software to see what influence recent advances might have on our software goals. This is done in this paper

  14. Advanced proton imaging in computed tomography

    CERN Document Server

    Mattiazzo, S; Giubilato, P; Pantano, D; Pozzobon, N; Snoeys, W; Wyss, J

    2015-01-01

    In recent years the use of hadrons for cancer radiation treatment has grown in importance, and many facilities are currently operational or under construction worldwide. To fully exploit the therapeutic advantages offered by hadron therapy, precise body imaging for accurate beam delivery is decisive. Proton computed tomography (pCT) scanners, currently in their R&D phase, provide the ultimate 3D imaging for hadrons treatment guidance. A key component of a pCT scanner is the detector used to track the protons, which has great impact on the scanner performances and ultimately limits its maximum speed. In this article, a novel proton-tracking detector was presented that would have higher scanning speed, better spatial resolution and lower material budget with respect to present state-of-the-art detectors, leading to enhanced performances. This advancement in performances is achieved by employing the very latest development in monolithic active pixel detectors (to build high granularity, low material budget, ...

  15. Advances in Integrated Computational Materials Engineering "ICME"

    Science.gov (United States)

    Hirsch, Jürgen

    The methods of Integrated Computational Materials Engineering that were developed and successfully applied for Aluminium have been constantly improved. The main aspects and recent advances of integrated material and process modeling are simulations of material properties like strength and forming properties and for the specific microstructure evolution during processing (rolling, extrusion, annealing) under the influence of material constitution and process variations through the production process down to the final application. Examples are discussed for the through-process simulation of microstructures and related properties of Aluminium sheet, including DC ingot casting, pre-heating and homogenization, hot and cold rolling, final annealing. New results are included of simulation solution annealing and age hardening of 6xxx alloys for automotive applications. Physically based quantitative descriptions and computer assisted evaluation methods are new ICME methods of integrating new simulation tools also for customer applications, like heat affected zones in welding of age hardening alloys. The aspects of estimating the effect of specific elements due to growing recycling volumes requested also for high end Aluminium products are also discussed, being of special interest in the Aluminium producing industries.

  16. OPENING REMARKS: Scientific Discovery through Advanced Computing

    Science.gov (United States)

    Strayer, Michael

    2006-01-01

    Good morning. Welcome to SciDAC 2006 and Denver. I share greetings from the new Undersecretary for Energy, Ray Orbach. Five years ago SciDAC was launched as an experiment in computational science. The goal was to form partnerships among science applications, computer scientists, and applied mathematicians to take advantage of the potential of emerging terascale computers. This experiment has been a resounding success. SciDAC has emerged as a powerful concept for addressing some of the biggest challenges facing our world. As significant as these successes were, I believe there is also significance in the teams that achieved them. In addition to their scientific aims these teams have advanced the overall field of computational science and set the stage for even larger accomplishments as we look ahead to SciDAC-2. I am sure that many of you are expecting to hear about the results of our current solicitation for SciDAC-2. I’m afraid we are not quite ready to make that announcement. Decisions are still being made and we will announce the results later this summer. Nearly 250 unique proposals were received and evaluated, involving literally thousands of researchers, postdocs, and students. These collectively requested more than five times our expected budget. This response is a testament to the success of SciDAC in the community. In SciDAC-2 our budget has been increased to about 70 million for FY 2007 and our partnerships have expanded to include the Environment and National Security missions of the Department. The National Science Foundation has also joined as a partner. These new partnerships are expected to expand the application space of SciDAC, and broaden the impact and visibility of the program. We have, with our recent solicitation, expanded to turbulence, computational biology, and groundwater reactive modeling and simulation. We are currently talking with the Department’s applied energy programs about risk assessment, optimization of complex systems - such

  17. Soft Computing Methods for Disulfide Connectivity Prediction.

    Science.gov (United States)

    Márquez-Chamorro, Alfonso E; Aguilar-Ruiz, Jesús S

    2015-01-01

    The problem of protein structure prediction (PSP) is one of the main challenges in structural bioinformatics. To tackle this problem, PSP can be divided into several subproblems. One of these subproblems is the prediction of disulfide bonds. The disulfide connectivity prediction problem consists in identifying which nonadjacent cysteines would be cross-linked from all possible candidates. Determining the disulfide bond connectivity between the cysteines of a protein is desirable as a previous step of the 3D PSP, as the protein conformational search space is highly reduced. The most representative soft computing approaches for the disulfide bonds connectivity prediction problem of the last decade are summarized in this paper. Certain aspects, such as the different methodologies based on soft computing approaches (artificial neural network or support vector machine) or features of the algorithms, are used for the classification of these methods.

  18. Advanced intelligent computational technologies and decision support systems

    CERN Document Server

    Kountchev, Roumen

    2014-01-01

    This book offers a state of the art collection covering themes related to Advanced Intelligent Computational Technologies and Decision Support Systems which can be applied to fields like healthcare assisting the humans in solving problems. The book brings forward a wealth of ideas, algorithms and case studies in themes like: intelligent predictive diagnosis; intelligent analyzing of medical images; new format for coding of single and sequences of medical images; Medical Decision Support Systems; diagnosis of Down’s syndrome; computational perspectives for electronic fetal monitoring; efficient compression of CT Images; adaptive interpolation and halftoning for medical images; applications of artificial neural networks for real-life problems solving; present and perspectives for Electronic Healthcare Record Systems; adaptive approaches for noise reduction in sequences of CT images etc.

  19. Application of advanced electronics to a future spacecraft computer design

    Science.gov (United States)

    Carney, P. C.

    1980-01-01

    Advancements in hardware and software technology are summarized with specific emphasis on spacecraft computer capabilities. Available state of the art technology is reviewed and candidate architectures are defined.

  20. Advances in computational actinide chemistry in China

    Energy Technology Data Exchange (ETDEWEB)

    Wang, Dongqi; Wu, Jingyi; Chai, Zhifang [Chinese Academy of Sciences, Beijing (China). Multidisciplinary Initiative Center; Su, Jing [Chinese Academy of Sciences, Shanghai (China). Div. of Nuclear Materials Science and Engineering; Li, Jun [Tsinghua Univ., Beijing (China). Dept. of Chemistry and Laboratory of Organic Optoelectronics and Molecular Engineering

    2014-04-01

    The advances in computational actinide chemistry made in China are reviewed. Several areas relevant to chemistry of actinides in gas, liquid, and solid phases have been explored. However, we limit the scope to selected contributions in the chemistry of molecular actinide systems in gas and liquid phases. These studies may be classified into two categories: treatment of relativistic effects, which cover the development of two- and four-component Hamiltonians and the optimization of relativistic pseudopotentials, and the applications of theoretical methods in actinide chemistry. The applications include (1) the electronic structures of actinocene, noble gas complexes, An-C multiple bonding compounds, uranyl and its isoelectronic species, fluorides and oxides, molecular systems with metal-metal bonding in their isolated forms (U{sub 2}, Pu{sub 2}) and in fullerene (U{sub 2} rate at C{sub 60}), and the excited states of actinide complexes; (2) chemical reactions, including oxidation, hydrolysis of UF{sub 6}, ligand exchange, reactivities of thorium oxo and sulfido metallocenes, CO{sub 2}/CS{sub 2} functionalization promoted by trivalent uranium complex; and (3) migration of actinides in the environment. A future outlook is discussed. (orig.)

  1. First Responders Guide to Computer Forensics: Advanced Topics

    National Research Council Canada - National Science Library

    Nolan, Richard; Baker, Marie; Branson, Jake; Hammerstein, Josh; Rush, Kris; Waits, Cal; Schweinsberg, Elizabeth

    2005-01-01

    First Responders Guide to Computer Forensics: Advanced Topics expands on the technical material presented in SEI handbook CMU/SEI-2005-HB-001, First Responders Guide to Computer Forensics [Nolan 05...

  2. UNEDF: Advanced Scientific Computing Transforms the Low-Energy Nuclear Many-Body Problem

    International Nuclear Information System (INIS)

    Stoitsov, Mario; Nam, Hai Ah; Nazarewicz, Witold; Bulgac, Aurel; Hagen, Gaute; Kortelainen, E.M.; Pei, Junchen; Roche, K.J.; Schunck, N.; Thompson, I.; Vary, J.P.; Wild, S.

    2011-01-01

    The UNEDF SciDAC collaboration of nuclear theorists, applied mathematicians, and computer scientists is developing a comprehensive description of nuclei and their reactions that delivers maximum predictive power with quantified uncertainties. This paper illustrates significant milestones accomplished by UNEDF through integration of the theoretical approaches, advanced numerical algorithms, and leadership class computational resources.

  3. Advanced topics in security computer system design

    International Nuclear Information System (INIS)

    Stachniak, D.E.; Lamb, W.R.

    1989-01-01

    The capability, performance, and speed of contemporary computer processors, plus the associated performance capability of the operating systems accommodating the processors, have enormously expanded the scope of possibilities for designers of nuclear power plant security computer systems. This paper addresses the choices that could be made by a designer of security computer systems working with contemporary computers and describes the improvement in functionality of contemporary security computer systems based on an optimally chosen design. Primary initial considerations concern the selection of (a) the computer hardware and (b) the operating system. Considerations for hardware selection concern processor and memory word length, memory capacity, and numerous processor features

  4. RNA secondary structure prediction using soft computing.

    Science.gov (United States)

    Ray, Shubhra Sankar; Pal, Sankar K

    2013-01-01

    Prediction of RNA structure is invaluable in creating new drugs and understanding genetic diseases. Several deterministic algorithms and soft computing-based techniques have been developed for more than a decade to determine the structure from a known RNA sequence. Soft computing gained importance with the need to get approximate solutions for RNA sequences by considering the issues related with kinetic effects, cotranscriptional folding, and estimation of certain energy parameters. A brief description of some of the soft computing-based techniques, developed for RNA secondary structure prediction, is presented along with their relevance. The basic concepts of RNA and its different structural elements like helix, bulge, hairpin loop, internal loop, and multiloop are described. These are followed by different methodologies, employing genetic algorithms, artificial neural networks, and fuzzy logic. The role of various metaheuristics, like simulated annealing, particle swarm optimization, ant colony optimization, and tabu search is also discussed. A relative comparison among different techniques, in predicting 12 known RNA secondary structures, is presented, as an example. Future challenging issues are then mentioned.

  5. Computational intelligence for big data analysis frontier advances and applications

    CERN Document Server

    Dehuri, Satchidananda; Sanyal, Sugata

    2015-01-01

    The work presented in this book is a combination of theoretical advancements of big data analysis, cloud computing, and their potential applications in scientific computing. The theoretical advancements are supported with illustrative examples and its applications in handling real life problems. The applications are mostly undertaken from real life situations. The book discusses major issues pertaining to big data analysis using computational intelligence techniques and some issues of cloud computing. An elaborate bibliography is provided at the end of each chapter. The material in this book includes concepts, figures, graphs, and tables to guide researchers in the area of big data analysis and cloud computing.

  6. Advanced Technologies, Embedded and Multimedia for Human-Centric Computing

    CERN Document Server

    Chao, Han-Chieh; Deng, Der-Jiunn; Park, James; HumanCom and EMC 2013

    2014-01-01

    The theme of HumanCom and EMC are focused on the various aspects of human-centric computing for advances in computer science and its applications, embedded and multimedia computing and provides an opportunity for academic and industry professionals to discuss the latest issues and progress in the area of human-centric computing. And the theme of EMC (Advanced in Embedded and Multimedia Computing) is focused on the various aspects of embedded system, smart grid, cloud and multimedia computing, and it provides an opportunity for academic, industry professionals to discuss the latest issues and progress in the area of embedded and multimedia computing. Therefore this book will be include the various theories and practical applications in human-centric computing and embedded and multimedia computing.

  7. Recent Advances in Computational Mechanics of the Human Knee Joint

    Science.gov (United States)

    Kazemi, M.; Dabiri, Y.; Li, L. P.

    2013-01-01

    Computational mechanics has been advanced in every area of orthopedic biomechanics. The objective of this paper is to provide a general review of the computational models used in the analysis of the mechanical function of the knee joint in different loading and pathological conditions. Major review articles published in related areas are summarized first. The constitutive models for soft tissues of the knee are briefly discussed to facilitate understanding the joint modeling. A detailed review of the tibiofemoral joint models is presented thereafter. The geometry reconstruction procedures as well as some critical issues in finite element modeling are also discussed. Computational modeling can be a reliable and effective method for the study of mechanical behavior of the knee joint, if the model is constructed correctly. Single-phase material models have been used to predict the instantaneous load response for the healthy knees and repaired joints, such as total and partial meniscectomies, ACL and PCL reconstructions, and joint replacements. Recently, poromechanical models accounting for fluid pressurization in soft tissues have been proposed to study the viscoelastic response of the healthy and impaired knee joints. While the constitutive modeling has been considerably advanced at the tissue level, many challenges still exist in applying a good material model to three-dimensional joint simulations. A complete model validation at the joint level seems impossible presently, because only simple data can be obtained experimentally. Therefore, model validation may be concentrated on the constitutive laws using multiple mechanical tests of the tissues. Extensive model verifications at the joint level are still crucial for the accuracy of the modeling. PMID:23509602

  8. Second International Conference on Advanced Computing, Networking and Informatics

    CERN Document Server

    Mohapatra, Durga; Konar, Amit; Chakraborty, Aruna

    2014-01-01

    Advanced Computing, Networking and Informatics are three distinct and mutually exclusive disciplines of knowledge with no apparent sharing/overlap among them. However, their convergence is observed in many real world applications, including cyber-security, internet banking, healthcare, sensor networks, cognitive radio, pervasive computing amidst many others. This two-volume proceedings explore the combined use of Advanced Computing and Informatics in the next generation wireless networks and security, signal and image processing, ontology and human-computer interfaces (HCI). The two volumes together include 148 scholarly papers, which have been accepted for presentation from over 640 submissions in the second International Conference on Advanced Computing, Networking and Informatics, 2014, held in Kolkata, India during June 24-26, 2014. The first volume includes innovative computing techniques and relevant research results in informatics with selective applications in pattern recognition, signal/image process...

  9. Advances in Future Computer and Control Systems v.1

    CERN Document Server

    Lin, Sally; 2012 International Conference on Future Computer and Control Systems(FCCS2012)

    2012-01-01

    FCCS2012 is an integrated conference concentrating its focus on Future Computer and Control Systems. “Advances in Future Computer and Control Systems” presents the proceedings of the 2012 International Conference on Future Computer and Control Systems(FCCS2012) held April 21-22,2012, in Changsha, China including recent research results on Future Computer and Control Systems of researchers from all around the world.

  10. Advances in Future Computer and Control Systems v.2

    CERN Document Server

    Lin, Sally; 2012 International Conference on Future Computer and Control Systems(FCCS2012)

    2012-01-01

    FCCS2012 is an integrated conference concentrating its focus on Future Computer and Control Systems. “Advances in Future Computer and Control Systems” presents the proceedings of the 2012 International Conference on Future Computer and Control Systems(FCCS2012) held April 21-22,2012, in Changsha, China including recent research results on Future Computer and Control Systems of researchers from all around the world.

  11. Thermal sensation prediction by soft computing methodology.

    Science.gov (United States)

    Jović, Srđan; Arsić, Nebojša; Vilimonović, Jovana; Petković, Dalibor

    2016-12-01

    Thermal comfort in open urban areas is very factor based on environmental point of view. Therefore it is need to fulfill demands for suitable thermal comfort during urban planning and design. Thermal comfort can be modeled based on climatic parameters and other factors. The factors are variables and they are changed throughout the year and days. Therefore there is need to establish an algorithm for thermal comfort prediction according to the input variables. The prediction results could be used for planning of time of usage of urban areas. Since it is very nonlinear task, in this investigation was applied soft computing methodology in order to predict the thermal comfort. The main goal was to apply extreme leaning machine (ELM) for forecasting of physiological equivalent temperature (PET) values. Temperature, pressure, wind speed and irradiance were used as inputs. The prediction results are compared with some benchmark models. Based on the results ELM can be used effectively in forecasting of PET. Copyright © 2016 Elsevier Ltd. All rights reserved.

  12. Power-efficient computer architectures recent advances

    CERN Document Server

    Själander, Magnus; Kaxiras, Stefanos

    2014-01-01

    As Moore's Law and Dennard scaling trends have slowed, the challenges of building high-performance computer architectures while maintaining acceptable power efficiency levels have heightened. Over the past ten years, architecture techniques for power efficiency have shifted from primarily focusing on module-level efficiencies, toward more holistic design styles based on parallelism and heterogeneity. This work highlights and synthesizes recent techniques and trends in power-efficient computer architecture.Table of Contents: Introduction / Voltage and Frequency Management / Heterogeneity and Sp

  13. Advanced Computational Methods for Monte Carlo Calculations

    Energy Technology Data Exchange (ETDEWEB)

    Brown, Forrest B. [Los Alamos National Lab. (LANL), Los Alamos, NM (United States)

    2018-01-12

    This course is intended for graduate students who already have a basic understanding of Monte Carlo methods. It focuses on advanced topics that may be needed for thesis research, for developing new state-of-the-art methods, or for working with modern production Monte Carlo codes.

  14. Advances in Computer, Communication, Control and Automation

    CERN Document Server

    011 International Conference on Computer, Communication, Control and Automation

    2012-01-01

    The volume includes a set of selected papers extended and revised from the 2011 International Conference on Computer, Communication, Control and Automation (3CA 2011). 2011 International Conference on Computer, Communication, Control and Automation (3CA 2011) has been held in Zhuhai, China, November 19-20, 2011. This volume  topics covered include signal and Image processing, speech and audio Processing, video processing and analysis, artificial intelligence, computing and intelligent systems, machine learning, sensor and neural networks, knowledge discovery and data mining, fuzzy mathematics and Applications, knowledge-based systems, hybrid systems modeling and design, risk analysis and management, system modeling and simulation. We hope that researchers, graduate students and other interested readers benefit scientifically from the proceedings and also find it stimulating in the process.

  15. Recent advances in computational structural reliability analysis methods

    Science.gov (United States)

    Thacker, Ben H.; Wu, Y.-T.; Millwater, Harry R.; Torng, Tony Y.; Riha, David S.

    1993-10-01

    The goal of structural reliability analysis is to determine the probability that the structure will adequately perform its intended function when operating under the given environmental conditions. Thus, the notion of reliability admits the possibility of failure. Given the fact that many different modes of failure are usually possible, achievement of this goal is a formidable task, especially for large, complex structural systems. The traditional (deterministic) design methodology attempts to assure reliability by the application of safety factors and conservative assumptions. However, the safety factor approach lacks a quantitative basis in that the level of reliability is never known and usually results in overly conservative designs because of compounding conservatisms. Furthermore, problem parameters that control the reliability are not identified, nor their importance evaluated. A summary of recent advances in computational structural reliability assessment is presented. A significant level of activity in the research and development community was seen recently, much of which was directed towards the prediction of failure probabilities for single mode failures. The focus is to present some early results and demonstrations of advanced reliability methods applied to structural system problems. This includes structures that can fail as a result of multiple component failures (e.g., a redundant truss), or structural components that may fail due to multiple interacting failure modes (e.g., excessive deflection, resonate vibration, or creep rupture). From these results, some observations and recommendations are made with regard to future research needs.

  16. CISM-IUTAM School on Advanced Turbulent Flow Computations

    CERN Document Server

    Krause, Egon

    2000-01-01

    This book collects the lecture notes concerning the IUTAM School on Advanced Turbulent Flow Computations held at CISM in Udine September 7–11, 1998. The course was intended for scientists, engineers and post-graduate students interested in the application of advanced numerical techniques for simulating turbulent flows. The topic comprises two closely connected main subjects: modelling and computation, mesh pionts necessary to simulate complex turbulent flow.

  17. 3rd International Conference on Advanced Computing, Networking and Informatics

    CERN Document Server

    Mohapatra, Durga; Chaki, Nabendu

    2016-01-01

    Advanced Computing, Networking and Informatics are three distinct and mutually exclusive disciplines of knowledge with no apparent sharing/overlap among them. However, their convergence is observed in many real world applications, including cyber-security, internet banking, healthcare, sensor networks, cognitive radio, pervasive computing amidst many others. This two volume proceedings explore the combined use of Advanced Computing and Informatics in the next generation wireless networks and security, signal and image processing, ontology and human-computer interfaces (HCI). The two volumes together include 132 scholarly articles, which have been accepted for presentation from over 550 submissions in the Third International Conference on Advanced Computing, Networking and Informatics, 2015, held in Bhubaneswar, India during June 23–25, 2015.

  18. Predictable nonlinear dynamics: Advances and limitations

    International Nuclear Information System (INIS)

    Anosov, L.A.; Butkovskii, O.Y.; Kravtsov, Y.A.; Surovyatkina, E.D.

    1996-01-01

    Methods for reconstruction chaotic dynamical system structure directly from experimental time series are described. Effectiveness of general methods is illustrated with the results of numerical simulation. It is of common interest that from the single time series it is possible to reconstruct a set of interconnected variables. Predictive power of dynamical models, provided by the nonlinear dynamics inverse problem solution, is limited firstly by the noise level in the system under study and is characterized by the horizon of predictability. New physical results are presented, concerning nonstationary and bifurcation nonlinear systems: (1) algorithms for revealing of nonstationarity in random-like chaotic time-series are suggested based on discriminant analysis with nonlinear discriminant function; (2) an opportunity is established to predict the final state in bifurcation system with quickly varying control parameters; (3) hysteresis is founded out in bifurcation system with quickly varying parameters; (4) delayed correlation left-angle noise-prediction error right-angle in chaotic systems is revealed. copyright 1996 American Institute of Physics

  19. Advances in Computer Science and Education

    CERN Document Server

    Huang, Xiong

    2012-01-01

    CSE2011 is an integrated conference concentration its focus on computer science and education. In the proceeding, you can learn much more knowledge about computer science and education of researchers from all around the world. The main role of the proceeding is to be used as an exchange pillar for researchers who are working in the mentioned fields. In order to meet the high quality of Springer, AISC series, the organization committee has made their efforts to do the following things. Firstly, poor quality paper has been refused after reviewing course by anonymous referee experts. Secondly, periodically review meetings have been held around the reviewers about five times for exchanging reviewing suggestions. Finally, the conference organizers had several preliminary sessions before the conference. Through efforts of different people and departments, the conference will be successful and fruitful

  20. Defense Science Board Report on Advanced Computing

    Science.gov (United States)

    2009-03-01

    computers  will  require extensive  research and development  to have a chance of  reaching  the  exascale   level.  Even  if  exascale   level machines  can...generations of petascale and then  exascale   level  computing  capability.  This  includes  both  the  hardware  and  the  complex  software  that  may  be...required  for  the  architectures  needed  for  exacscale  capability.  The  challenges  are  extremely  daunting,  especially  at  the  exascale

  1. ASDA - Advanced Suit Design Analyzer computer program

    Science.gov (United States)

    Bue, Grant C.; Conger, Bruce C.; Iovine, John V.; Chang, Chi-Min

    1992-01-01

    An ASDA model developed to evaluate the heat and mass transfer characteristics of advanced pressurized suit design concepts for low pressure or vacuum planetary applications is presented. The model is based on a generalized 3-layer suit that uses the Systems Integrated Numerical Differencing Analyzer '85 in conjunction with a 41-node FORTRAN routine. The latter simulates the transient heat transfer and respiratory processes of a human body in a suited environment. The user options for the suit encompass a liquid cooled garment, a removable jacket, a CO2/H2O permeable layer, and a phase change layer.

  2. Guest editorial preface : Special Issue on Advances in Computer Entertainment

    NARCIS (Netherlands)

    Nijholt, Anton; Romão, Teresa; Cheok, Adrian D.

    2013-01-01

    This special issue of the International Journal of Creative Interfaces and Computer Graphics contains a selection of papers from ACE 2012, the 9th International Conference on Advances in Computer Entertainment (Nijholt et al., 2012). ACE is the leading scientific forum for dissemination of

  3. Advanced Computing Tools and Models for Accelerator Physics

    International Nuclear Information System (INIS)

    Ryne, Robert; Ryne, Robert D.

    2008-01-01

    This paper is based on a transcript of my EPAC'08 presentation on advanced computing tools for accelerator physics. Following an introduction I present several examples, provide a history of the development of beam dynamics capabilities, and conclude with thoughts on the future of large scale computing in accelerator physics

  4. Advances in Computing and Information Technology : Proceedings of the Second International Conference on Advances in Computing and Information Technology

    CERN Document Server

    Nagamalai, Dhinaharan; Chaki, Nabendu

    2013-01-01

    The international conference on Advances in Computing and Information technology (ACITY 2012) provides an excellent international forum for both academics and professionals for sharing knowledge and results in theory, methodology and applications of Computer Science and Information Technology. The Second International Conference on Advances in Computing and Information technology (ACITY 2012), held in Chennai, India, during July 13-15, 2012, covered a number of topics in all major fields of Computer Science and Information Technology including: networking and communications, network security and applications, web and internet computing, ubiquitous computing, algorithms, bioinformatics, digital image processing and pattern recognition, artificial intelligence, soft computing and applications. Upon a strength review process, a number of high-quality, presenting not only innovative ideas but also a founded evaluation and a strong argumentation of the same, were selected and collected in the present proceedings, ...

  5. UNEDF: Advanced Scientific Computing Collaboration Transforms the Low-Energy Nuclear Many-Body Problem

    International Nuclear Information System (INIS)

    Nam, H; Stoitsov, M; Nazarewicz, W; Hagen, G; Kortelainen, M; Pei, J C; Bulgac, A; Maris, P; Vary, J P; Roche, K J; Schunck, N; Thompson, I; Wild, S M

    2012-01-01

    The demands of cutting-edge science are driving the need for larger and faster computing resources. With the rapidly growing scale of computing systems and the prospect of technologically disruptive architectures to meet these needs, scientists face the challenge of effectively using complex computational resources to advance scientific discovery. Multi-disciplinary collaborating networks of researchers with diverse scientific backgrounds are needed to address these complex challenges. The UNEDF SciDAC collaboration of nuclear theorists, applied mathematicians, and computer scientists is developing a comprehensive description of nuclei and their reactions that delivers maximum predictive power with quantified uncertainties. This paper describes UNEDF and identifies attributes that classify it as a successful computational collaboration. We illustrate significant milestones accomplished by UNEDF through integrative solutions using the most reliable theoretical approaches, most advanced algorithms, and leadership-class computational resources.

  6. Extending the horizons advances in computing, optimization, and decision technologies

    CERN Document Server

    Joseph, Anito; Mehrotra, Anuj; Trick, Michael

    2007-01-01

    Computer Science and Operations Research continue to have a synergistic relationship and this book represents the results of cross-fertilization between OR/MS and CS/AI. It is this interface of OR/CS that makes possible advances that could not have been achieved in isolation. Taken collectively, these articles are indicative of the state-of-the-art in the interface between OR/MS and CS/AI and of the high caliber of research being conducted by members of the INFORMS Computing Society. EXTENDING THE HORIZONS: Advances in Computing, Optimization, and Decision Technologies is a volume that presents the latest, leading research in the design and analysis of algorithms, computational optimization, heuristic search and learning, modeling languages, parallel and distributed computing, simulation, computational logic and visualization. This volume also emphasizes a variety of novel applications in the interface of CS, AI, and OR/MS.

  7. Advances in Reactor Physics, Mathematics and Computation. Volume 1

    Energy Technology Data Exchange (ETDEWEB)

    1987-01-01

    These proceedings of the international topical meeting on advances in reactor physics, mathematics and computation, volume one, are divided into 6 sessions bearing on: - session 1: Advances in computational methods including utilization of parallel processing and vectorization (7 conferences) - session 2: Fast, epithermal, reactor physics, calculation, versus measurements (9 conferences) - session 3: New fast and thermal reactor designs (9 conferences) - session 4: Thermal radiation and charged particles transport (7 conferences) - session 5: Super computers (7 conferences) - session 6: Thermal reactor design, validation and operating experience (8 conferences).

  8. Special issue on advances in computer entertainment: editorial

    OpenAIRE

    Romão, T.; Romão, Teresa; Nijholt, Antinus; Cheok, J.D.; Cheok, Adrian David

    2015-01-01

    This special issue of the International Journal of Arts and Technology comprises a selection of papers from ACE 2012, the 9th International Conference on Advances in Computer Entertainment (Nijholt et al., 2012). ACE is the leading scientific forum for dissemination of cutting-edge research results in the area of entertainment computing. The main goal of ACE is to stimulate discussion in the development of new and compelling entertainment computing and interactive art concepts and application...

  9. Computational thermofracture mechanics and life prediction

    International Nuclear Information System (INIS)

    Hsu Tairan

    1992-01-01

    This paper will present computational techniques used for the prediction of the thermofracture behaviour of structures subject to either monotonic or cyclic combined thermal and mechanical loadings. Two specific areas will be dealt with in the paper. (1) The Time-invariant thermofracture of leaking pipelines with non-uniform temperature fields; in this case, the induced non-uniform temperature fields near leaking cracks have shown to be significant. The severity of these temperature fields on the thermofracture behaviour of the pipeline will be demonstrated by a numerical example. (2) Thermomechanical creep fracture of structures: Recent developments, including those of the author's own work, on cyclic creep-fracture using damage theory will be presented. Long 'hold' and 'dwell' times, which occur in the actual operations of nuclear power plant components have been shown to have a significant effect on the overall creep-fracture behaviour of the material. Constitutive laws, which include most of these effects, have been incorporated into the existing TEPSAC code for the prediction of crack growth in solids under cyclic creep loadings. The effectiveness of using the damage parameters as fracture criteria, and the presence of plastic deformation in the overall results will be assessed. (orig.)

  10. Predicting Production Costs for Advanced Aerospace Vehicles

    Science.gov (United States)

    Bao, Han P.; Samareh, J. A.; Weston, R. P.

    2002-01-01

    For early design concepts, the conventional approach to cost is normally some kind of parametric weight-based cost model. There is now ample evidence that this approach can be misleading and inaccurate. By the nature of its development, a parametric cost model requires historical data and is valid only if the new design is analogous to those for which the model was derived. Advanced aerospace vehicles have no historical production data and are nowhere near the vehicles of the past. Using an existing weight-based cost model would only lead to errors and distortions of the true production cost. This paper outlines the development of a process-based cost model in which the physical elements of the vehicle are soared according to a first-order dynamics model. This theoretical cost model, first advocated by early work at MIT, has been expanded to cover the basic structures of an advanced aerospace vehicle. Elemental costs based on the geometry of the design can be summed up to provide an overall estimation of the total production cost for a design configuration. This capability to directly link any design configuration to realistic cost estimation is a key requirement for high payoff MDO problems. Another important consideration in this paper is the handling of part or product complexity. Here the concept of cost modulus is introduced to take into account variability due to different materials, sizes, shapes, precision of fabrication, and equipment requirements. The most important implication of the development of the proposed process-based cost model is that different design configurations can now be quickly related to their cost estimates in a seamless calculation process easily implemented on any spreadsheet tool.

  11. Advance in prediction of soil slope instabilities

    Science.gov (United States)

    Sigarán-Loría, C.; Hack, R.; Nieuwenhuis, J. D.

    2012-04-01

    Six generic soils (clays and sands) were systematically modeled with plane-strain finite elements (FE) at varying heights and inclinations. A dataset was generated in order to develop predictive relations of soil slope instabilities, in terms of co-seismic displacements (u), under strong motions with a linear multiple regression. For simplicity, the seismic loads are monochromatic artificial sinusoidal functions at four frequencies: 1, 2, 4, and 6 Hz, and the slope failure criterion used corresponds to near 10% Cartesian shear strains along a continuous region comparable to a slip surface. The generated dataset comprises variables from the slope geometry and site conditions: height, H, inclination, i, shear wave velocity from the upper 30 m, vs30, site period, Ts; as well as the input strong motion: yield acceleration, ay (equal to peak ground acceleration, PGA in this research), frequency, f; and in some cases moment magnitude, M, and Arias intensity, Ia, assumed from empirical correlations. Different datasets or scenarios were created: "Magnitude-independent", "Magnitude-dependent", and "Soil-dependent", and the data was statistically explored and analyzed with varying mathematical forms. Qualitative relations show that the permanent deformations are highly related to the soil class for the clay slopes, but not for the sand slopes. Furthermore, the slope height does not constrain the variability in the co-seismic displacements. The input frequency decreases the variability of the co-seismic displacements for the "Magnitude-dependent" and "Soil-dependent" datasets. The empirical models were developed with two and three predictors. For the sands it was not possible because they could not satisfy the constrains from the statistical method. For the clays, the best models with the smallest errors coincided with the simple general form of multiple regression with three predictors (e.g. near 0.16 and 0.21 standard error, S.E. and 0.75 and 0.55 R2 for the "M

  12. Computational neuroscience for advancing artificial intelligence

    Directory of Open Access Journals (Sweden)

    Fernando P. Ponce

    2011-07-01

    Full Text Available resumen del libro de Alonso, E. y Mondragón, E. (2011. Hershey, NY: Medical Information Science Reference. La neurociencia como disciplinapersigue el entendimiento del cerebro y su relación con el funcionamiento de la mente a través del análisis de la comprensión de la interacción de diversos procesos físicos, químicos y biológicos (Bassett & Gazzaniga, 2011. Por otra parte, numerosas disciplinasprogresivamente han realizado significativas contribuciones en esta empresa tales como la matemática, la psicología o la filosofía, entre otras. Producto de este esfuerzo, es que junto con la neurociencia tradicional han aparecido disciplinas complementarias como la neurociencia cognitiva, la neuropsicología o la neurocienciacomputacional (Bengio, 2007; Dayan & Abbott, 2005. En el contexto de la neurociencia computacional como disciplina complementaria a laneurociencia tradicional. Alonso y Mondragón (2011 editan el libroComputacional Neuroscience for Advancing Artificial Intelligence: Models, Methods and Applications.

  13. A survey on computational intelligence approaches for predictive modeling in prostate cancer

    OpenAIRE

    Cosma, G; Brown, D; Archer, M; Khan, M; Pockley, AG

    2017-01-01

    Predictive modeling in medicine involves the development of computational models which are capable of analysing large amounts of data in order to predict healthcare outcomes for individual patients. Computational intelligence approaches are suitable when the data to be modelled are too complex forconventional statistical techniques to process quickly and eciently. These advanced approaches are based on mathematical models that have been especially developed for dealing with the uncertainty an...

  14. Identification of Enhancers In Human: Advances In Computational Studies

    KAUST Repository

    Kleftogiannis, Dimitrios A.

    2016-01-01

    Finally, we take a step further by developing a novel feature selection method suitable for defining a computational framework capable of analyzing the genomic content of enhancers and reporting cell-line specific predictive signatures.

  15. Computational predictive methods for fracture and fatigue

    Science.gov (United States)

    Cordes, J.; Chang, A. T.; Nelson, N.; Kim, Y.

    1994-09-01

    The damage-tolerant design philosophy as used by aircraft industries enables aircraft components and aircraft structures to operate safely with minor damage, small cracks, and flaws. Maintenance and inspection procedures insure that damages developed during service remain below design values. When damage is found, repairs or design modifications are implemented and flight is resumed. Design and redesign guidelines, such as military specifications MIL-A-83444, have successfully reduced the incidence of damage and cracks. However, fatigue cracks continue to appear in aircraft well before the design life has expired. The F16 airplane, for instance, developed small cracks in the engine mount, wing support, bulk heads, the fuselage upper skin, the fuel shelf joints, and along the upper wings. Some cracks were found after 600 hours of the 8000 hour design service life and design modifications were required. Tests on the F16 plane showed that the design loading conditions were close to the predicted loading conditions. Improvements to analytic methods for predicting fatigue crack growth adjacent to holes, when multiple damage sites are present, and in corrosive environments would result in more cost-effective designs, fewer repairs, and fewer redesigns. The overall objective of the research described in this paper is to develop, verify, and extend the computational efficiency of analysis procedures necessary for damage tolerant design. This paper describes an elastic/plastic fracture method and an associated fatigue analysis method for damage tolerant design. Both methods are unique in that material parameters such as fracture toughness, R-curve data, and fatigue constants are not required. The methods are implemented with a general-purpose finite element package. Several proof-of-concept examples are given. With further development, the methods could be extended for analysis of multi-site damage, creep-fatigue, and corrosion fatigue problems.

  16. Advances in FDTD computational electrodynamics photonics and nanotechnology

    CERN Document Server

    Oskooi, Ardavan; Johnson, Steven G

    2013-01-01

    Advances in photonics and nanotechnology have the potential to revolutionize humanity s ability to communicate and compute. To pursue these advances, it is mandatory to understand and properly model interactions of light with materials such as silicon and gold at the nanoscale, i.e., the span of a few tens of atoms laid side by side. These interactions are governed by the fundamental Maxwell s equations of classical electrodynamics, supplemented by quantum electrodynamics. This book presents the current state-of-the-art in formulating and implementing computational models of these interactions. Maxwell s equations are solved using the finite-difference time-domain (FDTD) technique, pioneered by the senior editor, whose prior Artech books in this area are among the top ten most-cited in the history of engineering. You discover the most important advances in all areas of FDTD and PSTD computational modeling of electromagnetic wave interactions. This cutting-edge resource helps you understand the latest develo...

  17. 9th International Conference on Advanced Computing & Communication Technologies

    CERN Document Server

    Mandal, Jyotsna; Auluck, Nitin; Nagarajaram, H

    2016-01-01

    This book highlights a collection of high-quality peer-reviewed research papers presented at the Ninth International Conference on Advanced Computing & Communication Technologies (ICACCT-2015) held at Asia Pacific Institute of Information Technology, Panipat, India during 27–29 November 2015. The book discusses a wide variety of industrial, engineering and scientific applications of the emerging techniques. Researchers from academia and industry present their original work and exchange ideas, information, techniques and applications in the field of Advanced Computing and Communication Technology.

  18. New or improved computational methods and advanced reactor design

    International Nuclear Information System (INIS)

    Nakagawa, Masayuki; Takeda, Toshikazu; Ushio, Tadashi

    1997-01-01

    Nuclear computational method has been studied continuously up to date, as a fundamental technology supporting the nuclear development. At present, research on computational method according to new theory and the calculating method thought to be difficult to practise are also continued actively to find new development due to splendid improvement of features of computer. In Japan, many light water type reactors are now in operations, new computational methods are induced for nuclear design, and a lot of efforts are concentrated for intending to more improvement of economics and safety. In this paper, some new research results on the nuclear computational methods and their application to nuclear design of the reactor were described for introducing recent trend of the nuclear design of the reactor. 1) Advancement of the computational method, 2) Reactor core design and management of the light water reactor, and 3) Nuclear design of the fast reactor. (G.K.)

  19. Advances in equine computed tomography and use of contrast media.

    Science.gov (United States)

    Puchalski, Sarah M

    2012-12-01

    Advances in equine computed tomography have been made as a result of improvements in software and hardware and an increasing body of knowledge. Contrast media can be administered intravascularly or intrathecally. Contrast media is useful to differentiate between tissues of similar density. Equine computed tomography can be used for many different clinical conditions, including lameness diagnosis, fracture identification and characterization, preoperative planning, and characterization of skull diseases. Copyright © 2012 Elsevier Inc. All rights reserved.

  20. Seismic activity prediction using computational intelligence techniques in northern Pakistan

    Science.gov (United States)

    Asim, Khawaja M.; Awais, Muhammad; Martínez-Álvarez, F.; Iqbal, Talat

    2017-10-01

    Earthquake prediction study is carried out for the region of northern Pakistan. The prediction methodology includes interdisciplinary interaction of seismology and computational intelligence. Eight seismic parameters are computed based upon the past earthquakes. Predictive ability of these eight seismic parameters is evaluated in terms of information gain, which leads to the selection of six parameters to be used in prediction. Multiple computationally intelligent models have been developed for earthquake prediction using selected seismic parameters. These models include feed-forward neural network, recurrent neural network, random forest, multi layer perceptron, radial basis neural network, and support vector machine. The performance of every prediction model is evaluated and McNemar's statistical test is applied to observe the statistical significance of computational methodologies. Feed-forward neural network shows statistically significant predictions along with accuracy of 75% and positive predictive value of 78% in context of northern Pakistan.

  1. Advanced computational modeling for in vitro nanomaterial dosimetry.

    Science.gov (United States)

    DeLoid, Glen M; Cohen, Joel M; Pyrgiotakis, Georgios; Pirela, Sandra V; Pal, Anoop; Liu, Jiying; Srebric, Jelena; Demokritou, Philip

    2015-10-24

    Accurate and meaningful dose metrics are a basic requirement for in vitro screening to assess potential health risks of engineered nanomaterials (ENMs). Correctly and consistently quantifying what cells "see," during an in vitro exposure requires standardized preparation of stable ENM suspensions, accurate characterizatoin of agglomerate sizes and effective densities, and predictive modeling of mass transport. Earlier transport models provided a marked improvement over administered concentration or total mass, but included assumptions that could produce sizable inaccuracies, most notably that all particles at the bottom of the well are adsorbed or taken up by cells, which would drive transport downward, resulting in overestimation of deposition. Here we present development, validation and results of two robust computational transport models. Both three-dimensional computational fluid dynamics (CFD) and a newly-developed one-dimensional Distorted Grid (DG) model were used to estimate delivered dose metrics for industry-relevant metal oxide ENMs suspended in culture media. Both models allow simultaneous modeling of full size distributions for polydisperse ENM suspensions, and provide deposition metrics as well as concentration metrics over the extent of the well. The DG model also emulates the biokinetics at the particle-cell interface using a Langmuir isotherm, governed by a user-defined dissociation constant, K(D), and allows modeling of ENM dissolution over time. Dose metrics predicted by the two models were in remarkably close agreement. The DG model was also validated by quantitative analysis of flash-frozen, cryosectioned columns of ENM suspensions. Results of simulations based on agglomerate size distributions differed substantially from those obtained using mean sizes. The effect of cellular adsorption on delivered dose was negligible for K(D) values consistent with non-specific binding (> 1 nM), whereas smaller values (≤ 1 nM) typical of specific high

  2. Advancing alternatives analysis: The role of predictive toxicology in selecting safer chemical products and processes.

    Science.gov (United States)

    Malloy, Timothy; Zaunbrecher, Virginia; Beryt, Elizabeth; Judson, Richard; Tice, Raymond; Allard, Patrick; Blake, Ann; Cote, Ila; Godwin, Hilary; Heine, Lauren; Kerzic, Patrick; Kostal, Jakub; Marchant, Gary; McPartland, Jennifer; Moran, Kelly; Nel, Andre; Ogunseitan, Oladele; Rossi, Mark; Thayer, Kristina; Tickner, Joel; Whittaker, Margaret; Zarker, Ken

    2017-09-01

    Alternatives analysis (AA) is a method used in regulation and product design to identify, assess, and evaluate the safety and viability of potential substitutes for hazardous chemicals. It requires toxicological data for the existing chemical and potential alternatives. Predictive toxicology uses in silico and in vitro approaches, computational models, and other tools to expedite toxicological data generation in a more cost-effective manner than traditional approaches. The present article briefly reviews the challenges associated with using predictive toxicology in regulatory AA, then presents 4 recommendations for its advancement. It recommends using case studies to advance the integration of predictive toxicology into AA, adopting a stepwise process to employing predictive toxicology in AA beginning with prioritization of chemicals of concern, leveraging existing resources to advance the integration of predictive toxicology into the practice of AA, and supporting transdisciplinary efforts. The further incorporation of predictive toxicology into AA would advance the ability of companies and regulators to select alternatives to harmful ingredients, and potentially increase the use of predictive toxicology in regulation more broadly. Integr Environ Assess Manag 2017;13:915-925. © 2017 SETAC. © 2017 SETAC.

  3. Innovations and Advances in Computer, Information, Systems Sciences, and Engineering

    CERN Document Server

    Sobh, Tarek

    2013-01-01

    Innovations and Advances in Computer, Information, Systems Sciences, and Engineering includes the proceedings of the International Joint Conferences on Computer, Information, and Systems Sciences, and Engineering (CISSE 2011). The contents of this book are a set of rigorously reviewed, world-class manuscripts addressing and detailing state-of-the-art research projects in the areas of  Industrial Electronics, Technology and Automation, Telecommunications and Networking, Systems, Computing Sciences and Software Engineering, Engineering Education, Instructional Technology, Assessment, and E-learning.

  4. Advances in computers dependable and secure systems engineering

    CERN Document Server

    Hurson, Ali

    2012-01-01

    Since its first volume in 1960, Advances in Computers has presented detailed coverage of innovations in computer hardware, software, theory, design, and applications. It has also provided contributors with a medium in which they can explore their subjects in greater depth and breadth than journal articles usually allow. As a result, many articles have become standard references that continue to be of sugnificant, lasting value in this rapidly expanding field. In-depth surveys and tutorials on new computer technologyWell-known authors and researchers in the fieldExtensive bibliographies with m

  5. Advances in Reactor physics, mathematics and computation. Volume 3

    Energy Technology Data Exchange (ETDEWEB)

    1987-01-01

    These proceedings of the international topical meeting on advances in reactor physics, mathematics and computation, volume 3, are divided into sessions bearing on: - poster sessions on benchmark and codes: 35 conferences - review of status of assembly spectrum codes: 9 conferences - Numerical methods in fluid mechanics and thermal hydraulics: 16 conferences - stochastic transport and methods: 7 conferences.

  6. Editorial : Special Issue on Advances in Computer Entertainment

    NARCIS (Netherlands)

    Romão, Teresa; Nijholt, Anton; Cheok, Adrian David

    2015-01-01

    This special issue of the International Journal of Arts and Technology comprises a selection of papers from ACE 2012, the 9th International Conference on Advances in Computer Entertainment (Nijholt et al., 2012). ACE is the leading scientific forum for the dissemination of cutting-edge research

  7. Advances in Computer Entertainment. 10th International Conference, ACE 2013

    NARCIS (Netherlands)

    Reidsma, Dennis; Katayose, H.; Nijholt, Antinus; Unknown, [Unknown

    2013-01-01

    These are the proceedings of the 10th International Conference on Advances in Computer Entertainment (ACE 2013), hosted by the Human Media Interaction research group of the Centre for Telematics and Information Technology at the University of Twente, The Netherlands. The ACE series of conferences,

  8. Attitudes toward Advanced and Multivariate Statistics When Using Computers.

    Science.gov (United States)

    Kennedy, Robert L.; McCallister, Corliss Jean

    This study investigated the attitudes toward statistics of graduate students who studied advanced statistics in a course in which the focus of instruction was the use of a computer program in class. The use of the program made it possible to provide an individualized, self-paced, student-centered, and activity-based course. The three sections…

  9. Computer-Assisted Foreign Language Teaching and Learning: Technological Advances

    Science.gov (United States)

    Zou, Bin; Xing, Minjie; Wang, Yuping; Sun, Mingyu; Xiang, Catherine H.

    2013-01-01

    Computer-Assisted Foreign Language Teaching and Learning: Technological Advances highlights new research and an original framework that brings together foreign language teaching, experiments and testing practices that utilize the most recent and widely used e-learning resources. This comprehensive collection of research will offer linguistic…

  10. Scientific Discovery through Advanced Computing (SciDAC-3) Partnership Project Annual Report

    Energy Technology Data Exchange (ETDEWEB)

    Hoffman, Forest M. [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Bochev, Pavel B. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Cameron-Smith, Philip J.. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Easter, Richard C [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Elliott, Scott M. [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Ghan, Steven J. [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Liu, Xiaohong [Univ. of Wyoming, Laramie, WY (United States); Lowrie, Robert B. [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Lucas, Donald D. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Ma, Po-lun [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Sacks, William J. [National Center for Atmospheric Research (NCAR), Boulder, CO (United States); Shrivastava, Manish [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Singh, Balwinder [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Tautges, Timothy J. [Argonne National Lab. (ANL), Argonne, IL (United States); Taylor, Mark A. [Sandia National Lab. (SNL-CA), Livermore, CA (United States); Vertenstein, Mariana [National Center for Atmospheric Research (NCAR), Boulder, CO (United States); Worley, Patrick H. [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)

    2014-01-15

    The Applying Computationally Efficient Schemes for BioGeochemical Cycles ACES4BGC Project is advancing the predictive capabilities of Earth System Models (ESMs) by reducing two of the largest sources of uncertainty, aerosols and biospheric feedbacks, with a highly efficient computational approach. In particular, this project is implementing and optimizing new computationally efficient tracer advection algorithms for large numbers of tracer species; adding important biogeochemical interactions between the atmosphere, land, and ocean models; and applying uncertainty quanti cation (UQ) techniques to constrain process parameters and evaluate uncertainties in feedbacks between biogeochemical cycles and the climate system.

  11. [Activities of Research Institute for Advanced Computer Science

    Science.gov (United States)

    Gross, Anthony R. (Technical Monitor); Leiner, Barry M.

    2001-01-01

    The Research Institute for Advanced Computer Science (RIACS) carries out basic research and technology development in computer science, in support of the National Aeronautics and Space Administrations missions. RIACS is located at the NASA Ames Research Center, Moffett Field, California. RIACS research focuses on the three cornerstones of IT research necessary to meet the future challenges of NASA missions: 1. Automated Reasoning for Autonomous Systems Techniques are being developed enabling spacecraft that will be self-guiding and self-correcting to the extent that they will require little or no human intervention. Such craft will be equipped to independently solve problems as they arise, and fulfill their missions with minimum direction from Earth. 2. Human-Centered Computing Many NASA missions require synergy between humans and computers, with sophisticated computational aids amplifying human cognitive and perceptual abilities. 3. High Performance Computing and Networking Advances in the performance of computing and networking continue to have major impact on a variety of NASA endeavors, ranging from modeling and simulation to analysis of large scientific datasets to collaborative engineering, planning and execution. In addition, RIACS collaborates with NASA scientists to apply IT research to a variety of NASA application domains. RIACS also engages in other activities, such as workshops, seminars, visiting scientist programs and student summer programs, designed to encourage and facilitate collaboration between the university and NASA IT research communities.

  12. Emerging Nanophotonic Applications Explored with Advanced Scientific Parallel Computing

    Science.gov (United States)

    Meng, Xiang

    The domain of nanoscale optical science and technology is a combination of the classical world of electromagnetics and the quantum mechanical regime of atoms and molecules. Recent advancements in fabrication technology allows the optical structures to be scaled down to nanoscale size or even to the atomic level, which are far smaller than the wavelength they are designed for. These nanostructures can have unique, controllable, and tunable optical properties and their interactions with quantum materials can have important near-field and far-field optical response. Undoubtedly, these optical properties can have many important applications, ranging from the efficient and tunable light sources, detectors, filters, modulators, high-speed all-optical switches; to the next-generation classical and quantum computation, and biophotonic medical sensors. This emerging research of nanoscience, known as nanophotonics, is a highly interdisciplinary field requiring expertise in materials science, physics, electrical engineering, and scientific computing, modeling and simulation. It has also become an important research field for investigating the science and engineering of light-matter interactions that take place on wavelength and subwavelength scales where the nature of the nanostructured matter controls the interactions. In addition, the fast advancements in the computing capabilities, such as parallel computing, also become as a critical element for investigating advanced nanophotonic devices. This role has taken on even greater urgency with the scale-down of device dimensions, and the design for these devices require extensive memory and extremely long core hours. Thus distributed computing platforms associated with parallel computing are required for faster designs processes. Scientific parallel computing constructs mathematical models and quantitative analysis techniques, and uses the computing machines to analyze and solve otherwise intractable scientific challenges. In

  13. 2014 National Workshop on Advances in Communication and Computing

    CERN Document Server

    Prasanna, S; Sarma, Kandarpa; Saikia, Navajit

    2015-01-01

    The present volume is a compilation of research work in computation, communication, vision sciences, device design, fabrication, upcoming materials and related process design, etc. It is derived out of selected manuscripts submitted to the 2014 National Workshop on Advances in Communication and Computing (WACC 2014), Assam Engineering College, Guwahati, Assam, India which is emerging out to be a premier platform for discussion and dissemination of knowhow in this part of the world. The papers included in the volume are indicative of the recent thrust in computation, communications and emerging technologies. Certain recent advances in ZnO nanostructures for alternate energy generation provide emerging insights into an area that has promises for the energy sector including conservation and green technology. Similarly, scholarly contributions have focused on malware detection and related issues. Several contributions have focused on biomedical aspects including contributions related to cancer detection using act...

  14. Generic Model Predictive Control Framework for Advanced Driver Assistance Systems

    NARCIS (Netherlands)

    Wang, M.

    2014-01-01

    This thesis deals with a model predictive control framework for control design of Advanced Driver Assistance Systems, where car-following tasks are under control. The framework is applied to design several autonomous and cooperative controllers and to examine the controller properties at the

  15. Computer code qualification program for the Advanced CANDU Reactor

    International Nuclear Information System (INIS)

    Popov, N.K.; Wren, D.J.; Snell, V.G.; White, A.J.; Boczar, P.G.

    2003-01-01

    Atomic Energy of Canada Ltd (AECL) has developed and implemented a Software Quality Assurance program (SQA) to ensure that its analytical, scientific and design computer codes meet the required standards for software used in safety analyses. This paper provides an overview of the computer programs used in Advanced CANDU Reactor (ACR) safety analysis, and assessment of their applicability in the safety analyses of the ACR design. An outline of the incremental validation program, and an overview of the experimental program in support of the code validation are also presented. An outline of the SQA program used to qualify these computer codes is also briefly presented. To provide context to the differences in the SQA with respect to current CANDUs, the paper also provides an overview of the ACR design features that have an impact on the computer code qualification. (author)

  16. Advanced computer graphics techniques as applied to the nuclear industry

    International Nuclear Information System (INIS)

    Thomas, J.J.; Koontz, A.S.

    1985-08-01

    Computer graphics is a rapidly advancing technological area in computer science. This is being motivated by increased hardware capability coupled with reduced hardware costs. This paper will cover six topics in computer graphics, with examples forecasting how each of these capabilities could be used in the nuclear industry. These topics are: (1) Image Realism with Surfaces and Transparency; (2) Computer Graphics Motion; (3) Graphics Resolution Issues and Examples; (4) Iconic Interaction; (5) Graphic Workstations; and (6) Data Fusion - illustrating data coming from numerous sources, for display through high dimensional, greater than 3-D, graphics. All topics will be discussed using extensive examples with slides, video tapes, and movies. Illustrations have been omitted from the paper due to the complexity of color reproduction. 11 refs., 2 figs., 3 tabs

  17. Application of large computers for predicting the oil field production

    Energy Technology Data Exchange (ETDEWEB)

    Philipp, W; Gunkel, W; Marsal, D

    1971-10-01

    The flank injection drive plays a dominant role in the exploitation of the BEB-oil fields. Therefore, 2-phase flow computer models were built up, adapted to a predominance of a single flow direction and combining a high accuracy of prediction with a low job time. Any case study starts with the partitioning of the reservoir into blocks. Then the statistics of the time-independent reservoir properties are analyzed by means of an IBM 360/25 unit. Using these results and the past production of oil, water and gas, a Fortran-program running on a CDC-3300 computer yields oil recoveries and the ratios of the relative permeabilities as a function of the local oil saturation for all blocks penetrated by mobile water. In order to assign kDwU/KDoU-functions to blocks not yet reached by the advancing water-front, correlation analysis is used to relate reservoir properties to kDwU/KDoU-functions. All these results are used as input into a CDC-660 Fortran program, allowing short-, medium-, and long-term forecasts as well as the handling of special problems.

  18. Activities of the Research Institute for Advanced Computer Science

    Science.gov (United States)

    Oliger, Joseph

    1994-01-01

    The Research Institute for Advanced Computer Science (RIACS) was established by the Universities Space Research Association (USRA) at the NASA Ames Research Center (ARC) on June 6, 1983. RIACS is privately operated by USRA, a consortium of universities with research programs in the aerospace sciences, under contract with NASA. The primary mission of RIACS is to provide research and expertise in computer science and scientific computing to support the scientific missions of NASA ARC. The research carried out at RIACS must change its emphasis from year to year in response to NASA ARC's changing needs and technological opportunities. Research at RIACS is currently being done in the following areas: (1) parallel computing; (2) advanced methods for scientific computing; (3) high performance networks; and (4) learning systems. RIACS technical reports are usually preprints of manuscripts that have been submitted to research journals or conference proceedings. A list of these reports for the period January 1, 1994 through December 31, 1994 is in the Reports and Abstracts section of this report.

  19. Performance evaluation of scientific programs on advanced architecture computers

    International Nuclear Information System (INIS)

    Walker, D.W.; Messina, P.; Baille, C.F.

    1988-01-01

    Recently a number of advanced architecture machines have become commercially available. These new machines promise better cost-performance then traditional computers, and some of them have the potential of competing with current supercomputers, such as the Cray X/MP, in terms of maximum performance. This paper describes an on-going project to evaluate a broad range of advanced architecture computers using a number of complete scientific application programs. The computers to be evaluated include distributed- memory machines such as the NCUBE, INTEL and Caltech/JPL hypercubes, and the MEIKO computing surface, shared-memory, bus architecture machines such as the Sequent Balance and the Alliant, very long instruction word machines such as the Multiflow Trace 7/200 computer, traditional supercomputers such as the Cray X.MP and Cray-2, and SIMD machines such as the Connection Machine. Currently 11 application codes from a number of scientific disciplines have been selected, although it is not intended to run all codes on all machines. Results are presented for two of the codes (QCD and missile tracking), and future work is proposed

  20. Pretreatment tables predicting pathologic stage of locally advanced prostate cancer.

    Science.gov (United States)

    Joniau, Steven; Spahn, Martin; Briganti, Alberto; Gandaglia, Giorgio; Tombal, Bertrand; Tosco, Lorenzo; Marchioro, Giansilvio; Hsu, Chao-Yu; Walz, Jochen; Kneitz, Burkhard; Bader, Pia; Frohneberg, Detlef; Tizzani, Alessandro; Graefen, Markus; van Cangh, Paul; Karnes, R Jeffrey; Montorsi, Francesco; van Poppel, Hein; Gontero, Paolo

    2015-02-01

    Pretreatment tables for the prediction of pathologic stage have been published and validated for localized prostate cancer (PCa). No such tables are available for locally advanced (cT3a) PCa. To construct tables predicting pathologic outcome after radical prostatectomy (RP) for patients with cT3a PCa with the aim to help guide treatment decisions in clinical practice. This was a multicenter retrospective cohort study including 759 consecutive patients with cT3a PCa treated with RP between 1987 and 2010. Retropubic RP and pelvic lymphadenectomy. Patients were divided into pretreatment prostate-specific antigen (PSA) and biopsy Gleason score (GS) subgroups. These parameters were used to construct tables predicting pathologic outcome and the presence of positive lymph nodes (LNs) after RP for cT3a PCa using ordinal logistic regression. In the model predicting pathologic outcome, the main effects of biopsy GS and pretreatment PSA were significant. A higher GS and/or higher PSA level was associated with a more unfavorable pathologic outcome. The validation procedure, using a repeated split-sample method, showed good predictive ability. Regression analysis also showed an increasing probability of positive LNs with increasing PSA levels and/or higher GS. Limitations of the study are the retrospective design and the long study period. These novel tables predict pathologic stage after RP for patients with cT3a PCa based on pretreatment PSA level and biopsy GS. They can be used to guide decision making in men with locally advanced PCa. Our study might provide physicians with a useful tool to predict pathologic stage in locally advanced prostate cancer that might help select patients who may need multimodal treatment. Copyright © 2014 European Association of Urology. Published by Elsevier B.V. All rights reserved.

  1. A comparative analysis of soft computing techniques for gene prediction.

    Science.gov (United States)

    Goel, Neelam; Singh, Shailendra; Aseri, Trilok Chand

    2013-07-01

    The rapid growth of genomic sequence data for both human and nonhuman species has made analyzing these sequences, especially predicting genes in them, very important and is currently the focus of many research efforts. Beside its scientific interest in the molecular biology and genomics community, gene prediction is of considerable importance in human health and medicine. A variety of gene prediction techniques have been developed for eukaryotes over the past few years. This article reviews and analyzes the application of certain soft computing techniques in gene prediction. First, the problem of gene prediction and its challenges are described. These are followed by different soft computing techniques along with their application to gene prediction. In addition, a comparative analysis of different soft computing techniques for gene prediction is given. Finally some limitations of the current research activities and future research directions are provided. Copyright © 2013 Elsevier Inc. All rights reserved.

  2. Advances in Reactor Physics, Mathematics and Computation. Volume 2

    Energy Technology Data Exchange (ETDEWEB)

    1987-01-01

    These proceedings of the international topical meeting on advances in reactor physics, mathematics and computation, Volume 2, are divided into 7 sessions bearing on: - session 7: Deterministic transport methods 1 (7 conferences), - session 8: Interpretation and analysis of reactor instrumentation (6 conferences), - session 9: High speed computing applied to reactor operations (5 conferences), - session 10: Diffusion theory and kinetics (7 conferences), - session 11: Fast reactor design, validation and operating experience (8 conferences), - session 12: Deterministic transport methods 2 (7 conferences), - session 13: Application of expert systems to physical aspects of reactor design and operation.

  3. Predictive Models and Computational Toxicology (II IBAMTOX)

    Science.gov (United States)

    EPA’s ‘virtual embryo’ project is building an integrative systems biology framework for predictive models of developmental toxicity. One schema involves a knowledge-driven adverse outcome pathway (AOP) framework utilizing information from public databases, standardized ontologies...

  4. NATO Advanced Study Institute on Methods in Computational Molecular Physics

    CERN Document Server

    Diercksen, Geerd

    1992-01-01

    This volume records the lectures given at a NATO Advanced Study Institute on Methods in Computational Molecular Physics held in Bad Windsheim, Germany, from 22nd July until 2nd. August, 1991. This NATO Advanced Study Institute sought to bridge the quite considerable gap which exist between the presentation of molecular electronic structure theory found in contemporary monographs such as, for example, McWeeny's Methods 0/ Molecular Quantum Mechanics (Academic Press, London, 1989) or Wilson's Electron correlation in moleeules (Clarendon Press, Oxford, 1984) and the realization of the sophisticated computational algorithms required for their practical application. It sought to underline the relation between the electronic structure problem and the study of nuc1ear motion. Software for performing molecular electronic structure calculations is now being applied in an increasingly wide range of fields in both the academic and the commercial sectors. Numerous applications are reported in areas as diverse as catalysi...

  5. Soft computing in design and manufacturing of advanced materials

    Science.gov (United States)

    Cios, Krzysztof J.; Baaklini, George Y; Vary, Alex

    1993-01-01

    The potential of fuzzy sets and neural networks, often referred to as soft computing, for aiding in all aspects of manufacturing of advanced materials like ceramics is addressed. In design and manufacturing of advanced materials, it is desirable to find which of the many processing variables contribute most to the desired properties of the material. There is also interest in real time quality control of parameters that govern material properties during processing stages. The concepts of fuzzy sets and neural networks are briefly introduced and it is shown how they can be used in the design and manufacturing processes. These two computational methods are alternatives to other methods such as the Taguchi method. The two methods are demonstrated by using data collected at NASA Lewis Research Center. Future research directions are also discussed.

  6. Advanced computational simulations of water waves interacting with wave energy converters

    Science.gov (United States)

    Pathak, Ashish; Freniere, Cole; Raessi, Mehdi

    2017-03-01

    Wave energy converter (WEC) devices harness the renewable ocean wave energy and convert it into useful forms of energy, e.g. mechanical or electrical. This paper presents an advanced 3D computational framework to study the interaction between water waves and WEC devices. The computational tool solves the full Navier-Stokes equations and considers all important effects impacting the device performance. To enable large-scale simulations in fast turnaround times, the computational solver was developed in an MPI parallel framework. A fast multigrid preconditioned solver is introduced to solve the computationally expensive pressure Poisson equation. The computational solver was applied to two surface-piercing WEC geometries: bottom-hinged cylinder and flap. Their numerically simulated response was validated against experimental data. Additional simulations were conducted to investigate the applicability of Froude scaling in predicting full-scale WEC response from the model experiments.

  7. Advances in Cross-Cutting Ideas for Computational Climate Science

    Energy Technology Data Exchange (ETDEWEB)

    Ng, Esmond [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Evans, Katherine J. [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Caldwell, Peter [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Hoffman, Forrest M. [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Jackson, Charles [Univ. of Texas, Austin, TX (United States); Kerstin, Van Dam [Brookhaven National Lab. (BNL), Upton, NY (United States); Leung, Ruby [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Martin, Daniel F. [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Ostrouchov, George [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Tuminaro, Raymond [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Ullrich, Paul [Univ. of California, Davis, CA (United States); Wild, S. [Argonne National Lab. (ANL), Argonne, IL (United States); Williams, Samuel [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)

    2017-01-01

    This report presents results from the DOE-sponsored workshop titled, ``Advancing X-Cutting Ideas for Computational Climate Science Workshop,'' known as AXICCS, held on September 12--13, 2016 in Rockville, MD. The workshop brought together experts in climate science, computational climate science, computer science, and mathematics to discuss interesting but unsolved science questions regarding climate modeling and simulation, promoted collaboration among the diverse scientists in attendance, and brainstormed about possible tools and capabilities that could be developed to help address them. Emerged from discussions at the workshop were several research opportunities that the group felt could advance climate science significantly. These include (1) process-resolving models to provide insight into important processes and features of interest and inform the development of advanced physical parameterizations, (2) a community effort to develop and provide integrated model credibility, (3) including, organizing, and managing increasingly connected model components that increase model fidelity yet complexity, and (4) treating Earth system models as one interconnected organism without numerical or data based boundaries that limit interactions. The group also identified several cross-cutting advances in mathematics, computer science, and computational science that would be needed to enable one or more of these big ideas. It is critical to address the need for organized, verified, and optimized software, which enables the models to grow and continue to provide solutions in which the community can have confidence. Effectively utilizing the newest computer hardware enables simulation efficiency and the ability to handle output from increasingly complex and detailed models. This will be accomplished through hierarchical multiscale algorithms in tandem with new strategies for data handling, analysis, and storage. These big ideas and cross-cutting technologies for

  8. Advances in Cross-Cutting Ideas for Computational Climate Science

    Energy Technology Data Exchange (ETDEWEB)

    Ng, E.; Evans, K.; Caldwell, P.; Hoffman, F.; Jackson, C.; Van Dam, K.; Leung, R.; Martin, D.; Ostrouchov, G.; Tuminaro, R.; Ullrich, P.; Wild, S.; Williams, S.

    2017-01-01

    This report presents results from the DOE-sponsored workshop titled, Advancing X-Cutting Ideas for Computational Climate Science Workshop,'' known as AXICCS, held on September 12--13, 2016 in Rockville, MD. The workshop brought together experts in climate science, computational climate science, computer science, and mathematics to discuss interesting but unsolved science questions regarding climate modeling and simulation, promoted collaboration among the diverse scientists in attendance, and brainstormed about possible tools and capabilities that could be developed to help address them. Emerged from discussions at the workshop were several research opportunities that the group felt could advance climate science significantly. These include (1) process-resolving models to provide insight into important processes and features of interest and inform the development of advanced physical parameterizations, (2) a community effort to develop and provide integrated model credibility, (3) including, organizing, and managing increasingly connected model components that increase model fidelity yet complexity, and (4) treating Earth system models as one interconnected organism without numerical or data based boundaries that limit interactions. The group also identified several cross-cutting advances in mathematics, computer science, and computational science that would be needed to enable one or more of these big ideas. It is critical to address the need for organized, verified, and optimized software, which enables the models to grow and continue to provide solutions in which the community can have confidence. Effectively utilizing the newest computer hardware enables simulation efficiency and the ability to handle output from increasingly complex and detailed models. This will be accomplished through hierarchical multiscale algorithms in tandem with new strategies for data handling, analysis, and storage. These big ideas and cross-cutting technologies for enabling

  9. Advanced Computing for 21st Century Accelerator Science and Technology

    International Nuclear Information System (INIS)

    Dragt, Alex J.

    2004-01-01

    Dr. Dragt of the University of Maryland is one of the Institutional Principal Investigators for the SciDAC Accelerator Modeling Project Advanced Computing for 21st Century Accelerator Science and Technology whose principal investigators are Dr. Kwok Ko (Stanford Linear Accelerator Center) and Dr. Robert Ryne (Lawrence Berkeley National Laboratory). This report covers the activities of Dr. Dragt while at Berkeley during spring 2002 and at Maryland during fall 2003

  10. Condition Monitoring Through Advanced Sensor and Computational Technology

    International Nuclear Information System (INIS)

    Kim, Jung Taek; Park, Won Man; Kim, Jung Soo; Seong, Soeng Hwan; Hur, Sub; Cho, Jae Hwan; Jung, Hyung Gue

    2005-05-01

    The overall goal of this joint research project was to develop and demonstrate advanced sensors and computational technology for continuous monitoring of the condition of components, structures, and systems in advanced and next-generation nuclear power plants (NPPs). This project included investigating and adapting several advanced sensor technologies from Korean and US national laboratory research communities, some of which were developed and applied in non-nuclear industries. The project team investigated and developed sophisticated signal processing, noise reduction, and pattern recognition techniques and algorithms. The researchers installed sensors and conducted condition monitoring tests on two test loops, a check valve (an active component) and a piping elbow (a passive component), to demonstrate the feasibility of using advanced sensors and computational technology to achieve the project goal. Acoustic emission (AE) devices, optical fiber sensors, accelerometers, and ultrasonic transducers (UTs) were used to detect mechanical vibratory response of check valve and piping elbow in normal and degraded configurations. Chemical sensors were also installed to monitor the water chemistry in the piping elbow test loop. Analysis results of processed sensor data indicate that it is feasible to differentiate between the normal and degraded (with selected degradation mechanisms) configurations of these two components from the acquired sensor signals, but it is questionable that these methods can reliably identify the level and type of degradation. Additional research and development efforts are needed to refine the differentiation techniques and to reduce the level of uncertainties

  11. Why advanced computing? The key to space-based operations

    Science.gov (United States)

    Phister, Paul W., Jr.; Plonisch, Igor; Mineo, Jack

    2000-11-01

    The 'what is the requirement?' aspect of advanced computing and how it relates to and supports Air Force space-based operations is a key issue. In support of the Air Force Space Command's five major mission areas (space control, force enhancement, force applications, space support and mission support), two-fifths of the requirements have associated stringent computing/size implications. The Air Force Research Laboratory's 'migration to space' concept will eventually shift Science and Technology (S&T) dollars from predominantly airborne systems to airborne-and-space related S&T areas. One challenging 'space' area is in the development of sophisticated on-board computing processes for the next generation smaller, cheaper satellite systems. These new space systems (called microsats or nanosats) could be as small as a softball, yet perform functions that are currently being done by large, vulnerable ground-based assets. The Joint Battlespace Infosphere (JBI) concept will be used to manage the overall process of space applications coupled with advancements in computing. The JBI can be defined as a globally interoperable information 'space' which aggregates, integrates, fuses, and intelligently disseminates all relevant battlespace knowledge to support effective decision-making at all echelons of a Joint Task Force (JTF). This paper explores a single theme -- on-board processing is the best avenue to take advantage of advancements in high-performance computing, high-density memories, communications, and re-programmable architecture technologies. The goal is to break away from 'no changes after launch' design to a more flexible design environment that can take advantage of changing space requirements and needs while the space vehicle is 'on orbit.'

  12. Computationally efficient prediction of area per lipid

    DEFF Research Database (Denmark)

    Chaban, Vitaly V.

    2014-01-01

    dynamics increases exponentially with respect to temperature. APL dependence on temperature is linear over an entire temperature range. I provide numerical evidence that thermal expansion coefficient of a lipid bilayer can be computed at elevated temperatures and extrapolated to the temperature of interest...

  13. The advanced computational testing and simulation toolkit (ACTS)

    International Nuclear Information System (INIS)

    Drummond, L.A.; Marques, O.

    2002-01-01

    During the past decades there has been a continuous growth in the number of physical and societal problems that have been successfully studied and solved by means of computational modeling and simulation. Distinctively, a number of these are important scientific problems ranging in scale from the atomic to the cosmic. For example, ionization is a phenomenon as ubiquitous in modern society as the glow of fluorescent lights and the etching on silicon computer chips; but it was not until 1999 that researchers finally achieved a complete numerical solution to the simplest example of ionization, the collision of a hydrogen atom with an electron. On the opposite scale, cosmologists have long wondered whether the expansion of the Universe, which began with the Big Bang, would ever reverse itself, ending the Universe in a Big Crunch. In 2000, analysis of new measurements of the cosmic microwave background radiation showed that the geometry of the Universe is flat, and thus the Universe will continue expanding forever. Both of these discoveries depended on high performance computer simulations that utilized computational tools included in the Advanced Computational Testing and Simulation (ACTS) Toolkit. The ACTS Toolkit is an umbrella project that brought together a number of general purpose computational tool development projects funded and supported by the U.S. Department of Energy (DOE). These tools, which have been developed independently, mainly at DOE laboratories, make it easier for scientific code developers to write high performance applications for parallel computers. They tackle a number of computational issues that are common to a large number of scientific applications, mainly implementation of numerical algorithms, and support for code development, execution and optimization. The ACTS Toolkit Project enables the use of these tools by a much wider community of computational scientists, and promotes code portability, reusability, reduction of duplicate efforts

  14. The advanced computational testing and simulation toolkit (ACTS)

    Energy Technology Data Exchange (ETDEWEB)

    Drummond, L.A.; Marques, O.

    2002-05-21

    During the past decades there has been a continuous growth in the number of physical and societal problems that have been successfully studied and solved by means of computational modeling and simulation. Distinctively, a number of these are important scientific problems ranging in scale from the atomic to the cosmic. For example, ionization is a phenomenon as ubiquitous in modern society as the glow of fluorescent lights and the etching on silicon computer chips; but it was not until 1999 that researchers finally achieved a complete numerical solution to the simplest example of ionization, the collision of a hydrogen atom with an electron. On the opposite scale, cosmologists have long wondered whether the expansion of the Universe, which began with the Big Bang, would ever reverse itself, ending the Universe in a Big Crunch. In 2000, analysis of new measurements of the cosmic microwave background radiation showed that the geometry of the Universe is flat, and thus the Universe will continue expanding forever. Both of these discoveries depended on high performance computer simulations that utilized computational tools included in the Advanced Computational Testing and Simulation (ACTS) Toolkit. The ACTS Toolkit is an umbrella project that brought together a number of general purpose computational tool development projects funded and supported by the U.S. Department of Energy (DOE). These tools, which have been developed independently, mainly at DOE laboratories, make it easier for scientific code developers to write high performance applications for parallel computers. They tackle a number of computational issues that are common to a large number of scientific applications, mainly implementation of numerical algorithms, and support for code development, execution and optimization. The ACTS Toolkit Project enables the use of these tools by a much wider community of computational scientists, and promotes code portability, reusability, reduction of duplicate efforts

  15. Recent Advances in Explicit Multiparametric Nonlinear Model Predictive Control

    KAUST Repository

    Domínguez, Luis F.

    2011-01-19

    In this paper we present recent advances in multiparametric nonlinear programming (mp-NLP) algorithms for explicit nonlinear model predictive control (mp-NMPC). Three mp-NLP algorithms for NMPC are discussed, based on which novel mp-NMPC controllers are derived. The performance of the explicit controllers are then tested and compared in a simulation example involving the operation of a continuous stirred-tank reactor (CSTR). © 2010 American Chemical Society.

  16. Computational experiment approach to advanced secondary mathematics curriculum

    CERN Document Server

    Abramovich, Sergei

    2014-01-01

    This book promotes the experimental mathematics approach in the context of secondary mathematics curriculum by exploring mathematical models depending on parameters that were typically considered advanced in the pre-digital education era. This approach, by drawing on the power of computers to perform numerical computations and graphical constructions, stimulates formal learning of mathematics through making sense of a computational experiment. It allows one (in the spirit of Freudenthal) to bridge serious mathematical content and contemporary teaching practice. In other words, the notion of teaching experiment can be extended to include a true mathematical experiment. When used appropriately, the approach creates conditions for collateral learning (in the spirit of Dewey) to occur including the development of skills important for engineering applications of mathematics. In the context of a mathematics teacher education program, this book addresses a call for the preparation of teachers capable of utilizing mo...

  17. Predictive access control for distributed computation

    DEFF Research Database (Denmark)

    Yang, Fan; Hankin, Chris; Nielson, Flemming

    2013-01-01

    We show how to use aspect-oriented programming to separate security and trust issues from the logical design of mobile, distributed systems. The main challenge is how to enforce various types of security policies, in particular predictive access control policies — policies based on the future beh...... behavior of a program. A novel feature of our approach is that we can define policies concerning secondary use of data....

  18. Design and installation of advanced computer safety related instrumentation

    International Nuclear Information System (INIS)

    Koch, S.; Andolina, K.; Ruether, J.

    1993-01-01

    The rapidly developing area of computer systems creates new opportunities for commercial utilities operating nuclear reactors to improve plant operation and efficiency. Two of the main obstacles to utilizing the new technology in safety-related applications is the current policy of the licensing agencies and the fear of decision making managers to introduce new technologies. Once these obstacles are overcome, advanced diagnostic systems, CRT-based displays, and advanced communication channels can improve plant operation considerably. The article discusses outstanding issues in the area of designing, qualifying, and licensing of computer-based instrumentation and control systems. The authors describe the experience gained in designing three safety-related systems, that include a Programmable Logic Controller (PLC) based Safeguard Load Sequencer for NSP Prairie Island, a digital Containment Isolation monitoring system for TVA Browns Ferry, and a study that was conducted for EPRI/NSP regarding a PLC-based Reactor Protection system. This article presents the benefits to be gained in replacing existing, outdated equipment with new advanced instrumentation

  19. Computationally Efficient Prediction of Ionic Liquid Properties

    DEFF Research Database (Denmark)

    Chaban, V. V.; Prezhdo, O. V.

    2014-01-01

    Due to fundamental differences, room-temperature ionic liquids (RTIL) are significantly more viscous than conventional molecular liquids and require long simulation times. At the same time, RTILs remain in the liquid state over a much broader temperature range than the ordinary liquids. We exploit...... to ambient temperatures. We numerically prove the validity of the proposed concept for density and ionic diffusion of four different RTILs. This simple method enhances the computational efficiency of the existing simulation approaches as applied to RTILs by more than an order of magnitude....

  20. Predicting the acceptance of advanced rider assistance systems.

    Science.gov (United States)

    Huth, Véronique; Gelau, Christhard

    2013-01-01

    The strong prevalence of human error as a crash causation factor in motorcycle accidents calls for countermeasures that help tackling this issue. Advanced rider assistance systems pursue this goal, providing the riders with support and thus contributing to the prevention of crashes. However, the systems can only enhance riding safety if the riders use them. For this reason, acceptance is a decisive aspect to be considered in the development process of such systems. In order to be able to improve behavioural acceptance, the factors that influence the intention to use the system need to be identified. This paper examines the particularities of motorcycle riding and the characteristics of this user group that should be considered when predicting the acceptance of advanced rider assistance systems. Founded on theories predicting behavioural intention, the acceptance of technologies and the acceptance of driver support systems, a model on the acceptance of advanced rider assistance systems is proposed, including the perceived safety when riding without support, the interface design and the social norm as determinants of the usage intention. Since actual usage cannot be measured in the development stage of the systems, the willingness to have the system installed on the own motorcycle and the willingness to pay for the system are analyzed, constituting relevant conditions that allow for actual usage at a later stage. Its validation with the results from user tests on four advanced rider assistance systems allows confirming the social norm and the interface design as powerful predictors of the acceptance of ARAS, while the extent of perceived safety when riding without support did not have any predictive value in the present study. Copyright © 2012 Elsevier Ltd. All rights reserved.

  1. The history of cosmic baryons: discoveries using advanced computing

    International Nuclear Information System (INIS)

    Norman, Michael L

    2005-01-01

    We live in the era of the cosmological concordance model. This refers to the precise set of cosmological parameters which describe the average composition, geometry, and expansion rate of the universe we inhabit. Due to recent observational, theoretical, and computational advances, these parameters are now known to approximately 10% accuracy, and new efforts are underway to increase precision tenfold. It is found that we live in a spatially flat, dark matter-dominated universe whose rate of expansion is accelerating due to an unseen, unknown dark energy field. Baryons-the stuff of stars, galaxies, and us-account for only 4% of the total mass-energy inventory. And yet, it is through the astronomical study of baryons that we infer the rest. In this talk I will highlight the important role advanced scientific computing has played in getting us to the concordance model, and also the computational discoveries that have been made about the history of cosmic baryons using hydrodynamical cosmological simulations. I will conclude by discussing the central role that very large scale simulations of cosmological structure formation will play in deciphering the results of upcoming dark energy surveys

  2. A large-scale evaluation of computational protein function prediction

    NARCIS (Netherlands)

    Radivojac, P.; Clark, W.T.; Oron, T.R.; Schnoes, A.M.; Wittkop, T.; Kourmpetis, Y.A.I.; Dijk, van A.D.J.; Friedberg, I.

    2013-01-01

    Automated annotation of protein function is challenging. As the number of sequenced genomes rapidly grows, the overwhelming majority of protein products can only be annotated computationally. If computational predictions are to be relied upon, it is crucial that the accuracy of these methods be

  3. Evolutionary Computation Techniques for Predicting Atmospheric Corrosion

    Directory of Open Access Journals (Sweden)

    Amine Marref

    2013-01-01

    Full Text Available Corrosion occurs in many engineering structures such as bridges, pipelines, and refineries and leads to the destruction of materials in a gradual manner and thus shortening their lifespan. It is therefore crucial to assess the structural integrity of engineering structures which are approaching or exceeding their designed lifespan in order to ensure their correct functioning, for example, carrying ability and safety. An understanding of corrosion and an ability to predict corrosion rate of a material in a particular environment plays a vital role in evaluating the residual life of the material. In this paper we investigate the use of genetic programming and genetic algorithms in the derivation of corrosion-rate expressions for steel and zinc. Genetic programming is used to automatically evolve corrosion-rate expressions while a genetic algorithm is used to evolve the parameters of an already engineered corrosion-rate expression. We show that both evolutionary techniques yield corrosion-rate expressions that have good accuracy.

  4. Advances in Computational Stability Analysis of Composite Aerospace Structures

    International Nuclear Information System (INIS)

    Degenhardt, R.; Araujo, F. C. de

    2010-01-01

    European aircraft industry demands for reduced development and operating costs. Structural weight reduction by exploitation of structural reserves in composite aerospace structures contributes to this aim, however, it requires accurate and experimentally validated stability analysis of real structures under realistic loading conditions. This paper presents different advances from the area of computational stability analysis of composite aerospace structures which contribute to that field. For stringer stiffened panels main results of the finished EU project COCOMAT are given. It investigated the exploitation of reserves in primary fibre composite fuselage structures through an accurate and reliable simulation of postbuckling and collapse. For unstiffened cylindrical composite shells a proposal for a new design method is presented.

  5. 3D data processing with advanced computer graphics tools

    Science.gov (United States)

    Zhang, Song; Ekstrand, Laura; Grieve, Taylor; Eisenmann, David J.; Chumbley, L. Scott

    2012-09-01

    Often, the 3-D raw data coming from an optical profilometer contains spiky noises and irregular grid, which make it difficult to analyze and difficult to store because of the enormously large size. This paper is to address these two issues for an optical profilometer by substantially reducing the spiky noise of the 3-D raw data from an optical profilometer, and by rapidly re-sampling the raw data into regular grids at any pixel size and any orientation with advanced computer graphics tools. Experimental results will be presented to demonstrate the effectiveness of the proposed approach.

  6. Advanced computational modelling for drying processes – A review

    International Nuclear Information System (INIS)

    Defraeye, Thijs

    2014-01-01

    Highlights: • Understanding the product dehydration process is a key aspect in drying technology. • Advanced modelling thereof plays an increasingly important role for developing next-generation drying technology. • Dehydration modelling should be more energy-oriented. • An integrated “nexus” modelling approach is needed to produce more energy-smart products. • Multi-objective process optimisation requires development of more complete multiphysics models. - Abstract: Drying is one of the most complex and energy-consuming chemical unit operations. R and D efforts in drying technology have skyrocketed in the past decades, as new drivers emerged in this industry next to procuring prime product quality and high throughput, namely reduction of energy consumption and carbon footprint as well as improving food safety and security. Solutions are sought in optimising existing technologies or developing new ones which increase energy and resource efficiency, use renewable energy, recuperate waste heat and reduce product loss, thus also the embodied energy therein. Novel tools are required to push such technological innovations and their subsequent implementation. Particularly computer-aided drying process engineering has a large potential to develop next-generation drying technology, including more energy-smart and environmentally-friendly products and dryers systems. This review paper deals with rapidly emerging advanced computational methods for modelling dehydration of porous materials, particularly for foods. Drying is approached as a combined multiphysics, multiscale and multiphase problem. These advanced methods include computational fluid dynamics, several multiphysics modelling methods (e.g. conjugate modelling), multiscale modelling and modelling of material properties and the associated propagation of material property variability. Apart from the current challenges for each of these, future perspectives should be directed towards material property

  7. Software for the ACP [Advanced Computer Program] multiprocessor system

    International Nuclear Information System (INIS)

    Biel, J.; Areti, H.; Atac, R.

    1987-01-01

    Software has been developed for use with the Fermilab Advanced Computer Program (ACP) multiprocessor system. The software was designed to make a system of a hundred independent node processors as easy to use as a single, powerful CPU. Subroutines have been developed by which a user's host program can send data to and get results from the program running in each of his ACP node processors. Utility programs make it easy to compile and link host and node programs, to debug a node program on an ACP development system, and to submit a debugged program to an ACP production system

  8. Fermilab advanced computer program multi-microprocessor project

    International Nuclear Information System (INIS)

    Nash, T.; Areti, H.; Biel, J.

    1985-06-01

    Fermilab's Advanced Computer Program is constructing a powerful 128 node multi-microprocessor system for data analysis in high-energy physics. The system will use commercial 32-bit microprocessors programmed in Fortran-77. Extensive software supports easy migration of user applications from a uniprocessor environment to the multiprocessor and provides sophisticated program development, debugging, and error handling and recovery tools. This system is designed to be readily copied, providing computing cost effectiveness of below $2200 per VAX 11/780 equivalent. The low cost, commercial availability, compatibility with off-line analysis programs, and high data bandwidths (up to 160 MByte/sec) make the system an ideal choice for applications to on-line triggers as well as an offline data processor

  9. Review of research on advanced computational science in FY2016

    International Nuclear Information System (INIS)

    2017-12-01

    Research on advanced computational science for nuclear applications, based on “Plan to Achieve Medium- to Long-term Objectives of the Japan Atomic Energy Agency (Medium- to Long-term Plan)”, has been performed at Center for Computational Science and e-Systems (CCSE), Japan Atomic Energy Agency. CCSE established the committee consisting of outside experts and authorities which does research evaluation and advices for the assistance of the research and development. This report summarizes the followings. (1) Results of the R and D performed at CCSE in FY 2016 (April 1st, 2016 - March 31st, 2017), (2) Results of the evaluation on the R and D by the committee in FY 2016. (author)

  10. Advanced data analysis in neuroscience integrating statistical and computational models

    CERN Document Server

    Durstewitz, Daniel

    2017-01-01

    This book is intended for use in advanced graduate courses in statistics / machine learning, as well as for all experimental neuroscientists seeking to understand statistical methods at a deeper level, and theoretical neuroscientists with a limited background in statistics. It reviews almost all areas of applied statistics, from basic statistical estimation and test theory, linear and nonlinear approaches for regression and classification, to model selection and methods for dimensionality reduction, density estimation and unsupervised clustering.  Its focus, however, is linear and nonlinear time series analysis from a dynamical systems perspective, based on which it aims to convey an understanding also of the dynamical mechanisms that could have generated observed time series. Further, it integrates computational modeling of behavioral and neural dynamics with statistical estimation and hypothesis testing. This way computational models in neuroscience are not only explanat ory frameworks, but become powerfu...

  11. Review of research on advanced computational science in FY2015

    International Nuclear Information System (INIS)

    2017-01-01

    Research on advanced computational science for nuclear applications, based on 'Plan to Achieve Medium- to Long-term Objectives of the Japan Atomic Energy Agency (Medium- to Long-term Plan)', has been performed at Center for Computational Science and e-Systems (CCSE), Japan Atomic Energy Agency. CCSE established the committee consisting of outside experts and authorities which does research evaluation and advices for the assistance of the research and development. This report summarizes the followings. (1) Results of the R and D performed at CCSE in FY 2015 (April 1st, 2015 - March 31st, 2016), (2) Results of the evaluation on the R and D by the committee in FY 2015 (April 1st, 2015 - March 31st, 2016). (author)

  12. Advanced experimental and numerical techniques for cavitation erosion prediction

    CERN Document Server

    Chahine, Georges; Franc, Jean-Pierre; Karimi, Ayat

    2014-01-01

    This book provides a comprehensive treatment of the cavitation erosion phenomenon and state-of-the-art research in the field. It is divided into two parts. Part 1 consists of seven chapters, offering a wide range of computational and experimental approaches to cavitation erosion. It includes a general introduction to cavitation and cavitation erosion, a detailed description of facilities and measurement techniques commonly used in cavitation erosion studies, an extensive presentation of various stages of cavitation damage (including incubation and mass loss), and insights into the contribution of computational methods to the analysis of both fluid and material behavior. The proposed approach is based on a detailed description of impact loads generated by collapsing cavitation bubbles and a physical analysis of the material response to these loads. Part 2 is devoted to a selection of nine papers presented at the International Workshop on Advanced Experimental and Numerical Techniques for Cavitation Erosion (Gr...

  13. Computational prediction of chemical reactions: current status and outlook.

    Science.gov (United States)

    Engkvist, Ola; Norrby, Per-Ola; Selmi, Nidhal; Lam, Yu-Hong; Peng, Zhengwei; Sherer, Edward C; Amberg, Willi; Erhard, Thomas; Smyth, Lynette A

    2018-06-01

    Over the past few decades, various computational methods have become increasingly important for discovering and developing novel drugs. Computational prediction of chemical reactions is a key part of an efficient drug discovery process. In this review, we discuss important parts of this field, with a focus on utilizing reaction data to build predictive models, the existing programs for synthesis prediction, and usage of quantum mechanics and molecular mechanics (QM/MM) to explore chemical reactions. We also outline potential future developments with an emphasis on pre-competitive collaboration opportunities. Copyright © 2018 Elsevier Ltd. All rights reserved.

  14. The ACP (Advanced Computer Program) multiprocessor system at Fermilab

    Energy Technology Data Exchange (ETDEWEB)

    Nash, T.; Areti, H.; Atac, R.; Biel, J.; Case, G.; Cook, A.; Fischler, M.; Gaines, I.; Hance, R.; Husby, D.

    1986-09-01

    The Advanced Computer Program at Fermilab has developed a multiprocessor system which is easy to use and uniquely cost effective for many high energy physics problems. The system is based on single board computers which cost under $2000 each to build including 2 Mbytes of on board memory. These standard VME modules each run experiment reconstruction code in Fortran at speeds approaching that of a VAX 11/780. Two versions have been developed: one uses Motorola's 68020 32 bit microprocessor, the other runs with AT and T's 32100. both include the corresponding floating point coprocessor chip. The first system, when fully configured, uses 70 each of the two types of processors. A 53 processor system has been operated for several months with essentially no down time by computer operators in the Fermilab Computer Center, performing at nearly the capacity of 6 CDC Cyber 175 mainframe computers. The VME crates in which the processing ''nodes'' sit are connected via a high speed ''Branch Bus'' to one or more MicroVAX computers which act as hosts handling system resource management and all I/O in offline applications. An interface from Fastbus to the Branch Bus has been developed for online use which has been tested error free at 20 Mbytes/sec for 48 hours. ACP hardware modules are now available commercially. A major package of software, including a simulator that runs on any VAX, has been developed. It allows easy migration of existing programs to this multiprocessor environment. This paper describes the ACP Multiprocessor System and early experience with it at Fermilab and elsewhere.

  15. The ACP [Advanced Computer Program] multiprocessor system at Fermilab

    International Nuclear Information System (INIS)

    Nash, T.; Areti, H.; Atac, R.

    1986-09-01

    The Advanced Computer Program at Fermilab has developed a multiprocessor system which is easy to use and uniquely cost effective for many high energy physics problems. The system is based on single board computers which cost under $2000 each to build including 2 Mbytes of on board memory. These standard VME modules each run experiment reconstruction code in Fortran at speeds approaching that of a VAX 11/780. Two versions have been developed: one uses Motorola's 68020 32 bit microprocessor, the other runs with AT and T's 32100. both include the corresponding floating point coprocessor chip. The first system, when fully configured, uses 70 each of the two types of processors. A 53 processor system has been operated for several months with essentially no down time by computer operators in the Fermilab Computer Center, performing at nearly the capacity of 6 CDC Cyber 175 mainframe computers. The VME crates in which the processing ''nodes'' sit are connected via a high speed ''Branch Bus'' to one or more MicroVAX computers which act as hosts handling system resource management and all I/O in offline applications. An interface from Fastbus to the Branch Bus has been developed for online use which has been tested error free at 20 Mbytes/sec for 48 hours. ACP hardware modules are now available commercially. A major package of software, including a simulator that runs on any VAX, has been developed. It allows easy migration of existing programs to this multiprocessor environment. This paper describes the ACP Multiprocessor System and early experience with it at Fermilab and elsewhere

  16. Circulating CD147 predicts mortality in advanced hepatocellular carcinoma.

    Science.gov (United States)

    Lee, Aimei; Rode, Anthony; Nicoll, Amanda; Maczurek, Annette E; Lim, Lucy; Lim, Seok; Angus, Peter; Kronborg, Ian; Arachchi, Niranjan; Gorelik, Alexandra; Liew, Danny; Warner, Fiona J; McCaughan, Geoffrey W; McLennan, Susan V; Shackel, Nicholas A

    2016-02-01

    The glycoprotein CD147 has a role in tumor progression, is readily detectable in the circulation, and is abundantly expressed in hepatocellular carcinoma (HCC). Advanced HCC patients are a heterogeneous group with some individuals having dismal survival. The aim of this study was to examine circulating soluble CD147 levels as a prognostic marker in HCC patients. CD147 was measured in 277 patients (110 HCC, 115 chronic liver disease, and 52 non-liver disease). Clinical data included etiology, tumor progression, Barcelona Clinic Liver Cancer (BCLC) stage, and treatment response. Patients with HCC were stratified into two groups based upon the 75th percentile of CD147 levels (24 ng/mL). CD147 in HCC correlated inversely with poor survival (P = 0.031). Increased CD147 predicted poor survival in BCLC stages C and D (P = 0.045), and CD147 levels >24 ng/mL predicted a significantly diminished 90-day and 180-day survival time (hazard ratio [HR] = 6.1; 95% confidence interval [CI]: 2.1-63.2; P = 0.0045 and HR = 2.8; 95% CI: 1.2-12.6; P = 0.028, respectively). In BCLC stage C, CD147 predicted prognosis; levels >24 ng/mL were associated with a median survival of 1.5 months compared with 6.5 months with CD147 levels ≤24 ng/mL (P = 0.03). CD147 also identified patients with a poor prognosis independent from treatment frequency, modality, and tumor size. Circulating CD147 is an independent marker of survival in advanced HCC. CD147 requires further evaluation as a potential new prognostic measure in HCC to identify patients with advanced disease who have a poor prognosis. © 2015 Journal of Gastroenterology and Hepatology Foundation and John Wiley & Sons Australia, Ltd.

  17. Advanced soft computing diagnosis method for tumour grading.

    Science.gov (United States)

    Papageorgiou, E I; Spyridonos, P P; Stylios, C D; Ravazoula, P; Groumpos, P P; Nikiforidis, G N

    2006-01-01

    To develop an advanced diagnostic method for urinary bladder tumour grading. A novel soft computing modelling methodology based on the augmentation of fuzzy cognitive maps (FCMs) with the unsupervised active Hebbian learning (AHL) algorithm is applied. One hundred and twenty-eight cases of urinary bladder cancer were retrieved from the archives of the Department of Histopathology, University Hospital of Patras, Greece. All tumours had been characterized according to the classical World Health Organization (WHO) grading system. To design the FCM model for tumour grading, three experts histopathologists defined the main histopathological features (concepts) and their impact on grade characterization. The resulted FCM model consisted of nine concepts. Eight concepts represented the main histopathological features for tumour grading. The ninth concept represented the tumour grade. To increase the classification ability of the FCM model, the AHL algorithm was applied to adjust the weights of the FCM. The proposed FCM grading model achieved a classification accuracy of 72.5%, 74.42% and 95.55% for tumours of grades I, II and III, respectively. An advanced computerized method to support tumour grade diagnosis decision was proposed and developed. The novelty of the method is based on employing the soft computing method of FCMs to represent specialized knowledge on histopathology and on augmenting FCMs ability using an unsupervised learning algorithm, the AHL. The proposed method performs with reasonably high accuracy compared to other existing methods and at the same time meets the physicians' requirements for transparency and explicability.

  18. Computational methods in sequence and structure prediction

    Science.gov (United States)

    Lang, Caiyi

    This dissertation is organized into two parts. In the first part, we will discuss three computational methods for cis-regulatory element recognition in three different gene regulatory networks as the following: (a) Using a comprehensive "Phylogenetic Footprinting Comparison" method, we will investigate the promoter sequence structures of three enzymes (PAL, CHS and DFR) that catalyze sequential steps in the pathway from phenylalanine to anthocyanins in plants. Our result shows there exists a putative cis-regulatory element "AC(C/G)TAC(C)" in the upstream of these enzyme genes. We propose this cis-regulatory element to be responsible for the genetic regulation of these three enzymes and this element, might also be the binding site for MYB class transcription factor PAP1. (b) We will investigate the role of the Arabidopsis gene glutamate receptor 1.1 (AtGLR1.1) in C and N metabolism by utilizing the microarray data we obtained from AtGLR1.1 deficient lines (antiAtGLR1.1). We focus our investigation on the putatively co-regulated transcript profile of 876 genes we have collected in antiAtGLR1.1 lines. By (a) scanning the occurrence of several groups of known abscisic acid (ABA) related cisregulatory elements in the upstream regions of 876 Arabidopsis genes; and (b) exhaustive scanning of all possible 6-10 bps motif occurrence in the upstream regions of the same set of genes, we are able to make a quantative estimation on the enrichment level of each of the cis-regulatory element candidates. We finally conclude that one specific cis-regulatory element group, called "ABRE" elements, are statistically highly enriched within the 876-gene group as compared to their occurrence within the genome. (c) We will introduce a new general purpose algorithm, called "fuzzy REDUCE1", which we have developed recently for automated cis-regulatory element identification. In the second part, we will discuss our newly devised protein design framework. With this framework we have developed

  19. Image analysis and modeling in medical image computing. Recent developments and advances.

    Science.gov (United States)

    Handels, H; Deserno, T M; Meinzer, H-P; Tolxdorff, T

    2012-01-01

    Medical image computing is of growing importance in medical diagnostics and image-guided therapy. Nowadays, image analysis systems integrating advanced image computing methods are used in practice e.g. to extract quantitative image parameters or to support the surgeon during a navigated intervention. However, the grade of automation, accuracy, reproducibility and robustness of medical image computing methods has to be increased to meet the requirements in clinical routine. In the focus theme, recent developments and advances in the field of modeling and model-based image analysis are described. The introduction of models in the image analysis process enables improvements of image analysis algorithms in terms of automation, accuracy, reproducibility and robustness. Furthermore, model-based image computing techniques open up new perspectives for prediction of organ changes and risk analysis of patients. Selected contributions are assembled to present latest advances in the field. The authors were invited to present their recent work and results based on their outstanding contributions to the Conference on Medical Image Computing BVM 2011 held at the University of Lübeck, Germany. All manuscripts had to pass a comprehensive peer review. Modeling approaches and model-based image analysis methods showing new trends and perspectives in model-based medical image computing are described. Complex models are used in different medical applications and medical images like radiographic images, dual-energy CT images, MR images, diffusion tensor images as well as microscopic images are analyzed. The applications emphasize the high potential and the wide application range of these methods. The use of model-based image analysis methods can improve segmentation quality as well as the accuracy and reproducibility of quantitative image analysis. Furthermore, image-based models enable new insights and can lead to a deeper understanding of complex dynamic mechanisms in the human body

  20. Advanced Simulation and Computing Fiscal Year 14 Implementation Plan, Rev. 0.5

    Energy Technology Data Exchange (ETDEWEB)

    Meisner, Robert [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); McCoy, Michel [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Archer, Bill [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Matzen, M. Keith [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States)

    2013-09-11

    The Stockpile Stewardship Program (SSP) is a single, highly integrated technical program for maintaining the surety and reliability of the U.S. nuclear stockpile. The SSP uses nuclear test data, computational modeling and simulation, and experimental facilities to advance understanding of nuclear weapons. It includes stockpile surveillance, experimental research, development and engineering programs, and an appropriately scaled production capability to support stockpile requirements. This integrated national program requires the continued use of experimental facilities and programs, and the computational enhancements to support these programs. The Advanced Simulation and Computing Program (ASC) is a cornerstone of the SSP, providing simulation capabilities and computational resources that support annual stockpile assessment and certification, study advanced nuclear weapons design and manufacturing processes, analyze accident scenarios and weapons aging, and provide the tools to enable stockpile Life Extension Programs (LEPs) and the resolution of Significant Finding Investigations (SFIs). This requires a balanced resource, including technical staff, hardware, simulation software, and computer science solutions. In its first decade, the ASC strategy focused on demonstrating simulation capabilities of unprecedented scale in three spatial dimensions. In its second decade, ASC is now focused on increasing predictive capabilities in a three-dimensional (3D) simulation environment while maintaining support to the SSP. The program continues to improve its unique tools for solving progressively more difficult stockpile problems (sufficient resolution, dimensionality, and scientific details), quantify critical margins and uncertainties, and resolve increasingly difficult analyses needed for the SSP. Moreover, ASC’s business model is integrated and focused on requirements-driven products that address long-standing technical questions related to enhanced predictive

  1. Advanced Simulation and Computing Fiscal Year 2011-2012 Implementation Plan, Revision 0.5

    Energy Technology Data Exchange (ETDEWEB)

    McCoy, Michel [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Phillips, Julia [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Wampler, Cheryl [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Meisner, Robert [National Nuclear Security Administration (NNSA), Washington, DC (United States)

    2010-09-13

    The Stockpile Stewardship Program (SSP) is a single, highly integrated technical program for maintaining the surety and reliability of the U.S. nuclear stockpile. The SSP uses past nuclear test data along with current and future non-nuclear test data, computational modeling and simulation, and experimental facilities to advance understanding of nuclear weapons. It includes stockpile surveillance, experimental research, development and engineering (D&E) programs, and an appropriately scaled production capability to support stockpile requirements. This integrated national program requires the continued use of current facilities and programs along with new experimental facilities and computational enhancements to support these programs. The Advanced Simulation and Computing Program (ASC) is a cornerstone of the SSP, providing simulation capabilities and computational resources to support the annual stockpile assessment and certification, to study advanced nuclear weapons design and manufacturing processes, to analyze accident scenarios and weapons aging, and to provide the tools to enable stockpile Life Extension Programs (LEPs) and the resolution of Significant Finding Investigations (SFIs). This requires a balanced resource, including technical staff, hardware, simulation software, and computer science solutions. In its first decade, the ASC strategy focused on demonstrating simulation capabilities of unprecedented scale in three spatial dimensions. In its second decade, ASC is focused on increasing its predictive capabilities in a three-dimensional (3D) simulation environment while maintaining support to the SSP. The program continues to improve its unique tools for solving progressively more difficult stockpile problems (focused on sufficient resolution, dimensionality, and scientific details); to quantify critical margins and uncertainties; and to resolve increasingly difficult analyses needed for the SSP. Moreover, ASC has restructured its business model from

  2. Scaling predictive modeling in drug development with cloud computing.

    Science.gov (United States)

    Moghadam, Behrooz Torabi; Alvarsson, Jonathan; Holm, Marcus; Eklund, Martin; Carlsson, Lars; Spjuth, Ola

    2015-01-26

    Growing data sets with increased time for analysis is hampering predictive modeling in drug discovery. Model building can be carried out on high-performance computer clusters, but these can be expensive to purchase and maintain. We have evaluated ligand-based modeling on cloud computing resources where computations are parallelized and run on the Amazon Elastic Cloud. We trained models on open data sets of varying sizes for the end points logP and Ames mutagenicity and compare with model building parallelized on a traditional high-performance computing cluster. We show that while high-performance computing results in faster model building, the use of cloud computing resources is feasible for large data sets and scales well within cloud instances. An additional advantage of cloud computing is that the costs of predictive models can be easily quantified, and a choice can be made between speed and economy. The easy access to computational resources with no up-front investments makes cloud computing an attractive alternative for scientists, especially for those without access to a supercomputer, and our study shows that it enables cost-efficient modeling of large data sets on demand within reasonable time.

  3. Predictive Control of Networked Multiagent Systems via Cloud Computing.

    Science.gov (United States)

    Liu, Guo-Ping

    2017-01-18

    This paper studies the design and analysis of networked multiagent predictive control systems via cloud computing. A cloud predictive control scheme for networked multiagent systems (NMASs) is proposed to achieve consensus and stability simultaneously and to compensate for network delays actively. The design of the cloud predictive controller for NMASs is detailed. The analysis of the cloud predictive control scheme gives the necessary and sufficient conditions of stability and consensus of closed-loop networked multiagent control systems. The proposed scheme is verified to characterize the dynamical behavior and control performance of NMASs through simulations. The outcome provides a foundation for the development of cooperative and coordinative control of NMASs and its applications.

  4. DOE Advanced Scientific Computing Advisory Committee (ASCAC) Report: Exascale Computing Initiative Review

    Energy Technology Data Exchange (ETDEWEB)

    Reed, Daniel [University of Iowa; Berzins, Martin [University of Utah; Pennington, Robert; Sarkar, Vivek [Rice University; Taylor, Valerie [Texas A& M University

    2015-08-01

    On November 19, 2014, the Advanced Scientific Computing Advisory Committee (ASCAC) was charged with reviewing the Department of Energy’s conceptual design for the Exascale Computing Initiative (ECI). In particular, this included assessing whether there are significant gaps in the ECI plan or areas that need to be given priority or extra management attention. Given the breadth and depth of previous reviews of the technical challenges inherent in exascale system design and deployment, the subcommittee focused its assessment on organizational and management issues, considering technical issues only as they informed organizational or management priorities and structures. This report presents the observations and recommendations of the subcommittee.

  5. International conference on Advances in Intelligent Control and Innovative Computing

    CERN Document Server

    Castillo, Oscar; Huang, Xu; Intelligent Control and Innovative Computing

    2012-01-01

    In the lightning-fast world of intelligent control and cutting-edge computing, it is vitally important to stay abreast of developments that seem to follow each other without pause. This publication features the very latest and some of the very best current research in the field, with 32 revised and extended research articles written by prominent researchers in the field. Culled from contributions to the key 2011 conference Advances in Intelligent Control and Innovative Computing, held in Hong Kong, the articles deal with a wealth of relevant topics, from the most recent work in artificial intelligence and decision-supporting systems, to automated planning, modelling and simulation, signal processing, and industrial applications. Not only does this work communicate the current state of the art in intelligent control and innovative computing, it is also an illuminating guide to up-to-date topics for researchers and graduate students in the field. The quality of the contents is absolutely assured by the high pro...

  6. Computational brain models: Advances from system biology and future challenges

    Directory of Open Access Journals (Sweden)

    George E. Barreto

    2015-02-01

    Full Text Available Computational brain models focused on the interactions between neurons and astrocytes, modeled via metabolic reconstructions, are reviewed. The large source of experimental data provided by the -omics techniques and the advance/application of computational and data-management tools are being fundamental. For instance, in the understanding of the crosstalk between these cells, the key neuroprotective mechanisms mediated by astrocytes in specific metabolic scenarios (1 and the identification of biomarkers for neurodegenerative diseases (2,3. However, the modeling of these interactions demands a clear view of the metabolic and signaling pathways implicated, but most of them are controversial and are still under evaluation (4. Hence, to gain insight into the complexity of these interactions a current view of the main pathways implicated in the neuron-astrocyte communication processes have been made from recent experimental reports and reviews. Furthermore, target problems, limitations and main conclusions have been identified from metabolic models of the brain reported from 2010. Finally, key aspects to take into account into the development of a computational model of the brain and topics that could be approached from a systems biology perspective in future research are highlighted.

  7. Advances in engineering turbulence modeling. [computational fluid dynamics

    Science.gov (United States)

    Shih, T.-H.

    1992-01-01

    Some new developments in two equation models and second order closure models are presented. In this paper, modified two equation models are proposed to remove shortcomings such as computing flows over complex geometries and the ad hoc treatment near the separation and reattachment points. The calculations using various two equation models are compared with direct numerical solutions of channel flows and flat plate boundary layers. Development of second order closure models will also be discussed with emphasis on the modeling of pressure related correlation terms and dissipation rates in the second moment equations. All existing models poorly predict the normal stresses near the wall and fail to predict the three dimensional effect of mean flow on the turbulence. The newly developed second order near-wall turbulence model to be described in this paper is capable of capturing the near-wall behavior of turbulence as well as the effect of three dimension mean flow on the turbulence.

  8. Analytical predictions of SGEMP response and comparisons with computer calculations

    International Nuclear Information System (INIS)

    de Plomb, E.P.

    1976-01-01

    An analytical formulation for the prediction of SGEMP surface current response is presented. Only two independent dimensionless parameters are required to predict the peak magnitude and rise time of SGEMP induced surface currents. The analysis applies to limited (high fluence) emission as well as unlimited (low fluence) emission. Cause-effect relationships for SGEMP response are treated quantitatively, and yield simple power law dependencies between several physical variables. Analytical predictions for a large matrix of SGEMP cases are compared with an array of about thirty-five computer solutions of similar SGEMP problems, which were collected from three independent research groups. The theoretical solutions generally agree with the computer solutions as well as the computer solutions agree with one another. Such comparisons typically show variations less than a ''factor of two.''

  9. Thermal Model Predictions of Advanced Stirling Radioisotope Generator Performance

    Science.gov (United States)

    Wang, Xiao-Yen J.; Fabanich, William Anthony; Schmitz, Paul C.

    2014-01-01

    This paper presents recent thermal model results of the Advanced Stirling Radioisotope Generator (ASRG). The three-dimensional (3D) ASRG thermal power model was built using the Thermal Desktop(trademark) thermal analyzer. The model was correlated with ASRG engineering unit test data and ASRG flight unit predictions from Lockheed Martin's (LM's) I-deas(trademark) TMG thermal model. The auxiliary cooling system (ACS) of the ASRG is also included in the ASRG thermal model. The ACS is designed to remove waste heat from the ASRG so that it can be used to heat spacecraft components. The performance of the ACS is reported under nominal conditions and during a Venus flyby scenario. The results for the nominal case are validated with data from Lockheed Martin. Transient thermal analysis results of ASRG for a Venus flyby with a representative trajectory are also presented. In addition, model results of an ASRG mounted on a Cassini-like spacecraft with a sunshade are presented to show a way to mitigate the high temperatures of a Venus flyby. It was predicted that the sunshade can lower the temperature of the ASRG alternator by 20 C for the representative Venus flyby trajectory. The 3D model also was modified to predict generator performance after a single Advanced Stirling Convertor failure. The geometry of the Microtherm HT insulation block on the outboard side was modified to match deformation and shrinkage observed during testing of a prototypic ASRG test fixture by LM. Test conditions and test data were used to correlate the model by adjusting the thermal conductivity of the deformed insulation to match the post-heat-dump steady state temperatures. Results for these conditions showed that the performance of the still-functioning inboard ACS was unaffected.

  10. Advanced Simulation & Computing FY15 Implementation Plan Volume 2, Rev. 0.5

    Energy Technology Data Exchange (ETDEWEB)

    McCoy, Michel [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Archer, Bill [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Matzen, M. Keith [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States)

    2014-09-16

    The Stockpile Stewardship Program (SSP) is a single, highly integrated technical program for maintaining the surety and reliability of the U.S. nuclear stockpile. The SSP uses nuclear test data, computational modeling and simulation, and experimental facilities to advance understanding of nuclear weapons. It includes stockpile surveillance, experimental research, development and engineering programs, and an appropriately scaled production capability to support stockpile requirements. This integrated national program requires the continued use of experimental facilities and programs, and the computational enhancements to support these programs. The Advanced Simulation and Computing Program (ASC) is a cornerstone of the SSP, providing simulation capabilities and computational resources that support annual stockpile assessment and certification, study advanced nuclear weapons design and manufacturing processes, analyze accident scenarios and weapons aging, and provide the tools to enable stockpile Life Extension Programs (LEPs) and the resolution of Significant Finding Investigations (SFIs). This requires a balance of resource, including technical staff, hardware, simulation software, and computer science solutions. As the program approaches the end of its second decade, ASC is intently focused on increasing predictive capabilities in a three-dimensional (3D) simulation environment while maintaining support to the SSP. The program continues to improve its unique tools for solving progressively more difficult stockpile problems (sufficient resolution, dimensionality, and scientific details), quantify critical margins and uncertainties, and resolve increasingly difficult analyses needed for the SSP. Where possible, the program also enables the use of high-performance simulation and computing tools to address broader national security needs, such as foreign nuclear weapon assessments and counternuclear terrorism.

  11. Three-dimensional protein structure prediction: Methods and computational strategies.

    Science.gov (United States)

    Dorn, Márcio; E Silva, Mariel Barbachan; Buriol, Luciana S; Lamb, Luis C

    2014-10-12

    A long standing problem in structural bioinformatics is to determine the three-dimensional (3-D) structure of a protein when only a sequence of amino acid residues is given. Many computational methodologies and algorithms have been proposed as a solution to the 3-D Protein Structure Prediction (3-D-PSP) problem. These methods can be divided in four main classes: (a) first principle methods without database information; (b) first principle methods with database information; (c) fold recognition and threading methods; and (d) comparative modeling methods and sequence alignment strategies. Deterministic computational techniques, optimization techniques, data mining and machine learning approaches are typically used in the construction of computational solutions for the PSP problem. Our main goal with this work is to review the methods and computational strategies that are currently used in 3-D protein prediction. Copyright © 2014 Elsevier Ltd. All rights reserved.

  12. Advanced Simulation and Computing FY08-09 Implementation Plan Volume 2 Revision 0

    International Nuclear Information System (INIS)

    McCoy, M; Kusnezov, D; Bikkel, T; Hopson, J

    2007-01-01

    The Stockpile Stewardship Program (SSP) is a single, highly integrated technical program for maintaining the safety and reliability of the U.S. nuclear stockpile. The SSP uses past nuclear test data along with current and future nonnuclear test data, computational modeling and simulation, and experimental facilities to advance understanding of nuclear weapons. It includes stockpile surveillance, experimental research, development and engineering programs, and an appropriately scaled production capability to support stockpile requirements. This integrated national program requires the continued use of current facilities and programs along with new experimental facilities and computational enhancements to support these programs. The Advanced Simulation and Computing Program (ASC) is a cornerstone of the SSP, providing simulation capabilities and computational resources to support the annual stockpile assessment and certification, to study advanced nuclear-weapons design and manufacturing processes, to analyze accident scenarios and weapons aging, and to provide the tools to enable Stockpile Life Extension Programs (SLEPs) and the resolution of Significant Finding Investigations (SFIs). This requires a balanced resource, including technical staff, hardware, simulation software, and computer science solutions. In its first decade, the ASC strategy focused on demonstrating simulation capabilities of unprecedented scale in three spatial dimensions. In its second decade, ASC is focused on increasing its predictive capabilities in a three-dimensional simulation environment while maintaining the support to the SSP. The program continues to improve its unique tools for solving progressively more difficult stockpile problems (focused on sufficient resolution, dimensionality and scientific details); to quantify critical margins and uncertainties (QMU); and to resolve increasingly difficult analyses needed for the SSP. Moreover, ASC has restructured its business model from one

  13. Advanced Simulation and Computing FY10-FY11 Implementation Plan Volume 2, Rev. 0.5

    Energy Technology Data Exchange (ETDEWEB)

    Meisner, R; Peery, J; McCoy, M; Hopson, J

    2009-09-08

    The Stockpile Stewardship Program (SSP) is a single, highly integrated technical program for maintaining the surety and reliability of the U.S. nuclear stockpile. The SSP uses past nuclear test data along with current and future non-nuclear test data, computational modeling and simulation, and experimental facilities to advance understanding of nuclear weapons. It includes stockpile surveillance, experimental research, development and engineering (D&E) programs, and an appropriately scaled production capability to support stockpile requirements. This integrated national program requires the continued use of current facilities and programs along with new experimental facilities and computational enhancements to support these programs. The Advanced Simulation and Computing Program (ASC) is a cornerstone of the SSP, providing simulation capabilities and computational resources to support the annual stockpile assessment and certification, to study advanced nuclear weapons design and manufacturing processes, to analyze accident scenarios and weapons aging, and to provide the tools to enable stockpile Life Extension Programs (LEPs) and the resolution of Significant Finding Investigations (SFIs). This requires a balanced resource, including technical staff, hardware, simulation software, and computer science solutions. In its first decade, the ASC strategy focused on demonstrating simulation capabilities of unprecedented scale in three spatial dimensions. In its second decade, ASC is focused on increasing its predictive capabilities in a three-dimensional (3D) simulation environment while maintaining support to the SSP. The program continues to improve its unique tools for solving progressively more difficult stockpile problems (focused on sufficient resolution, dimensionality and scientific details); to quantify critical margins and uncertainties (QMU); and to resolve increasingly difficult analyses needed for the SSP. Moreover, ASC has restructured its business model

  14. Advanced Simulation and Computing FY09-FY10 Implementation Plan Volume 2, Rev. 1

    Energy Technology Data Exchange (ETDEWEB)

    Kissel, L

    2009-04-01

    The Stockpile Stewardship Program (SSP) is a single, highly integrated technical program for maintaining the surety and reliability of the U.S. nuclear stockpile. The SSP uses past nuclear test data along with current and future non-nuclear test data, computational modeling and simulation, and experimental facilities to advance understanding of nuclear weapons. It includes stockpile surveillance, experimental research, development and engineering programs, and an appropriately scaled production capability to support stockpile requirements. This integrated national program requires the continued use of current facilities and programs along with new experimental facilities and computational enhancements to support these programs. The Advanced Simulation and Computing Program (ASC) is a cornerstone of the SSP, providing simulation capabilities and computational resources to support the annual stockpile assessment and certification, to study advanced nuclear weapons design and manufacturing processes, to analyze accident scenarios and weapons aging, and to provide the tools to enable stockpile Life Extension Programs (LEPs) and the resolution of Significant Finding Investigations (SFIs). This requires a balanced resource, including technical staff, hardware, simulation software, and computer science solutions. In its first decade, the ASC strategy focused on demonstrating simulation capabilities of unprecedented scale in three spatial dimensions. In its second decade, ASC is focused on increasing its predictive capabilities in a three-dimensional simulation environment while maintaining support to the SSP. The program continues to improve its unique tools for solving progressively more difficult stockpile problems (focused on sufficient resolution, dimensionality and scientific details); to quantify critical margins and uncertainties (QMU); and to resolve increasingly difficult analyses needed for the SSP. Moreover, ASC has restructured its business model from one that

  15. Advanced Simulation and Computing FY09-FY10 Implementation Plan, Volume 2, Revision 0.5

    Energy Technology Data Exchange (ETDEWEB)

    Meisner, R; Hopson, J; Peery, J; McCoy, M

    2008-10-07

    The Stockpile Stewardship Program (SSP) is a single, highly integrated technical program for maintaining the surety and reliability of the U.S. nuclear stockpile. The SSP uses past nuclear test data along with current and future non-nuclear test data, computational modeling and simulation, and experimental facilities to advance understanding of nuclear weapons. It includes stockpile surveillance, experimental research, development and engineering programs, and an appropriately scaled production capability to support stockpile requirements. This integrated national program requires the continued use of current facilities and programs along with new experimental facilities and computational enhancements to support these programs. The Advanced Simulation and Computing Program (ASC)1 is a cornerstone of the SSP, providing simulation capabilities and computational resources to support the annual stockpile assessment and certification, to study advanced nuclear weapons design and manufacturing processes, to analyze accident scenarios and weapons aging, and to provide the tools to enable stockpile Life Extension Programs (LEPs) and the resolution of Significant Finding Investigations (SFIs). This requires a balanced resource, including technical staff, hardware, simulation software, and computer science solutions. In its first decade, the ASC strategy focused on demonstrating simulation capabilities of unprecedented scale in three spatial dimensions. In its second decade, ASC is focused on increasing its predictive capabilities in a three-dimensional simulation environment while maintaining support to the SSP. The program continues to improve its unique tools for solving progressively more difficult stockpile problems (focused on sufficient resolution, dimensionality and scientific details); to quantify critical margins and uncertainties (QMU); and to resolve increasingly difficult analyses needed for the SSP. Moreover, ASC has restructured its business model from one

  16. Advanced Simulation and Computing FY10-11 Implementation Plan Volume 2, Rev. 0

    Energy Technology Data Exchange (ETDEWEB)

    Carnes, B

    2009-06-08

    The Stockpile Stewardship Program (SSP) is a single, highly integrated technical program for maintaining the surety and reliability of the U.S. nuclear stockpile. The SSP uses past nuclear test data along with current and future non-nuclear test data, computational modeling and simulation, and experimental facilities to advance understanding of nuclear weapons. It includes stockpile surveillance, experimental research, development and engineering programs, and an appropriately scaled production capability to support stockpile requirements. This integrated national program requires the continued use of current facilities and programs along with new experimental facilities and computational enhancements to support these programs. The Advanced Simulation and Computing Program (ASC) is a cornerstone of the SSP, providing simulation capabilities and computational resources to support the annual stockpile assessment and certification, to study advanced nuclear weapons design and manufacturing processes, to analyze accident scenarios and weapons aging, and to provide the tools to enable stockpile Life Extension Programs (LEPs) and the resolution of Significant Finding Investigations (SFIs). This requires a balanced resource, including technical staff, hardware, simulation software, and computer science solutions. In its first decade, the ASC strategy focused on demonstrating simulation capabilities of unprecedented scale in three spatial dimensions. In its second decade, ASC is focused on increasing its predictive capabilities in a three-dimensional simulation environment while maintaining support to the SSP. The program continues to improve its unique tools for solving progressively more difficult stockpile problems (focused on sufficient resolution, dimensionality and scientific details); to quantify critical margins and uncertainties (QMU); and to resolve increasingly difficult analyses needed for the SSP. Moreover, ASC has restructured its business model from one that

  17. Advanced Simulation and Computing Fiscal Year 2011-2012 Implementation Plan, Revision 0

    Energy Technology Data Exchange (ETDEWEB)

    McCoy, M; Phillips, J; Hpson, J; Meisner, R

    2010-04-22

    The Stockpile Stewardship Program (SSP) is a single, highly integrated technical program for maintaining the surety and reliability of the U.S. nuclear stockpile. The SSP uses past nuclear test data along with current and future non-nuclear test data, computational modeling and simulation, and experimental facilities to advance understanding of nuclear weapons. It includes stockpile surveillance, experimental research, development and engineering (D&E) programs, and an appropriately scaled production capability to support stockpile requirements. This integrated national program requires the continued use of current facilities and programs along with new experimental facilities and computational enhancements to support these programs. The Advanced Simulation and Computing Program (ASC) is a cornerstone of the SSP, providing simulation capabilities and computational resources to support the annual stockpile assessment and certification, to study advanced nuclear weapons design and manufacturing processes, to analyze accident scenarios and weapons aging, and to provide the tools to enable stockpile Life Extension Programs (LEPs) and the resolution of Significant Finding Investigations (SFIs). This requires a balanced resource, including technical staff, hardware, simulation software, and computer science solutions. In its first decade, the ASC strategy focused on demonstrating simulation capabilities of unprecedented scale in three spatial dimensions. In its second decade, ASC is focused on increasing its predictive capabilities in a three-dimensional (3D) simulation environment while maintaining support to the SSP. The program continues to improve its unique tools for solving progressively more difficult stockpile problems (focused on sufficient resolution, dimensionality and scientific details); to quantify critical margins and uncertainties (QMU); and to resolve increasingly difficult analyses needed for the SSP. Moreover, ASC has restructured its business model

  18. Advanced Simulation and Computing FY08-09 Implementation Plan, Volume 2, Revision 0.5

    Energy Technology Data Exchange (ETDEWEB)

    Kusnezov, D; Bickel, T; McCoy, M; Hopson, J

    2007-09-13

    The Stockpile Stewardship Program (SSP) is a single, highly integrated technical program for maintaining the surety and reliability of the U.S. nuclear stockpile. The SSP uses past nuclear test data along with current and future non-nuclear test data, computational modeling and simulation, and experimental facilities to advance understanding of nuclear weapons. It includes stockpile surveillance, experimental research, development and engineering programs, and an appropriately scaled production capability to support stockpile requirements. This integrated national program requires the continued use of current facilities and programs along with new experimental facilities and computational enhancements to support these programs. The Advanced Simulation and Computing Program (ASC)1 is a cornerstone of the SSP, providing simulation capabilities and computational resources to support the annual stockpile assessment and certification, to study advanced nuclear-weapons design and manufacturing processes, to analyze accident scenarios and weapons aging, and to provide the tools to enable Stockpile Life Extension Programs (SLEPs) and the resolution of Significant Finding Investigations (SFIs). This requires a balanced resource, including technical staff, hardware, simulation software, and computer science solutions. In its first decade, the ASC strategy focused on demonstrating simulation capabilities of unprecedented scale in three spatial dimensions. In its second decade, ASC is focused on increasing its predictive capabilities in a three-dimensional simulation environment while maintaining the support to the SSP. The program continues to improve its unique tools for solving progressively more difficult stockpile problems (focused on sufficient resolution, dimensionality and scientific details); to quantify critical margins and uncertainties (QMU); and to resolve increasingly difficult analyses needed for the SSP. Moreover, ASC has restructured its business model from

  19. Microarray-based cancer prediction using soft computing approach.

    Science.gov (United States)

    Wang, Xiaosheng; Gotoh, Osamu

    2009-05-26

    One of the difficulties in using gene expression profiles to predict cancer is how to effectively select a few informative genes to construct accurate prediction models from thousands or ten thousands of genes. We screen highly discriminative genes and gene pairs to create simple prediction models involved in single genes or gene pairs on the basis of soft computing approach and rough set theory. Accurate cancerous prediction is obtained when we apply the simple prediction models for four cancerous gene expression datasets: CNS tumor, colon tumor, lung cancer and DLBCL. Some genes closely correlated with the pathogenesis of specific or general cancers are identified. In contrast with other models, our models are simple, effective and robust. Meanwhile, our models are interpretable for they are based on decision rules. Our results demonstrate that very simple models may perform well on cancerous molecular prediction and important gene markers of cancer can be detected if the gene selection approach is chosen reasonably.

  20. PSPP: a protein structure prediction pipeline for computing clusters.

    Directory of Open Access Journals (Sweden)

    Michael S Lee

    2009-07-01

    Full Text Available Protein structures are critical for understanding the mechanisms of biological systems and, subsequently, for drug and vaccine design. Unfortunately, protein sequence data exceed structural data by a factor of more than 200 to 1. This gap can be partially filled by using computational protein structure prediction. While structure prediction Web servers are a notable option, they often restrict the number of sequence queries and/or provide a limited set of prediction methodologies. Therefore, we present a standalone protein structure prediction software package suitable for high-throughput structural genomic applications that performs all three classes of prediction methodologies: comparative modeling, fold recognition, and ab initio. This software can be deployed on a user's own high-performance computing cluster.The pipeline consists of a Perl core that integrates more than 20 individual software packages and databases, most of which are freely available from other research laboratories. The query protein sequences are first divided into domains either by domain boundary recognition or Bayesian statistics. The structures of the individual domains are then predicted using template-based modeling or ab initio modeling. The predicted models are scored with a statistical potential and an all-atom force field. The top-scoring ab initio models are annotated by structural comparison against the Structural Classification of Proteins (SCOP fold database. Furthermore, secondary structure, solvent accessibility, transmembrane helices, and structural disorder are predicted. The results are generated in text, tab-delimited, and hypertext markup language (HTML formats. So far, the pipeline has been used to study viral and bacterial proteomes.The standalone pipeline that we introduce here, unlike protein structure prediction Web servers, allows users to devote their own computing assets to process a potentially unlimited number of queries as well as perform

  1. Advanced information processing system: Inter-computer communication services

    Science.gov (United States)

    Burkhardt, Laura; Masotto, Tom; Sims, J. Terry; Whittredge, Roy; Alger, Linda S.

    1991-01-01

    The purpose is to document the functional requirements and detailed specifications for the Inter-Computer Communications Services (ICCS) of the Advanced Information Processing System (AIPS). An introductory section is provided to outline the overall architecture and functional requirements of the AIPS and to present an overview of the ICCS. An overview of the AIPS architecture as well as a brief description of the AIPS software is given. The guarantees of the ICCS are provided, and the ICCS is described as a seven-layered International Standards Organization (ISO) Model. The ICCS functional requirements, functional design, and detailed specifications as well as each layer of the ICCS are also described. A summary of results and suggestions for future work are presented.

  2. SciDAC advances and applications in computational beam dynamics

    International Nuclear Information System (INIS)

    Ryne, R; Abell, D; Adelmann, A; Amundson, J; Bohn, C; Cary, J; Colella, P; Dechow, D; Decyk, V; Dragt, A; Gerber, R; Habib, S; Higdon, D; Katsouleas, T; Ma, K-L; McCorquodale, P; Mihalcea, D; Mitchell, C; Mori, W; Mottershead, C T; Neri, F; Pogorelov, I; Qiang, J; Samulyak, R; Serafini, D; Shalf, J; Siegerist, C; Spentzouris, P; Stoltz, P; Terzic, B; Venturini, M; Walstrom, P

    2005-01-01

    SciDAC has had a major impact on computational beam dynamics and the design of particle accelerators. Particle accelerators-which account for half of the facilities in the DOE Office of Science Facilities for the Future of Science 20 Year Outlook-are crucial for US scientific, industrial, and economic competitiveness. Thanks to SciDAC, accelerator design calculations that were once thought impossible are now carried routinely, and new challenging and important calculations are within reach. SciDAC accelerator modeling codes are being used to get the most science out of existing facilities, to produce optimal designs for future facilities, and to explore advanced accelerator concepts that may hold the key to qualitatively new ways of accelerating charged particle beams. In this paper we present highlights from the SciDAC Accelerator Science and Technology (AST) project Beam Dynamics focus area in regard to algorithm development, software development, and applications

  3. SciDAC Advances and Applications in Computational Beam Dynamics

    International Nuclear Information System (INIS)

    Ryne, R.; Abell, D.; Adelmann, A.; Amundson, J.; Bohn, C.; Cary, J.; Colella, P.; Dechow, D.; Decyk, V.; Dragt, A.; Gerber, R.; Habib, S.; Higdon, D.; Katsouleas, T.; Ma, K.-L.; McCorquodale, P.; Mihalcea, D.; Mitchell, C.; Mori, W.; Mottershead, C.T.; Neri, F.; Pogorelov, I.; Qiang, J.; Samulyak, R.; Serafini, D.; Shalf, J.; Siegerist, C.; Spentzouris, P.; Stoltz, P.; Terzic, B.; Venturini, M.; Walstrom, P.

    2005-01-01

    SciDAC has had a major impact on computational beam dynamics and the design of particle accelerators. Particle accelerators--which account for half of the facilities in the DOE Office of Science Facilities for the Future of Science 20 Year Outlook--are crucial for US scientific, industrial, and economic competitiveness. Thanks to SciDAC, accelerator design calculations that were once thought impossible are now carried routinely, and new challenging and important calculations are within reach. SciDAC accelerator modeling codes are being used to get the most science out of existing facilities, to produce optimal designs for future facilities, and to explore advanced accelerator concepts that may hold the key to qualitatively new ways of accelerating charged particle beams. In this poster we present highlights from the SciDAC Accelerator Science and Technology (AST) project Beam Dynamics focus area in regard to algorithm development, software development, and applications

  4. Computational modeling, optimization and manufacturing simulation of advanced engineering materials

    CERN Document Server

    2016-01-01

    This volume presents recent research work focused in the development of adequate theoretical and numerical formulations to describe the behavior of advanced engineering materials.  Particular emphasis is devoted to applications in the fields of biological tissues, phase changing and porous materials, polymers and to micro/nano scale modeling. Sensitivity analysis, gradient and non-gradient based optimization procedures are involved in many of the chapters, aiming at the solution of constitutive inverse problems and parameter identification. All these relevant topics are exposed by experienced international and inter institutional research teams resulting in a high level compilation. The book is a valuable research reference for scientists, senior undergraduate and graduate students, as well as for engineers acting in the area of computational material modeling.

  5. Computer Prediction of Air Quality in Livestock Buildings

    DEFF Research Database (Denmark)

    Svidt, Kjeld; Bjerg, Bjarne

    In modem livestock buildings the design of ventilation systems is important in order to obtain good air quality. The use of Computational Fluid Dynamics for predicting the air distribution makes it possible to include the effect of room geometry and heat sources in the design process. This paper...... presents numerical prediction of air flow in a livestock building compared with laboratory measurements. An example of the calculation of contaminant distribution is given, and the future possibilities of the method are discussed....

  6. OPENING REMARKS: SciDAC: Scientific Discovery through Advanced Computing

    Science.gov (United States)

    Strayer, Michael

    2005-01-01

    with industry and virtual prototyping. New instruments of collaboration will include institutes and centers while summer schools, workshops and outreach will invite new talent and expertise. Computational science adds new dimensions to science and its practice. Disciplines of fusion, accelerator science, and combustion are poised to blur the boundaries between pure and applied science. As we open the door into FY2006 we shall see a landscape of new scientific challenges: in biology, chemistry, materials, and astrophysics to name a few. The enabling technologies of SciDAC have been transformational as drivers of change. Planning for major new software systems assumes a base line employing Common Component Architectures and this has become a household word for new software projects. While grid algorithms and mesh refinement software have transformed applications software, data management and visualization have transformed our understanding of science from data. The Gordon Bell prize now seems to be dominated by computational science and solvers developed by TOPS ISIC. The priorities of the Office of Science in the Department of Energy are clear. The 20 year facilities plan is driven by new science. High performance computing is placed amongst the two highest priorities. Moore's law says that by the end of the next cycle of SciDAC we shall have peta-flop computers. The challenges of petascale computing are enormous. These and the associated computational science are the highest priorities for computing within the Office of Science. Our effort in Leadership Class computing is just a first step towards this goal. Clearly, computational science at this scale will face enormous challenges and possibilities. Performance evaluation and prediction will be critical to unraveling the needed software technologies. We must not lose sight of our overarching goal—that of scientific discovery. Science does not stand still and the landscape of science discovery and computing holds

  7. High performance parallel computers for science: New developments at the Fermilab advanced computer program

    International Nuclear Information System (INIS)

    Nash, T.; Areti, H.; Atac, R.

    1988-08-01

    Fermilab's Advanced Computer Program (ACP) has been developing highly cost effective, yet practical, parallel computers for high energy physics since 1984. The ACP's latest developments are proceeding in two directions. A Second Generation ACP Multiprocessor System for experiments will include $3500 RISC processors each with performance over 15 VAX MIPS. To support such high performance, the new system allows parallel I/O, parallel interprocess communication, and parallel host processes. The ACP Multi-Array Processor, has been developed for theoretical physics. Each $4000 node is a FORTRAN or C programmable pipelined 20 MFlops (peak), 10 MByte single board computer. These are plugged into a 16 port crossbar switch crate which handles both inter and intra crate communication. The crates are connected in a hypercube. Site oriented applications like lattice gauge theory are supported by system software called CANOPY, which makes the hardware virtually transparent to users. A 256 node, 5 GFlop, system is under construction. 10 refs., 7 figs

  8. Identification of Enhancers In Human: Advances In Computational Studies

    KAUST Repository

    Kleftogiannis, Dimitrios A.

    2016-03-24

    framework for identifying enhancers. The proposed system called Dragon Ensemble Enhancer Predictor (DEEP) is based on the novel deep learning two-layer ensemble algorithm capable of identifying enhancers characterized by different cellular conditions. Experimental results using data from ENCODE and FANTOM5, demonstrate that DEEP surpasses in terms of recognition performance the major systems for enhancer prediction and shows very good generalization capabilities in unknown cell-lines and tissues. Finally, we take a step further by developing a novel feature selection method suitable for defining a computational framework capable of analyzing the genomic content of enhancers and reporting cell-line specific predictive signatures.

  9. Reliability of an interactive computer program for advance care planning.

    Science.gov (United States)

    Schubart, Jane R; Levi, Benjamin H; Camacho, Fabian; Whitehead, Megan; Farace, Elana; Green, Michael J

    2012-06-01

    Despite widespread efforts to promote advance directives (ADs), completion rates remain low. Making Your Wishes Known: Planning Your Medical Future (MYWK) is an interactive computer program that guides individuals through the process of advance care planning, explaining health conditions and interventions that commonly involve life or death decisions, helps them articulate their values/goals, and translates users' preferences into a detailed AD document. The purpose of this study was to demonstrate that (in the absence of major life changes) the AD generated by MYWK reliably reflects an individual's values/preferences. English speakers ≥30 years old completed MYWK twice, 4 to 6 weeks apart. Reliability indices were assessed for three AD components: General Wishes; Specific Wishes for treatment; and Quality-of-Life values (QoL). Twenty-four participants completed the study. Both the Specific Wishes and QoL scales had high internal consistency in both time periods (Knuder Richardson formula 20 [KR-20]=0.83-0.95, and 0.86-0.89). Test-retest reliability was perfect for General Wishes (κ=1), high for QoL (Pearson's correlation coefficient=0.83), but lower for Specific Wishes (Pearson's correlation coefficient=0.57). MYWK generates an AD where General Wishes and QoL (but not Specific Wishes) statements remain consistent over time.

  10. Reliability of an Interactive Computer Program for Advance Care Planning

    Science.gov (United States)

    Levi, Benjamin H.; Camacho, Fabian; Whitehead, Megan; Farace, Elana; Green, Michael J

    2012-01-01

    Abstract Despite widespread efforts to promote advance directives (ADs), completion rates remain low. Making Your Wishes Known: Planning Your Medical Future (MYWK) is an interactive computer program that guides individuals through the process of advance care planning, explaining health conditions and interventions that commonly involve life or death decisions, helps them articulate their values/goals, and translates users' preferences into a detailed AD document. The purpose of this study was to demonstrate that (in the absence of major life changes) the AD generated by MYWK reliably reflects an individual's values/preferences. English speakers ≥30 years old completed MYWK twice, 4 to 6 weeks apart. Reliability indices were assessed for three AD components: General Wishes; Specific Wishes for treatment; and Quality-of-Life values (QoL). Twenty-four participants completed the study. Both the Specific Wishes and QoL scales had high internal consistency in both time periods (Knuder Richardson formula 20 [KR-20]=0.83–0.95, and 0.86–0.89). Test-retest reliability was perfect for General Wishes (κ=1), high for QoL (Pearson's correlation coefficient=0.83), but lower for Specific Wishes (Pearson's correlation coefficient=0.57). MYWK generates an AD where General Wishes and QoL (but not Specific Wishes) statements remain consistent over time. PMID:22512830

  11. Prediction of Corrosion of Advanced Materials and Fabricated Components

    Energy Technology Data Exchange (ETDEWEB)

    A. Anderko; G. Engelhardt; M.M. Lencka (OLI Systems Inc.); M.A. Jakab; G. Tormoen; N. Sridhar (Southwest Research Institute)

    2007-09-29

    The goal of this project is to provide materials engineers, chemical engineers and plant operators with a software tool that will enable them to predict localized corrosion of process equipment including fabricated components as well as base alloys. For design and revamp purposes, the software predicts the occurrence of localized corrosion as a function of environment chemistry and assists the user in selecting the optimum alloy for a given environment. For the operation of existing plants, the software enables the users to predict the remaining life of equipment and help in scheduling maintenance activities. This project combined fundamental understanding of mechanisms of corrosion with focused experimental results to predict the corrosion of advanced, base or fabricated, alloys in real-world environments encountered in the chemical industry. At the heart of this approach is the development of models that predict the fundamental parameters that control the occurrence of localized corrosion as a function of environmental conditions and alloy composition. The fundamental parameters that dictate the occurrence of localized corrosion are the corrosion and repassivation potentials. The program team, OLI Systems and Southwest Research Institute, has developed theoretical models for these parameters. These theoretical models have been applied to predict the occurrence of localized corrosion of base materials and heat-treated components in a variety of environments containing aggressive and non-aggressive species. As a result of this project, a comprehensive model has been established and extensively verified for predicting the occurrence of localized corrosion as a function of environment chemistry and temperature by calculating the corrosion and repassivation potentials.To support and calibrate the model, an experimental database has been developed to elucidate (1) the effects of various inhibiting species as well as aggressive species on localized corrosion of nickel

  12. Condition monitoring through advanced sensor and computational technology

    International Nuclear Information System (INIS)

    Kim, Jung Taek; Hur, S.; Seong, S. H.; Hwang, Il Soon; Lee, Joon Hyun; You, Jun; Lee, Sang Jung

    2004-01-01

    In order to successfully implement the extended-life operation plan of the nuclear power plant (NPP), predictive maintenance based on on-line monitoring of deteriorated components becomes highly important. In this work, we present progresses in the development of an advanced monitoring system to detect the health condition on check valve failures and pipe wall-thinning phenomena. The failures of check valves have resulted in significant maintenance efforts, on occasion, have resulted in water hammer, over-pressurization of low-pressure systems, and damage to flow system components. Pipe wall-thinning is usually caused by Flow-Accelerated Corrosion (FAC) under the undesirable combination of water chemistry, flow velocity and material composition. A piping elbow in the moisture separator/reheater drain line on the secondary waterside of a PWR is chosen as a monitoring target

  13. TerraFERMA: Harnessing Advanced Computational Libraries in Earth Science

    Science.gov (United States)

    Wilson, C. R.; Spiegelman, M.; van Keken, P.

    2012-12-01

    Many important problems in Earth sciences can be described by non-linear coupled systems of partial differential equations. These "multi-physics" problems include thermo-chemical convection in Earth and planetary interiors, interactions of fluids and magmas with the Earth's mantle and crust and coupled flow of water and ice. These problems are of interest to a large community of researchers but are complicated to model and understand. Much of this complexity stems from the nature of multi-physics where small changes in the coupling between variables or constitutive relations can lead to radical changes in behavior, which in turn affect critical computational choices such as discretizations, solvers and preconditioners. To make progress in understanding such coupled systems requires a computational framework where multi-physics problems can be described at a high-level while maintaining the flexibility to easily modify the solution algorithm. Fortunately, recent advances in computational science provide a basis for implementing such a framework. Here we present the Transparent Finite Element Rapid Model Assembler (TerraFERMA), which leverages several advanced open-source libraries for core functionality. FEniCS (fenicsproject.org) provides a high level language for describing the weak forms of coupled systems of equations, and an automatic code generator that produces finite element assembly code. PETSc (www.mcs.anl.gov/petsc) provides a wide range of scalable linear and non-linear solvers that can be composed into effective multi-physics preconditioners. SPuD (amcg.ese.ic.ac.uk/Spud) is an application neutral options system that provides both human and machine-readable interfaces based on a single xml schema. Our software integrates these libraries and provides the user with a framework for exploring multi-physics problems. A single options file fully describes the problem, including all equations, coefficients and solver options. Custom compiled applications are

  14. Real-time Tsunami Inundation Prediction Using High Performance Computers

    Science.gov (United States)

    Oishi, Y.; Imamura, F.; Sugawara, D.

    2014-12-01

    Recently off-shore tsunami observation stations based on cabled ocean bottom pressure gauges are actively being deployed especially in Japan. These cabled systems are designed to provide real-time tsunami data before tsunamis reach coastlines for disaster mitigation purposes. To receive real benefits of these observations, real-time analysis techniques to make an effective use of these data are necessary. A representative study was made by Tsushima et al. (2009) that proposed a method to provide instant tsunami source prediction based on achieving tsunami waveform data. As time passes, the prediction is improved by using updated waveform data. After a tsunami source is predicted, tsunami waveforms are synthesized from pre-computed tsunami Green functions of linear long wave equations. Tsushima et al. (2014) updated the method by combining the tsunami waveform inversion with an instant inversion of coseismic crustal deformation and improved the prediction accuracy and speed in the early stages. For disaster mitigation purposes, real-time predictions of tsunami inundation are also important. In this study, we discuss the possibility of real-time tsunami inundation predictions, which require faster-than-real-time tsunami inundation simulation in addition to instant tsunami source analysis. Although the computational amount is large to solve non-linear shallow water equations for inundation predictions, it has become executable through the recent developments of high performance computing technologies. We conducted parallel computations of tsunami inundation and achieved 6.0 TFLOPS by using 19,000 CPU cores. We employed a leap-frog finite difference method with nested staggered grids of which resolution range from 405 m to 5 m. The resolution ratio of each nested domain was 1/3. Total number of grid points were 13 million, and the time step was 0.1 seconds. Tsunami sources of 2011 Tohoku-oki earthquake were tested. The inundation prediction up to 2 hours after the

  15. Computer Hardware, Advanced Mathematics and Model Physics pilot project final report

    International Nuclear Information System (INIS)

    1992-05-01

    The Computer Hardware, Advanced Mathematics and Model Physics (CHAMMP) Program was launched in January, 1990. A principal objective of the program has been to utilize the emerging capabilities of massively parallel scientific computers in the challenge of regional scale predictions of decade-to-century climate change. CHAMMP has already demonstrated the feasibility of achieving a 10,000 fold increase in computational throughput for climate modeling in this decade. What we have also recognized, however, is the need for new algorithms and computer software to capitalize on the radically new computing architectures. This report describes the pilot CHAMMP projects at the DOE National Laboratories and the National Center for Atmospheric Research (NCAR). The pilot projects were selected to identify the principal challenges to CHAMMP and to entrain new scientific computing expertise. The success of some of these projects has aided in the definition of the CHAMMP scientific plan. Many of the papers in this report have been or will be submitted for publication in the open literature. Readers are urged to consult with the authors directly for questions or comments about their papers

  16. The value of computed tomography-urography in predicting the ...

    African Journals Online (AJOL)

    Background The natural course of pelviureteric junction (PUJ) obstruction is variable. Of those who require surgical intervention, there is no definite reliable preoperative predictor of the likely postoperative outcome. We evaluated the value of preoperative computed tomography (CT)-urography in predicting the ...

  17. Advanced computational model for three-phase slurry reactors

    International Nuclear Information System (INIS)

    Goodarz Ahmadi

    2001-10-01

    In the second year of the project, the Eulerian-Lagrangian formulation for analyzing three-phase slurry flows in a bubble column is further developed. The approach uses an Eulerian analysis of liquid flows in the bubble column, and makes use of the Lagrangian trajectory analysis for the bubbles and particle motions. An experimental set for studying a two-dimensional bubble column is also developed. The operation of the bubble column is being tested and diagnostic methodology for quantitative measurements is being developed. An Eulerian computational model for the flow condition in the two-dimensional bubble column is also being developed. The liquid and bubble motions are being analyzed and the results are being compared with the experimental setup. Solid-fluid mixture flows in ducts and passages at different angle of orientations were analyzed. The model predictions were compared with the experimental data and good agreement was found. Gravity chute flows of solid-liquid mixtures is also being studied. Further progress was also made in developing a thermodynamically consistent model for multiphase slurry flows with and without chemical reaction in a state of turbulent motion. The balance laws are obtained and the constitutive laws are being developed. Progress was also made in measuring concentration and velocity of particles of different sizes near a wall in a duct flow. The technique of Phase-Doppler anemometry was used in these studies. The general objective of this project is to provide the needed fundamental understanding of three-phase slurry reactors in Fischer-Tropsch (F-T) liquid fuel synthesis. The other main goal is to develop a computational capability for predicting the transport and processing of three-phase coal slurries. The specific objectives are: (1) To develop a thermodynamically consistent rate-dependent anisotropic model for multiphase slurry flows with and without chemical reaction for application to coal liquefaction. Also establish the

  18. A COMPARISON BETWEEN THREE PREDICTIVE MODELS OF COMPUTATIONAL INTELLIGENCE

    Directory of Open Access Journals (Sweden)

    DUMITRU CIOBANU

    2013-12-01

    Full Text Available Time series prediction is an open problem and many researchers are trying to find new predictive methods and improvements for the existing ones. Lately methods based on neural networks are used extensively for time series prediction. Also, support vector machines have solved some of the problems faced by neural networks and they began to be widely used for time series prediction. The main drawback of those two methods is that they are global models and in the case of a chaotic time series it is unlikely to find such model. In this paper it is presented a comparison between three predictive from computational intelligence field one based on neural networks one based on support vector machine and another based on chaos theory. We show that the model based on chaos theory is an alternative to the other two methods.

  19. A community computational challenge to predict the activity of pairs of compounds.

    Science.gov (United States)

    Bansal, Mukesh; Yang, Jichen; Karan, Charles; Menden, Michael P; Costello, James C; Tang, Hao; Xiao, Guanghua; Li, Yajuan; Allen, Jeffrey; Zhong, Rui; Chen, Beibei; Kim, Minsoo; Wang, Tao; Heiser, Laura M; Realubit, Ronald; Mattioli, Michela; Alvarez, Mariano J; Shen, Yao; Gallahan, Daniel; Singer, Dinah; Saez-Rodriguez, Julio; Xie, Yang; Stolovitzky, Gustavo; Califano, Andrea

    2014-12-01

    Recent therapeutic successes have renewed interest in drug combinations, but experimental screening approaches are costly and often identify only small numbers of synergistic combinations. The DREAM consortium launched an open challenge to foster the development of in silico methods to computationally rank 91 compound pairs, from the most synergistic to the most antagonistic, based on gene-expression profiles of human B cells treated with individual compounds at multiple time points and concentrations. Using scoring metrics based on experimental dose-response curves, we assessed 32 methods (31 community-generated approaches and SynGen), four of which performed significantly better than random guessing. We highlight similarities between the methods. Although the accuracy of predictions was not optimal, we find that computational prediction of compound-pair activity is possible, and that community challenges can be useful to advance the field of in silico compound-synergy prediction.

  20. Burnout prediction using advance image analysis coal characterization techniques

    Energy Technology Data Exchange (ETDEWEB)

    Edward Lester; Dave Watts; Michael Cloke [University of Nottingham, Nottingham (United Kingdom). School of Chemical Environmental and Mining Engineering

    2003-07-01

    The link between petrographic composition and burnout has been investigated previously by the authors. However, these predictions were based on 'bulk' properties of the coal, including the proportion of each maceral or the reflectance of the macerals in the whole sample. Combustion studies relating burnout with microlithotype analysis, or similar, remain less common partly because the technique is more complex than maceral analysis. Despite this, it is likely that any burnout prediction based on petrographic characteristics will become more accurate if it includes information about the maceral associations and the size of each particle. Chars from 13 coals, 106-125 micron size fractions, were prepared using a Drop Tube Furnace (DTF) at 1300{degree}C and 200 millisecond and 1% Oxygen. These chars were then refired in the DTF at 1300{degree}C 5% oxygen and residence times of 200, 400 and 600 milliseconds. The progressive burnout of each char was compared with the characteristics of the initial coals. This paper presents an extension of previous studies in that it relates combustion behaviour to coals that have been characterized on a particle by particle basis using advanced image analysis techniques. 13 refs., 7 figs.

  1. An advanced course in computational nuclear physics bridging the scales from quarks to neutron stars

    CERN Document Server

    Lombardo, Maria; Kolck, Ubirajara

    2017-01-01

    This graduate-level text collects and synthesizes a series of ten lectures on the nuclear quantum many-body problem. Starting from our current understanding of the underlying forces, it presents recent advances within the field of lattice quantum chromodynamics before going on to discuss effective field theories, central many-body methods like Monte Carlo methods, coupled cluster theories, the similarity renormalization group approach, Green’s function methods and large-scale diagonalization approaches. Algorithmic and computational advances show particular promise for breakthroughs in predictive power, including proper error estimates, a better understanding of the underlying effective degrees of freedom and of the respective forces at play. Enabled by recent improvements in theoretical, experimental and numerical techniques, the state-of-the art applications considered in this volume span the entire range, from our smallest components – quarks and gluons as the mediators of the strong force – to the c...

  2. Prediction of Software Reliability using Bio Inspired Soft Computing Techniques.

    Science.gov (United States)

    Diwaker, Chander; Tomar, Pradeep; Poonia, Ramesh C; Singh, Vijander

    2018-04-10

    A lot of models have been made for predicting software reliability. The reliability models are restricted to using particular types of methodologies and restricted number of parameters. There are a number of techniques and methodologies that may be used for reliability prediction. There is need to focus on parameters consideration while estimating reliability. The reliability of a system may increase or decreases depending on the selection of different parameters used. Thus there is need to identify factors that heavily affecting the reliability of the system. In present days, reusability is mostly used in the various area of research. Reusability is the basis of Component-Based System (CBS). The cost, time and human skill can be saved using Component-Based Software Engineering (CBSE) concepts. CBSE metrics may be used to assess those techniques which are more suitable for estimating system reliability. Soft computing is used for small as well as large-scale problems where it is difficult to find accurate results due to uncertainty or randomness. Several possibilities are available to apply soft computing techniques in medicine related problems. Clinical science of medicine using fuzzy-logic, neural network methodology significantly while basic science of medicine using neural-networks-genetic algorithm most frequently and preferably. There is unavoidable interest shown by medical scientists to use the various soft computing methodologies in genetics, physiology, radiology, cardiology and neurology discipline. CBSE boost users to reuse the past and existing software for making new products to provide quality with a saving of time, memory space, and money. This paper focused on assessment of commonly used soft computing technique like Genetic Algorithm (GA), Neural-Network (NN), Fuzzy Logic, Support Vector Machine (SVM), Ant Colony Optimization (ACO), Particle Swarm Optimization (PSO), and Artificial Bee Colony (ABC). This paper presents working of soft computing

  3. Recovery Act: Advanced Direct Methanol Fuel Cell for Mobile Computing

    Energy Technology Data Exchange (ETDEWEB)

    Fletcher, James H. [University of North Florida; Cox, Philip [University of North Florida; Harrington, William J [University of North Florida; Campbell, Joseph L [University of North Florida

    2013-09-03

    ABSTRACT Project Title: Recovery Act: Advanced Direct Methanol Fuel Cell for Mobile Computing PROJECT OBJECTIVE The objective of the project was to advance portable fuel cell system technology towards the commercial targets of power density, energy density and lifetime. These targets were laid out in the DOE’s R&D roadmap to develop an advanced direct methanol fuel cell power supply that meets commercial entry requirements. Such a power supply will enable mobile computers to operate non-stop, unplugged from the wall power outlet, by using the high energy density of methanol fuel contained in a replaceable fuel cartridge. Specifically this project focused on balance-of-plant component integration and miniaturization, as well as extensive component, subassembly and integrated system durability and validation testing. This design has resulted in a pre-production power supply design and a prototype that meet the rigorous demands of consumer electronic applications. PROJECT TASKS The proposed work plan was designed to meet the project objectives, which corresponded directly with the objectives outlined in the Funding Opportunity Announcement: To engineer the fuel cell balance-of-plant and packaging to meet the needs of consumer electronic systems, specifically at power levels required for mobile computing. UNF used existing balance-of-plant component technologies developed under its current US Army CERDEC project, as well as a previous DOE project completed by PolyFuel, to further refine them to both miniaturize and integrate their functionality to increase the system power density and energy density. Benefits of UNF’s novel passive water recycling MEA (membrane electrode assembly) and the simplified system architecture it enabled formed the foundation of the design approach. The package design was hardened to address orientation independence, shock, vibration, and environmental requirements. Fuel cartridge and fuel subsystems were improved to ensure effective fuel

  4. Further development of the Dynamic Control Assemblies Worth Measurement Method for Advanced Reactivity Computers

    International Nuclear Information System (INIS)

    Petenyi, V.; Strmensky, C.; Jagrik, J.; Minarcin, M.; Sarvaic, I.

    2005-01-01

    The dynamic control assemblies worth measurement technique is a quick method for validation of predicted control assemblies worth. The dynamic control assemblies worth measurement utilize space-time corrections for the measured out of core ionization chamber readings calculated by DYN 3D computer code. The space-time correction arising from the prompt neutron density redistribution in the measured ionization chamber reading can be directly applied in the advanced reactivity computer. The second correction concerning the difference of spatial distribution of delayed neutrons can be calculated by simulation the measurement procedure by dynamic version of the DYN 3D code. In the paper some results of dynamic control assemblies worth measurement applied for NPP Mochovce are presented (Authors)

  5. Advanced computational model for three-phase slurry reactors

    International Nuclear Information System (INIS)

    Goodarz Ahmadi

    2000-11-01

    In the first year of the project, solid-fluid mixture flows in ducts and passages at different angle of orientations were analyzed. The model predictions are compared with the experimental data and good agreement was found. Progress was also made in analyzing the gravity chute flows of solid-liquid mixtures. An Eulerian-Lagrangian formulation for analyzing three-phase slurry flows in a bubble column is being developed. The approach uses an Eulerian analysis of gas liquid flows in the bubble column, and makes use of the Lagrangian particle tracking procedure to analyze the particle motions. Progress was also made in developing a rate dependent thermodynamically consistent model for multiphase slurry flows in a state of turbulent motion. The new model includes the effect of phasic interactions and leads to anisotropic effective phasic stress tensors. Progress was also made in measuring concentration and velocity of particles of different sizes near a wall in a duct flow. The formulation of a thermodynamically consistent model for chemically active multiphase solid-fluid flows in a turbulent state of motion was also initiated. The general objective of this project is to provide the needed fundamental understanding of three-phase slurry reactors in Fischer-Tropsch (F-T) liquid fuel synthesis. The other main goal is to develop a computational capability for predicting the transport and processing of three-phase coal slurries. The specific objectives are: (1) To develop a thermodynamically consistent rate-dependent anisotropic model for multiphase slurry flows with and without chemical reaction for application to coal liquefaction. Also to establish the material parameters of the model. (2) To provide experimental data for phasic fluctuation and mean velocities, as well as the solid volume fraction in the shear flow devices. (3) To develop an accurate computational capability incorporating the new rate-dependent and anisotropic model for analyzing reacting and

  6. The origins of computer weather prediction and climate modeling

    International Nuclear Information System (INIS)

    Lynch, Peter

    2008-01-01

    Numerical simulation of an ever-increasing range of geophysical phenomena is adding enormously to our understanding of complex processes in the Earth system. The consequences for mankind of ongoing climate change will be far-reaching. Earth System Models are capable of replicating climate regimes of past millennia and are the best means we have of predicting the future of our climate. The basic ideas of numerical forecasting and climate modeling were developed about a century ago, long before the first electronic computer was constructed. There were several major practical obstacles to be overcome before numerical prediction could be put into practice. A fuller understanding of atmospheric dynamics allowed the development of simplified systems of equations; regular radiosonde observations of the free atmosphere and, later, satellite data, provided the initial conditions; stable finite difference schemes were developed; and powerful electronic computers provided a practical means of carrying out the prodigious calculations required to predict the changes in the weather. Progress in weather forecasting and in climate modeling over the past 50 years has been dramatic. In this presentation, we will trace the history of computer forecasting through the ENIAC integrations to the present day. The useful range of deterministic prediction is increasing by about one day each decade, and our understanding of climate change is growing rapidly as Earth System Models of ever-increasing sophistication are developed

  7. Nonlinear dynamics of laser systems with elements of a chaos: Advanced computational code

    Science.gov (United States)

    Buyadzhi, V. V.; Glushkov, A. V.; Khetselius, O. Yu; Kuznetsova, A. A.; Buyadzhi, A. A.; Prepelitsa, G. P.; Ternovsky, V. B.

    2017-10-01

    A general, uniform chaos-geometric computational approach to analysis, modelling and prediction of the non-linear dynamics of quantum and laser systems (laser and quantum generators system etc) with elements of the deterministic chaos is briefly presented. The approach is based on using the advanced generalized techniques such as the wavelet analysis, multi-fractal formalism, mutual information approach, correlation integral analysis, false nearest neighbour algorithm, the Lyapunov’s exponents analysis, and surrogate data method, prediction models etc There are firstly presented the numerical data on the topological and dynamical invariants (in particular, the correlation, embedding, Kaplan-York dimensions, the Lyapunov’s exponents, Kolmogorov’s entropy and other parameters) for laser system (the semiconductor GaAs/GaAlAs laser with a retarded feedback) dynamics in a chaotic and hyperchaotic regimes.

  8. Recent Advances in Computational Methods for Nuclear Magnetic Resonance Data Processing

    KAUST Repository

    Gao, Xin

    2013-01-01

    research attention from specialists in bioinformatics and computational biology. In this paper, we review recent advances in computational methods for NMR protein structure determination. We summarize the advantages of and bottlenecks in the existing

  9. Osteotomy simulation and soft tissue prediction using computer tomography scans

    International Nuclear Information System (INIS)

    Teschner, M.; Girod, S.; Girod, B.

    1999-01-01

    In this paper, a system is presented that can be used to simulate osteotomies of the skull and to estimate the resulting of tissue changes. Thus, the three-dimensional, photorealistic, postoperative appearance of a patient can be assessed. The system is based on a computer tomography scan and a photorealistic laser scan of the patient's face. In order to predict the postoperative appearance of a patient the soft tissue must follow the movement of the underlying bone. In this paper, a multi-layer soft tissue model is proposed that is based on springs. It incorporates features like skin turgor, gravity and sliding bone contact. The prediction of soft tissue changes due to bone realignments is computed using a very efficient and robust optimization method. The system can handle individual patient data sets and has been tested with several clinical cases. (author)

  10. ADVANCED COMPUTATIONAL MODEL FOR THREE-PHASE SLURRY REACTORS

    International Nuclear Information System (INIS)

    Ahmadi, Goodarz

    2004-01-01

    In this project, an Eulerian-Lagrangian formulation for analyzing three-phase slurry flows in a bubble column was developed. The approach used an Eulerian analysis of liquid flows in the bubble column, and made use of the Lagrangian trajectory analysis for the bubbles and particle motions. The bubble-bubble and particle-particle collisions are included the model. The model predictions are compared with the experimental data and good agreement was found An experimental setup for studying two-dimensional bubble columns was developed. The multiphase flow conditions in the bubble column were measured using optical image processing and Particle Image Velocimetry techniques (PIV). A simple shear flow device for bubble motion in a constant shear flow field was also developed. The flow conditions in simple shear flow device were studied using PIV method. Concentration and velocity of particles of different sizes near a wall in a duct flow was also measured. The technique of Phase-Doppler anemometry was used in these studies. An Eulerian volume of fluid (VOF) computational model for the flow condition in the two-dimensional bubble column was also developed. The liquid and bubble motions were analyzed and the results were compared with observed flow patterns in the experimental setup. Solid-fluid mixture flows in ducts and passages at different angle of orientations were also analyzed. The model predictions were compared with the experimental data and good agreement was found. Gravity chute flows of solid-liquid mixtures were also studied. The simulation results were compared with the experimental data and discussed A thermodynamically consistent model for multiphase slurry flows with and without chemical reaction in a state of turbulent motion was developed. The balance laws were obtained and the constitutive laws established

  11. Why do Reservoir Computing Networks Predict Chaotic Systems so Well?

    Science.gov (United States)

    Lu, Zhixin; Pathak, Jaideep; Girvan, Michelle; Hunt, Brian; Ott, Edward

    Recently a new type of artificial neural network, which is called a reservoir computing network (RCN), has been employed to predict the evolution of chaotic dynamical systems from measured data and without a priori knowledge of the governing equations of the system. The quality of these predictions has been found to be spectacularly good. Here, we present a dynamical-system-based theory for how RCN works. Basically a RCN is thought of as consisting of three parts, a randomly chosen input layer, a randomly chosen recurrent network (the reservoir), and an output layer. The advantage of the RCN framework is that training is done only on the linear output layer, making it computationally feasible for the reservoir dimensionality to be large. In this presentation, we address the underlying dynamical mechanisms of RCN function by employing the concepts of generalized synchronization and conditional Lyapunov exponents. Using this framework, we propose conditions on reservoir dynamics necessary for good prediction performance. By looking at the RCN from this dynamical systems point of view, we gain a deeper understanding of its surprising computational power, as well as insights on how to design a RCN. Supported by Army Research Office Grant Number W911NF1210101.

  12. Can human experts predict solubility better than computers?

    Science.gov (United States)

    Boobier, Samuel; Osbourn, Anne; Mitchell, John B O

    2017-12-13

    In this study, we design and carry out a survey, asking human experts to predict the aqueous solubility of druglike organic compounds. We investigate whether these experts, drawn largely from the pharmaceutical industry and academia, can match or exceed the predictive power of algorithms. Alongside this, we implement 10 typical machine learning algorithms on the same dataset. The best algorithm, a variety of neural network known as a multi-layer perceptron, gave an RMSE of 0.985 log S units and an R 2 of 0.706. We would not have predicted the relative success of this particular algorithm in advance. We found that the best individual human predictor generated an almost identical prediction quality with an RMSE of 0.942 log S units and an R 2 of 0.723. The collection of algorithms contained a higher proportion of reasonably good predictors, nine out of ten compared with around half of the humans. We found that, for either humans or algorithms, combining individual predictions into a consensus predictor by taking their median generated excellent predictivity. While our consensus human predictor achieved very slightly better headline figures on various statistical measures, the difference between it and the consensus machine learning predictor was both small and statistically insignificant. We conclude that human experts can predict the aqueous solubility of druglike molecules essentially equally well as machine learning algorithms. We find that, for either humans or algorithms, combining individual predictions into a consensus predictor by taking their median is a powerful way of benefitting from the wisdom of crowds.

  13. Verifying a computational method for predicting extreme ground motion

    Science.gov (United States)

    Harris, R.A.; Barall, M.; Andrews, D.J.; Duan, B.; Ma, S.; Dunham, E.M.; Gabriel, A.-A.; Kaneko, Y.; Kase, Y.; Aagaard, Brad T.; Oglesby, D.D.; Ampuero, J.-P.; Hanks, T.C.; Abrahamson, N.

    2011-01-01

    In situations where seismological data is rare or nonexistent, computer simulations may be used to predict ground motions caused by future earthquakes. This is particularly practical in the case of extreme ground motions, where engineers of special buildings may need to design for an event that has not been historically observed but which may occur in the far-distant future. Once the simulations have been performed, however, they still need to be tested. The SCEC-USGS dynamic rupture code verification exercise provides a testing mechanism for simulations that involve spontaneous earthquake rupture. We have performed this examination for the specific computer code that was used to predict maximum possible ground motion near Yucca Mountain. Our SCEC-USGS group exercises have demonstrated that the specific computer code that was used for the Yucca Mountain simulations produces similar results to those produced by other computer codes when tackling the same science problem. We also found that the 3D ground motion simulations produced smaller ground motions than the 2D simulations.

  14. Integrated Computational Solution for Predicting Skin Sensitization Potential of Molecules.

    Directory of Open Access Journals (Sweden)

    Konda Leela Sarath Kumar

    Full Text Available Skin sensitization forms a major toxicological endpoint for dermatology and cosmetic products. Recent ban on animal testing for cosmetics demands for alternative methods. We developed an integrated computational solution (SkinSense that offers a robust solution and addresses the limitations of existing computational tools i.e. high false positive rate and/or limited coverage.The key components of our solution include: QSAR models selected from a combinatorial set, similarity information and literature-derived sub-structure patterns of known skin protein reactive groups. Its prediction performance on a challenge set of molecules showed accuracy = 75.32%, CCR = 74.36%, sensitivity = 70.00% and specificity = 78.72%, which is better than several existing tools including VEGA (accuracy = 45.00% and CCR = 54.17% with 'High' reliability scoring, DEREK (accuracy = 72.73% and CCR = 71.44% and TOPKAT (accuracy = 60.00% and CCR = 61.67%. Although, TIMES-SS showed higher predictive power (accuracy = 90.00% and CCR = 92.86%, the coverage was very low (only 10 out of 77 molecules were predicted reliably.Owing to improved prediction performance and coverage, our solution can serve as a useful expert system towards Integrated Approaches to Testing and Assessment for skin sensitization. It would be invaluable to cosmetic/ dermatology industry for pre-screening their molecules, and reducing time, cost and animal testing.

  15. Life prediction methodology for ceramic components of advanced heat engines. Phase 1: Volume 1, Final report

    Energy Technology Data Exchange (ETDEWEB)

    Cuccio, J.C.; Brehm, P.; Fang, H.T. [Allied-Signal Aerospace Co., Phoenix, AZ (United States). Garrett Engine Div.] [and others

    1995-03-01

    Emphasis of this program is to develop and demonstrate ceramics life prediction methods, including fast fracture, stress rupture, creep, oxidation, and nondestructive evaluation. Significant advancements were made in these methods and their predictive capabilities successfully demonstrated.

  16. Advancing Environmental Prediction Capabilities for the Polar Regions and Beyond during The Year of Polar Prediction

    Science.gov (United States)

    Werner, Kirstin; Goessling, Helge; Hoke, Winfried; Kirchhoff, Katharina; Jung, Thomas

    2017-04-01

    Environmental changes in polar regions open up new opportunities for economic and societal operations such as vessel traffic related to scientific, fishery and tourism activities, and in the case of the Arctic also enhanced resource development. The availability of current and accurate weather and environmental information and forecasts will therefore play an increasingly important role in aiding risk reduction and safety management around the poles. The Year of Polar Prediction (YOPP) has been established by the World Meteorological Organization's World Weather Research Programme as the key activity of the ten-year Polar Prediction Project (PPP; see more on www.polarprediction.net). YOPP is an internationally coordinated initiative to significantly advance our environmental prediction capabilities for the polar regions and beyond, supporting improved weather and climate services. Scheduled to take place from mid-2017 to mid-2019, the YOPP core phase covers an extended period of intensive observing, modelling, prediction, verification, user-engagement and education activities in the Arctic and Antarctic, on a wide range of time scales from hours to seasons. The Year of Polar Prediction will entail periods of enhanced observational and modelling campaigns in both polar regions. With the purpose to close the gaps in the conventional polar observing systems in regions where the observation network is sparse, routine observations will be enhanced during Special Observing Periods for an extended period of time (several weeks) during YOPP. This will allow carrying out subsequent forecasting system experiments aimed at optimizing observing systems in the polar regions and providing insight into the impact of better polar observations on forecast skills in lower latitudes. With various activities and the involvement of a wide range of stakeholders, YOPP will contribute to the knowledge base needed to managing the opportunities and risks that come with polar climate change.

  17. Computational neurorehabilitation: modeling plasticity and learning to predict recovery.

    Science.gov (United States)

    Reinkensmeyer, David J; Burdet, Etienne; Casadio, Maura; Krakauer, John W; Kwakkel, Gert; Lang, Catherine E; Swinnen, Stephan P; Ward, Nick S; Schweighofer, Nicolas

    2016-04-30

    Despite progress in using computational approaches to inform medicine and neuroscience in the last 30 years, there have been few attempts to model the mechanisms underlying sensorimotor rehabilitation. We argue that a fundamental understanding of neurologic recovery, and as a result accurate predictions at the individual level, will be facilitated by developing computational models of the salient neural processes, including plasticity and learning systems of the brain, and integrating them into a context specific to rehabilitation. Here, we therefore discuss Computational Neurorehabilitation, a newly emerging field aimed at modeling plasticity and motor learning to understand and improve movement recovery of individuals with neurologic impairment. We first explain how the emergence of robotics and wearable sensors for rehabilitation is providing data that make development and testing of such models increasingly feasible. We then review key aspects of plasticity and motor learning that such models will incorporate. We proceed by discussing how computational neurorehabilitation models relate to the current benchmark in rehabilitation modeling - regression-based, prognostic modeling. We then critically discuss the first computational neurorehabilitation models, which have primarily focused on modeling rehabilitation of the upper extremity after stroke, and show how even simple models have produced novel ideas for future investigation. Finally, we conclude with key directions for future research, anticipating that soon we will see the emergence of mechanistic models of motor recovery that are informed by clinical imaging results and driven by the actual movement content of rehabilitation therapy as well as wearable sensor-based records of daily activity.

  18. Self-learning computers for surgical planning and prediction of postoperative alignment.

    Science.gov (United States)

    Lafage, Renaud; Pesenti, Sébastien; Lafage, Virginie; Schwab, Frank J

    2018-02-01

    In past decades, the role of sagittal alignment has been widely demonstrated in the setting of spinal conditions. As several parameters can be affected, identifying the driver of the deformity is the cornerstone of a successful treatment approach. Despite the importance of restoring sagittal alignment for optimizing outcome, this task remains challenging. Self-learning computers and optimized algorithms are of great interest in spine surgery as in that they facilitate better planning and prediction of postoperative alignment. Nowadays, computer-assisted tools are part of surgeons' daily practice; however, the use of such tools remains to be time-consuming. NARRATIVE REVIEW AND RESULTS: Computer-assisted methods for the prediction of postoperative alignment consist of a three step analysis: identification of anatomical landmark, definition of alignment objectives, and simulation of surgery. Recently, complex rules for the prediction of alignment have been proposed. Even though this kind of work leads to more personalized objectives, the number of parameters involved renders it difficult for clinical use, stressing the importance of developing computer-assisted tools. The evolution of our current technology, including machine learning and other types of advanced algorithms, will provide powerful tools that could be useful in improving surgical outcomes and alignment prediction. These tools can combine different types of advanced technologies, such as image recognition and shape modeling, and using this technique, computer-assisted methods are able to predict spinal shape. The development of powerful computer-assisted methods involves the integration of several sources of information such as radiographic parameters (X-rays, MRI, CT scan, etc.), demographic information, and unusual non-osseous parameters (muscle quality, proprioception, gait analysis data). In using a larger set of data, these methods will aim to mimic what is actually done by spine surgeons, leading

  19. Computational prediction of miRNA genes from small RNA sequencing data

    Directory of Open Access Journals (Sweden)

    Wenjing eKang

    2015-01-01

    Full Text Available Next-generation sequencing now for the first time allows researchers to gauge the depth and variation of entire transcriptomes. However, now as rare transcripts can be detected that are present in cells at single copies, more advanced computational tools are needed to accurately annotate and profile them. miRNAs are 22 nucleotide small RNAs (sRNAs that post-transcriptionally reduce the output of protein coding genes. They have established roles in numerous biological processes, including cancers and other diseases. During miRNA biogenesis, the sRNAs are sequentially cleaved from precursor molecules that have a characteristic hairpin RNA structure. The vast majority of new miRNA genes that are discovered are mined from small RNA sequencing (sRNA-seq, which can detect more than a billion RNAs in a single run. However, given that many of the detected RNAs are degradation products from all types of transcripts, the accurate identification of miRNAs remain a non-trivial computational problem. Here we review the tools available to predict animal miRNAs from sRNA sequencing data. We present tools for generalist and specialist use cases, including prediction from massively pooled data or in species without reference genome. We also present wet-lab methods used to validate predicted miRNAs, and approaches to computationally benchmark prediction accuracy. For each tool, we reference validation experiments and benchmarking efforts. Last, we discuss the future of the field.

  20. Workflow Support for Advanced Grid-Enabled Computing

    OpenAIRE

    Xu, Fenglian; Eres, M.H.; Tao, Feng; Cox, Simon J.

    2004-01-01

    The Geodise project brings computer scientists and engineer's skills together to build up a service-oriented computing environmnet for engineers to perform complicated computations in a distributed system. The workflow tool is a front GUI to provide a full life cycle of workflow functions for Grid-enabled computing. The full life cycle of workflow functions have been enhanced based our initial research and development. The life cycle starts with a composition of a workflow, followed by an ins...

  1. Advanced Certification Program for Computer Graphic Specialists. Final Performance Report.

    Science.gov (United States)

    Parkland Coll., Champaign, IL.

    A pioneer program in computer graphics was implemented at Parkland College (Illinois) to meet the demand for specialized technicians to visualize data generated on high performance computers. In summer 1989, 23 students were accepted into the pilot program. Courses included C programming, calculus and analytic geometry, computer graphics, and…

  2. [Computational prediction of human immunodeficiency resistance to reverse transcriptase inhibitors].

    Science.gov (United States)

    Tarasova, O A; Filimonov, D A; Poroikov, V V

    2017-10-01

    Human immunodeficiency virus (HIV) causes acquired immunodeficiency syndrome (AIDS) and leads to over one million of deaths annually. Highly active antiretroviral treatment (HAART) is a gold standard in the HIV/AIDS therapy. Nucleoside and non-nucleoside inhibitors of HIV reverse transcriptase (RT) are important component of HAART, but their effect depends on the HIV susceptibility/resistance. HIV resistance mainly occurs due to mutations leading to conformational changes in the three-dimensional structure of HIV RT. The aim of our work was to develop and test a computational method for prediction of HIV resistance associated with the mutations in HIV RT. Earlier we have developed a method for prediction of HIV type 1 (HIV-1) resistance; it is based on the usage of position-specific descriptors. These descriptors are generated using the particular amino acid residue and its position; the position of certain residue is determined in a multiple alignment. The training set consisted of more than 1900 sequences of HIV RT from the Stanford HIV Drug Resistance database; for these HIV RT variants experimental data on their resistance to ten inhibitors are presented. Balanced accuracy of prediction varies from 80% to 99% depending on the method of classification (support vector machine, Naive Bayes, random forest, convolutional neural networks) and the drug, resistance to which is obtained. Maximal balanced accuracy was obtained for prediction of resistance to zidovudine, stavudine, didanosine and efavirenz by the random forest classifier. Average accuracy of prediction is 89%.

  3. Experimental and computational prediction of glass transition temperature of drugs.

    Science.gov (United States)

    Alzghoul, Ahmad; Alhalaweh, Amjad; Mahlin, Denny; Bergström, Christel A S

    2014-12-22

    Glass transition temperature (Tg) is an important inherent property of an amorphous solid material which is usually determined experimentally. In this study, the relation between Tg and melting temperature (Tm) was evaluated using a data set of 71 structurally diverse druglike compounds. Further, in silico models for prediction of Tg were developed based on calculated molecular descriptors and linear (multilinear regression, partial least-squares, principal component regression) and nonlinear (neural network, support vector regression) modeling techniques. The models based on Tm predicted Tg with an RMSE of 19.5 K for the test set. Among the five computational models developed herein the support vector regression gave the best result with RMSE of 18.7 K for the test set using only four chemical descriptors. Hence, two different models that predict Tg of drug-like molecules with high accuracy were developed. If Tm is available, a simple linear regression can be used to predict Tg. However, the results also suggest that support vector regression and calculated molecular descriptors can predict Tg with equal accuracy, already before compound synthesis.

  4. First 3 years of operation of RIACS (Research Institute for Advanced Computer Science) (1983-1985)

    Science.gov (United States)

    Denning, P. J.

    1986-01-01

    The focus of the Research Institute for Advanced Computer Science (RIACS) is to explore matches between advanced computing architectures and the processes of scientific research. An architecture evaluation of the MIT static dataflow machine, specification of a graphical language for expressing distributed computations, and specification of an expert system for aiding in grid generation for two-dimensional flow problems was initiated. Research projects for 1984 and 1985 are summarized.

  5. Predictive Simulation of Material Failure Using Peridynamics -- Advanced Constitutive Modeling, Verification and Validation

    Science.gov (United States)

    2016-03-31

    AFRL-AFOSR-VA-TR-2016-0309 Predictive simulation of material failure using peridynamics- advanced constitutive modeling, verification , and validation... Self -explanatory. 8. PERFORMING ORGANIZATION REPORT NUMBER. Enter all unique alphanumeric report numbers assigned by the performing organization, e.g...for public release. Predictive simulation of material failure using peridynamics-advanced constitutive modeling, verification , and validation John T

  6. Parallel computing in genomic research: advances and applications

    Directory of Open Access Journals (Sweden)

    Ocaña K

    2015-11-01

    Full Text Available Kary Ocaña,1 Daniel de Oliveira2 1National Laboratory of Scientific Computing, Petrópolis, Rio de Janeiro, 2Institute of Computing, Fluminense Federal University, Niterói, Brazil Abstract: Today's genomic experiments have to process the so-called "biological big data" that is now reaching the size of Terabytes and Petabytes. To process this huge amount of data, scientists may require weeks or months if they use their own workstations. Parallelism techniques and high-performance computing (HPC environments can be applied for reducing the total processing time and to ease the management, treatment, and analyses of this data. However, running bioinformatics experiments in HPC environments such as clouds, grids, clusters, and graphics processing unit requires the expertise from scientists to integrate computational, biological, and mathematical techniques and technologies. Several solutions have already been proposed to allow scientists for processing their genomic experiments using HPC capabilities and parallelism techniques. This article brings a systematic review of literature that surveys the most recently published research involving genomics and parallel computing. Our objective is to gather the main characteristics, benefits, and challenges that can be considered by scientists when running their genomic experiments to benefit from parallelism techniques and HPC capabilities. Keywords: high-performance computing, genomic research, cloud computing, grid computing, cluster computing, parallel computing

  7. DEEP: a general computational framework for predicting enhancers

    KAUST Repository

    Kleftogiannis, Dimitrios A.

    2014-11-05

    Transcription regulation in multicellular eukaryotes is orchestrated by a number of DNA functional elements located at gene regulatory regions. Some regulatory regions (e.g. enhancers) are located far away from the gene they affect. Identification of distal regulatory elements is a challenge for the bioinformatics research. Although existing methodologies increased the number of computationally predicted enhancers, performance inconsistency of computational models across different cell-lines, class imbalance within the learning sets and ad hoc rules for selecting enhancer candidates for supervised learning, are some key questions that require further examination. In this study we developed DEEP, a novel ensemble prediction framework. DEEP integrates three components with diverse characteristics that streamline the analysis of enhancer\\'s properties in a great variety of cellular conditions. In our method we train many individual classification models that we combine to classify DNA regions as enhancers or non-enhancers. DEEP uses features derived from histone modification marks or attributes coming from sequence characteristics. Experimental results indicate that DEEP performs better than four state-of-the-art methods on the ENCODE data. We report the first computational enhancer prediction results on FANTOM5 data where DEEP achieves 90.2% accuracy and 90% geometric mean (GM) of specificity and sensitivity across 36 different tissues. We further present results derived using in vivo-derived enhancer data from VISTA database. DEEP-VISTA, when tested on an independent test set, achieved GM of 80.1% and accuracy of 89.64%. DEEP framework is publicly available at http://cbrc.kaust.edu.sa/deep/.

  8. DEEP: a general computational framework for predicting enhancers

    KAUST Repository

    Kleftogiannis, Dimitrios A.; Kalnis, Panos; Bajic, Vladimir B.

    2014-01-01

    Transcription regulation in multicellular eukaryotes is orchestrated by a number of DNA functional elements located at gene regulatory regions. Some regulatory regions (e.g. enhancers) are located far away from the gene they affect. Identification of distal regulatory elements is a challenge for the bioinformatics research. Although existing methodologies increased the number of computationally predicted enhancers, performance inconsistency of computational models across different cell-lines, class imbalance within the learning sets and ad hoc rules for selecting enhancer candidates for supervised learning, are some key questions that require further examination. In this study we developed DEEP, a novel ensemble prediction framework. DEEP integrates three components with diverse characteristics that streamline the analysis of enhancer's properties in a great variety of cellular conditions. In our method we train many individual classification models that we combine to classify DNA regions as enhancers or non-enhancers. DEEP uses features derived from histone modification marks or attributes coming from sequence characteristics. Experimental results indicate that DEEP performs better than four state-of-the-art methods on the ENCODE data. We report the first computational enhancer prediction results on FANTOM5 data where DEEP achieves 90.2% accuracy and 90% geometric mean (GM) of specificity and sensitivity across 36 different tissues. We further present results derived using in vivo-derived enhancer data from VISTA database. DEEP-VISTA, when tested on an independent test set, achieved GM of 80.1% and accuracy of 89.64%. DEEP framework is publicly available at http://cbrc.kaust.edu.sa/deep/.

  9. Advanced numerical methods for uncertainty reduction when predicting heat exchanger dynamic stability limits: Review and perspectives

    International Nuclear Information System (INIS)

    Longatte, E.; Baj, F.; Hoarau, Y.; Braza, M.; Ruiz, D.; Canteneur, C.

    2013-01-01

    Highlights: ► Proposal of hybrid computational methods for investigating dynamical system stability. ► Modeling turbulence disequilibrium due to interaction with moving solid boundaries. ► Providing computational procedure for large size system solution approximation through model reduction. -- Abstract: This article proposes a review of recent and current developments in the modeling and advanced numerical methods used to simulate large-size systems involving multi-physics in the field of mechanics. It addresses the complex issue of stability analysis of dynamical systems submitted to external turbulent flows and aims to establish accurate stability maps applicable to heat exchanger design. The purpose is to provide dimensionless stability limit modeling that is suitable for a variety of configurations and is as accurate as possible in spite of the large scale of the systems to be considered. The challenge lies in predicting local effects that may impact global systems. A combination of several strategies that are suited concurrently to multi-physics, multi-scale and large-size system computation is therefore required. Based on empirical concepts, the heuristic models currently used in the framework of standard stability analysis suffer from a lack of predictive capabilities. On the other hand, numerical approaches based on fully-coupled fluid–solid dynamics system computation remain expensive due to the multi-physics patterns of physics and the large number of degrees of freedom involved. In this context, since experimentation cannot be achieved and numerical simulation is unavoidable but prohibitive, a hybrid strategy is proposed in order to take advantage of both numerical local solutions and empirical global solutions

  10. Vehicular traffic noise prediction using soft computing approach.

    Science.gov (United States)

    Singh, Daljeet; Nigam, S P; Agrawal, V P; Kumar, Maneek

    2016-12-01

    A new approach for the development of vehicular traffic noise prediction models is presented. Four different soft computing methods, namely, Generalized Linear Model, Decision Trees, Random Forests and Neural Networks, have been used to develop models to predict the hourly equivalent continuous sound pressure level, Leq, at different locations in the Patiala city in India. The input variables include the traffic volume per hour, percentage of heavy vehicles and average speed of vehicles. The performance of the four models is compared on the basis of performance criteria of coefficient of determination, mean square error and accuracy. 10-fold cross validation is done to check the stability of the Random Forest model, which gave the best results. A t-test is performed to check the fit of the model with the field data. Copyright © 2016 Elsevier Ltd. All rights reserved.

  11. Recent Advances in Computational Methods for Nuclear Magnetic Resonance Data Processing

    KAUST Repository

    Gao, Xin

    2013-01-11

    Although three-dimensional protein structure determination using nuclear magnetic resonance (NMR) spectroscopy is a computationally costly and tedious process that would benefit from advanced computational techniques, it has not garnered much research attention from specialists in bioinformatics and computational biology. In this paper, we review recent advances in computational methods for NMR protein structure determination. We summarize the advantages of and bottlenecks in the existing methods and outline some open problems in the field. We also discuss current trends in NMR technology development and suggest directions for research on future computational methods for NMR.

  12. Computationally efficient model predictive control algorithms a neural network approach

    CERN Document Server

    Ławryńczuk, Maciej

    2014-01-01

    This book thoroughly discusses computationally efficient (suboptimal) Model Predictive Control (MPC) techniques based on neural models. The subjects treated include: ·         A few types of suboptimal MPC algorithms in which a linear approximation of the model or of the predicted trajectory is successively calculated on-line and used for prediction. ·         Implementation details of the MPC algorithms for feedforward perceptron neural models, neural Hammerstein models, neural Wiener models and state-space neural models. ·         The MPC algorithms based on neural multi-models (inspired by the idea of predictive control). ·         The MPC algorithms with neural approximation with no on-line linearization. ·         The MPC algorithms with guaranteed stability and robustness. ·         Cooperation between the MPC algorithms and set-point optimization. Thanks to linearization (or neural approximation), the presented suboptimal algorithms do not require d...

  13. DYNAMIC MODELLING AND ADVANCED PREDICTIVE CONTROL OF A CONTINUOUS PROCESS OF ENZYME PURIFICATION

    Directory of Open Access Journals (Sweden)

    Dechechi E.C.

    1997-01-01

    Full Text Available A dynamic mathematical model, simulation and computer control of a Continuous Affinity Recycle Extraction (CARE process, a protein purification technique based on protein adsorption on solid-phase adsorbents is described in this work. This process, consisting of three reactors, is a multivariable process with considerable time delay in the on-line analyses of the controlled variable. An advanced predictive control configuration, specifically the Dynamic Matrix Control (DMC, was applied. The DMC algorithm was applied in process schemes where the aim was to maintain constant the enzyme concentration in the outlet of the third reactor. The performance of the DMC controller was analyzed in the feed-flow disturbances and the results are presented.

  14. First Responders Guide to Computer Forensics: Advanced Topics

    National Research Council Canada - National Science Library

    Nolan, Richard; Baker, Marie; Branson, Jake; Hammerstein, Josh; Rush, Kris; Waits, Cal; Schweinsberg, Elizabeth

    2005-01-01

    ... on more advanced technical operations like process characterization and spoofed email. It is designed for experienced security and network professionals who already have a fundamental understanding of forensic methodology...

  15. Thermal Model Predictions of Advanced Stirling Radioisotope Generator Performance

    Science.gov (United States)

    Wang, Xiao-Yen J.; Fabanich, William Anthony; Schmitz, Paul C.

    2014-01-01

    This presentation describes the capabilities of three-dimensional thermal power model of advanced stirling radioisotope generator (ASRG). The performance of the ASRG is presented for different scenario, such as Venus flyby with or without the auxiliary cooling system.

  16. The Advance of Computing from the Ground to the Cloud

    Science.gov (United States)

    Breeding, Marshall

    2009-01-01

    A trend toward the abstraction of computing platforms that has been developing in the broader IT arena over the last few years is just beginning to make inroads into the library technology scene. Cloud computing offers for libraries many interesting possibilities that may help reduce technology costs and increase capacity, reliability, and…

  17. Development and external validation of a risk-prediction model to predict 5-year overall survival in advanced larynx cancer

    NARCIS (Netherlands)

    Petersen, Japke F.; Stuiver, Martijn M.; Timmermans, Adriana J.; Chen, Amy; Zhang, Hongzhen; O'Neill, James P.; Deady, Sandra; Vander Poorten, Vincent; Meulemans, Jeroen; Wennerberg, Johan; Skroder, Carl; Day, Andrew T.; Koch, Wayne; van den Brekel, Michiel W. M.

    2017-01-01

    TNM-classification inadequately estimates patient-specific overall survival (OS). We aimed to improve this by developing a risk-prediction model for patients with advanced larynx cancer. Cohort study. We developed a risk prediction model to estimate the 5-year OS rate based on a cohort of 3,442

  18. Advances in soft computing, intelligent robotics and control

    CERN Document Server

    Fullér, Robert

    2014-01-01

    Soft computing, intelligent robotics and control are in the core interest of contemporary engineering. Essential characteristics of soft computing methods are the ability to handle vague information, to apply human-like reasoning, their learning capability, and ease of application. Soft computing techniques are widely applied in the control of dynamic systems, including mobile robots. The present volume is a collection of 20 chapters written by respectable experts of the fields, addressing various theoretical and practical aspects in soft computing, intelligent robotics and control. The first part of the book concerns with issues of intelligent robotics, including robust xed point transformation design, experimental verification of the input-output feedback linearization of differentially driven mobile robot and applying kinematic synthesis to micro electro-mechanical systems design. The second part of the book is devoted to fundamental aspects of soft computing. This includes practical aspects of fuzzy rule ...

  19. Seasonal Drought Prediction: Advances, Challenges, and Future Prospects

    Science.gov (United States)

    Hao, Zengchao; Singh, Vijay P.; Xia, Youlong

    2018-03-01

    Drought prediction is of critical importance to early warning for drought managements. This review provides a synthesis of drought prediction based on statistical, dynamical, and hybrid methods. Statistical drought prediction is achieved by modeling the relationship between drought indices of interest and a suite of potential predictors, including large-scale climate indices, local climate variables, and land initial conditions. Dynamical meteorological drought prediction relies on seasonal climate forecast from general circulation models (GCMs), which can be employed to drive hydrological models for agricultural and hydrological drought prediction with the predictability determined by both climate forcings and initial conditions. Challenges still exist in drought prediction at long lead time and under a changing environment resulting from natural and anthropogenic factors. Future research prospects to improve drought prediction include, but are not limited to, high-quality data assimilation, improved model development with key processes related to drought occurrence, optimal ensemble forecast to select or weight ensembles, and hybrid drought prediction to merge statistical and dynamical forecasts.

  20. Mathematical modeling and computational prediction of cancer drug resistance.

    Science.gov (United States)

    Sun, Xiaoqiang; Hu, Bin

    2017-06-23

    Diverse forms of resistance to anticancer drugs can lead to the failure of chemotherapy. Drug resistance is one of the most intractable issues for successfully treating cancer in current clinical practice. Effective clinical approaches that could counter drug resistance by restoring the sensitivity of tumors to the targeted agents are urgently needed. As numerous experimental results on resistance mechanisms have been obtained and a mass of high-throughput data has been accumulated, mathematical modeling and computational predictions using systematic and quantitative approaches have become increasingly important, as they can potentially provide deeper insights into resistance mechanisms, generate novel hypotheses or suggest promising treatment strategies for future testing. In this review, we first briefly summarize the current progress of experimentally revealed resistance mechanisms of targeted therapy, including genetic mechanisms, epigenetic mechanisms, posttranslational mechanisms, cellular mechanisms, microenvironmental mechanisms and pharmacokinetic mechanisms. Subsequently, we list several currently available databases and Web-based tools related to drug sensitivity and resistance. Then, we focus primarily on introducing some state-of-the-art computational methods used in drug resistance studies, including mechanism-based mathematical modeling approaches (e.g. molecular dynamics simulation, kinetic model of molecular networks, ordinary differential equation model of cellular dynamics, stochastic model, partial differential equation model, agent-based model, pharmacokinetic-pharmacodynamic model, etc.) and data-driven prediction methods (e.g. omics data-based conventional screening approach for node biomarkers, static network approach for edge biomarkers and module biomarkers, dynamic network approach for dynamic network biomarkers and dynamic module network biomarkers, etc.). Finally, we discuss several further questions and future directions for the use of

  1. Computational prediction of protein-protein interactions in Leishmania predicted proteomes.

    Directory of Open Access Journals (Sweden)

    Antonio M Rezende

    Full Text Available The Trypanosomatids parasites Leishmania braziliensis, Leishmania major and Leishmania infantum are important human pathogens. Despite of years of study and genome availability, effective vaccine has not been developed yet, and the chemotherapy is highly toxic. Therefore, it is clear just interdisciplinary integrated studies will have success in trying to search new targets for developing of vaccines and drugs. An essential part of this rationale is related to protein-protein interaction network (PPI study which can provide a better understanding of complex protein interactions in biological system. Thus, we modeled PPIs for Trypanosomatids through computational methods using sequence comparison against public database of protein or domain interaction for interaction prediction (Interolog Mapping and developed a dedicated combined system score to address the predictions robustness. The confidence evaluation of network prediction approach was addressed using gold standard positive and negative datasets and the AUC value obtained was 0.94. As result, 39,420, 43,531 and 45,235 interactions were predicted for L. braziliensis, L. major and L. infantum respectively. For each predicted network the top 20 proteins were ranked by MCC topological index. In addition, information related with immunological potential, degree of protein sequence conservation among orthologs and degree of identity compared to proteins of potential parasite hosts was integrated. This information integration provides a better understanding and usefulness of the predicted networks that can be valuable to select new potential biological targets for drug and vaccine development. Network modularity which is a key when one is interested in destabilizing the PPIs for drug or vaccine purposes along with multiple alignments of the predicted PPIs were performed revealing patterns associated with protein turnover. In addition, around 50% of hypothetical protein present in the networks

  2. Predictive Capability Maturity Model for computational modeling and simulation.

    Energy Technology Data Exchange (ETDEWEB)

    Oberkampf, William Louis; Trucano, Timothy Guy; Pilch, Martin M.

    2007-10-01

    The Predictive Capability Maturity Model (PCMM) is a new model that can be used to assess the level of maturity of computational modeling and simulation (M&S) efforts. The development of the model is based on both the authors experience and their analysis of similar investigations in the past. The perspective taken in this report is one of judging the usefulness of a predictive capability that relies on the numerical solution to partial differential equations to better inform and improve decision making. The review of past investigations, such as the Software Engineering Institute's Capability Maturity Model Integration and the National Aeronautics and Space Administration and Department of Defense Technology Readiness Levels, indicates that a more restricted, more interpretable method is needed to assess the maturity of an M&S effort. The PCMM addresses six contributing elements to M&S: (1) representation and geometric fidelity, (2) physics and material model fidelity, (3) code verification, (4) solution verification, (5) model validation, and (6) uncertainty quantification and sensitivity analysis. For each of these elements, attributes are identified that characterize four increasing levels of maturity. Importantly, the PCMM is a structured method for assessing the maturity of an M&S effort that is directed toward an engineering application of interest. The PCMM does not assess whether the M&S effort, the accuracy of the predictions, or the performance of the engineering system satisfies or does not satisfy specified application requirements.

  3. Tutorial on Computing: Technological Advances, Social Implications, Ethical and Legal Issues

    OpenAIRE

    Debnath, Narayan

    2012-01-01

    Computing and information technology have made significant advances. The use of computing and technology is a major aspect of our lives, and this use will only continue to increase in our lifetime. Electronic digital computers and high performance communication networks are central to contemporary information technology. The computing applications in a wide range of areas including business, communications, medical research, transportation, entertainments, and education are transforming lo...

  4. Center for Advanced Energy Studies: Computer Assisted Virtual Environment (CAVE)

    Data.gov (United States)

    Federal Laboratory Consortium — The laboratory contains a four-walled 3D computer assisted virtual environment - or CAVE TM — that allows scientists and engineers to literally walk into their data...

  5. Advances in Physarum machines sensing and computing with Slime mould

    CERN Document Server

    2016-01-01

    This book is devoted to Slime mould Physarum polycephalum, which is a large single cell capable for distributed sensing, concurrent information processing, parallel computation and decentralized actuation. The ease of culturing and experimenting with Physarum makes this slime mould an ideal substrate for real-world implementations of unconventional sensing and computing devices The book is a treatise of theoretical and experimental laboratory studies on sensing and computing properties of slime mould, and on the development of mathematical and logical theories of Physarum behavior. It is shown how to make logical gates and circuits, electronic devices (memristors, diodes, transistors, wires, chemical and tactile sensors) with the slime mould. The book demonstrates how to modify properties of Physarum computing circuits with functional nano-particles and polymers, to interface the slime mould with field-programmable arrays, and to use Physarum as a controller of microbial fuel cells. A unique multi-agent model...

  6. Chest computed tomography scores are predictive of survival in patients with cystic fibrosis awaiting lung transplantation

    DEFF Research Database (Denmark)

    Loeve, Martine; Hop, Wim C. J.; de Bruijne, Marleen

    2012-01-01

    Rationale: Up to a third of cystic fibrosis (CF) patients awaiting lung transplantation (LTX) die while waiting. Inclusion of computed tomography (CT) scores may improve survival prediction models such as the lung allocation score (LAS). Objectives: This study investigated the association between...... CT and survival in CF patients screened for LTX. Methods: Clinical data and chest CTs of 411 CF patients screened for LTX between 1990 and 2005 were collected from 17 centers. CTs were scored with the Severe Advanced Lung Disease (SALD) 4-category scoring system, including the components "infection....../inflammation" (INF), air trapping/hypoperfusion (AT), normal/hyperperfusion (NOR) and bulla/cysts (BUL). The volume of each component was computed using semi-automated software. Survival analysis included Kaplan-Meier curves, and Cox-regression models. Measurements and main results: 366 (186 males) out of 411...

  7. An advanced tube wear and fatigue workstation to predict flow induced vibrations of steam generator tubes

    International Nuclear Information System (INIS)

    Gay, N.; Baratte, C.; Flesch, B.

    1997-01-01

    Flow induced tube vibration damage is a major concern for designers and operators of nuclear power plant steam generators (SG). The operating flow-induced vibrational behaviour has to be estimated accurately to allow a precise evaluation of the new safety margins in order to optimize the maintenance policy. For this purpose, an industrial 'Tube Wear and Fatigue Workstation', called 'GEVIBUS Workstation' and based on an advanced methodology for predictive analysis of flow-induced vibration of tube bundles subject to cross-flow has been developed at Electricite de France. The GEVIBUS Workstation is an interactive processor linking modules as: thermalhydraulic computation, parametric finite element builder, interface between finite element model, thermalhydraulic code and vibratory response computations, refining modelling of fluid-elastic and random forces, linear and non-linear dynamic response and the coupled fluid-structure system, evaluation of tube damage due to fatigue and wear, graphical outputs. Two practical applications are also presented in the paper; the first simulation refers to an experimental set-up consisting of a straight tube bundle subject to water cross-flow, while the second one deals with an industrial configuration which has been observed in some operating steam generators i.e., top tube support plate degradation. In the first case the GEVIBUS predictions in terms of tube displacement time histories and phase planes have been found in very good agreement with experiment. In the second application the GEVIBUS computation showed that a tube with localized degradation is much more stable than a tube located in an extended degradation zone. Important conclusions are also drawn concerning maintenance. (author)

  8. Advancements in Violin-Related Human-Computer Interaction

    DEFF Research Database (Denmark)

    Overholt, Daniel

    2014-01-01

    of human intelligence and emotion is at the core of the Musical Interface Technology Design Space, MITDS. This is a framework that endeavors to retain and enhance such traits of traditional instruments in the design of interactive live performance interfaces. Utilizing the MITDS, advanced Human...

  9. Perceptions and Predictions of Expertise in Advanced Musical Learners

    Science.gov (United States)

    Papageorgi, Ioulia; Creech, Andrea; Haddon, Elizabeth; Morton, Frances; De Bezenac, Christophe; Himonides, Evangelos; Potter, John; Duffy, Celia; Whyton, Tony; Welch, Graham

    2010-01-01

    The aim of this article was to compare musicians' views on (a) the importance of musical skills and (b) the nature of expertise. Data were obtained from a specially devised web-based questionnaire completed by advanced musicians representing four musical genres (classical, popular, jazz, Scottish traditional) and varying degrees of professional…

  10. Next Generation Risk Assessment: Incorporation of Recent Advances in Molecular, Computational, and Systems Biology (Final Report)

    Science.gov (United States)

    EPA announced the release of the final report, Next Generation Risk Assessment: Incorporation of Recent Advances in Molecular, Computational, and Systems Biology. This report describes new approaches that are faster, less resource intensive, and more robust that can help ...

  11. Predictive analysis and Dataviz: An advanced solution for the ...

    African Journals Online (AJOL)

    pc

    2018-03-05

    Mar 5, 2018 ... information systems, transport now generates an exponential. Research Article .... distribution of sales by products. • Bars: They are often used to compare ... Optimize transit resources: With predictive analysis, citizens can be ...

  12. firestar--advances in the prediction of functionally important residues.

    Science.gov (United States)

    Lopez, Gonzalo; Maietta, Paolo; Rodriguez, Jose Manuel; Valencia, Alfonso; Tress, Michael L

    2011-07-01

    firestar is a server for predicting catalytic and ligand-binding residues in protein sequences. Here, we present the important developments since the first release of firestar. Previous versions of the server required human interpretation of the results; the server is now fully automatized. firestar has been implemented as a web service and can now be run in high-throughput mode. Prediction coverage has been greatly improved with the extension of the FireDB database and the addition of alignments generated by HHsearch. Ligands in FireDB are now classified for biological relevance. Many of the changes have been motivated by the critical assessment of techniques for protein structure prediction (CASP) ligand-binding prediction experiment, which provided us with a framework to test the performance of firestar. URL: http://firedb.bioinfo.cnio.es/Php/FireStar.php.

  13. Advances in criticality predictions for EBR-II

    International Nuclear Information System (INIS)

    Schaefer, R.W.; Imel, G.R.

    1994-01-01

    Improvements to startup criticality predictions for the EBR-II reactor have been made. More exact calculational models, methods and data are now used, and better procedures for obtaining experimental data that enter into the prediction are in place. Accuracy improved by more than a factor of two and the largest ECP error observed since the changes is only 18 cents. An experimental method using subcritical counts is also being implemented

  14. Advances in Computing and Information Technology : Proceedings of the Second International

    CERN Document Server

    Nagamalai, Dhinaharan; Chaki, Nabendu

    2012-01-01

    The international conference on Advances in Computing and Information technology (ACITY 2012) provides an excellent international forum for both academics and professionals for sharing knowledge and results in theory, methodology and applications of Computer Science and Information Technology. The Second International Conference on Advances in Computing and Information technology (ACITY 2012), held in Chennai, India, during July 13-15, 2012, covered a number of topics in all major fields of Computer Science and Information Technology including: networking and communications, network security and applications, web and internet computing, ubiquitous computing, algorithms, bioinformatics, digital image processing and pattern recognition, artificial intelligence, soft computing and applications. Upon a strength review process, a number of high-quality, presenting not only innovative ideas but also a founded evaluation and a strong argumentation of the same, were selected and collected in the present proceedings, ...

  15. [Advancements of computer chemistry in separation of Chinese medicine].

    Science.gov (United States)

    Li, Lingjuan; Hong, Hong; Xu, Xuesong; Guo, Liwei

    2011-12-01

    Separating technique of Chinese medicine is not only a key technique in the field of Chinese medicine' s research and development, but also a significant step in the modernization of Chinese medicinal preparation. Computer chemistry can build model and look for the regulations from Chinese medicine system which is full of complicated data. This paper analyzed the applicability, key technology, basic mode and common algorithm of computer chemistry applied in the separation of Chinese medicine, introduced the mathematic mode and the setting methods of Extraction kinetics, investigated several problems which based on traditional Chinese medicine membrane procession, and forecasted the application prospect.

  16. A computational model predicting disruption of blood vessel development.

    Directory of Open Access Journals (Sweden)

    Nicole Kleinstreuer

    2013-04-01

    Full Text Available Vascular development is a complex process regulated by dynamic biological networks that vary in topology and state across different tissues and developmental stages. Signals regulating de novo blood vessel formation (vasculogenesis and remodeling (angiogenesis come from a variety of biological pathways linked to endothelial cell (EC behavior, extracellular matrix (ECM remodeling and the local generation of chemokines and growth factors. Simulating these interactions at a systems level requires sufficient biological detail about the relevant molecular pathways and associated cellular behaviors, and tractable computational models that offset mathematical and biological complexity. Here, we describe a novel multicellular agent-based model of vasculogenesis using the CompuCell3D (http://www.compucell3d.org/ modeling environment supplemented with semi-automatic knowledgebase creation. The model incorporates vascular endothelial growth factor signals, pro- and anti-angiogenic inflammatory chemokine signals, and the plasminogen activating system of enzymes and proteases linked to ECM interactions, to simulate nascent EC organization, growth and remodeling. The model was shown to recapitulate stereotypical capillary plexus formation and structural emergence of non-coded cellular behaviors, such as a heterologous bridging phenomenon linking endothelial tip cells together during formation of polygonal endothelial cords. Molecular targets in the computational model were mapped to signatures of vascular disruption derived from in vitro chemical profiling using the EPA's ToxCast high-throughput screening (HTS dataset. Simulating the HTS data with the cell-agent based model of vascular development predicted adverse effects of a reference anti-angiogenic thalidomide analog, 5HPP-33, on in vitro angiogenesis with respect to both concentration-response and morphological consequences. These findings support the utility of cell agent-based models for simulating a

  17. Using Advanced Data Mining And Integration In Environmental Prediction Scenarios

    Directory of Open Access Journals (Sweden)

    Habala Ondrej

    2012-01-01

    Full Text Available We present one of the meteorological and hydrological experiments performed in the FP7 project ADMIRE. It serves as an experimental platform for hydrologists, and we have used it also as a testing platform for a suite of advanced data integration and data mining (DMI tools, developed within ADMIRE. The idea of ADMIRE is to develop an advanced DMI platform accessible even to users who are not familiar with data mining techniques. To this end, we have designed a novel DMI architecture, supported by a set of software tools, managed by DMI process descriptions written in a specialized high-level DMI language called DISPEL, and controlled via several different user interfaces, each performing a different set of tasks and targeting different user group.

  18. USING ADVANCED DATA MINING AND INTEGRATION IN ENVIRONMENTAL PREDICTION SCENARIOS

    Directory of Open Access Journals (Sweden)

    Ondrej Habala

    2012-01-01

    Full Text Available We present one of the meteorological and hydrological experiments performed inthe FP7 project ADMIRE. It serves as an experimental platform for hydrologists,and we have used it also as a testing platform for a suite of advanced dataintegration and data mining (DMI tools, developed within ADMIRE. The ideaof ADMIRE is to develop an advanced DMI platform accessible even to userswho are not familiar with data mining techniques. To this end, we have designeda novel DMI architecture, supported by a set of software tools, managed by DMIprocess descriptions written in a specialized high-level DMI language calledDISPEL, and controlled via several different user interfaces, each performinga different set of tasks and targeting different user group.

  19. Advanced Scientific Computing Research Exascale Requirements Review. An Office of Science review sponsored by Advanced Scientific Computing Research, September 27-29, 2016, Rockville, Maryland

    Energy Technology Data Exchange (ETDEWEB)

    Almgren, Ann [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); DeMar, Phil [Fermi National Accelerator Lab. (FNAL), Batavia, IL (United States); Vetter, Jeffrey [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Riley, Katherine [Argonne Leadership Computing Facility, Argonne, IL (United States); Antypas, Katie [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Bard, Deborah [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States). National Energy Research Scientific Computing Center (NERSC); Coffey, Richard [Argonne National Lab. (ANL), Argonne, IL (United States); Dart, Eli [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States). Energy Science Network; Dosanjh, Sudip [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Gerber, Richard [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Hack, James [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Monga, Inder [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States). Energy Science Network; Papka, Michael E. [Argonne National Lab. (ANL), Argonne, IL (United States); Rotman, Lauren [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States). Energy Science Network; Straatsma, Tjerk [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Wells, Jack [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Bernholdt, David E. [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Bethel, Wes [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Bosilca, George [Univ. of Tennessee, Knoxville, TN (United States); Cappello, Frank [Argonne National Lab. (ANL), Argonne, IL (United States); Gamblin, Todd [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Habib, Salman [Argonne National Lab. (ANL), Argonne, IL (United States); Hill, Judy [Oak Ridge Leadership Computing Facility, Oak Ridge, TN (United States); Hollingsworth, Jeffrey K. [Univ. of Maryland, College Park, MD (United States); McInnes, Lois Curfman [Argonne National Lab. (ANL), Argonne, IL (United States); Mohror, Kathryn [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Moore, Shirley [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Moreland, Ken [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Roser, Rob [Fermi National Accelerator Lab. (FNAL), Batavia, IL (United States); Shende, Sameer [Univ. of Oregon, Eugene, OR (United States); Shipman, Galen [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Williams, Samuel [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)

    2017-06-20

    The widespread use of computing in the American economy would not be possible without a thoughtful, exploratory research and development (R&D) community pushing the performance edge of operating systems, computer languages, and software libraries. These are the tools and building blocks — the hammers, chisels, bricks, and mortar — of the smartphone, the cloud, and the computing services on which we rely. Engineers and scientists need ever-more specialized computing tools to discover new material properties for manufacturing, make energy generation safer and more efficient, and provide insight into the fundamentals of the universe, for example. The research division of the U.S. Department of Energy’s (DOE’s) Office of Advanced Scientific Computing and Research (ASCR Research) ensures that these tools and building blocks are being developed and honed to meet the extreme needs of modern science. See also http://exascaleage.org/ascr/ for additional information.

  20. 77 FR 12823 - Advanced Scientific Computing Advisory Committee

    Science.gov (United States)

    2012-03-02

    ... Early Career technical talks Summary of Applied Math and Computer Science Workshops ASCR's new SBIR... least 5 business days prior to the meeting. Reasonable provision will be made to include the scheduled... the orderly conduct of business. Public comment will follow the 10-minute rule. Minutes: The minutes...

  1. Advanced Simulation and Computing Co-Design Strategy

    Energy Technology Data Exchange (ETDEWEB)

    Ang, James A. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Hoang, Thuc T. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Kelly, Suzanne M. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); McPherson, Allen [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Neely, Rob [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)

    2015-11-01

    This ASC Co-design Strategy lays out the full continuum and components of the co-design process, based on what we have experienced thus far and what we wish to do more in the future to meet the program’s mission of providing high performance computing (HPC) and simulation capabilities for NNSA to carry out its stockpile stewardship responsibility.

  2. Connecting Performance Analysis and Visualization to Advance Extreme Scale Computing

    Energy Technology Data Exchange (ETDEWEB)

    Bremer, Peer-Timo [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Mohr, Bernd [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Schulz, Martin [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Pasccci, Valerio [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Gamblin, Todd [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Brunst, Holger [Dresden Univ. of Technology (Germany)

    2015-07-29

    The characterization, modeling, analysis, and tuning of software performance has been a central topic in High Performance Computing (HPC) since its early beginnings. The overall goal is to make HPC software run faster on particular hardware, either through better scheduling, on-node resource utilization, or more efficient distributed communication.

  3. Gyrokinetic particle-in-cell simulations of plasma microturbulence on advanced computing platforms

    International Nuclear Information System (INIS)

    Ethier, S; Tang, W M; Lin, Z

    2005-01-01

    Since its introduction in the early 1980s, the gyrokinetic particle-in-cell (PIC) method has been very successfully applied to the exploration of many important kinetic stability issues in magnetically confined plasmas. Its self-consistent treatment of charged particles and the associated electromagnetic fluctuations makes this method appropriate for studying enhanced transport driven by plasma turbulence. Advances in algorithms and computer hardware have led to the development of a parallel, global, gyrokinetic code in full toroidal geometry, the gyrokinetic toroidal code (GTC), developed at the Princeton Plasma Physics Laboratory. It has proven to be an invaluable tool to study key effects of low-frequency microturbulence in fusion plasmas. As a high-performance computing applications code, its flexible mixed-model parallel algorithm has allowed GTC to scale to over a thousand processors, which is routinely used for simulations. Improvements are continuously being made. As the US ramps up its support for the International Tokamak Experimental Reactor (ITER), the need for understanding the impact of turbulent transport in burning plasma fusion devices is of utmost importance. Accordingly, the GTC code is at the forefront of the set of numerical tools being used to assess and predict the performance of ITER on critical issues such as the efficiency of energy confinement in reactors

  4. A computational model that predicts behavioral sensitivity to intracortical microstimulation

    Science.gov (United States)

    Kim, Sungshin; Callier, Thierri; Bensmaia, Sliman J.

    2017-02-01

    Objective. Intracortical microstimulation (ICMS) is a powerful tool to investigate the neural mechanisms of perception and can be used to restore sensation for patients who have lost it. While sensitivity to ICMS has previously been characterized, no systematic framework has been developed to summarize the detectability of individual ICMS pulse trains or the discriminability of pairs of pulse trains. Approach. We develop a simple simulation that describes the responses of a population of neurons to a train of electrical pulses delivered through a microelectrode. We then perform an ideal observer analysis on the simulated population responses to predict the behavioral performance of non-human primates in ICMS detection and discrimination tasks. Main results. Our computational model can predict behavioral performance across a wide range of stimulation conditions with high accuracy (R 2 = 0.97) and generalizes to novel ICMS pulse trains that were not used to fit its parameters. Furthermore, the model provides a theoretical basis for the finding that amplitude discrimination based on ICMS violates Weber’s law. Significance. The model can be used to characterize the sensitivity to ICMS across the range of perceptible and safe stimulation regimes. As such, it will be a useful tool for both neuroscience and neuroprosthetics.

  5. Advanced Materials Test Methods for Improved Life Prediction of Turbine Engine Components

    National Research Council Canada - National Science Library

    Stubbs, Jack

    2000-01-01

    Phase I final report developed under SBIR contract for Topic # AF00-149, "Durability of Turbine Engine Materials/Advanced Material Test Methods for Improved Use Prediction of Turbine Engine Components...

  6. Recent advances in swarm intelligence and evolutionary computation

    CERN Document Server

    2015-01-01

    This timely review volume summarizes the state-of-the-art developments in nature-inspired algorithms and applications with the emphasis on swarm intelligence and bio-inspired computation. Topics include the analysis and overview of swarm intelligence and evolutionary computation, hybrid metaheuristic algorithms, bat algorithm, discrete cuckoo search, firefly algorithm, particle swarm optimization, and harmony search as well as convergent hybridization. Application case studies have focused on the dehydration of fruits and vegetables by the firefly algorithm and goal programming, feature selection by the binary flower pollination algorithm, job shop scheduling, single row facility layout optimization, training of feed-forward neural networks, damage and stiffness identification, synthesis of cross-ambiguity functions by the bat algorithm, web document clustering, truss analysis, water distribution networks, sustainable building designs and others. As a timely review, this book can serve as an ideal reference f...

  7. Advances in Computer Science and Information Engineering Volume 2

    CERN Document Server

    Lin, Sally

    2012-01-01

    CSIE2012 is an integrated conference concentrating its focus on Computer Science and Information Engineering . In the proceeding, you can learn much more knowledge about Computer Science and Information Engineering of researchers from all around the world. The main role of the proceeding is to be used as an exchange pillar for researchers who are working in the mentioned fields. In order to meet the high quality of Springer, AISC series, the organization committee has made their efforts to do the following things. Firstly, poor quality paper has been refused after reviewing course by anonymous referee experts. Secondly, periodically review meetings have been held around the reviewers about five times for exchanging reviewing suggestions. Finally, the conference organizers had several preliminary sessions before the conference. Through efforts of different people and departments, the conference will be successful and fruitful.

  8. Advances in neural networks computational intelligence for ICT

    CERN Document Server

    Esposito, Anna; Morabito, Francesco; Pasero, Eros

    2016-01-01

    This carefully edited book is putting emphasis on computational and artificial intelligent methods for learning and their relative applications in robotics, embedded systems, and ICT interfaces for psychological and neurological diseases. The book is a follow-up of the scientific workshop on Neural Networks (WIRN 2015) held in Vietri sul Mare, Italy, from the 20th to the 22nd of May 2015. The workshop, at its 27th edition became a traditional scientific event that brought together scientists from many countries, and several scientific disciplines. Each chapter is an extended version of the original contribution presented at the workshop, and together with the reviewers’ peer revisions it also benefits from the live discussion during the presentation. The content of book is organized in the following sections. 1. Introduction, 2. Machine Learning, 3. Artificial Neural Networks: Algorithms and models, 4. Intelligent Cyberphysical and Embedded System, 5. Computational Intelligence Methods for Biomedical ICT in...

  9. Advances in Computer Science and Information Engineering Volume 1

    CERN Document Server

    Lin, Sally

    2012-01-01

    CSIE2012 is an integrated conference concentrating its focus on Computer Science and Information Engineering . In the proceeding, you can learn much more knowledge about Computer Science and Information Engineering of researchers from all around the world. The main role of the proceeding is to be used as an exchange pillar for researchers who are working in the mentioned fields. In order to meet the high quality of Springer, AISC series, the organization committee has made their efforts to do the following things. Firstly, poor quality paper has been refused after reviewing course by anonymous referee experts. Secondly, periodically review meetings have been held around the reviewers about five times for exchanging reviewing suggestions. Finally, the conference organizers had several preliminary sessions before the conference. Through efforts of different people and departments, the conference will be successful and fruitful.

  10. Advances in bio-inspired computing for combinatorial optimization problems

    CERN Document Server

    Pintea, Camelia-Mihaela

    2013-01-01

    Advances in Bio-inspired Combinatorial Optimization Problems' illustrates several recent bio-inspired efficient algorithms for solving NP-hard problems.Theoretical bio-inspired concepts and models, in particular for agents, ants and virtual robots are described. Large-scale optimization problems, for example: the Generalized Traveling Salesman Problem and the Railway Traveling Salesman Problem, are solved and their results are discussed.Some of the main concepts and models described in this book are: inner rule to guide ant search - a recent model in ant optimization, heterogeneous sensitive a

  11. Teaching Advanced Concepts in Computer Networks: VNUML-UM Virtualization Tool

    Science.gov (United States)

    Ruiz-Martinez, A.; Pereniguez-Garcia, F.; Marin-Lopez, R.; Ruiz-Martinez, P. M.; Skarmeta-Gomez, A. F.

    2013-01-01

    In the teaching of computer networks the main problem that arises is the high price and limited number of network devices the students can work with in the laboratories. Nowadays, with virtualization we can overcome this limitation. In this paper, we present a methodology that allows students to learn advanced computer network concepts through…

  12. Parallel computing in genomic research: advances and applications.

    Science.gov (United States)

    Ocaña, Kary; de Oliveira, Daniel

    2015-01-01

    Today's genomic experiments have to process the so-called "biological big data" that is now reaching the size of Terabytes and Petabytes. To process this huge amount of data, scientists may require weeks or months if they use their own workstations. Parallelism techniques and high-performance computing (HPC) environments can be applied for reducing the total processing time and to ease the management, treatment, and analyses of this data. However, running bioinformatics experiments in HPC environments such as clouds, grids, clusters, and graphics processing unit requires the expertise from scientists to integrate computational, biological, and mathematical techniques and technologies. Several solutions have already been proposed to allow scientists for processing their genomic experiments using HPC capabilities and parallelism techniques. This article brings a systematic review of literature that surveys the most recently published research involving genomics and parallel computing. Our objective is to gather the main characteristics, benefits, and challenges that can be considered by scientists when running their genomic experiments to benefit from parallelism techniques and HPC capabilities.

  13. Proceedings of the international conference on advances in computer and communication technology

    International Nuclear Information System (INIS)

    Bakal, J.W.; Kunte, A.S.; Walinjkar, P.B.; Karnani, N.K.

    2012-02-01

    A nation's development is coupled with advancement and adoption of new technologies. During the past decade advancements in computer and communication technologies have grown multi fold. For the growth of any country it is necessary to keep pace with the latest innovations in technology. International Conference on Advances in Computer and Communication Technology organised by Institution of Electronics and Telecommunication Engineers, Mumbai Centre is an attempt to provide a platform for scientists, engineering students, educators and experts to share their knowledge and discuss the efforts put by them in the field of R and D. The papers relevant to INIS are indexed separately

  14. National facility for advanced computational science: A sustainable path to scientific discovery

    Energy Technology Data Exchange (ETDEWEB)

    Simon, Horst; Kramer, William; Saphir, William; Shalf, John; Bailey, David; Oliker, Leonid; Banda, Michael; McCurdy, C. William; Hules, John; Canning, Andrew; Day, Marc; Colella, Philip; Serafini, David; Wehner, Michael; Nugent, Peter

    2004-04-02

    Lawrence Berkeley National Laboratory (Berkeley Lab) proposes to create a National Facility for Advanced Computational Science (NFACS) and to establish a new partnership between the American computer industry and a national consortium of laboratories, universities, and computing facilities. NFACS will provide leadership-class scientific computing capability to scientists and engineers nationwide, independent of their institutional affiliation or source of funding. This partnership will bring into existence a new class of computational capability in the United States that is optimal for science and will create a sustainable path towards petaflops performance.

  15. Teaching advance care planning to medical students with a computer-based decision aid.

    Science.gov (United States)

    Green, Michael J; Levi, Benjamin H

    2011-03-01

    Discussing end-of-life decisions with cancer patients is a crucial skill for physicians. This article reports findings from a pilot study evaluating the effectiveness of a computer-based decision aid for teaching medical students about advance care planning. Second-year medical students at a single medical school were randomized to use a standard advance directive or a computer-based decision aid to help patients with advance care planning. Students' knowledge, skills, and satisfaction were measured by self-report; their performance was rated by patients. 121/133 (91%) of students participated. The Decision-Aid Group (n = 60) outperformed the Standard Group (n = 61) in terms of students' knowledge (p satisfaction with their learning experience (p student performance. Use of a computer-based decision aid may be an effective way to teach medical students how to discuss advance care planning with cancer patients.

  16. Advanced and intelligent computations in diagnosis and control

    CERN Document Server

    2016-01-01

    This book is devoted to the demands of research and industrial centers for diagnostics, monitoring and decision making systems that result from the increasing complexity of automation and systems, the need to ensure the highest level of reliability and safety, and continuing research and the development of innovative approaches to fault diagnosis. The contributions combine domains of engineering knowledge for diagnosis, including detection, isolation, localization, identification, reconfiguration and fault-tolerant control. The book is divided into six parts:  (I) Fault Detection and Isolation; (II) Estimation and Identification; (III) Robust and Fault Tolerant Control; (IV) Industrial and Medical Diagnostics; (V) Artificial Intelligence; (VI) Expert and Computer Systems.

  17. Advanced Computational Methods for Thermal Radiative Heat Transfer

    Energy Technology Data Exchange (ETDEWEB)

    Tencer, John; Carlberg, Kevin Thomas; Larsen, Marvin E.; Hogan, Roy E.,

    2016-10-01

    Participating media radiation (PMR) in weapon safety calculations for abnormal thermal environments are too costly to do routinely. This cost may be s ubstantially reduced by applying reduced order modeling (ROM) techniques. The application of ROM to PMR is a new and unique approach for this class of problems. This approach was investigated by the authors and shown to provide significant reductions in the computational expense associated with typical PMR simulations. Once this technology is migrated into production heat transfer analysis codes this capability will enable the routine use of PMR heat transfer in higher - fidelity simulations of weapon resp onse in fire environments.

  18. Vision 20/20: Automation and advanced computing in clinical radiation oncology

    International Nuclear Information System (INIS)

    Moore, Kevin L.; Moiseenko, Vitali; Kagadis, George C.; McNutt, Todd R.; Mutic, Sasa

    2014-01-01

    This Vision 20/20 paper considers what computational advances are likely to be implemented in clinical radiation oncology in the coming years and how the adoption of these changes might alter the practice of radiotherapy. Four main areas of likely advancement are explored: cloud computing, aggregate data analyses, parallel computation, and automation. As these developments promise both new opportunities and new risks to clinicians and patients alike, the potential benefits are weighed against the hazards associated with each advance, with special considerations regarding patient safety under new computational platforms and methodologies. While the concerns of patient safety are legitimate, the authors contend that progress toward next-generation clinical informatics systems will bring about extremely valuable developments in quality improvement initiatives, clinical efficiency, outcomes analyses, data sharing, and adaptive radiotherapy

  19. Vision 20/20: Automation and advanced computing in clinical radiation oncology

    Energy Technology Data Exchange (ETDEWEB)

    Moore, Kevin L., E-mail: kevinmoore@ucsd.edu; Moiseenko, Vitali [Department of Radiation Medicine and Applied Sciences, University of California San Diego, La Jolla, California 92093 (United States); Kagadis, George C. [Department of Medical Physics, School of Medicine, University of Patras, Rion, GR 26504 (Greece); McNutt, Todd R. [Department of Radiation Oncology and Molecular Radiation Science, School of Medicine, Johns Hopkins University, Baltimore, Maryland 21231 (United States); Mutic, Sasa [Department of Radiation Oncology, Washington University in St. Louis, St. Louis, Missouri 63110 (United States)

    2014-01-15

    This Vision 20/20 paper considers what computational advances are likely to be implemented in clinical radiation oncology in the coming years and how the adoption of these changes might alter the practice of radiotherapy. Four main areas of likely advancement are explored: cloud computing, aggregate data analyses, parallel computation, and automation. As these developments promise both new opportunities and new risks to clinicians and patients alike, the potential benefits are weighed against the hazards associated with each advance, with special considerations regarding patient safety under new computational platforms and methodologies. While the concerns of patient safety are legitimate, the authors contend that progress toward next-generation clinical informatics systems will bring about extremely valuable developments in quality improvement initiatives, clinical efficiency, outcomes analyses, data sharing, and adaptive radiotherapy.

  20. Vision 20/20: Automation and advanced computing in clinical radiation oncology.

    Science.gov (United States)

    Moore, Kevin L; Kagadis, George C; McNutt, Todd R; Moiseenko, Vitali; Mutic, Sasa

    2014-01-01

    This Vision 20/20 paper considers what computational advances are likely to be implemented in clinical radiation oncology in the coming years and how the adoption of these changes might alter the practice of radiotherapy. Four main areas of likely advancement are explored: cloud computing, aggregate data analyses, parallel computation, and automation. As these developments promise both new opportunities and new risks to clinicians and patients alike, the potential benefits are weighed against the hazards associated with each advance, with special considerations regarding patient safety under new computational platforms and methodologies. While the concerns of patient safety are legitimate, the authors contend that progress toward next-generation clinical informatics systems will bring about extremely valuable developments in quality improvement initiatives, clinical efficiency, outcomes analyses, data sharing, and adaptive radiotherapy.

  1. Advances in Intelligent Control Systems and Computer Science

    CERN Document Server

    2013-01-01

    The conception of real-time control networks taking into account, as an integrating approach, both the specific aspects of information and knowledge processing and the dynamic and energetic particularities of physical processes and of communication networks is representing one of the newest scientific and technological challenges. The new paradigm of Cyber-Physical Systems (CPS) reflects this tendency and will certainly change the evolution of the technology, with major social and economic impact. This book presents significant results in the field of process control and advanced information and knowledge processing, with applications in the fields of robotics, biotechnology, environment, energy, transportation, et al.. It introduces intelligent control concepts and strategies as well as real-time implementation aspects for complex control approaches. One of the sections is dedicated to the complex problem of designing software systems for distributed information processing networks. Problems as complexity an...

  2. Integrated Computational Materials Engineering Development of Advanced High Strength Steel for Lightweight Vehicles

    Energy Technology Data Exchange (ETDEWEB)

    Hector, Jr., Louis G. [General Motors, Warren, MI (United States); McCarty, Eric D. [United States Automotive Materials Partnership LLC (USAMP), Southfield, MI (United States)

    2017-07-31

    The goal of the ICME 3GAHSS project was to successfully demonstrate the applicability of Integrated Computational Materials Engineering (ICME) for the development and deployment of third generation advanced high strength steels (3GAHSS) for immediate weight reduction in passenger vehicles. The ICME approach integrated results from well-established computational and experimental methodologies to develop a suite of material constitutive models (deformation and failure), manufacturing process and performance simulation modules, a properties database, as well as the computational environment linking them together for both performance prediction and material optimization. This is the Final Report for the ICME 3GAHSS project, which achieved the fol-lowing objectives: 1) Developed a 3GAHSS ICME model, which includes atomistic, crystal plasticity, state variable and forming models. The 3GAHSS model was implemented in commercially available LS-DYNA and a user guide was developed to facilitate use of the model. 2) Developed and produced two 3GAHSS alloys using two different chemistries and manufacturing processes, for use in calibrating and validating the 3GAHSS ICME Model. 3) Optimized the design of an automotive subassembly by substituting 3GAHSS for AHSS yielding a design that met or exceeded all baseline performance requirements with a 30% mass savings. A technical cost model was also developed to estimate the cost per pound of weight saved when substituting 3GAHSS for AHSS. The project demonstrated the potential for 3GAHSS to achieve up to 30% weight savings in an automotive structure at a cost penalty of up to $0.32 to $1.26 per pound of weight saved. The 3GAHSS ICME Model enables the user to design 3GAHSS to desired mechanical properties in terms of strength and ductility.

  3. User's Self-Prediction of Performance in Motor Imagery Brain-Computer Interface.

    Science.gov (United States)

    Ahn, Minkyu; Cho, Hohyun; Ahn, Sangtae; Jun, Sung C

    2018-01-01

    Performance variation is a critical issue in motor imagery brain-computer interface (MI-BCI), and various neurophysiological, psychological, and anatomical correlates have been reported in the literature. Although the main aim of such studies is to predict MI-BCI performance for the prescreening of poor performers, studies which focus on the user's sense of the motor imagery process and directly estimate MI-BCI performance through the user's self-prediction are lacking. In this study, we first test each user's self-prediction idea regarding motor imagery experimental datasets. Fifty-two subjects participated in a classical, two-class motor imagery experiment and were asked to evaluate their easiness with motor imagery and to predict their own MI-BCI performance. During the motor imagery experiment, an electroencephalogram (EEG) was recorded; however, no feedback on motor imagery was given to subjects. From EEG recordings, the offline classification accuracy was estimated and compared with several questionnaire scores of subjects, as well as with each subject's self-prediction of MI-BCI performance. The subjects' performance predictions during motor imagery task showed a high positive correlation ( r = 0.64, p performance even without feedback information. This implies that the human brain is an active learning system and, by self-experiencing the endogenous motor imagery process, it can sense and adopt the quality of the process. Thus, it is believed that users may be able to predict MI-BCI performance and results may contribute to a better understanding of low performance and advancing BCI.

  4. Life prediction of advanced materials for gas turbine application

    Energy Technology Data Exchange (ETDEWEB)

    Zamrik, S.Y.; Ray, A.; Koss, D.A. [Pennsylvania State Univ., University Park, PA (United States)

    1995-10-01

    Most of the studies on the low cycle fatigue life prediction have been reported under isothermal conditions where the deformation of the material is strain dependent. In the development of gas turbines, components such as blades and vanes are exposed to temperature variations in addition to strain cycling. As a result, the deformation process becomes temperature and strain dependent. Therefore, the life of the component becomes sensitive to temperature-strain cycling which produces a process known as {open_quotes}thermomechanical fatigue, or TMF{close_quotes}. The TMF fatigue failure phenomenon has been modeled using conventional fatigue life prediction methods, which are not sufficiently accurate to quantitatively establish an allowable design procedure. To add to the complexity of TMF life prediction, blade and vane substrates are normally coated with aluminide, overlay or thermal barrier type coatings (TBC) where the durability of the component is dominated by the coating/substrate constitutive response and by the fatigue behavior of the coating. A number of issues arise from TMF depending on the type of temperature/strain phase cycle: (1) time-dependent inelastic behavior can significantly affect the stress response. For example, creep relaxation during a tensile or compressive loading at elevated temperatures leads to a progressive increase in the mean stress level under cyclic loading. (2) the mismatch in elastic and thermal expansion properties between the coating and the substrate can lead to significant deviations in the coating stress levels due to changes in the elastic modulii. (3) the {open_quotes}dry{close_quotes} corrosion resistance coatings applied to the substrate may act as primary crack initiation sites. Crack initiation in the coating is a function of the coating composition, its mechanical properties, creep relaxation behavior, thermal strain range and the strain/temperature phase relationship.

  5. Predicting ionospheric scintillation: Recent advancements and future challenges

    Science.gov (United States)

    Carter, B. A.; Currie, J. L.; Terkildsen, M.; Bouya, Z.; Parkinson, M. L.

    2017-12-01

    Society greatly benefits from space-based infrastructure and technology. For example, signals from Global Navigation Satellite Systems (GNSS) are used across a wide range of industrial sectors; including aviation, mining, agriculture and finance. Current trends indicate that the use of these space-based technologies is likely to increase over the coming decades as the global economy becomes more technology-dependent. Space weather represents a key vulnerability to space-based technology, both in terms of the space environment effects on satellite infrastructure and the influence of the ionosphere on the radio signals used for satellite communications. In recent decades, the impact of the ionosphere on GNSS signals has re-ignited research interest into the equatorial ionosphere, particularly towards understanding Equatorial Plasma Bubbles (EPBs). EPBs are a dominant source of nighttime plasma irregularities in the low-latitude ionosphere, which can cause severe scintillation on GNSS signals and subsequent degradation on GNSS product quality. Currently, ionospheric scintillation event forecasts are not being routinely released by any space weather prediction agency around the world, but this is likely to change in the near future. In this contribution, an overview of recent efforts to develop a global ionospheric scintillation prediction capability within Australia will be given. The challenges in understanding user requirements for ionospheric scintillation predictions will be discussed. Next, the use of ground- and space-based datasets for the purpose of near-real time ionospheric scintillation monitoring will be explored. Finally, some modeling that has shown significant promise in transitioning towards an operational ionospheric scintillation forecasting system will be discussed.

  6. Recent advances in computational intelligence in defense and security

    CERN Document Server

    Falcon, Rafael; Zincir-Heywood, Nur; Abbass, Hussein

    2016-01-01

    This volume is an initiative undertaken by the IEEE Computational Intelligence Society’s Task Force on Security, Surveillance and Defense to consolidate and disseminate the role of CI techniques in the design, development and deployment of security and defense solutions. Applications range from the detection of buried explosive hazards in a battlefield to the control of unmanned underwater vehicles, the delivery of superior video analytics for protecting critical infrastructures or the development of stronger intrusion detection systems and the design of military surveillance networks. Defense scientists, industry experts, academicians and practitioners alike will all benefit from the wide spectrum of successful applications compiled in this volume. Senior undergraduate or graduate students may also discover uncharted territory for their own research endeavors.

  7. Advances in neural networks computational and theoretical issues

    CERN Document Server

    Esposito, Anna; Morabito, Francesco

    2015-01-01

    This book collects research works that exploit neural networks and machine learning techniques from a multidisciplinary perspective. Subjects covered include theoretical, methodological and computational topics which are grouped together into chapters devoted to the discussion of novelties and innovations related to the field of Artificial Neural Networks as well as the use of neural networks for applications, pattern recognition, signal processing, and special topics such as the detection and recognition of multimodal emotional expressions and daily cognitive functions, and  bio-inspired memristor-based networks.  Providing insights into the latest research interest from a pool of international experts coming from different research fields, the volume becomes valuable to all those with any interest in a holistic approach to implement believable, autonomous, adaptive, and context-aware Information Communication Technologies.

  8. Advances in x-ray computed microtomography at the NSLS

    International Nuclear Information System (INIS)

    Dowd, B.A.; Andrews, A.B.; Marr, R.B.; Siddons, D.P.; Jones, K.W.; Peskin, A.M.

    1998-08-01

    The X-Ray Computed Microtomography workstation at beamline X27A at the NSLS has been utilized by scientists from a broad range of disciplines from industrial materials processing to environmental science. The most recent applications are presented here as well as a description of the facility that has evolved to accommodate a wide variety of materials and sample sizes. One of the most exciting new developments reported here resulted from a pursuit of faster reconstruction techniques. A Fast Filtered Back Transform (FFBT) reconstruction program has been developed and implemented, that is based on a refinement of the gridding algorithm first developed for use with radio astronomical data. This program has reduced the reconstruction time to 8.5 sec for a 929 x 929 pixel 2 slice on an R10,000 CPU, more than 8x reduction compared with the Filtered Back-Projection method

  9. A Quantum Annealing Computer Team Addresses Climate Change Predictability

    Science.gov (United States)

    Halem, M. (Principal Investigator); LeMoigne, J.; Dorband, J.; Lomonaco, S.; Yesha, Ya.; Simpson, D.; Clune, T.; Pelissier, C.; Nearing, G.; Gentine, P.; hide

    2016-01-01

    The near confluence of the successful launch of the Orbiting Carbon Observatory2 on July 2, 2014 and the acceptance on August 20, 2015 by Google, NASA Ames Research Center and USRA of a 1152 qubit D-Wave 2X Quantum Annealing Computer (QAC), offered an exceptional opportunity to explore the potential of this technology to address the scientific prediction of global annual carbon uptake by land surface processes. At UMBC,we have collected and processed 20 months of global Level 2 light CO2 data as well as fluorescence data. In addition we have collected ARM data at 2sites in the US and Ameriflux data at more than 20 stations. J. Dorband has developed and implemented a multi-hidden layer Boltzmann Machine (BM) algorithm on the QAC. Employing the BM, we are calculating CO2 fluxes by training collocated OCO-2 level 2 CO2 data with ARM ground station tower data to infer to infer measured CO2 flux data. We generate CO2 fluxes with a regression analysis using these BM derived weights on the level 2 CO2 data for three Ameriflux sites distinct from the ARM stations. P. Gentine has negotiated for the access of K34 Ameriflux data in the Amazon and is applying a neural net to infer the CO2 fluxes. N. Talik validated the accuracy of the BM performance on the QAC against a restricted BM implementation on the IBM Softlayer Cloud with the Nvidia co-processors utilizing the same data sets. G. Nearing and K. Harrison have extended the GSFC LIS model with the NCAR Noah photosynthetic parameterization and have run a 10 year global prediction of the net ecosystem exchange. C. Pellisier is preparing a BM implementation of the Kalman filter data assimilation of CO2 fluxes. At UMBC, R. Prouty is conducting OSSE experiments with the LISNoah model on the IBM iDataPlex to simulate the impact of CO2 fluxes to improve the prediction of global annual carbon uptake. J. LeMoigne and D. Simpson have developed a neural net image registration system that will be used for MODIS ENVI and will be

  10. Experimental and computing strategies in advanced material characterization problems

    Energy Technology Data Exchange (ETDEWEB)

    Bolzon, G. [Department of Civil and Environmental Engineering, Politecnico di Milano, piazza Leonardo da Vinci 32, 20133 Milano, Italy gabriella.bolzon@polimi.it (Italy)

    2015-10-28

    The mechanical characterization of materials relies more and more often on sophisticated experimental methods that permit to acquire a large amount of data and, contemporarily, to reduce the invasiveness of the tests. This evolution accompanies the growing demand of non-destructive diagnostic tools that assess the safety level of components in use in structures and infrastructures, for instance in the strategic energy sector. Advanced material systems and properties that are not amenable to traditional techniques, for instance thin layered structures and their adhesion on the relevant substrates, can be also characterized by means of combined experimental-numerical tools elaborating data acquired by full-field measurement techniques. In this context, parameter identification procedures involve the repeated simulation of the laboratory or in situ tests by sophisticated and usually expensive non-linear analyses while, in some situation, reliable and accurate results would be required in real time. The effectiveness and the filtering capabilities of reduced models based on decomposition and interpolation techniques can be profitably used to meet these conflicting requirements. This communication intends to summarize some results recently achieved in this field by the author and her co-workers. The aim is to foster further interaction between engineering and mathematical communities.

  11. Experimental and computing strategies in advanced material characterization problems

    International Nuclear Information System (INIS)

    Bolzon, G.

    2015-01-01

    The mechanical characterization of materials relies more and more often on sophisticated experimental methods that permit to acquire a large amount of data and, contemporarily, to reduce the invasiveness of the tests. This evolution accompanies the growing demand of non-destructive diagnostic tools that assess the safety level of components in use in structures and infrastructures, for instance in the strategic energy sector. Advanced material systems and properties that are not amenable to traditional techniques, for instance thin layered structures and their adhesion on the relevant substrates, can be also characterized by means of combined experimental-numerical tools elaborating data acquired by full-field measurement techniques. In this context, parameter identification procedures involve the repeated simulation of the laboratory or in situ tests by sophisticated and usually expensive non-linear analyses while, in some situation, reliable and accurate results would be required in real time. The effectiveness and the filtering capabilities of reduced models based on decomposition and interpolation techniques can be profitably used to meet these conflicting requirements. This communication intends to summarize some results recently achieved in this field by the author and her co-workers. The aim is to foster further interaction between engineering and mathematical communities

  12. 16th International workshop on Advanced Computing and Analysis Techniques in physics (ACAT)

    CERN Document Server

    Lokajicek, M; Tumova, N

    2015-01-01

    16th International workshop on Advanced Computing and Analysis Techniques in physics (ACAT). The ACAT workshop series, formerly AIHENP (Artificial Intelligence in High Energy and Nuclear Physics), was created back in 1990. Its main purpose is to gather researchers related with computing in physics research together, from both physics and computer science sides, and bring them a chance to communicate with each other. It has established bridges between physics and computer science research, facilitating the advances in our understanding of the Universe at its smallest and largest scales. With the Large Hadron Collider and many astronomy and astrophysics experiments collecting larger and larger amounts of data, such bridges are needed now more than ever. The 16th edition of ACAT aims to bring related researchers together, once more, to explore and confront the boundaries of computing, automatic data analysis and theoretical calculation technologies. It will create a forum for exchanging ideas among the fields an...

  13. Recent advances using rodent models for predicting human allergenicity

    International Nuclear Information System (INIS)

    Knippels, Leon M.J.; Penninks, Andre H.

    2005-01-01

    The potential allergenicity of newly introduced proteins in genetically engineered foods has become an important safety evaluation issue. However, to evaluate the potential allergenicity and the potency of new proteins in our food, there are still no widely accepted and reliable test systems. The best-known allergy assessment proposal for foods derived from genetically engineered plants was the careful stepwise process presented in the so-called ILSI/IFBC decision tree. A revision of this decision tree strategy was proposed by a FAO/WHO expert consultation. As prediction of the sensitizing potential of the novel introduced protein based on animal testing was considered to be very important, animal models were introduced as one of the new test items, despite the fact that non of the currently studied models has been widely accepted and validated yet. In this paper, recent results are summarized of promising models developed in rat and mouse

  14. Cryogenic systems advanced monitoring, fault diagnostics, and predictive maintenance

    CERN Document Server

    Arpaia, Pasquale; Inglese, Vitaliano; Pezzetti, Marco

    2018-01-01

    Cryogenics, the study and technology of materials and systems at very low temperature, is widely used for sensors and instruments requiring very highly precise measurements with low electrical resistance, especially for measurements of materials and energies at a very small scale. Thus, the need to understand how instruments operate and perform over time at temperatures below -2920 F (-1800 C) is critical, for applications from Magnetic Resonance Imaging (MRI) to Nuclear Magnetic Resonance Spectroscopy to instrumentation for particle accelerators of all kinds. This book brings to the reader guidance learned from work at the European Laboratory for Nuclear Research (CERN), and its large scale particle accelerator in Switzerland to help engineers and technicians implement best practices in instrumentation at cryogenic temperatures, including a better understanding of fault detection and predictive maintenance. Special problems with devices like flow meters, pressure gauges, and temperature gauges when operating...

  15. National Energy Research Scientific Computing Center (NERSC): Advancing the frontiers of computational science and technology

    Energy Technology Data Exchange (ETDEWEB)

    Hules, J. [ed.

    1996-11-01

    National Energy Research Scientific Computing Center (NERSC) provides researchers with high-performance computing tools to tackle science`s biggest and most challenging problems. Founded in 1974 by DOE/ER, the Controlled Thermonuclear Research Computer Center was the first unclassified supercomputer center and was the model for those that followed. Over the years the center`s name was changed to the National Magnetic Fusion Energy Computer Center and then to NERSC; it was relocated to LBNL. NERSC, one of the largest unclassified scientific computing resources in the world, is the principal provider of general-purpose computing services to DOE/ER programs: Magnetic Fusion Energy, High Energy and Nuclear Physics, Basic Energy Sciences, Health and Environmental Research, and the Office of Computational and Technology Research. NERSC users are a diverse community located throughout US and in several foreign countries. This brochure describes: the NERSC advantage, its computational resources and services, future technologies, scientific resources, and computational science of scale (interdisciplinary research over a decade or longer; examples: combustion in engines, waste management chemistry, global climate change modeling).

  16. Extreme-Scale Computing Project Aims to Advance Precision Oncology | FNLCR Staging

    Science.gov (United States)

    Two government agencies and five national laboratories are collaborating to develop extremely high-performance computing capabilities that will analyze mountains of research and clinical data to improve scientific understanding of cancer, predict dru

  17. Extreme-Scale Computing Project Aims to Advance Precision Oncology | Poster

    Science.gov (United States)

    Two government agencies and five national laboratories are collaborating to develop extremely high-performance computing capabilities that will analyze mountains of research and clinical data to improve scientific understanding of cancer, predict drug response, and improve treatments for patients.

  18. Extreme-Scale Computing Project Aims to Advance Precision Oncology | FNLCR

    Science.gov (United States)

    Two government agencies and five national laboratories are collaborating to develop extremely high-performance computing capabilities that will analyze mountains of research and clinical data to improve scientific understanding of cancer, predict dru

  19. Advances in computed radiography systems and their physical imaging characteristics

    International Nuclear Information System (INIS)

    Cowen, A.R.; Davies, A.G.; Kengyelics, S.M.

    2007-01-01

    Radiological imaging is progressing towards an all-digital future, across the spectrum of medical imaging techniques. Computed radiography (CR) has provided a ready pathway from screen film to digital radiography and a convenient entry point to PACS. This review briefly revisits the principles of modern CR systems and their physical imaging characteristics. Wide dynamic range and digital image enhancement are well-established benefits of CR, which lend themselves to improved image presentation and reduced rates of repeat exposures. However, in its original form CR offered limited scope for reducing the radiation dose per radiographic exposure, compared with screen film. Recent innovations in CR, including the use of dual-sided image readout and channelled storage phosphor have eased these concerns. For example, introduction of these technologies has improved detective quantum efficiency (DQE) by approximately 50 and 100%, respectively, compared with standard CR. As a result CR currently affords greater scope for reducing patient dose, and provides a more substantive challenge to the new solid-state, flat-panel, digital radiography detectors

  20. Contingency Analysis Post-Processing With Advanced Computing and Visualization

    Energy Technology Data Exchange (ETDEWEB)

    Chen, Yousu; Glaesemann, Kurt; Fitzhenry, Erin

    2017-07-01

    Contingency analysis is a critical function widely used in energy management systems to assess the impact of power system component failures. Its outputs are important for power system operation for improved situational awareness, power system planning studies, and power market operations. With the increased complexity of power system modeling and simulation caused by increased energy production and demand, the penetration of renewable energy and fast deployment of smart grid devices, and the trend of operating grids closer to their capacity for better efficiency, more and more contingencies must be executed and analyzed quickly in order to ensure grid reliability and accuracy for the power market. Currently, many researchers have proposed different techniques to accelerate the computational speed of contingency analysis, but not much work has been published on how to post-process the large amount of contingency outputs quickly. This paper proposes a parallel post-processing function that can analyze contingency analysis outputs faster and display them in a web-based visualization tool to help power engineers improve their work efficiency by fast information digestion. Case studies using an ESCA-60 bus system and a WECC planning system are presented to demonstrate the functionality of the parallel post-processing technique and the web-based visualization tool.

  1. Ethnicity prediction and classification from iris texture patterns: A survey on recent advances

    CSIR Research Space (South Africa)

    Mabuza-Hocquet, Gugulethu

    2017-03-01

    Full Text Available The prediction and classification of ethnicity based on iris texture patterns using image processing, artificial intelligence and computer vision techniques is still a recent topic in iris biometrics. While the large body of knowledge and research...

  2. Advances in computational modelling for personalised medicine after myocardial infarction.

    Science.gov (United States)

    Mangion, Kenneth; Gao, Hao; Husmeier, Dirk; Luo, Xiaoyu; Berry, Colin

    2018-04-01

    Myocardial infarction (MI) is a leading cause of premature morbidity and mortality worldwide. Determining which patients will experience heart failure and sudden cardiac death after an acute MI is notoriously difficult for clinicians. The extent of heart damage after an acute MI is informed by cardiac imaging, typically using echocardiography or sometimes, cardiac magnetic resonance (CMR). These scans provide complex data sets that are only partially exploited by clinicians in daily practice, implying potential for improved risk assessment. Computational modelling of left ventricular (LV) function can bridge the gap towards personalised medicine using cardiac imaging in patients with post-MI. Several novel biomechanical parameters have theoretical prognostic value and may be useful to reflect the biomechanical effects of novel preventive therapy for adverse remodelling post-MI. These parameters include myocardial contractility (regional and global), stiffness and stress. Further, the parameters can be delineated spatially to correspond with infarct pathology and the remote zone. While these parameters hold promise, there are challenges for translating MI modelling into clinical practice, including model uncertainty, validation and verification, as well as time-efficient processing. More research is needed to (1) simplify imaging with CMR in patients with post-MI, while preserving diagnostic accuracy and patient tolerance (2) to assess and validate novel biomechanical parameters against established prognostic biomarkers, such as LV ejection fraction and infarct size. Accessible software packages with minimal user interaction are also needed. Translating benefits to patients will be achieved through a multidisciplinary approach including clinicians, mathematicians, statisticians and industry partners. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2018. All rights reserved. No commercial use is permitted unless

  3. Visceral fat area predicts survival in patients with advanced hepatocellular carcinoma treated with tyrosine kinase inhibitors.

    Science.gov (United States)

    Nault, Jean-Charles; Pigneur, Frédéric; Nelson, Anaïs Charles; Costentin, Charlotte; Tselikas, Lambros; Katsahian, Sandrine; Diao, Guoqing; Laurent, Alexis; Mallat, Ariane; Duvoux, Christophe; Luciani, Alain; Decaens, Thomas

    2015-10-01

    Anthropometric measurements have been linked to resistance to anti-angiogenic treatment and survival. Patients with advanced hepatocellular carcinoma treated with sorafenib or brivanib in 2008-2011 were included in this retrospective study. Anthropometric measurements were assessed using computed tomography and were correlated with drug toxicity, radiological response, and overall survival. 52 patients were included, Barcelona Clinic Liver Classification B (38%) and C (62%), with a mean value of α-fetoprotein of 29,554±85,654 ng/mL, with a median overall survival of 10.5 months. Sarcopenia was associated with a greater rate of hand-foot syndrome (P=0.049). Modified Response Evaluation Criteria In Solid Tumours (mRECIST) and Choi criteria were significantly associated with survival, but RECIST criteria were not. An absence of hand-foot syndrome and high-visceral fat area were associated with progressive disease as assessed by RECIST and mRECIST criteria. In multivariate analyses, high visceral fat area (HR=3.6; P=0.002), low lean body mass (HR=2.4; P=0.015), and presence of hand-foot syndrome (HR=1.8; P=0.004) were significantly associated with overall survival. In time-dependent multivariate analyses; only high visceral fat area was associated with survival. Visceral fat area is associated with survival and seems to be a predictive marker for primary resistance to tyrosine kinase inhibitors in patients with advanced hepatocellular carcinoma. Copyright © 2015 Editrice Gastroenterologica Italiana S.r.l. Published by Elsevier Ltd. All rights reserved.

  4. Advanced entry guidance algorithm with landing footprint computation

    Science.gov (United States)

    Leavitt, James Aaron

    -determined angle of attack profile. The method is also capable of producing orbital footprints using an automatically-generated set of angle of attack profiles of varying range, with the lowest profile designed for near-maximum range in the absence of an active heat load constraint. The accuracy of the footprint method is demonstrated by direct comparison with footprints computed independently by an optimization program.

  5. Towards early software reliability prediction for computer forensic tools (case study).

    Science.gov (United States)

    Abu Talib, Manar

    2016-01-01

    Versatility, flexibility and robustness are essential requirements for software forensic tools. Researchers and practitioners need to put more effort into assessing this type of tool. A Markov model is a robust means for analyzing and anticipating the functioning of an advanced component based system. It is used, for instance, to analyze the reliability of the state machines of real time reactive systems. This research extends the architecture-based software reliability prediction model for computer forensic tools, which is based on Markov chains and COSMIC-FFP. Basically, every part of the computer forensic tool is linked to a discrete time Markov chain. If this can be done, then a probabilistic analysis by Markov chains can be performed to analyze the reliability of the components and of the whole tool. The purposes of the proposed reliability assessment method are to evaluate the tool's reliability in the early phases of its development, to improve the reliability assessment process for large computer forensic tools over time, and to compare alternative tool designs. The reliability analysis can assist designers in choosing the most reliable topology for the components, which can maximize the reliability of the tool and meet the expected reliability level specified by the end-user. The approach of assessing component-based tool reliability in the COSMIC-FFP context is illustrated with the Forensic Toolkit Imager case study.

  6. NATO Advanced Study Institute on Advances in the Computer Simulations of Liquid Crystals

    CERN Document Server

    Zannoni, Claudio

    2000-01-01

    Computer simulations provide an essential set of tools for understanding the macroscopic properties of liquid crystals and of their phase transitions in terms of molecular models. While simulations of liquid crystals are based on the same general Monte Carlo and molecular dynamics techniques as are used for other fluids, they present a number of specific problems and peculiarities connected to the intrinsic properties of these mesophases. The field of computer simulations of anisotropic fluids is interdisciplinary and is evolving very rapidly. The present volume covers a variety of techniques and model systems, from lattices to hard particle and Gay-Berne to atomistic, for thermotropics, lyotropics, and some biologically interesting liquid crystals. Contributions are written by an excellent panel of international lecturers and provides a timely account of the techniques and problems in the field.

  7. Development of advanced stability theory suction prediction techniques for laminar flow control. [on swept wings

    Science.gov (United States)

    Srokowski, A. J.

    1978-01-01

    The problem of obtaining accurate estimates of suction requirements on swept laminar flow control wings was discussed. A fast accurate computer code developed to predict suction requirements by integrating disturbance amplification rates was described. Assumptions and approximations used in the present computer code are examined in light of flow conditions on the swept wing which may limit their validity.

  8. Recent advances in Optical Computed Tomography (OCT) imaging system for three dimensional (3D) radiotherapy dosimetry

    Science.gov (United States)

    Rahman, Ahmad Taufek Abdul; Farah Rosli, Nurul; Zain, Shafirah Mohd; Zin, Hafiz M.

    2018-01-01

    Radiotherapy delivery techniques for cancer treatment are becoming more complex and highly focused, to enable accurate radiation dose delivery to the cancerous tissue and minimum dose to the healthy tissue adjacent to tumour. Instrument to verify the complex dose delivery in radiotherapy such as optical computed tomography (OCT) measures the dose from a three-dimensional (3D) radiochromic dosimeter to ensure the accuracy of the radiotherapy beam delivery to the patient. OCT measures the optical density in radiochromic material that changes predictably upon exposure to radiotherapy beams. OCT systems have been developed using a photodiode and charged coupled device (CCD) as the detector. The existing OCT imaging systems have limitation in terms of the accuracy and the speed of the measurement. Advances in on-pixel intelligence CMOS image sensor (CIS) will be exploited in this work to replace current detector in OCT imaging systems. CIS is capable of on-pixel signal processing at a very fast imaging speed (over several hundred images per second) that will allow improvement in the 3D measurement of the optical density. The paper will review 3D radiochromic dosimeters and OCT systems developed and discuss how CMOS based OCT imaging will provide accurate and fast optical density measurements in 3D. The paper will also discuss the configuration of the CMOS based OCT developed in this work and how it may improve the existing OCT system.

  9. Advanced Computational and Experimental Techniques for Nacelle Liner Performance Evaluation

    Science.gov (United States)

    Gerhold, Carl H.; Jones, Michael G.; Brown, Martha C.; Nark, Douglas

    2009-01-01

    The Curved Duct Test Rig (CDTR) has been developed to investigate sound propagation through a duct of size comparable to the aft bypass duct of typical aircraft engines. The axial dimension of the bypass duct is often curved and this geometric characteristic is captured in the CDTR. The semiannular bypass duct is simulated by a rectangular test section in which the height corresponds to the circumferential dimension and the width corresponds to the radial dimension. The liner samples are perforate over honeycomb core and are installed on the side walls of the test section. The top and bottom surfaces of the test section are acoustically rigid to simulate a hard wall bifurcation or pylon. A unique feature of the CDTR is the control system that generates sound incident on the liner test section in specific modes. Uniform air flow, at ambient temperature and flow speed Mach 0.275, is introduced through the duct. Experiments to investigate configuration effects such as curvature along the flow path on the acoustic performance of a sample liner are performed in the CDTR and reported in this paper. Combinations of treated and acoustically rigid side walls are investigated. The scattering of modes of the incident wave, both by the curvature and by the asymmetry of wall treatment, is demonstrated in the experimental results. The effect that mode scattering has on total acoustic effectiveness of the liner treatment is also shown. Comparisons of measured liner attenuation with numerical results predicted by an analytic model based on the parabolic approximation to the convected Helmholtz equation are reported. The spectra of attenuation produced by the analytic model are similar to experimental results for both walls treated, straight and curved flow path, with plane wave and higher order modes incident. The numerical model is used to define the optimized resistance and reactance of a liner that significantly improves liner attenuation in the frequency range 1900-2400 Hz. A

  10. Computational data sciences for assessment and prediction of climate extremes

    Science.gov (United States)

    Ganguly, A. R.

    2011-12-01

    Climate extremes may be defined inclusively as severe weather events or large shifts in global or regional weather patterns which may be caused or exacerbated by natural climate variability or climate change. This area of research arguably represents one of the largest knowledge-gaps in climate science which is relevant for informing resource managers and policy makers. While physics-based climate models are essential in view of non-stationary and nonlinear dynamical processes, their current pace of uncertainty reduction may not be adequate for urgent stakeholder needs. The structure of the models may in some cases preclude reduction of uncertainty for critical processes at scales or for the extremes of interest. On the other hand, methods based on complex networks, extreme value statistics, machine learning, and space-time data mining, have demonstrated significant promise to improve scientific understanding and generate enhanced predictions. When combined with conceptual process understanding at multiple spatiotemporal scales and designed to handle massive data, interdisciplinary data science methods and algorithms may complement or supplement physics-based models. Specific examples from the prior literature and our ongoing work suggests how data-guided improvements may be possible, for example, in the context of ocean meteorology, climate oscillators, teleconnections, and atmospheric process understanding, which in turn can improve projections of regional climate, precipitation extremes and tropical cyclones in an useful and interpretable fashion. A community-wide effort is motivated to develop and adapt computational data science tools for translating climate model simulations to information relevant for adaptation and policy, as well as for improving our scientific understanding of climate extremes from both observed and model-simulated data.

  11. Blinded prospective evaluation of computer-based mechanistic schizophrenia disease model for predicting drug response.

    Directory of Open Access Journals (Sweden)

    Hugo Geerts

    Full Text Available The tremendous advances in understanding the neurobiological circuits involved in schizophrenia have not translated into more effective treatments. An alternative strategy is to use a recently published 'Quantitative Systems Pharmacology' computer-based mechanistic disease model of cortical/subcortical and striatal circuits based upon preclinical physiology, human pathology and pharmacology. The physiology of 27 relevant dopamine, serotonin, acetylcholine, norepinephrine, gamma-aminobutyric acid (GABA and glutamate-mediated targets is calibrated using retrospective clinical data on 24 different antipsychotics. The model was challenged to predict quantitatively the clinical outcome in a blinded fashion of two experimental antipsychotic drugs; JNJ37822681, a highly selective low-affinity dopamine D(2 antagonist and ocaperidone, a very high affinity dopamine D(2 antagonist, using only pharmacology and human positron emission tomography (PET imaging data. The model correctly predicted the lower performance of JNJ37822681 on the positive and negative syndrome scale (PANSS total score and the higher extra-pyramidal symptom (EPS liability compared to olanzapine and the relative performance of ocaperidone against olanzapine, but did not predict the absolute PANSS total score outcome and EPS liability for ocaperidone, possibly due to placebo responses and EPS assessment methods. Because of its virtual nature, this modeling approach can support central nervous system research and development by accounting for unique human drug properties, such as human metabolites, exposure, genotypes and off-target effects and can be a helpful tool for drug discovery and development.

  12. The Nuclear Energy Advanced Modeling and Simulation Enabling Computational Technologies FY09 Report

    Energy Technology Data Exchange (ETDEWEB)

    Diachin, L F; Garaizar, F X; Henson, V E; Pope, G

    2009-10-12

    In this document we report on the status of the Nuclear Energy Advanced Modeling and Simulation (NEAMS) Enabling Computational Technologies (ECT) effort. In particular, we provide the context for ECT In the broader NEAMS program and describe the three pillars of the ECT effort, namely, (1) tools and libraries, (2) software quality assurance, and (3) computational facility (computers, storage, etc) needs. We report on our FY09 deliverables to determine the needs of the integrated performance and safety codes (IPSCs) in these three areas and lay out the general plan for software quality assurance to meet the requirements of DOE and the DOE Advanced Fuel Cycle Initiative (AFCI). We conclude with a brief description of our interactions with the Idaho National Laboratory computer center to determine what is needed to expand their role as a NEAMS user facility.

  13. Advances in Computational Fluid-Structure Interaction and Flow Simulation Conference

    CERN Document Server

    Takizawa, Kenji

    2016-01-01

    This contributed volume celebrates the work of Tayfun E. Tezduyar on the occasion of his 60th birthday. The articles it contains were born out of the Advances in Computational Fluid-Structure Interaction and Flow Simulation (AFSI 2014) conference, also dedicated to Prof. Tezduyar and held at Waseda University in Tokyo, Japan on March 19-21, 2014. The contributing authors represent a group of international experts in the field who discuss recent trends and new directions in computational fluid dynamics (CFD) and fluid-structure interaction (FSI). Organized into seven distinct parts arranged by thematic topics, the papers included cover basic methods and applications of CFD, flows with moving boundaries and interfaces, phase-field modeling, computer science and high-performance computing (HPC) aspects of flow simulation, mathematical methods, biomedical applications, and FSI. Researchers, practitioners, and advanced graduate students working on CFD, FSI, and related topics will find this collection to be a defi...

  14. Development of a prediction model for residual disease in newly diagnosed advanced ovarian cancer.

    Science.gov (United States)

    Janco, Jo Marie Tran; Glaser, Gretchen; Kim, Bohyun; McGree, Michaela E; Weaver, Amy L; Cliby, William A; Dowdy, Sean C; Bakkum-Gamez, Jamie N

    2015-07-01

    To construct a tool, using computed tomography (CT) imaging and preoperative clinical variables, to estimate successful primary cytoreduction for advanced epithelial ovarian cancer (EOC). Women who underwent primary cytoreductive surgery for stage IIIC/IV EOC at Mayo Clinic between 1/2/2003 and 12/30/2011 and had preoperative CT images of the abdomen and pelvis within 90days prior to their surgery available for review were included. CT images were reviewed for large-volume ascites, diffuse peritoneal thickening (DPT), omental cake, lymphadenopathy (LP), and spleen or liver involvement. Preoperative factors included age, body mass index (BMI), Eastern Cooperative Oncology Group performance status (ECOG PS), American Society of Anesthesiologists (ASA) score, albumin, CA-125, and thrombocytosis. Two prediction models were developed to estimate the probability of (i) complete and (ii) suboptimal cytoreduction (residual disease (RD) >1cm) using multivariable logistic analysis with backward and stepwise variable selection methods. Internal validation was assessed using bootstrap resampling to derive an optimism-corrected estimate of the c-index. 279 patients met inclusion criteria: 143 had complete cytoreduction, 26 had suboptimal cytoreduction (RD>1cm), and 110 had measurable RD ≤1cm. On multivariable analysis, age, absence of ascites, omental cake, and DPT on CT imaging independently predicted complete cytoreduction (c-index=0.748). Conversely, predictors of suboptimal cytoreduction were ECOG PS, DPT, and LP on preoperative CT imaging (c-index=0.685). The generated models serve as preoperative evaluation tools that may improve counseling and selection for primary surgery, but need to be externally validated. Copyright © 2015 Elsevier Inc. All rights reserved.

  15. Advanced imaging in acute stroke management-Part I: Computed tomographic.

    Science.gov (United States)

    Saini, Monica; Butcher, Ken

    2009-01-01

    Neuroimaging is fundamental to stroke diagnosis and management. Non-contrast computed tomography (NCCT) has been the primary imaging modality utilized for this purpose for almost four decades. Although NCCT does permit identification of intracranial hemorrhage and parenchymal ischemic changes, insights into blood vessel patency and cerebral perfusion are limited. Advances in reperfusion strategies have made identification of potentially salvageable brain tissue a more practical concern. Advances in CT technology now permit identification of acute and chronic arterial lesions, as well as cerebral blood flow deficits. This review outlines principles of advanced CT image acquisition and its utility in acute stroke management.

  16. Accuracy of depolarization and delay spread predictions using advanced ray-based modeling in indoor scenarios

    Directory of Open Access Journals (Sweden)

    Mani Francesco

    2011-01-01

    Full Text Available Abstract This article investigates the prediction accuracy of an advanced deterministic propagation model in terms of channel depolarization and frequency selectivity for indoor wireless propagation. In addition to specular reflection and diffraction, the developed ray tracing tool considers penetration through dielectric blocks and/or diffuse scattering mechanisms. The sensitivity and prediction accuracy analysis is based on two measurement campaigns carried out in a warehouse and an office building. It is shown that the implementation of diffuse scattering into RT significantly increases the accuracy of the cross-polar discrimination prediction, whereas the delay-spread prediction is only marginally improved.

  17. A comparative analysis among computational intelligence techniques for dissolved oxygen prediction in Delaware River

    Directory of Open Access Journals (Sweden)

    Ehsan Olyaie

    2017-05-01

    Full Text Available Most of the water quality models previously developed and used in dissolved oxygen (DO prediction are complex. Moreover, reliable data available to develop/calibrate new DO models is scarce. Therefore, there is a need to study and develop models that can handle easily measurable parameters of a particular site, even with short length. In recent decades, computational intelligence techniques, as effective approaches for predicting complicated and significant indicator of the state of aquatic ecosystems such as DO, have created a great change in predictions. In this study, three different AI methods comprising: (1 two types of artificial neural networks (ANN namely multi linear perceptron (MLP and radial based function (RBF; (2 an advancement of genetic programming namely linear genetic programming (LGP; and (3 a support vector machine (SVM technique were used for DO prediction in Delaware River located at Trenton, USA. For evaluating the performance of the proposed models, root mean square error (RMSE, Nash–Sutcliffe efficiency coefficient (NS, mean absolute relative error (MARE and, correlation coefficient statistics (R were used to choose the best predictive model. The comparison of estimation accuracies of various intelligence models illustrated that the SVM was able to develop the most accurate model in DO estimation in comparison to other models. Also, it was found that the LGP model performs better than the both ANNs models. For example, the determination coefficient was 0.99 for the best SVM model, while it was 0.96, 0.91 and 0.81 for the best LGP, MLP and RBF models, respectively. In general, the results indicated that an SVM model could be employed satisfactorily in DO estimation.

  18. Predictive modeling of liquid-sodium thermal–hydraulics experiments and computations

    International Nuclear Information System (INIS)

    Arslan, Erkan; Cacuci, Dan G.

    2014-01-01

    Highlights: • We applied the predictive modeling method of Cacuci and Ionescu-Bujor (2010). • We assimilated data from sodium flow experiments. • We used computational fluid dynamics simulations of sodium experiments. • The predictive modeling method greatly reduced uncertainties in predicted results. - Abstract: This work applies the predictive modeling procedure formulated by Cacuci and Ionescu-Bujor (2010) to assimilate data from liquid-sodium thermal–hydraulics experiments in order to reduce systematically the uncertainties in the predictions of computational fluid dynamics (CFD) simulations. The predicted CFD-results for the best-estimate model parameters and results describing sodium-flow velocities and temperature distributions are shown to be significantly more precise than the original computations and experiments, in that the predicted uncertainties for the best-estimate results and model parameters are significantly smaller than both the originally computed and the experimental uncertainties

  19. Projected role of advanced computational aerodynamic methods at the Lockheed-Georgia company

    Science.gov (United States)

    Lores, M. E.

    1978-01-01

    Experience with advanced computational methods being used at the Lockheed-Georgia Company to aid in the evaluation and design of new and modified aircraft indicates that large and specialized computers will be needed to make advanced three-dimensional viscous aerodynamic computations practical. The Numerical Aerodynamic Simulation Facility should be used to provide a tool for designing better aerospace vehicles while at the same time reducing development costs by performing computations using Navier-Stokes equations solution algorithms and permitting less sophisticated but nevertheless complex calculations to be made efficiently. Configuration definition procedures and data output formats can probably best be defined in cooperation with industry, therefore, the computer should handle many remote terminals efficiently. The capability of transferring data to and from other computers needs to be provided. Because of the significant amount of input and output associated with 3-D viscous flow calculations and because of the exceedingly fast computation speed envisioned for the computer, special attention should be paid to providing rapid, diversified, and efficient input and output.

  20. Computational Prediction of the Aerodynamic Characteristics of SSTO Vehicle Configurations

    OpenAIRE

    Keiichiro, FUJIMOTO; Kozo, FUJI

    2003-01-01

    Flow-fields around basic SSTO-rocket configurations are numerically simulated by the Navier-Stokes computations. The study starts with the simulations of the Apollo-type configuration, in which the simulated results arecomparing with NASA's experiments and the capability of CFD approach is discussed.Computed aerodynamic coeffcients of Apollo configuration agree well with the experiments at subsonic, transonic and supersonic regime at all angles of attack and the present computational approach...

  1. Impact of computer advances on future finite elements computations. [for aircraft and spacecraft design

    Science.gov (United States)

    Fulton, Robert E.

    1985-01-01

    Research performed over the past 10 years in engineering data base management and parallel computing is discussed, and certain opportunities for research toward the next generation of structural analysis capability are proposed. Particular attention is given to data base management associated with the IPAD project and parallel processing associated with the Finite Element Machine project, both sponsored by NASA, and a near term strategy for a distributed structural analysis capability based on relational data base management software and parallel computers for a future structural analysis system.

  2. COLLABORATIVE RESEARCH: TOWARDS ADVANCED UNDERSTANDING AND PREDICTIVE CAPABILITY OF CLIMATE CHANGE IN THE ARCTIC USING A HIGH-RESOLUTION REGIONAL ARCTIC CLIMATE SYSTEM MODEL

    Energy Technology Data Exchange (ETDEWEB)

    Gutowski, William J.

    2013-02-07

    The motivation for this project was to advance the science of climate change and prediction in the Arctic region. Its primary goals were to (i) develop a state-of-the-art Regional Arctic Climate system Model (RACM) including high-resolution atmosphere, land, ocean, sea ice and land hydrology components and (ii) to perform extended numerical experiments using high performance computers to minimize uncertainties and fundamentally improve current predictions of climate change in the northern polar regions. These goals were realized first through evaluation studies of climate system components via one-way coupling experiments. Simulations were then used to examine the effects of advancements in climate component systems on their representation of main physics, time-mean fields and to understand variability signals at scales over many years. As such this research directly addressed some of the major science objectives of the BER Climate Change Research Division (CCRD) regarding the advancement of long-term climate prediction.

  3. The European computer model for optronic system performance prediction (ECOMOS)

    NARCIS (Netherlands)

    Kessler, S.; Bijl, P.; Labarre, L.; Repasi, E.; Wittenstein, W.; Bürsing, H.

    2017-01-01

    ECOMOS is a multinational effort within the framework of an EDA Project Arrangement. Its aim is to provide a generally accepted and harmonized European computer model for computing nominal Target Acquisition (TA) ranges of optronic imagers operating in the Visible or thermal Infrared (IR). The

  4. Advanced computational tools and methods for nuclear analyses of fusion technology systems

    International Nuclear Information System (INIS)

    Fischer, U.; Chen, Y.; Pereslavtsev, P.; Simakov, S.P.; Tsige-Tamirat, H.; Loughlin, M.; Perel, R.L.; Petrizzi, L.; Tautges, T.J.; Wilson, P.P.H.

    2005-01-01

    An overview is presented of advanced computational tools and methods developed recently for nuclear analyses of Fusion Technology systems such as the experimental device ITER ('International Thermonuclear Experimental Reactor') and the intense neutron source IFMIF ('International Fusion Material Irradiation Facility'). These include Monte Carlo based computational schemes for the calculation of three-dimensional shut-down dose rate distributions, methods, codes and interfaces for the use of CAD geometry models in Monte Carlo transport calculations, algorithms for Monte Carlo based sensitivity/uncertainty calculations, as well as computational techniques and data for IFMIF neutronics and activation calculations. (author)

  5. Computational modeling for prediction of the shear stress of three-dimensional isotropic and aligned fiber networks.

    Science.gov (United States)

    Park, Seungman

    2017-09-01

    computational models will provide new tools for predicting accurate functional properties and designing fibrous porous materials, thereby significantly advancing tissue engineering. Copyright © 2017 Elsevier B.V. All rights reserved.

  6. A first attempt to bring computational biology into advanced high school biology classrooms.

    Science.gov (United States)

    Gallagher, Suzanne Renick; Coon, William; Donley, Kristin; Scott, Abby; Goldberg, Debra S

    2011-10-01

    Computer science has become ubiquitous in many areas of biological research, yet most high school and even college students are unaware of this. As a result, many college biology majors graduate without adequate computational skills for contemporary fields of biology. The absence of a computational element in secondary school biology classrooms is of growing concern to the computational biology community and biology teachers who would like to acquaint their students with updated approaches in the discipline. We present a first attempt to correct this absence by introducing a computational biology element to teach genetic evolution into advanced biology classes in two local high schools. Our primary goal was to show students how computation is used in biology and why a basic understanding of computation is necessary for research in many fields of biology. This curriculum is intended to be taught by a computational biologist who has worked with a high school advanced biology teacher to adapt the unit for his/her classroom, but a motivated high school teacher comfortable with mathematics and computing may be able to teach this alone. In this paper, we present our curriculum, which takes into consideration the constraints of the required curriculum, and discuss our experiences teaching it. We describe the successes and challenges we encountered while bringing this unit to high school students, discuss how we addressed these challenges, and make suggestions for future versions of this curriculum.We believe that our curriculum can be a valuable seed for further development of computational activities aimed at high school biology students. Further, our experiences may be of value to others teaching computational biology at this level. Our curriculum can be obtained at http://ecsite.cs.colorado.edu/?page_id=149#biology or by contacting the authors.

  7. Advanced approaches to characterize the human intestinal microbiota by computational meta-analysis

    NARCIS (Netherlands)

    Nikkilä, J.; Vos, de W.M.

    2010-01-01

    GOALS: We describe advanced approaches for the computational meta-analysis of a collection of independent studies, including over 1000 phylogenetic array datasets, as a means to characterize the variability of human intestinal microbiota. BACKGROUND: The human intestinal microbiota is a complex

  8. Computed tomography findings after radiofrequency ablation in locally advanced pancreatic cancer

    NARCIS (Netherlands)

    Rombouts, Steffi J. E.; Derksen, Tyche C.; Nio, Chung Y.; van Hillegersberg, Richard; van Santvoort, Hjalmar C.; Walma, Marieke S.; Molenaar, Izaak Q.; van Leeuwen, Maarten S.

    2018-01-01

    The purpose of the study was to provide a systematic evaluation of the computed tomography(CT) findings after radiofrequency ablation (RFA) in locally advanced pancreatic cancer(LAPC). Eighteen patients with intra-operative RFA-treated LAPC were included in a prospective case series. All CT-scans

  9. Computed tomography, nuclear medicine, ultrasound. Advanced diagnostic imaging for problematic areas in paediatric otolaryngology

    International Nuclear Information System (INIS)

    Noyek, A.M.; Friedberg, J.; Fitz, C.R.; Greyson, N.D.; Gilday, D.; Ash, J.; Miskin, M.; Rothberg, R.

    1982-01-01

    This presentation considers the diagnostic role of three major advanced imaging modalities in paediatric otolaryngology: computed tomography, nuclear medicine and ultrasound. These techniques allow for both more specific diagnosis, and for more precise understanding of the natural history of diagnoses already rendered. (Auth.)

  10. Innovations and advances in computing, informatics, systems sciences, networking and engineering

    CERN Document Server

    Elleithy, Khaled

    2015-01-01

    Innovations and Advances in Computing, Informatics, Systems Sciences, Networking and Engineering  This book includes a set of rigorously reviewed world-class manuscripts addressing and detailing state-of-the-art research projects in the areas of Computer Science, Informatics, and Systems Sciences, and Engineering. It includes selected papers from the conference proceedings of the Eighth and some selected papers of the Ninth International Joint Conferences on Computer, Information, and Systems Sciences, and Engineering (CISSE 2012 & CISSE 2013). Coverage includes topics in: Industrial Electronics, Technology & Automation, Telecommunications and Networking, Systems, Computing Sciences and Software Engineering, Engineering Education, Instructional Technology, Assessment, and E-learning.  ·       Provides the latest in a series of books growing out of the International Joint Conferences on Computer, Information, and Systems Sciences, and Engineering; ·       Includes chapters in the most a...

  11. 1st International Conference on Computational Advancement in Communication Circuits and Systems

    CERN Document Server

    Dalapati, Goutam; Banerjee, P; Mallick, Amiya; Mukherjee, Moumita

    2015-01-01

    This book comprises the proceedings of 1st International Conference on Computational Advancement in Communication Circuits and Systems (ICCACCS 2014) organized by Narula Institute of Technology under the patronage of JIS group, affiliated to West Bengal University of Technology. The conference was supported by Technical Education Quality Improvement Program (TEQIP), New Delhi, India and had technical collaboration with IEEE Kolkata Section, along with publication partner by Springer. The book contains 62 refereed papers that aim to highlight new theoretical and experimental findings in the field of Electronics and communication engineering including interdisciplinary fields like Advanced Computing, Pattern Recognition and Analysis, Signal and Image Processing. The proceedings cover the principles, techniques and applications in microwave & devices, communication & networking, signal & image processing, and computations & mathematics & control. The proceedings reflect the conference’s emp...

  12. Computational Embryology and Predictive Toxicology of Cleft Palate

    Science.gov (United States)

    Capacity to model and simulate key events in developmental toxicity using computational systems biology and biological knowledge steps closer to hazard identification across the vast landscape of untested environmental chemicals. In this context, we chose cleft palate as a model ...

  13. Advanced 2-dimensional quantitative coronary angiographic analysis for prediction of fractional flow reserve in intermediate coronary stenoses.

    Science.gov (United States)

    Opolski, Maksymilian P; Pregowski, Jerzy; Kruk, Mariusz; Kepka, Cezary; Staruch, Adam D; Witkowski, Adam

    2014-07-01

    The widespread clinical application of coronary computed tomography angiography (CCTA) has resulted in increased referral patterns of patients with intermediate coronary stenoses to invasive coronary angiography. We evaluated the application of advanced quantitative coronary angiography (A-QCA) for predicting fractional flow reserve (FFR) in intermediate coronary lesions detected on CCTA. Fifty-six patients with 66 single intermediate coronary lesions (≥ 50% to 80% stenosis) on CCTA prospectively underwent coronary angiography and FFR. A-QCA including calculation of the Poiseuille-based index defined as the ratio of lesion length to the fourth power of the minimal lumen diameter (MLD) was performed. Significant stenosis was defined as FFR ≤ 0.80. The mean FFR was 0.86 ± 0.09, and 18 lesions (27%) were functionally significant. FFR correlated with lesion length (R=-0.303, P=0.013), MLD (R=0.527, P44%, and >69%, respectively (maximum negative predictive value of 94% for MLA, maximum positive predictive value of 58% for diameter stenosis). The Poiseuille-based index was the most accurate (C statistic 0.86, sensitivity 100%, specificity 71%, positive predictive value 56%, and negative predictive value 100%) predictor of FFR ≤ 0.80, but showed the lowest interobserver agreement (intraclass correlation coefficient 0.37). A-QCA might be used to rule out significant ischemia in intermediate stenoses detected by CCTA. The diagnostic application of the Poiseuille-based angiographic index is precluded by its high interobserver variability.

  14. THE COMPUTATIONAL INTELLIGENCE TECHNIQUES FOR PREDICTIONS - ARTIFICIAL NEURAL NETWORKS

    OpenAIRE

    Mary Violeta Bar

    2014-01-01

    The computational intelligence techniques are used in problems which can not be solved by traditional techniques when there is insufficient data to develop a model problem or when they have errors.Computational intelligence, as he called Bezdek (Bezdek, 1992) aims at modeling of biological intelligence. Artificial Neural Networks( ANNs) have been applied to an increasing number of real world problems of considerable complexity. Their most important advantage is solving problems that are too c...

  15. Review of some advances of the literature about predictive variables concerning subjective well-being

    Directory of Open Access Journals (Sweden)

    Gloria Cajiao

    2013-06-01

    Full Text Available This review of scientific literature presents some tendencies, conceptual advances, empirical findings and tests that measure the predictive variables of subjective well-being. It was done through the search in bibliographical database like ProQuest, PsycArticles, Psyctest, OVID SP, books and Thesis. Two types of predictive variables were recognized- internal and external to the individual-. Both of them influence the achievement of the subjective well-being. Besides, the studies and conceptualization about Subjetive well-being and some of the Predictive Variables were analyzed in the conclusion.

  16. Computational Appliance for Rapid Prediction of Aircraft Trajectories, Phase I

    Data.gov (United States)

    National Aeronautics and Space Administration — Next generation air traffic management systems will be based to a greater degree on predicted trajectories of aircraft. Due to the iterative nature of future air...

  17. Advanced Daily Prediction Model for National Suicide Numbers with Social Media Data.

    Science.gov (United States)

    Lee, Kyung Sang; Lee, Hyewon; Myung, Woojae; Song, Gil-Young; Lee, Kihwang; Kim, Ho; Carroll, Bernard J; Kim, Doh Kwan

    2018-04-01

    Suicide is a significant public health concern worldwide. Social media data have a potential role in identifying high suicide risk individuals and also in predicting suicide rate at the population level. In this study, we report an advanced daily suicide prediction model using social media data combined with economic/meteorological variables along with observed suicide data lagged by 1 week. The social media data were drawn from weblog posts. We examined a total of 10,035 social media keywords for suicide prediction. We made predictions of national suicide numbers 7 days in advance daily for 2 years, based on a daily moving 5-year prediction modeling period. Our model predicted the likely range of daily national suicide numbers with 82.9% accuracy. Among the social media variables, words denoting economic issues and mood status showed high predictive strength. Observed number of suicides one week previously, recent celebrity suicide, and day of week followed by stock index, consumer price index, and sunlight duration 7 days before the target date were notable predictors along with the social media variables. These results strengthen the case for social media data to supplement classical social/economic/climatic data in forecasting national suicide events.

  18. Genomic Prediction of Seed Quality Traits Using Advanced Barley Breeding Lines

    Science.gov (United States)

    Nielsen, Nanna Hellum; Jahoor, Ahmed; Jensen, Jens Due; Orabi, Jihad; Cericola, Fabio; Edriss, Vahid; Jensen, Just

    2016-01-01

    Genomic selection was recently introduced in plant breeding. The objective of this study was to develop genomic prediction for important seed quality parameters in spring barley. The aim was to predict breeding values without expensive phenotyping of large sets of lines. A total number of 309 advanced spring barley lines tested at two locations each with three replicates were phenotyped and each line was genotyped by Illumina iSelect 9Kbarley chip. The population originated from two different breeding sets, which were phenotyped in two different years. Phenotypic measurements considered were: seed size, protein content, protein yield, test weight and ergosterol content. A leave-one-out cross-validation strategy revealed high prediction accuracies ranging between 0.40 and 0.83. Prediction across breeding sets resulted in reduced accuracies compared to the leave-one-out strategy. Furthermore, predicting across full and half-sib-families resulted in reduced prediction accuracies. Additionally, predictions were performed using reduced marker sets and reduced training population sets. In conclusion, using less than 200 lines in the training set can result in low prediction accuracy, and the accuracy will then be highly dependent on the family structure of the selected training set. However, the results also indicate that relatively small training sets (200 lines) are sufficient for genomic prediction in commercial barley breeding. In addition, our results indicate a minimum marker set of 1,000 to decrease the risk of low prediction accuracy for some traits or some families. PMID:27783639

  19. Genomic Prediction of Seed Quality Traits Using Advanced Barley Breeding Lines.

    Directory of Open Access Journals (Sweden)

    Nanna Hellum Nielsen

    Full Text Available Genomic selection was recently introduced in plant breeding. The objective of this study was to develop genomic prediction for important seed quality parameters in spring barley. The aim was to predict breeding values without expensive phenotyping of large sets of lines. A total number of 309 advanced spring barley lines tested at two locations each with three replicates were phenotyped and each line was genotyped by Illumina iSelect 9Kbarley chip. The population originated from two different breeding sets, which were phenotyped in two different years. Phenotypic measurements considered were: seed size, protein content, protein yield, test weight and ergosterol content. A leave-one-out cross-validation strategy revealed high prediction accuracies ranging between 0.40 and 0.83. Prediction across breeding sets resulted in reduced accuracies compared to the leave-one-out strategy. Furthermore, predicting across full and half-sib-families resulted in reduced prediction accuracies. Additionally, predictions were performed using reduced marker sets and reduced training population sets. In conclusion, using less than 200 lines in the training set can result in low prediction accuracy, and the accuracy will then be highly dependent on the family structure of the selected training set. However, the results also indicate that relatively small training sets (200 lines are sufficient for genomic prediction in commercial barley breeding. In addition, our results indicate a minimum marker set of 1,000 to decrease the risk of low prediction accuracy for some traits or some families.

  20. Advanced digital computers, controls, and automation technologies for power plants: Proceedings

    International Nuclear Information System (INIS)

    Bhatt, S.C.

    1992-08-01

    This document is a compilation of the papers that were presented at an EPRI workshop on Advances in Computers, Controls, and Automation Technologies for Power Plants. The workshop, sponsored by EPRI's Nuclear Power Division, took place February 1992. It was attended by 157 representatives from electric utilities, equipment manufacturers, engineering consulting organizations, universities, national laboratories, government agencies and international utilities. More than 40% of the attendees were from utilities representing the majority group. There were 30% attendees from equipment manufacturers and the engineering consulting organizations. The participants from government agencies, universities, and national laboratories were about 10% each. The workshop included a keynote address, 35 technical papers, and vendor's equipment demonstrations. The technical papers described the state-of-the-art in the areas of recent utility digital upgrades such as digital feedwater controllers, steam generator level controllers, integrated plant computer systems, computer aided diagnostics, automated testing and surveillance and other applications. A group of technical papers presented the ongoing B ampersand W PWR integrated plant control system prototype developments with the triple redundant advanced digital control system. Several international papers from France, Japan and U.K. presented their programs on advance power plant design and applications. Significant advances in the control and automation technologies such as adaptive controls, self-tuning methods, neural networks and expert systems were presented by developers, universities, and national laboratories. Individual papers are indexed separately

  1. Abs-initio, Predictive Calculations for Optoelectronic and Advanced Materials Research

    Science.gov (United States)

    Bagayoko, Diola

    2010-10-01

    Most density functional theory (DFT) calculations find band gaps that are 30-50 percent smaller than the experimental ones. Some explanations of this serious underestimation by theory include self-interaction and the derivative discontinuity of the exchange correlation energy. Several approaches have been developed in the search for a solution to this problem. Most of them entail some modification of DFT potentials. The Green function and screened Coulomb approximation (GWA) is a non-DFT formalism that has led to some improvements. Despite these efforts, the underestimation problem has mostly persisted in the literature. Using the Rayleigh theorem, we describe a basis set and variational effect inherently associated with calculations that employ a linear combination of atomic orbitals (LCAO) in a variational approach of the Rayleigh-Ritz type. This description concomitantly shows a source of large underestimation errors in calculated band gaps, i.e., an often dramatic lowering of some unoccupied energies on account of the Rayleigh theorem as opposed to a physical interaction. We present the Bagayoko, Zhao, and Williams (BZW) method [Phys. Rev. B 60, 1563 (1999); PRB 74, 245214 (2006); and J. Appl. Phys. 103, 096101 (2008)] that systematically avoids this effect and leads (a) to DFT and LDA calculated band gaps of semiconductors in agreement with experiment and (b) theoretical predictions of band gaps that are confirmed by experiment. Unlike most calculations, BZW computations solve, self-consistently, a system of two coupled equations. DFT-BZW calculated effective masses and optical properties (dielectric functions) also agree with measurements. We illustrate ten years of success of the BZW method with its results for GaN, C, Si, 3C-SIC, 4H-SiC, ZnO, AlAs, Ge, ZnSe, w-InN, c-InN, InAs, CdS, AlN and nanostructures. We conclude with potential applications of the BZW method in optoelectronic and advanced materials research.

  2. APPLICATION OF SOFT COMPUTING TECHNIQUES FOR PREDICTING COOLING TIME REQUIRED DROPPING INITIAL TEMPERATURE OF MASS CONCRETE

    Directory of Open Access Journals (Sweden)

    Santosh Bhattarai

    2017-07-01

    Full Text Available Minimizing the thermal cracks in mass concrete at an early age can be achieved by removing the hydration heat as quickly as possible within initial cooling period before the next lift is placed. Recognizing the time needed to remove hydration heat within initial cooling period helps to take an effective and efficient decision on temperature control plan in advance. Thermal properties of concrete, water cooling parameters and construction parameter are the most influencing factors involved in the process and the relationship between these parameters are non-linear in a pattern, complicated and not understood well. Some attempts had been made to understand and formulate the relationship taking account of thermal properties of concrete and cooling water parameters. Thus, in this study, an effort have been made to formulate the relationship for the same taking account of thermal properties of concrete, water cooling parameters and construction parameter, with the help of two soft computing techniques namely: Genetic programming (GP software “Eureqa” and Artificial Neural Network (ANN. Relationships were developed from the data available from recently constructed high concrete double curvature arch dam. The value of R for the relationship between the predicted and real cooling time from GP and ANN model is 0.8822 and 0.9146 respectively. Relative impact on target parameter due to input parameters was evaluated through sensitivity analysis and the results reveal that, construction parameter influence the target parameter significantly. Furthermore, during the testing phase of proposed models with an independent set of data, the absolute and relative errors were significantly low, which indicates the prediction power of the employed soft computing techniques deemed satisfactory as compared to the measured data.

  3. Computational code in atomic and nuclear quantum optics: Advanced computing multiphoton resonance parameters for atoms in a strong laser field

    Science.gov (United States)

    Glushkov, A. V.; Gurskaya, M. Yu; Ignatenko, A. V.; Smirnov, A. V.; Serga, I. N.; Svinarenko, A. A.; Ternovsky, E. V.

    2017-10-01

    The consistent relativistic energy approach to the finite Fermi-systems (atoms and nuclei) in a strong realistic laser field is presented and applied to computing the multiphoton resonances parameters in some atoms and nuclei. The approach is based on the Gell-Mann and Low S-matrix formalism, multiphoton resonance lines moments technique and advanced Ivanov-Ivanova algorithm of calculating the Green’s function of the Dirac equation. The data for multiphoton resonance width and shift for the Cs atom and the 57Fe nucleus in dependence upon the laser intensity are listed.

  4. Computed tomography scan based prediction of the vulnerable carotid plaque

    DEFF Research Database (Denmark)

    Diab, Hadi Mahmoud Haider; Rasmussen, Lars Melholt; Duvnjak, Stevo

    2017-01-01

    BACKGROUND: Primary to validate a commercial semi-automated computed tomography angiography (CTA) -software for vulnerable plaque detection compared to histology of carotid endarterectomy (CEA) specimens and secondary validating calcifications scores by in vivo CTA with ex vivo non......-contrast enhanced computed tomography (NCCT). METHODS: From January 2014 to October 2016 53 patients were included retrospectively, using a cross-sectional design. All patients underwent both CTA and CEA. Sixteen patients had their CEA specimen NCCT scanned. The semi-automated CTA software analyzed carotid stenosis...

  5. Performance predictions for solar-chemical convertors by computer simulation

    Energy Technology Data Exchange (ETDEWEB)

    Luttmer, J.D.; Trachtenberg, I.

    1985-08-01

    A computer model which simulates the operation of Texas Instruments solar-chemical convertor (SCC) was developed. The model allows optimization of SCC processes, material, and configuration by facilitating decisions on tradeoffs among ease of manufacturing, power conversion efficiency, and cost effectiveness. The model includes various algorithms which define the electrical, electrochemical, and resistance parameters and which describ the operation of the discrete components of the SCC. Results of the model which depict the effect of material and geometric changes on various parameters are presented. The computer-calculated operation is compared with experimentall observed hydrobromic acid electrolysis rates.

  6. Development and external validation of a risk-prediction model to predict 5-year overall survival in advanced larynx cancer.

    Science.gov (United States)

    Petersen, Japke F; Stuiver, Martijn M; Timmermans, Adriana J; Chen, Amy; Zhang, Hongzhen; O'Neill, James P; Deady, Sandra; Vander Poorten, Vincent; Meulemans, Jeroen; Wennerberg, Johan; Skroder, Carl; Day, Andrew T; Koch, Wayne; van den Brekel, Michiel W M

    2018-05-01

    TNM-classification inadequately estimates patient-specific overall survival (OS). We aimed to improve this by developing a risk-prediction model for patients with advanced larynx cancer. Cohort study. We developed a risk prediction model to estimate the 5-year OS rate based on a cohort of 3,442 patients with T3T4N0N+M0 larynx cancer. The model was internally validated using bootstrapping samples and externally validated on patient data from five external centers (n = 770). The main outcome was performance of the model as tested by discrimination, calibration, and the ability to distinguish risk groups based on tertiles from the derivation dataset. The model performance was compared to a model based on T and N classification only. We included age, gender, T and N classification, and subsite as prognostic variables in the standard model. After external validation, the standard model had a significantly better fit than a model based on T and N classification alone (C statistic, 0.59 vs. 0.55, P statistic to 0.68. A risk prediction model for patients with advanced larynx cancer, consisting of readily available clinical variables, gives more accurate estimations of the estimated 5-year survival rate when compared to a model based on T and N classification alone. 2c. Laryngoscope, 128:1140-1145, 2018. © 2017 The American Laryngological, Rhinological and Otological Society, Inc.

  7. Coupling of EIT with computational lung modeling for predicting patient-specific ventilatory responses.

    Science.gov (United States)

    Roth, Christian J; Becher, Tobias; Frerichs, Inéz; Weiler, Norbert; Wall, Wolfgang A

    2017-04-01

    Providing optimal personalized mechanical ventilation for patients with acute or chronic respiratory failure is still a challenge within a clinical setting for each case anew. In this article, we integrate electrical impedance tomography (EIT) monitoring into a powerful patient-specific computational lung model to create an approach for personalizing protective ventilatory treatment. The underlying computational lung model is based on a single computed tomography scan and able to predict global airflow quantities, as well as local tissue aeration and strains for any ventilation maneuver. For validation, a novel "virtual EIT" module is added to our computational lung model, allowing to simulate EIT images based on the patient's thorax geometry and the results of our numerically predicted tissue aeration. Clinically measured EIT images are not used to calibrate the computational model. Thus they provide an independent method to validate the computational predictions at high temporal resolution. The performance of this coupling approach has been tested in an example patient with acute respiratory distress syndrome. The method shows good agreement between computationally predicted and clinically measured airflow data and EIT images. These results imply that the proposed framework can be used for numerical prediction of patient-specific responses to certain therapeutic measures before applying them to an actual patient. In the long run, definition of patient-specific optimal ventilation protocols might be assisted by computational modeling. NEW & NOTEWORTHY In this work, we present a patient-specific computational lung model that is able to predict global and local ventilatory quantities for a given patient and any selected ventilation protocol. For the first time, such a predictive lung model is equipped with a virtual electrical impedance tomography module allowing real-time validation of the computed results with the patient measurements. First promising results

  8. Predicting Lexical Proficiency in Language Learner Texts Using Computational Indices

    Science.gov (United States)

    Crossley, Scott A.; Salsbury, Tom; McNamara, Danielle S.; Jarvis, Scott

    2011-01-01

    The authors present a model of lexical proficiency based on lexical indices related to vocabulary size, depth of lexical knowledge, and accessibility to core lexical items. The lexical indices used in this study come from the computational tool Coh-Metrix and include word length scores, lexical diversity values, word frequency counts, hypernymy…

  9. Predictive Behavior of a Computational Foot/Ankle Model through Artificial Neural Networks

    Directory of Open Access Journals (Sweden)

    Ruchi D. Chande

    2017-01-01

    Full Text Available Computational models are useful tools to study the biomechanics of human joints. Their predictive performance is heavily dependent on bony anatomy and soft tissue properties. Imaging data provides anatomical requirements while approximate tissue properties are implemented from literature data, when available. We sought to improve the predictive capability of a computational foot/ankle model by optimizing its ligament stiffness inputs using feedforward and radial basis function neural networks. While the former demonstrated better performance than the latter per mean square error, both networks provided reasonable stiffness predictions for implementation into the computational model.

  10. Predictive Behavior of a Computational Foot/Ankle Model through Artificial Neural Networks.

    Science.gov (United States)

    Chande, Ruchi D; Hargraves, Rosalyn Hobson; Ortiz-Robinson, Norma; Wayne, Jennifer S

    2017-01-01

    Computational models are useful tools to study the biomechanics of human joints. Their predictive performance is heavily dependent on bony anatomy and soft tissue properties. Imaging data provides anatomical requirements while approximate tissue properties are implemented from literature data, when available. We sought to improve the predictive capability of a computational foot/ankle model by optimizing its ligament stiffness inputs using feedforward and radial basis function neural networks. While the former demonstrated better performance than the latter per mean square error, both networks provided reasonable stiffness predictions for implementation into the computational model.

  11. PREFACE: 16th International workshop on Advanced Computing and Analysis Techniques in physics research (ACAT2014)

    Science.gov (United States)

    Fiala, L.; Lokajicek, M.; Tumova, N.

    2015-05-01

    This volume of the IOP Conference Series is dedicated to scientific contributions presented at the 16th International Workshop on Advanced Computing and Analysis Techniques in Physics Research (ACAT 2014), this year the motto was ''bridging disciplines''. The conference took place on September 1-5, 2014, at the Faculty of Civil Engineering, Czech Technical University in Prague, Czech Republic. The 16th edition of ACAT explored the boundaries of computing system architectures, data analysis algorithmics, automatic calculations, and theoretical calculation technologies. It provided a forum for confronting and exchanging ideas among these fields, where new approaches in computing technologies for scientific research were explored and promoted. This year's edition of the workshop brought together over 140 participants from all over the world. The workshop's 16 invited speakers presented key topics on advanced computing and analysis techniques in physics. During the workshop, 60 talks and 40 posters were presented in three tracks: Computing Technology for Physics Research, Data Analysis - Algorithms and Tools, and Computations in Theoretical Physics: Techniques and Methods. The round table enabled discussions on expanding software, knowledge sharing and scientific collaboration in the respective areas. ACAT 2014 was generously sponsored by Western Digital, Brookhaven National Laboratory, Hewlett Packard, DataDirect Networks, M Computers, Bright Computing, Huawei and PDV-Systemhaus. Special appreciations go to the track liaisons Lorenzo Moneta, Axel Naumann and Grigory Rubtsov for their work on the scientific program and the publication preparation. ACAT's IACC would also like to express its gratitude to all referees for their work on making sure the contributions are published in the proceedings. Our thanks extend to the conference liaisons Andrei Kataev and Jerome Lauret who worked with the local contacts and made this conference possible as well as to the program

  12. Prediction of velocity and attitude of a yacht sailing upwind by computational fluid dynamics

    OpenAIRE

    Lee, Heebum; Park, Mi Yeon; Park, Sunho; Rhee, Shin Hyung

    2016-01-01

    One of the most important factors in sailing yacht design is accurate velocity prediction. Velocity prediction programs (VPP's) are widely used to predict velocity of sailing yachts. VPP's, which are primarily based on experimental data and experience of long years, however suffer limitations when applied in realistic conditions. Thus, in the present study, a high fidelity velocity prediction method using computational fluid dynamics (CFD) was proposed. Using the developed method, velocity an...

  13. DOE Advanced Scientific Computing Advisory Subcommittee (ASCAC) Report: Top Ten Exascale Research Challenges

    Energy Technology Data Exchange (ETDEWEB)

    Lucas, Robert [University of Southern California, Information Sciences Institute; Ang, James [Sandia National Laboratories; Bergman, Keren [Columbia University; Borkar, Shekhar [Intel; Carlson, William [Institute for Defense Analyses; Carrington, Laura [University of California, San Diego; Chiu, George [IBM; Colwell, Robert [DARPA; Dally, William [NVIDIA; Dongarra, Jack [University of Tennessee; Geist, Al [Oak Ridge National Laboratory; Haring, Rud [IBM; Hittinger, Jeffrey [Lawrence Livermore National Laboratory; Hoisie, Adolfy [Pacific Northwest National Laboratory; Klein, Dean Micron; Kogge, Peter [University of Notre Dame; Lethin, Richard [Reservoir Labs; Sarkar, Vivek [Rice University; Schreiber, Robert [Hewlett Packard; Shalf, John [Lawrence Berkeley National Laboratory; Sterling, Thomas [Indiana University; Stevens, Rick [Argonne National Laboratory; Bashor, Jon [Lawrence Berkeley National Laboratory; Brightwell, Ron [Sandia National Laboratories; Coteus, Paul [IBM; Debenedictus, Erik [Sandia National Laboratories; Hiller, Jon [Science and Technology Associates; Kim, K. H. [IBM; Langston, Harper [Reservoir Labs; Murphy, Richard Micron; Webster, Clayton [Oak Ridge National Laboratory; Wild, Stefan [Argonne National Laboratory; Grider, Gary [Los Alamos National Laboratory; Ross, Rob [Argonne National Laboratory; Leyffer, Sven [Argonne National Laboratory; Laros III, James [Sandia National Laboratories

    2014-02-10

    Exascale computing systems are essential for the scientific fields that will transform the 21st century global economy, including energy, biotechnology, nanotechnology, and materials science. Progress in these fields is predicated on the ability to perform advanced scientific and engineering simulations, and analyze the deluge of data. On July 29, 2013, ASCAC was charged by Patricia Dehmer, the Acting Director of the Office of Science, to assemble a subcommittee to provide advice on exascale computing. This subcommittee was directed to return a list of no more than ten technical approaches (hardware and software) that will enable the development of a system that achieves the Department's goals for exascale computing. Numerous reports over the past few years have documented the technical challenges and the non¬-viability of simply scaling existing computer designs to reach exascale. The technical challenges revolve around energy consumption, memory performance, resilience, extreme concurrency, and big data. Drawing from these reports and more recent experience, this ASCAC subcommittee has identified the top ten computing technology advancements that are critical to making a capable, economically viable, exascale system.

  14. Variability, trends, and predictability of seasonal sea ice retreat and advance in the Chukchi Sea

    Science.gov (United States)

    Serreze, Mark C.; Crawford, Alex D.; Stroeve, Julienne C.; Barrett, Andrew P.; Woodgate, Rebecca A.

    2016-10-01

    As assessed over the period 1979-2014, the date that sea ice retreats to the shelf break (150 m contour) of the Chukchi Sea has a linear trend of -0.7 days per year. The date of seasonal ice advance back to the shelf break has a steeper trend of about +1.5 days per year, together yielding an increase in the open water period of 80 days. Based on detrended time series, we ask how interannual variability in advance and retreat dates relate to various forcing parameters including radiation fluxes, temperature and wind (from numerical reanalyses), and the oceanic heat inflow through the Bering Strait (from in situ moorings). Of all variables considered, the retreat date is most strongly correlated (r ˜ 0.8) with the April through June Bering Strait heat inflow. After testing a suite of statistical linear models using several potential predictors, the best model for predicting the date of retreat includes only the April through June Bering Strait heat inflow, which explains 68% of retreat date variance. The best model predicting the ice advance date includes the July through September inflow and the date of retreat, explaining 67% of advance date variance. We address these relationships by discussing heat balances within the Chukchi Sea, and the hypothesis of oceanic heat transport triggering ocean heat uptake and ice-albedo feedback. Developing an operational prediction scheme for seasonal retreat and advance would require timely acquisition of Bering Strait heat inflow data. Predictability will likely always be limited by the chaotic nature of atmospheric circulation patterns.

  15. NUMERICAL COMPUTATION AND PREDICTION OF ELECTRICITY CONSUMPTION IN TOBACCO INDUSTRY

    Directory of Open Access Journals (Sweden)

    Mirjana Laković

    2017-12-01

    Full Text Available Electricity is a key energy source in each country and an important condition for economic development. It is necessary to use modern methods and tools to predict energy consumption for different types of systems and weather conditions. In every industrial plant, electricity consumption presents one of the greatest operating costs. Monitoring and forecasting of this parameter provide the opportunity to rationalize the use of electricity and thus significantly reduce the costs. The paper proposes the prediction of energy consumption by a new time-series model. This involves time series models using a set of previously collected data to predict the future load. The most commonly used linear time series models are the AR (Autoregressive Model, MA (Moving Average and ARMA (Autoregressive Moving Average Model. The AR model is used in this paper. Using the AR (Autoregressive Model model, the Monte Carlo simulation method is utilized for predicting and analyzing the energy consumption change in the considered tobacco industrial plant. One of the main parts of the AR model is a seasonal pattern that takes into account the climatic conditions for a given geographical area. This part of the model was delineated by the Fourier transform and was used with the aim of avoiding the model complexity. As an example, the numerical results were performed for tobacco production in one industrial plant. A probabilistic range of input values is used to determine the future probabilistic level of energy consumption.

  16. Continued rise of the cloud advances and trends in cloud computing

    CERN Document Server

    Mahmood, Zaigham

    2014-01-01

    Cloud computing is no-longer a novel paradigm, but instead an increasingly robust and established technology, yet new developments continue to emerge in this area. Continued Rise of the Cloud: Advances and Trends in Cloud Computing captures the state of the art in cloud technologies, infrastructures, and service delivery and deployment models. The book provides guidance and case studies on the development of cloud-based services and infrastructures from an international selection of expert researchers and practitioners. A careful analysis is provided of relevant theoretical frameworks, prac

  17. In silico assessment of the acute toxicity of chemicals: recent advances and new model for multitasking prediction of toxic effect.

    Science.gov (United States)

    Kleandrova, Valeria V; Luan, Feng; Speck-Planche, Alejandro; Cordeiro, M Natália D S

    2015-01-01

    The assessment of acute toxicity is one of the most important stages to ensure the safety of chemicals with potential applications in pharmaceutical sciences, biomedical research, or any other industrial branch. A huge and indiscriminate number of toxicity assays have been carried out on laboratory animals. In this sense, computational approaches involving models based on quantitative-structure activity/toxicity relationships (QSAR/QSTR) can help to rationalize time and financial costs. Here, we discuss the most significant advances in the last 6 years focused on the use of QSAR/QSTR models to predict acute toxicity of drugs/chemicals in laboratory animals, employing large and heterogeneous datasets. The advantages and drawbacks of the different QSAR/QSTR models are analyzed. As a contribution to the field, we introduce the first multitasking (mtk) QSTR model for simultaneous prediction of acute toxicity of compounds by considering different routes of administration, diverse breeds of laboratory animals, and the reliability of the experimental conditions. The mtk-QSTR model was based on artificial neural networks (ANN), allowing the classification of compounds as toxic or non-toxic. This model correctly classified more than 94% of the 1646 cases present in the whole dataset, and its applicability was demonstrated by performing predictions of different chemicals such as drugs, dietary supplements, and molecules which could serve as nanocarriers for drug delivery. The predictions given by the mtk-QSTR model are in very good agreement with the experimental results.

  18. Predicting survival time in noncurative patients with advanced cancer: a prospective study in China.

    Science.gov (United States)

    Cui, Jing; Zhou, Lingjun; Wee, B; Shen, Fengping; Ma, Xiuqiang; Zhao, Jijun

    2014-05-01

    Accurate prediction of prognosis for cancer patients is important for good clinical decision making in therapeutic and care strategies. The application of prognostic tools and indicators could improve prediction accuracy. This study aimed to develop a new prognostic scale to predict survival time of advanced cancer patients in China. We prospectively collected items that we anticipated might influence survival time of advanced cancer patients. Participants were recruited from 12 hospitals in Shanghai, China. We collected data including demographic information, clinical symptoms and signs, and biochemical test results. Log-rank tests, Cox regression, and linear regression were performed to develop a prognostic scale. Three hundred twenty patients with advanced cancer were recruited. Fourteen prognostic factors were included in the prognostic scale: Karnofsky Performance Scale (KPS) score, pain, ascites, hydrothorax, edema, delirium, cachexia, white blood cell (WBC) count, hemoglobin, sodium, total bilirubin, direct bilirubin, aspartate aminotransferase (AST), and alkaline phosphatase (ALP) values. The score was calculated by summing the partial scores, ranging from 0 to 30. When using the cutoff points of 7-day, 30-day, 90-day, and 180-day survival time, the scores were calculated as 12, 10, 8, and 6, respectively. We propose a new prognostic scale including KPS, pain, ascites, hydrothorax, edema, delirium, cachexia, WBC count, hemoglobin, sodium, total bilirubin, direct bilirubin, AST, and ALP values, which may help guide physicians in predicting the likely survival time of cancer patients more accurately. More studies are needed to validate this scale in the future.

  19. Echocardiography and risk prediction in advanced heart failure: incremental value over clinical markers.

    Science.gov (United States)

    Agha, Syed A; Kalogeropoulos, Andreas P; Shih, Jeffrey; Georgiopoulou, Vasiliki V; Giamouzis, Grigorios; Anarado, Perry; Mangalat, Deepa; Hussain, Imad; Book, Wendy; Laskar, Sonjoy; Smith, Andrew L; Martin, Randolph; Butler, Javed

    2009-09-01

    Incremental value of echocardiography over clinical parameters for outcome prediction in advanced heart failure (HF) is not well established. We evaluated 223 patients with advanced HF receiving optimal therapy (91.9% angiotensin-converting enzyme inhibitor/angiotensin receptor blocker, 92.8% beta-blockers, 71.8% biventricular pacemaker, and/or defibrillator use). The Seattle Heart Failure Model (SHFM) was used as the reference clinical risk prediction scheme. The incremental value of echocardiographic parameters for event prediction (death or urgent heart transplantation) was measured by the improvement in fit and discrimination achieved by addition of standard echocardiographic parameters to the SHFM. After a median follow-up of 2.4 years, there were 38 (17.0%) events (35 deaths; 3 urgent transplants). The SHFM had likelihood ratio (LR) chi(2) 32.0 and C statistic 0.756 for event prediction. Left ventricular end-systolic volume, stroke volume, and severe tricuspid regurgitation were independent echocardiographic predictors of events. The addition of these parameters to SHFM improved LR chi(2) to 72.0 and C statistic to 0.866 (P advanced HF.

  20. Diffusion Weighted MRI as a predictive tool for effect of radiotherapy in locally advanced cervical cancer

    DEFF Research Database (Denmark)

    Haack, Søren; Tanderup, Kari; Fokdal, Lars

    Diffusion weighted MRI has shown great potential in diagnostic cancer imaging and may also have value for monitoring tumor response during radiotherapy. Patients with advanced cervical cancer are treated with external beam radiotherapy followed by brachytherapy. This study evaluates the value of DW......-MRI for predicting outcome of patients with advanced cervical cancer at time of brachytherapy. Volume of hyper-intensity on highly diffusion sensitive images and resulting ADC value for treatment responders and non-responders is compared. The change of ADC and volume of hyper-intensity over time of BT is also...

  1. The European computer model for optronic system performance prediction (ECOMOS)

    Science.gov (United States)

    Keßler, Stefan; Bijl, Piet; Labarre, Luc; Repasi, Endre; Wittenstein, Wolfgang; Bürsing, Helge

    2017-10-01

    ECOMOS is a multinational effort within the framework of an EDA Project Arrangement. Its aim is to provide a generally accepted and harmonized European computer model for computing nominal Target Acquisition (TA) ranges of optronic imagers operating in the Visible or thermal Infrared (IR). The project involves close co-operation of defence and security industry and public research institutes from France, Germany, Italy, The Netherlands and Sweden. ECOMOS uses and combines well-accepted existing European tools to build up a strong competitive position. This includes two TA models: the analytical TRM4 model and the image-based TOD model. In addition, it uses the atmosphere model MATISSE. In this paper, the central idea of ECOMOS is exposed. The overall software structure and the underlying models are shown and elucidated. The status of the project development is given as well as a short discussion of validation tests and an outlook on the future potential of simulation for sensor assessment.

  2. Advances in mobile cloud computing and big data in the 5G era

    CERN Document Server

    Mastorakis, George; Dobre, Ciprian

    2017-01-01

    This book reports on the latest advances on the theories, practices, standards and strategies that are related to the modern technology paradigms, the Mobile Cloud computing (MCC) and Big Data, as the pillars and their association with the emerging 5G mobile networks. The book includes 15 rigorously refereed chapters written by leading international researchers, providing the readers with technical and scientific information about various aspects of Big Data and Mobile Cloud Computing, from basic concepts to advanced findings, reporting the state-of-the-art on Big Data management. It demonstrates and discusses methods and practices to improve multi-source Big Data manipulation techniques, as well as the integration of resources availability through the 3As (Anywhere, Anything, Anytime) paradigm, using the 5G access technologies.

  3. Approximator: Predicting Interruptibility in Software Development with Commodity Computers

    DEFF Research Database (Denmark)

    Tell, Paolo; Jalaliniya, Shahram; Andersen, Kristian S. M.

    2015-01-01

    Assessing the presence and availability of a remote colleague is key in coordination in global software development but is not easily done using existing computer-mediated channels. Previous research has shown that automated estimation of interruptibility is feasible and can achieve a precision....... These early but promising results represent a starting point for designing tools with support for interruptibility capable of improving distributed awareness and cooperation to be used in global software development....

  4. Embedded Platforms for Computer Vision-based Advanced Driver Assistance Systems: a Survey

    OpenAIRE

    Velez, Gorka; Otaegui, Oihana

    2015-01-01

    Computer Vision, either alone or combined with other technologies such as radar or Lidar, is one of the key technologies used in Advanced Driver Assistance Systems (ADAS). Its role understanding and analysing the driving scene is of great importance as it can be noted by the number of ADAS applications that use this technology. However, porting a vision algorithm to an embedded automotive system is still very challenging, as there must be a trade-off between several design requisites. Further...

  5. Recent Advances in Cardiac Computed Tomography: Dual Energy, Spectral and Molecular CT Imaging

    Science.gov (United States)

    Danad, Ibrahim; Fayad, Zahi A.; Willemink, Martin J.; Min, James K.

    2015-01-01

    Computed tomography (CT) evolved into a powerful diagnostic tool and it is impossible to imagine current clinical practice without CT imaging. Due to its widespread availability, ease of clinical application, superb sensitivity for detection of CAD, and non-invasive nature, CT has become a valuable tool within the armamentarium of the cardiologist. In the last few years, numerous technological advances in CT have occurred—including dual energy CT (DECT), spectral CT and CT-based molecular imaging. By harnessing the advances in technology, cardiac CT has advanced beyond the mere evaluation of coronary stenosis to an imaging modality tool that permits accurate plaque characterization, assessment of myocardial perfusion and even probing of molecular processes that are involved in coronary atherosclerosis. Novel innovations in CT contrast agents and pre-clinical spectral CT devices have paved the way for CT-based molecular imaging. PMID:26068288

  6. Development of a noise prediction model based on advanced fuzzy approaches in typical industrial workrooms.

    Science.gov (United States)

    Aliabadi, Mohsen; Golmohammadi, Rostam; Khotanlou, Hassan; Mansoorizadeh, Muharram; Salarpour, Amir

    2014-01-01

    Noise prediction is considered to be the best method for evaluating cost-preventative noise controls in industrial workrooms. One of the most important issues is the development of accurate models for analysis of the complex relationships among acoustic features affecting noise level in workrooms. In this study, advanced fuzzy approaches were employed to develop relatively accurate models for predicting noise in noisy industrial workrooms. The data were collected from 60 industrial embroidery workrooms in the Khorasan Province, East of Iran. The main acoustic and embroidery process features that influence the noise were used to develop prediction models using MATLAB software. Multiple regression technique was also employed and its results were compared with those of fuzzy approaches. Prediction errors of all prediction models based on fuzzy approaches were within the acceptable level (lower than one dB). However, Neuro-fuzzy model (RMSE=0.53dB and R2=0.88) could slightly improve the accuracy of noise prediction compared with generate fuzzy model. Moreover, fuzzy approaches provided more accurate predictions than did regression technique. The developed models based on fuzzy approaches as useful prediction tools give professionals the opportunity to have an optimum decision about the effectiveness of acoustic treatment scenarios in embroidery workrooms.

  7. Mould growth prediction by computational simulation on historic buildings

    OpenAIRE

    Krus, M.; Kilian, R.; Sedlbauer, K.

    2007-01-01

    Historical buildings are often renovated with a high expenditure of time and money without investigating and considering the causes of the damages. In many cases historic buildings can only be maintained by changing their usage. This change of use may influence the interior climate enormously. To assess the effect on the risk of mould growth on building parts or historic monuments a predictive model has been developed recently, describing the hygrothermal behaviour of the spore. It allows for...

  8. Research Institute for Advanced Computer Science: Annual Report October 1998 through September 1999

    Science.gov (United States)

    Leiner, Barry M.; Gross, Anthony R. (Technical Monitor)

    1999-01-01

    The Research Institute for Advanced Computer Science (RIACS) carries out basic research and technology development in computer science, in support of the National Aeronautics and Space Administration's missions. RIACS is located at the NASA Ames Research Center (ARC). It currently operates under a multiple year grant/cooperative agreement that began on October 1, 1997 and is up for renewal in the year 2002. ARC has been designated NASA's Center of Excellence in Information Technology. In this capacity, ARC is charged with the responsibility to build an Information Technology Research Program that is preeminent within NASA. RIACS serves as a bridge between NASA ARC and the academic community, and RIACS scientists and visitors work in close collaboration with NASA scientists. RIACS has the additional goal of broadening the base of researchers in these areas of importance to the nation's space and aeronautics enterprises. RIACS research focuses on the three cornerstones of information technology research necessary to meet the future challenges of NASA missions: (1) Automated Reasoning for Autonomous Systems. Techniques are being developed enabling spacecraft that will be self-guiding and self-correcting to the extent that they will require little or no human intervention. Such craft will be equipped to independently solve problems as they arise, and fulfill their missions with minimum direction from Earth. (2) Human-Centered Computing. Many NASA missions require synergy between humans and computers, with sophisticated computational aids amplifying human cognitive and perceptual abilities; (3) High Performance Computing and Networking Advances in the performance of computing and networking continue to have major impact on a variety of NASA endeavors, ranging from modeling and simulation to data analysis of large datasets to collaborative engineering, planning and execution. In addition, RIACS collaborates with NASA scientists to apply information technology research to

  9. Recent advances in 3D computed tomography techniques for simulation and navigation in hepatobiliary pancreatic surgery.

    Science.gov (United States)

    Uchida, Masafumi

    2014-04-01

    A few years ago it could take several hours to complete a 3D image using a 3D workstation. Thanks to advances in computer science, obtaining results of interest now requires only a few minutes. Many recent 3D workstations or multimedia computers are equipped with onboard 3D virtual patient modeling software, which enables patient-specific preoperative assessment and virtual planning, navigation, and tool positioning. Although medical 3D imaging can now be conducted using various modalities, including computed tomography (CT), magnetic resonance imaging (MRI), positron emission tomography (PET), and ultrasonography (US) among others, the highest quality images are obtained using CT data, and CT images are now the most commonly used source of data for 3D simulation and navigation image. If the 2D source image is bad, no amount of 3D image manipulation in software will provide a quality 3D image. In this exhibition, the recent advances in CT imaging technique and 3D visualization of the hepatobiliary and pancreatic abnormalities are featured, including scan and image reconstruction technique, contrast-enhanced techniques, new application of advanced CT scan techniques, and new virtual reality simulation and navigation imaging. © 2014 Japanese Society of Hepato-Biliary-Pancreatic Surgery.

  10. Global discriminative learning for higher-accuracy computational gene prediction.

    Directory of Open Access Journals (Sweden)

    Axel Bernal

    2007-03-01

    Full Text Available Most ab initio gene predictors use a probabilistic sequence model, typically a hidden Markov model, to combine separately trained models of genomic signals and content. By combining separate models of relevant genomic features, such gene predictors can exploit small training sets and incomplete annotations, and can be trained fairly efficiently. However, that type of piecewise training does not optimize prediction accuracy and has difficulty in accounting for statistical dependencies among different parts of the gene model. With genomic information being created at an ever-increasing rate, it is worth investigating alternative approaches in which many different types of genomic evidence, with complex statistical dependencies, can be integrated by discriminative learning to maximize annotation accuracy. Among discriminative learning methods, large-margin classifiers have become prominent because of the success of support vector machines (SVM in many classification tasks. We describe CRAIG, a new program for ab initio gene prediction based on a conditional random field model with semi-Markov structure that is trained with an online large-margin algorithm related to multiclass SVMs. Our experiments on benchmark vertebrate datasets and on regions from the ENCODE project show significant improvements in prediction accuracy over published gene predictors that use intrinsic features only, particularly at the gene level and on genes with long introns.

  11. Condition monitoring through advanced sensor and computational technology : final report (January 2002 to May 2005).

    Energy Technology Data Exchange (ETDEWEB)

    Kim, Jung-Taek (Korea Atomic Energy Research Institute, Daejon, Korea); Luk, Vincent K.

    2005-05-01

    The overall goal of this joint research project was to develop and demonstrate advanced sensors and computational technology for continuous monitoring of the condition of components, structures, and systems in advanced and next-generation nuclear power plants (NPPs). This project included investigating and adapting several advanced sensor technologies from Korean and US national laboratory research communities, some of which were developed and applied in non-nuclear industries. The project team investigated and developed sophisticated signal processing, noise reduction, and pattern recognition techniques and algorithms. The researchers installed sensors and conducted condition monitoring tests on two test loops, a check valve (an active component) and a piping elbow (a passive component), to demonstrate the feasibility of using advanced sensors and computational technology to achieve the project goal. Acoustic emission (AE) devices, optical fiber sensors, accelerometers, and ultrasonic transducers (UTs) were used to detect mechanical vibratory response of check valve and piping elbow in normal and degraded configurations. Chemical sensors were also installed to monitor the water chemistry in the piping elbow test loop. Analysis results of processed sensor data indicate that it is feasible to differentiate between the normal and degraded (with selected degradation mechanisms) configurations of these two components from the acquired sensor signals, but it is questionable that these methods can reliably identify the level and type of degradation. Additional research and development efforts are needed to refine the differentiation techniques and to reduce the level of uncertainties.

  12. Torque converter transient characteristics prediction using computational fluid dynamics

    International Nuclear Information System (INIS)

    Yamaguchi, T; Tanaka, K

    2012-01-01

    The objective of this research is to investigate the transient torque converter performance used in an automobile. A new technique in computational fluid dynamics is introduced, which includes the inertia of the turbine in a three dimensional simulation of the torque converter during a launch condition. The simulation results are compared to experimental test data with good agreement across the range of data. In addition, the simulated flow structure inside the torque converter is visualized and compared to results from a steady-state calculation.

  13. ADVANCING THE FUNDAMENTAL UNDERSTANDING AND SCALE-UP OF TRISO FUEL COATERS VIA ADVANCED MEASUREMENT AND COMPUTATIONAL TECHNIQUES

    Energy Technology Data Exchange (ETDEWEB)

    Biswas, Pratim; Al-Dahhan, Muthanna

    2012-11-01

    to advance the fundamental understanding of the hydrodynamics by systematically investigating the effect of design and operating variables, to evaluate the reported dimensionless groups as scaling factors, and to establish a reliable scale-up methodology for the TRISO fuel particle spouted bed coaters based on hydrodynamic similarity via advanced measurement and computational techniques. An additional objective is to develop an on-line non-invasive measurement technique based on gamma ray densitometry (i.e. Nuclear Gauge Densitometry) that can be installed and used for coater process monitoring to ensure proper performance and operation and to facilitate the developed scale-up methodology. To achieve the objectives set for the project, the work will use optical probes and gamma ray computed tomography (CT) (for the measurements of solids/voidage holdup cross-sectional distribution and radial profiles along the bed height, spouted diameter, and fountain height) and radioactive particle tracking (RPT) (for the measurements of the 3D solids flow field, velocity, turbulent parameters, circulation time, solids lagrangian trajectories, and many other of spouted bed related hydrodynamic parameters). In addition, gas dynamic measurement techniques and pressure transducers will be utilized to complement the obtained information. The measurements obtained by these techniques will be used as benchmark data to evaluate and validate the computational fluid dynamic (CFD) models (two fluid model or discrete particle model) and their closures. The validated CFD models and closures will be used to facilitate the developed methodology for scale-up, design and hydrodynamic similarity. Successful execution of this work and the proposed tasks will advance the fundamental understanding of the coater flow field and quantify it for proper and safe design, scale-up, and performance. Such achievements will overcome the barriers to AGR applications and will help assure that the US maintains

  14. Can clinical prediction tools predict the need for computed tomography in blunt abdominal? A systematic review.

    Science.gov (United States)

    Sharples, Alistair; Brohi, Karim

    2016-08-01

    Blunt abdominal trauma is a common reason for admission to the Emergency Department. Early detection of injuries is an important goal but is often not straightforward as physical examination alone is not a good predictor of serious injury. Computed tomography (CT) has become the primary method for assessing the stable trauma patient. It has high sensitivity and specificity but there remains concern regarding the long term consequences of high doses of radiation. Therefore an accurate and reliable method of assessing which patients are at higher risk of injury and hence require a CT would be clinically useful. We perform a systematic review to investigate the use of clinical prediction tools (CPTs) for the identification of abdominal injuries in patients suffering blunt trauma. A literature search was performed using Medline, Embase, The Cochrane Library and NHS Evidence up to August 2014. English language, prospective and retrospective studies were included if they derived, validated or assessed a CPT, aimed at identifying intra-abdominal injuries or the need for intervention to treat an intra-abdominal after blunt trauma. Methodological quality was assessed using a 14 point scale. Performance was assessed predominantly by sensitivity. Seven relevant studies were identified. All studies were derivative studies and no CPT was validated in a separate study. There were large differences in the study design, composition of the CPTs, the outcomes analysed and the methodological quality of the included studies. Sensitivities ranged from 86 to 100%. The highest performing CPT had a lower limit of the 95% CI of 95.8% and was of high methodological quality (11 of 14). Had this rule been applied to the population then 25.1% of patients would have avoided a CT scan. Seven CPTs were identified of varying designs and methodological quality. All demonstrate relatively high sensitivity with some achieving very high sensitivity whilst still managing to reduce the number of CTs

  15. Sexual selection predicts advancement of avian spring migration in response to climate change

    DEFF Research Database (Denmark)

    Spottiswoode, Claire N; Tøttrup, Anders P; Coppack, Timothy

    2006-01-01

    Global warming has led to earlier spring arrival of migratory birds, but the extent of this advancement varies greatly among species, and it remains uncertain to what degree these changes are phenotypically plastic responses or microevolutionary adaptations to changing environmental conditions. We...... suggest that sexual selection could help to understand this variation, since early spring arrival of males is favoured by female choice. Climate change could weaken the strength of natural selection opposing sexual selection for early migration, which would predict greatest advancement in species...... in the timing of first-arriving individuals, suggesting that selection has not only acted on protandrous males. These results suggest that sexual selection may have an impact on the responses of organisms to climate change, and knowledge of a species' mating system might help to inform attempts at predicting...

  16. Preservice Teachers' Computer Use in Single Computer Training Courses; Relationships and Predictions

    Science.gov (United States)

    Zogheib, Salah

    2015-01-01

    Single computer courses offered at colleges of education are expected to provide preservice teachers with the skills and expertise needed to adopt computer technology in their future classrooms. However, preservice teachers still find difficulty adopting such technology. This research paper investigated relationships among preservice teachers'…

  17. Advanced methods for the computation of particle beam transport and the computation of electromagnetic fields and beam-cavity interactions

    International Nuclear Information System (INIS)

    Dragt, A.J.; Gluckstern, R.L.

    1992-11-01

    The University of Maryland Dynamical Systems and Accelerator Theory Group carries out research in two broad areas: the computation of charged particle beam transport using Lie algebraic methods and advanced methods for the computation of electromagnetic fields and beam-cavity interactions. Important improvements in the state of the art are believed to be possible in both of these areas. In addition, applications of these methods are made to problems of current interest in accelerator physics including the theoretical performance of present and proposed high energy machines. The Lie algebraic method of computing and analyzing beam transport handles both linear and nonlinear beam elements. Tests show this method to be superior to the earlier matrix or numerical integration methods. It has wide application to many areas including accelerator physics, intense particle beams, ion microprobes, high resolution electron microscopy, and light optics. With regard to the area of electromagnetic fields and beam cavity interactions, work is carried out on the theory of beam breakup in single pulses. Work is also done on the analysis of the high frequency behavior of longitudinal and transverse coupling impedances, including the examination of methods which may be used to measure these impedances. Finally, work is performed on the electromagnetic analysis of coupled cavities and on the coupling of cavities to waveguides

  18. Advancing Predictive Hepatotoxicity at the Intersection of Experimental, in Silico, and Artificial Intelligence Technologies.

    Science.gov (United States)

    Fraser, Keith; Bruckner, Dylan M; Dordick, Jonathan S

    2018-06-18

    Adverse drug reactions, particularly those that result in drug-induced liver injury (DILI), are a major cause of drug failure in clinical trials and drug withdrawals. Hepatotoxicity-mediated drug attrition occurs despite substantial investments of time and money in developing cellular assays, animal models, and computational models to predict its occurrence in humans. Underperformance in predicting hepatotoxicity associated with drugs and drug candidates has been attributed to existing gaps in our understanding of the mechanisms involved in driving hepatic injury after these compounds perfuse and are metabolized by the liver. Herein we assess in vitro, in vivo (animal), and in silico strategies used to develop predictive DILI models. We address the effectiveness of several two- and three-dimensional in vitro cellular methods that are frequently employed in hepatotoxicity screens and how they can be used to predict DILI in humans. We also explore how humanized animal models can recapitulate human drug metabolic profiles and associated liver injury. Finally, we highlight the maturation of computational methods for predicting hepatotoxicity, the untapped potential of artificial intelligence for improving in silico DILI screens, and how knowledge acquired from these predictions can shape the refinement of experimental methods.

  19. PREFACE: 14th International Workshop on Advanced Computing and Analysis Techniques in Physics Research (ACAT 2011)

    Science.gov (United States)

    Teodorescu, Liliana; Britton, David; Glover, Nigel; Heinrich, Gudrun; Lauret, Jérôme; Naumann, Axel; Speer, Thomas; Teixeira-Dias, Pedro

    2012-06-01

    ACAT2011 This volume of Journal of Physics: Conference Series is dedicated to scientific contributions presented at the 14th International Workshop on Advanced Computing and Analysis Techniques in Physics Research (ACAT 2011) which took place on 5-7 September 2011 at Brunel University, UK. The workshop series, which began in 1990 in Lyon, France, brings together computer science researchers and practitioners, and researchers from particle physics and related fields in order to explore and confront the boundaries of computing and of automatic data analysis and theoretical calculation techniques. It is a forum for the exchange of ideas among the fields, exploring and promoting cutting-edge computing, data analysis and theoretical calculation techniques in fundamental physics research. This year's edition of the workshop brought together over 100 participants from all over the world. 14 invited speakers presented key topics on computing ecosystems, cloud computing, multivariate data analysis, symbolic and automatic theoretical calculations as well as computing and data analysis challenges in astrophysics, bioinformatics and musicology. Over 80 other talks and posters presented state-of-the art developments in the areas of the workshop's three tracks: Computing Technologies, Data Analysis Algorithms and Tools, and Computational Techniques in Theoretical Physics. Panel and round table discussions on data management and multivariate data analysis uncovered new ideas and collaboration opportunities in the respective areas. This edition of ACAT was generously sponsored by the Science and Technology Facility Council (STFC), the Institute for Particle Physics Phenomenology (IPPP) at Durham University, Brookhaven National Laboratory in the USA and Dell. We would like to thank all the participants of the workshop for the high level of their scientific contributions and for the enthusiastic participation in all its activities which were, ultimately, the key factors in the

  20. PREFACE: 15th International Workshop on Advanced Computing and Analysis Techniques in Physics Research (ACAT2013)

    Science.gov (United States)

    Wang, Jianxiong

    2014-06-01

    This volume of Journal of Physics: Conference Series is dedicated to scientific contributions presented at the 15th International Workshop on Advanced Computing and Analysis Techniques in Physics Research (ACAT 2013) which took place on 16-21 May 2013 at the Institute of High Energy Physics, Chinese Academy of Sciences, Beijing, China. The workshop series brings together computer science researchers and practitioners, and researchers from particle physics and related fields to explore and confront the boundaries of computing and of automatic data analysis and theoretical calculation techniques. This year's edition of the workshop brought together over 120 participants from all over the world. 18 invited speakers presented key topics on the universe in computer, Computing in Earth Sciences, multivariate data analysis, automated computation in Quantum Field Theory as well as computing and data analysis challenges in many fields. Over 70 other talks and posters presented state-of-the-art developments in the areas of the workshop's three tracks: Computing Technologies, Data Analysis Algorithms and Tools, and Computational Techniques in Theoretical Physics. The round table discussions on open-source, knowledge sharing and scientific collaboration stimulate us to think over the issue in the respective areas. ACAT 2013 was generously sponsored by the Chinese Academy of Sciences (CAS), National Natural Science Foundation of China (NFSC), Brookhaven National Laboratory in the USA (BNL), Peking University (PKU), Theoretical Physics Cernter for Science facilities of CAS (TPCSF-CAS) and Sugon. We would like to thank all the participants for their scientific contributions and for the en- thusiastic participation in all its activities of the workshop. Further information on ACAT 2013 can be found at http://acat2013.ihep.ac.cn. Professor Jianxiong Wang Institute of High Energy Physics Chinese Academy of Science Details of committees and sponsors are available in the PDF

  1. The fitness landscape of HIV-1 gag: advanced modeling approaches and validation of model predictions by in vitro testing.

    Directory of Open Access Journals (Sweden)

    Jaclyn K Mann

    2014-08-01

    Full Text Available Viral immune evasion by sequence variation is a major hindrance to HIV-1 vaccine design. To address this challenge, our group has developed a computational model, rooted in physics, that aims to predict the fitness landscape of HIV-1 proteins in order to design vaccine immunogens that lead to impaired viral fitness, thus blocking viable escape routes. Here, we advance the computational models to address previous limitations, and directly test model predictions against in vitro fitness measurements of HIV-1 strains containing multiple Gag mutations. We incorporated regularization into the model fitting procedure to address finite sampling. Further, we developed a model that accounts for the specific identity of mutant amino acids (Potts model, generalizing our previous approach (Ising model that is unable to distinguish between different mutant amino acids. Gag mutation combinations (17 pairs, 1 triple and 25 single mutations within these predicted to be either harmful to HIV-1 viability or fitness-neutral were introduced into HIV-1 NL4-3 by site-directed mutagenesis and replication capacities of these mutants were assayed in vitro. The predicted and measured fitness of the corresponding mutants for the original Ising model (r = -0.74, p = 3.6×10-6 are strongly correlated, and this was further strengthened in the regularized Ising model (r = -0.83, p = 3.7×10-12. Performance of the Potts model (r = -0.73, p = 9.7×10-9 was similar to that of the Ising model, indicating that the binary approximation is sufficient for capturing fitness effects of common mutants at sites of low amino acid diversity. However, we show that the Potts model is expected to improve predictive power for more variable proteins. Overall, our results support the ability of the computational models to robustly predict the relative fitness of mutant viral strains, and indicate the potential value of this approach for understanding viral immune evasion

  2. A systematic investigation of computation models for predicting Adverse Drug Reactions (ADRs.

    Directory of Open Access Journals (Sweden)

    Qifan Kuang

    Full Text Available Early and accurate identification of adverse drug reactions (ADRs is critically important for drug development and clinical safety. Computer-aided prediction of ADRs has attracted increasing attention in recent years, and many computational models have been proposed. However, because of the lack of systematic analysis and comparison of the different computational models, there remain limitations in designing more effective algorithms and selecting more useful features. There is therefore an urgent need to review and analyze previous computation models to obtain general conclusions that can provide useful guidance to construct more effective computational models to predict ADRs.In the current study, the main work is to compare and analyze the performance of existing computational methods to predict ADRs, by implementing and evaluating additional algorithms that have been earlier used for predicting drug targets. Our results indicated that topological and intrinsic features were complementary to an extent and the Jaccard coefficient had an important and general effect on the prediction of drug-ADR associations. By comparing the structure of each algorithm, final formulas of these algorithms were all converted to linear model in form, based on this finding we propose a new algorithm called the general weighted profile method and it yielded the best overall performance among the algorithms investigated in this paper.Several meaningful conclusions and useful findings regarding the prediction of ADRs are provided for selecting optimal features and algorithms.

  3. A systematic investigation of computation models for predicting Adverse Drug Reactions (ADRs).

    Science.gov (United States)

    Kuang, Qifan; Wang, MinQi; Li, Rong; Dong, YongCheng; Li, Yizhou; Li, Menglong

    2014-01-01

    Early and accurate identification of adverse drug reactions (ADRs) is critically important for drug development and clinical safety. Computer-aided prediction of ADRs has attracted increasing attention in recent years, and many computational models have been proposed. However, because of the lack of systematic analysis and comparison of the different computational models, there remain limitations in designing more effective algorithms and selecting more useful features. There is therefore an urgent need to review and analyze previous computation models to obtain general conclusions that can provide useful guidance to construct more effective computational models to predict ADRs. In the current study, the main work is to compare and analyze the performance of existing computational methods to predict ADRs, by implementing and evaluating additional algorithms that have been earlier used for predicting drug targets. Our results indicated that topological and intrinsic features were complementary to an extent and the Jaccard coefficient had an important and general effect on the prediction of drug-ADR associations. By comparing the structure of each algorithm, final formulas of these algorithms were all converted to linear model in form, based on this finding we propose a new algorithm called the general weighted profile method and it yielded the best overall performance among the algorithms investigated in this paper. Several meaningful conclusions and useful findings regarding the prediction of ADRs are provided for selecting optimal features and algorithms.

  4. Brain systems for probabilistic and dynamic prediction: computational specificity and integration.

    Directory of Open Access Journals (Sweden)

    Jill X O'Reilly

    2013-09-01

    Full Text Available A computational approach to functional specialization suggests that brain systems can be characterized in terms of the types of computations they perform, rather than their sensory or behavioral domains. We contrasted the neural systems associated with two computationally distinct forms of predictive model: a reinforcement-learning model of the environment obtained through experience with discrete events, and continuous dynamic forward modeling. By manipulating the precision with which each type of prediction could be used, we caused participants to shift computational strategies within a single spatial prediction task. Hence (using fMRI we showed that activity in two brain systems (typically associated with reward learning and motor control could be dissociated in terms of the forms of computations that were performed there, even when both systems were used to make parallel predictions of the same event. A region in parietal cortex, which was sensitive to the divergence between the predictions of the models and anatomically connected to both computational networks, is proposed to mediate integration of the two predictive modes to produce a single behavioral output.

  5. Do plasma concentrations of apelin predict prognosis in patients with advanced heart failure?

    Science.gov (United States)

    Dalzell, Jonathan R; Jackson, Colette E; Chong, Kwok S; McDonagh, Theresa A; Gardner, Roy S

    2014-01-01

    Apelin is an endogenous vasodilator and inotrope, plasma concentrations of which are reduced in advanced heart failure (HF). We determined the prognostic significance of plasma concentrations of apelin in advanced HF. Plasma concentrations of apelin were measured in 182 patients with advanced HF secondary to left ventricular systolic dysfunction. The predictive value of apelin for the primary end point of all-cause mortality was assessed over a median follow-up period of 544 (IQR: 196-923) days. In total, 30 patients (17%) reached the primary end point. Of those patients with a plasma apelin concentration above the median, 14 (16%) reached the primary end point compared with 16 (17%) of those with plasma apelin levels below the median (p = NS). NT-proBNP was the most powerful prognostic marker in this population (log rank statistic: 10.37; p = 0.001). Plasma apelin concentrations do not predict medium to long-term prognosis in patients with advanced HF secondary to left ventricular systolic dysfunction.

  6. Computational intelligence in wireless sensor networks recent advances and future challenges

    CERN Document Server

    Falcon, Rafael; Koeppen, Mario

    2017-01-01

    This book emphasizes the increasingly important role that Computational Intelligence (CI) methods are playing in solving a myriad of entangled Wireless Sensor Networks (WSN) related problems. The book serves as a guide for surveying several state-of-the-art WSN scenarios in which CI approaches have been employed. The reader finds in this book how CI has contributed to solve a wide range of challenging problems, ranging from balancing the cost and accuracy of heterogeneous sensor deployments to recovering from real-time sensor failures to detecting attacks launched by malicious sensor nodes and enacting CI-based security schemes. Network managers, industry experts, academicians and practitioners alike (mostly in computer engineering, computer science or applied mathematics) benefit from the spectrum of successful applications reported in this book. Senior undergraduate or graduate students may discover in this book some problems well suited for their own research endeavors. USP: Presents recent advances and fu...

  7. Recent advances in computational methods and clinical applications for spine imaging

    CERN Document Server

    Glocker, Ben; Klinder, Tobias; Li, Shuo

    2015-01-01

    This book contains the full papers presented at the MICCAI 2014 workshop on Computational Methods and Clinical Applications for Spine Imaging. The workshop brought together scientists and clinicians in the field of computational spine imaging. The chapters included in this book present and discuss the new advances and challenges in these fields, using several methods and techniques in order to address more efficiently different and timely applications involving signal and image acquisition, image processing and analysis, image segmentation, image registration and fusion, computer simulation, image based modeling, simulation and surgical planning, image guided robot assisted surgical and image based diagnosis. The book also includes papers and reports from the first challenge on vertebra segmentation held at the workshop.

  8. NATO Advanced Research Workshop on Exploiting Mental Imagery with Computers in Mathematics Education

    CERN Document Server

    Mason, John

    1995-01-01

    The advent of fast and sophisticated computer graphics has brought dynamic and interactive images under the control of professional mathematicians and mathematics teachers. This volume in the NATO Special Programme on Advanced Educational Technology takes a comprehensive and critical look at how the computer can support the use of visual images in mathematical problem solving. The contributions are written by researchers and teachers from a variety of disciplines including computer science, mathematics, mathematics education, psychology, and design. Some focus on the use of external visual images and others on the development of individual mental imagery. The book is the first collected volume in a research area that is developing rapidly, and the authors pose some challenging new questions.

  9. 17th International Workshop on Advanced Computing and Analysis Techniques in Physics Research (ACAT 2016)

    International Nuclear Information System (INIS)

    2016-01-01

    Preface The 2016 version of the International Workshop on Advanced Computing and Analysis Techniques in Physics Research took place on January 18-22, 2016, at the Universidad Técnica Federico Santa Maria -UTFSM- in Valparaiso, Chile. The present volume of IOP Conference Series is devoted to the selected scientific contributions presented at the workshop. In order to guarantee the scientific quality of the Proceedings all papers were thoroughly peer-reviewed by an ad-hoc Editorial Committee with the help of many careful reviewers. The ACAT Workshop series has a long tradition starting in 1990 (Lyon, France), and takes place in intervals of a year and a half. Formerly these workshops were known under the name AIHENP (Artificial Intelligence for High Energy and Nuclear Physics). Each edition brings together experimental and theoretical physicists and computer scientists/experts, from particle and nuclear physics, astronomy and astrophysics in order to exchange knowledge and experience in computing and data analysis in physics. Three tracks cover the main topics: Computing technology: languages and system architectures. Data analysis: algorithms and tools. Theoretical Physics: techniques and methods. Although most contributions and discussions are related to particle physics and computing, other fields like condensed matter physics, earth physics, biophysics are often addressed in the hope to share our approaches and visions. It created a forum for exchanging ideas among fields, exploring and promoting cutting-edge computing technologies and debating hot topics. (paper)

  10. Advanced scientific computational methods and their applications of nuclear technologies. (1) Overview of scientific computational methods, introduction of continuum simulation methods and their applications (1)

    International Nuclear Information System (INIS)

    Oka, Yoshiaki; Okuda, Hiroshi

    2006-01-01

    Scientific computational methods have advanced remarkably with the progress of nuclear development. They have played the role of weft connecting each realm of nuclear engineering and then an introductory course of advanced scientific computational methods and their applications to nuclear technologies were prepared in serial form. This is the first issue showing their overview and introduction of continuum simulation methods. Finite element method as their applications is also reviewed. (T. Tanaka)

  11. A computational approach to mechanistic and predictive toxicology of pesticides

    DEFF Research Database (Denmark)

    Kongsbak, Kristine Grønning; Vinggaard, Anne Marie; Hadrup, Niels

    2014-01-01

    Emerging challenges of managing and interpreting large amounts of complex biological data have given rise to the growing field of computational biology. We investigated the applicability of an integrated systems toxicology approach on five selected pesticides to get an overview of their modes...... of action in humans, to group them according to their modes of action, and to hypothesize on their potential effects on human health. We extracted human proteins associated to prochloraz, tebuconazole, epoxiconazole, procymidone, and mancozeb and enriched each protein set by using a high confidence human......, and procymidone exerted their effects mainly via interference with steroidogenesis and nuclear receptors. Prochloraz was associated to a large number of human diseases, and together with tebuconazole showed several significant associations to Testicular Dysgenesis Syndrome. Mancozeb showed a differential mode...

  12. Nanotoxicity prediction using computational modelling - review and future directions

    Science.gov (United States)

    Saini, Bhavna; Srivastava, Sumit

    2018-04-01

    Nanomaterials has stimulated various outlooks for future in a number of industries and scientific ventures. A number of applications such as cosmetics, medicines, and electronics are employing nanomaterials due to their various compelling properties. The unending growth of nanomaterials usage in our daily life has escalated the health and environmental risks. Early nanotoxicity recognition is a big challenge. Various researches are going on in the field of nanotoxicity, which comprised of several problems such as inadequacy of proper datasets, lack of appropriate rules and characterization of nanomaterials. Computational modelling would be beneficial asset for nanomaterials researchers because it can foresee the toxicity, rest on previous experimental data. In this study, we have reviewed sufficient work demonstrating a proper pathway to proceed with QSAR analysis of Nanomaterials for toxicity modelling. The paper aims at providing comprehensive insight of Nano QSAR, various theories, tools and approaches used, along with an outline for future research directions to work on.

  13. Prediction of the behavior of pedestrian bridges using computer models

    Directory of Open Access Journals (Sweden)

    Jonathan José Cala Monroy

    2017-07-01

    Full Text Available Introduction: The present article is aimed to present a brief introduction of the issues related to the low-frequency vibrations, by indicating human walking as its relevant source which affecting structures of the footbridges and is turned into inconveniences to the pedestrian traffic. Objective: The main objective of this research paper is to explain the most common methods used by engineers for the evaluation of the vibrations and their effects as well as their limitations, furthermore a computer modeling technique was developed in order to approach it to the reality of the phenomenon of vibrations in pedestrian bridges. Methodology: The present work was divided into main phases: The first phase was a conceptual bibliographical review of the subject of floor vibrations by focusing on the use of the Design Guide No. 11 of the American Institute of Steel Constructions, with regard to the second phase, it had to do with the developing of a computer model which included a definition of variables, the elaboration of a dynamic model of the structure, the calibration of the model, the evaluation of the parameters under study and the analysis of results and conclusions. Results: Consequently, and according to the preliminary stages, the results of the acceleration were obtained to different frequencies and to different degrees of damping by observing that the chosen sample was potentially susceptible between four and eight Hz ranges, hence when resonances took place the mentioned structure presented a peak acceleration above the threshold recommended by human beings comfort related to pedestrian bridges. Conclusions: To conclude it can be said that through the appropriate modeling techniques and finite elements convenient and reliable results should be accomplished that leading the design process of structures as pedestrian bridges.

  14. Probable mode prediction for H.264 advanced video coding P slices using removable SKIP mode distortion estimation

    Science.gov (United States)

    You, Jongmin; Jeong, Jechang

    2010-02-01

    The H.264/AVC (advanced video coding) is used in a wide variety of applications including digital broadcasting and mobile applications, because of its high compression efficiency. The variable block mode scheme in H.264/AVC contributes much to its high compression efficiency but causes a selection problem. In general, rate-distortion optimization (RDO) is the optimal mode selection strategy, but it is computationally intensive. For this reason, the H.264/AVC encoder requires a fast mode selection algorithm for use in applications that require low-power and real-time processing. A probable mode prediction algorithm for the H.264/AVC encoder is proposed. To reduce the computational complexity of RDO, the proposed method selects probable modes among all allowed block modes using removable SKIP mode distortion estimation. Removable SKIP mode distortion is used to estimate whether or not a further divided block mode is appropriate for a macroblock. It is calculated using a no-motion reference block with a few computations. Then the proposed method reduces complexity by performing the RDO process only for probable modes. Experimental results show that the proposed algorithm can reduce encoding time by an average of 55.22% without significant visual quality degradation and increased bit rate.

  15. Computability, Gödel's incompleteness theorem, and an inherent limit on the predictability of evolution.

    Science.gov (United States)

    Day, Troy

    2012-04-07

    The process of evolutionary diversification unfolds in a vast genotypic space of potential outcomes. During the past century, there have been remarkable advances in the development of theory for this diversification, and the theory's success rests, in part, on the scope of its applicability. A great deal of this theory focuses on a relatively small subset of the space of potential genotypes, chosen largely based on historical or contemporary patterns, and then predicts the evolutionary dynamics within this pre-defined set. To what extent can such an approach be pushed to a broader perspective that accounts for the potential open-endedness of evolutionary diversification? There have been a number of significant theoretical developments along these lines but the question of how far such theory can be pushed has not been addressed. Here a theorem is proven demonstrating that, because of the digital nature of inheritance, there are inherent limits on the kinds of questions that can be answered using such an approach. In particular, even in extremely simple evolutionary systems, a complete theory accounting for the potential open-endedness of evolution is unattainable unless evolution is progressive. The theorem is closely related to Gödel's incompleteness theorem, and to the halting problem from computability theory.

  16. Computational Model-Based Prediction of Human Episodic Memory Performance Based on Eye Movements

    Science.gov (United States)

    Sato, Naoyuki; Yamaguchi, Yoko

    Subjects' episodic memory performance is not simply reflected by eye movements. We use a ‘theta phase coding’ model of the hippocampus to predict subjects' memory performance from their eye movements. Results demonstrate the ability of the model to predict subjects' memory performance. These studies provide a novel approach to computational modeling in the human-machine interface.

  17. Prediction of velocity and attitude of a yacht sailing upwind by computational fluid dynamics

    Directory of Open Access Journals (Sweden)

    Heebum Lee

    2016-01-01

    Full Text Available One of the most important factors in sailing yacht design is accurate velocity prediction. Velocity prediction programs (VPP's are widely used to predict velocity of sailing yachts. VPP's, which are primarily based on experimental data and experience of long years, however suffer limitations when applied in realistic conditions. Thus, in the present study, a high fidelity velocity prediction method using computational fluid dynamics (CFD was proposed. Using the developed method, velocity and attitude of a 30 feet sloop yacht, which was developed by Korea Research Institute of Ship and Ocean (KRISO and termed KORDY30, were predicted in upwind sailing condition.

  18. CE-ACCE: The Cloud Enabled Advanced sCience Compute Environment

    Science.gov (United States)

    Cinquini, L.; Freeborn, D. J.; Hardman, S. H.; Wong, C.

    2017-12-01

    Traditionally, Earth Science data from NASA remote sensing instruments has been processed by building custom data processing pipelines (often based on a common workflow engine or framework) which are typically deployed and run on an internal cluster of computing resources. This approach has some intrinsic limitations: it requires each mission to develop and deploy a custom software package on top of the adopted framework; it makes use of dedicated hardware, network and storage resources, which must be specifically purchased, maintained and re-purposed at mission completion; and computing services cannot be scaled on demand beyond the capability of the available servers.More recently, the rise of Cloud computing, coupled with other advances in containerization technology (most prominently, Docker) and micro-services architecture, has enabled a new paradigm, whereby space mission data can be processed through standard system architectures, which can be seamlessly deployed and scaled on demand on either on-premise clusters, or commercial Cloud providers. In this talk, we will present one such architecture named CE-ACCE ("Cloud Enabled Advanced sCience Compute Environment"), which we have been developing at the NASA Jet Propulsion Laboratory over the past year. CE-ACCE is based on the Apache OODT ("Object Oriented Data Technology") suite of services for full data lifecycle management, which are turned into a composable array of Docker images, and complemented by a plug-in model for mission-specific customization. We have applied this infrastructure to both flying and upcoming NASA missions, such as ECOSTRESS and SMAP, and demonstrated deployment on the Amazon Cloud, either using simple EC2 instances, or advanced AWS services such as Amazon Lambda and ECS (EC2 Container Services).

  19. Serotonergic modulation of spatial working memory: predictions from a computational network model

    Directory of Open Access Journals (Sweden)

    Maria eCano-Colino

    2013-09-01

    Full Text Available Serotonin (5-HT receptors of types 1A and 2A are massively expressed in prefrontal cortex (PFC neurons, an area associated with cognitive function. Hence, 5-HT could be effective in modulating prefrontal-dependent cognitive functions, such as spatial working memory (SWM. However, a direct association between 5-HT and SWM has proved elusive in psycho-pharmacological studies. Recently, a computational network model of the PFC microcircuit was used to explore the relationship between 5‑HT and SWM (Cano-Colino et al. 2013. This study found that both excessive and insufficient 5-HT levels lead to impaired SWM performance in the network, and it concluded that analyzing behavioral responses based on confidence reports could facilitate the experimental identification of SWM behavioral effects of 5‑HT neuromodulation. Such analyses may have confounds based on our limited understanding of metacognitive processes. Here, we extend these results by deriving three additional predictions from the model that do not rely on confidence reports. Firstly, only excessive levels of 5-HT should result in SWM deficits that increase with delay duration. Secondly, excessive 5-HT baseline concentration makes the network vulnerable to distractors at distances that were robust to distraction in control conditions, while the network still ignores distractors efficiently for low 5‑HT levels that impair SWM. Finally, 5-HT modulates neuronal memory fields in neurophysiological experiments: Neurons should be better tuned to the cued stimulus than to the behavioral report for excessive 5-HT levels, while the reverse should happen for low 5-HT concentrations. In all our simulations agonists of 5-HT1A receptors and antagonists of 5-HT2A receptors produced behavioral and physiological effects in line with global 5-HT level increases. Our model makes specific predictions to be tested experimentally and advance our understanding of the neural basis of SWM and its neuromodulation

  20. Prediction of intestinal absorption and blood-brain barrier penetration by computational methods.

    Science.gov (United States)

    Clark, D E

    2001-09-01

    This review surveys the computational methods that have been developed with the aim of identifying drug candidates likely to fail later on the road to market. The specifications for such computational methods are outlined, including factors such as speed, interpretability, robustness and accuracy. Then, computational filters aimed at predicting "drug-likeness" in a general sense are discussed before methods for the prediction of more specific properties--intestinal absorption and blood-brain barrier penetration--are reviewed. Directions for future research are discussed and, in concluding, the impact of these methods on the drug discovery process, both now and in the future, is briefly considered.

  1. Can advanced paramedics in the field diagnose patients and predict hospital admission?

    LENUS (Irish Health Repository)

    Cummins, Niamh Maria

    2013-02-13

    BACKGROUND: Accurate patient diagnosis in the prehospital environment is essential to initiate suitable care pathways. The advanced paramedic (AP) is a relatively recent role in Ireland, and refers to a prehospital practitioner with advanced life-support skills and training. OBJECTIVES: The objectives of this study were to compare the diagnostic decisions of APs with emergency medicine (EM) physicians, and to investigate if APs, as currently trained, can predict the requirement for hospital admission. METHODS: A prospective study was initiated, whereby each emergency ambulance call received via the statutory 999 system was recorded by the attending AP. The AP was asked to provide a clinical diagnosis for each patient, and to predict if hospital admission was required. The data was then cross-referenced with the working diagnosis of the receiving emergency physician and the hospital admission records. RESULTS: A total of 17 APs participated in the study, and 1369 emergency calls were recorded over a 6-month period. Cases where a general practitioner attended the scene were excluded from the concordance analysis. Concordance with the receiving emergency physician represents 70% (525\\/748) for all cases of AP diagnosis, and is mirrored with 70% (604\\/859) correct hospital admission predictions. CONCLUSIONS: AP diagnosis and admission prediction for emergency calls is similar to other emergency medical services systems despite the relative recency of the AP programme in Ireland. Recognition of non-concordance case types may identify priorities for AP education, and drive future AP practice in areas such as \\'treat and refer\\'.

  2. Advanced Computational Thermal Fluid Physics (CTFP) and Its Assessment for Light Water Reactors and Supercritical Reactors

    International Nuclear Information System (INIS)

    D.M. McEligot; K. G. Condie; G. E. McCreery; H. M. McIlroy; R. J. Pink; L.E. Hochreiter; J.D. Jackson; R.H. Pletcher; B.L. Smith; P. Vukoslavcevic; J.M. Wallace; J.Y. Yoo; J.S. Lee; S.T. Ro; S.O. Park

    2005-01-01

    Background: The ultimate goal of the study is the improvement of predictive methods for safety analyses and design of Generation IV reactor systems such as supercritical water reactors (SCWR) for higher efficiency, improved performance and operation, design simplification, enhanced safety and reduced waste and cost. The objective of this Korean/US/laboratory/university collaboration of coupled fundamental computational and experimental studies is to develop the supporting knowledge needed for improved predictive techniques for use in the technology development of Generation IV reactor concepts and their passive safety systems. The present study emphasizes SCWR concepts in the Generation IV program

  3. Advanced Computational Thermal Fluid Physics (CTFP) and Its Assessment for Light Water Reactors and Supercritical Reactors

    Energy Technology Data Exchange (ETDEWEB)

    D.M. McEligot; K. G. Condie; G. E. McCreery; H. M. McIlroy; R. J. Pink; L.E. Hochreiter; J.D. Jackson; R.H. Pletcher; B.L. Smith; P. Vukoslavcevic; J.M. Wallace; J.Y. Yoo; J.S. Lee; S.T. Ro; S.O. Park

    2005-10-01

    Background: The ultimate goal of the study is the improvement of predictive methods for safety analyses and design of Generation IV reactor systems such as supercritical water reactors (SCWR) for higher efficiency, improved performance and operation, design simplification, enhanced safety and reduced waste and cost. The objective of this Korean / US / laboratory / university collaboration of coupled fundamental computational and experimental studies is to develop the supporting knowledge needed for improved predictive techniques for use in the technology development of Generation IV reactor concepts and their passive safety systems. The present study emphasizes SCWR concepts in the Generation IV program.

  4. Computer prediction of subsurface radionuclide transport: an adaptive numerical method

    International Nuclear Information System (INIS)

    Neuman, S.P.

    1983-01-01

    Radionuclide transport in the subsurface is often modeled with the aid of the advection-dispersion equation. A review of existing computer methods for the solution of this equation shows that there is need for improvement. To answer this need, a new adaptive numerical method is proposed based on an Eulerian-Lagrangian formulation. The method is based on a decomposition of the concentration field into two parts, one advective and one dispersive, in a rigorous manner that does not leave room for ambiguity. The advective component of steep concentration fronts is tracked forward with the aid of moving particles clustered around each front. Away from such fronts the advection problem is handled by an efficient modified method of characteristics called single-step reverse particle tracking. When a front dissipates with time, its forward tracking stops automatically and the corresponding cloud of particles is eliminated. The dispersion problem is solved by an unconventional Lagrangian finite element formulation on a fixed grid which involves only symmetric and diagonal matrices. Preliminary tests against analytical solutions of ne- and two-dimensional dispersion in a uniform steady state velocity field suggest that the proposed adaptive method can handle the entire range of Peclet numbers from 0 to infinity, with Courant numbers well in excess of 1

  5. SOFT COMPUTING SINGLE HIDDEN LAYER MODELS FOR SHELF LIFE PREDICTION OF BURFI

    Directory of Open Access Journals (Sweden)

    Sumit Goyal

    2012-05-01

    Full Text Available Burfi is an extremely popular sweetmeat, which is prepared by desiccating the standardized water buffalo milk. Soft computing feedforward single layer models were developed for predicting the shelf life of burfi stored at 30g.C. The data of the product relating to moisture, titratable acidity, free fatty acids, tyrosine, and peroxide value were used as input variables, and the overall acceptability score as output variable. The results showed excellent agreement between the experimental and the predicted data, suggesting that the developed soft computing model can alternatively be used for predicting the shelf life of burfi.

  6. Reduction of wind power induced reserve requirements by advanced shortest-term forecasts and prediction intervals

    Energy Technology Data Exchange (ETDEWEB)

    Dobschinski, Jan; Wessel, Arne; Lange, Bernhard; Bremen, Lueder von [Fraunhofer Institut fuer Windenergie und Energiesystemtechnik (IWES), Kassel (Germany)

    2009-07-01

    In electricity systems with large penetration of wind power, the limited predictability of the wind power generation leads to an increase in reserve and balancing requirements. At first the present study concentrates on the capability of dynamic day-ahead prediction intervals to reduce the wind power induced reserve and balancing requirements. Alternatively the reduction of large forecast errors of the German wind power generation by using advanced shortest-term predictions has been evaluated in a second approach. With focus on the allocation of minute reserve power the aim is to estimate the maximal remaining uncertainty after trading activities on the intraday market. Finally both approaches were used in a case study concerning the reserve requirements induced by the total German wind power expansion in 2007. (orig.)

  7. Predictions of of fast wave heating, current drive, and current drive antenna arrays for advanced tokamaks

    International Nuclear Information System (INIS)

    Batchelor, D.B.; Baity, F.W.; Carter, M.D.

    1995-01-01

    The objective of the advanced tokamak program is to optimize plasma performance leading to a compact tokamak reactor through active, steady state control of the current profile using non-inductive current drive and profile control. To achieve this objective requires compatibility and flexibility in the use of available heating and current drive systems - ion cyclotron radio frequency (ICRF), neutral beams, and lower hybrid. For any advanced tokamak, the following are important challenges to effective use of fast waves in various role of direct electron heating, minority ion heating, and current drive: (1) to employ the heating and current drive systems to give self-consistent pressure and current profiles leading to the desired advanced tokamak operating modes; (2) to minimize absorption of the fast waves by parasitic resonances, which limit current drive; (3) to optimize and control the spectrum of fast waves launched by the antenna array for the required mix of simultaneous heating and current drive. The paper addresses these issues using theoretical and computational tools developed at a number of institutions by benchmarking the computations against available experimental data and applying them to the specific case of TPX. (author). 6 refs, 3 figs

  8. Predictions of fast wave heating, current drive, and current drive antenna arrays for advanced tokamaks

    International Nuclear Information System (INIS)

    Batchelor, D.B.; Baity, F.W.; Carter, M.D.

    1994-01-01

    The objective of the advanced tokamak program is to optimize plasma performance leading to a compact tokamak reactor through active, steady state control of the current profile using non-inductive current drive and profile control. To achieve these objectives requires compatibility and flexibility in the use of available heating and current drive systems--ion cyclotron radio frequency (ICRF), neutral beams, and lower hybrid. For any advanced tokamak, the following are important challenges to effective use of fast waves in various roles of direct electron heating, minority ion heating, and current drive: (1) to employ the heating and current drive systems to give self-consistent pressure and current profiles leading to the desired advanced tokamak operating modes; (2) to minimize absorption of the fast waves by parasitic resonances, which limit current drive; (3) to optimize and control the spectrum of fast waves launched by the antenna array for the required mix of simultaneous heating and current drive. The authors have addressed these issues using theoretical and computational tools developed at a number of institutions by benchmarking the computations against available experimental data and applying them to the specific case of TPX

  9. Prediction of Indian Summer-Monsoon Onset Variability: A Season in Advance.

    Science.gov (United States)

    Pradhan, Maheswar; Rao, A Suryachandra; Srivastava, Ankur; Dakate, Ashish; Salunke, Kiran; Shameera, K S

    2017-10-27

    Monsoon onset is an inherent transient phenomenon of Indian Summer Monsoon and it was never envisaged that this transience can be predicted at long lead times. Though onset is precipitous, its variability exhibits strong teleconnections with large scale forcing such as ENSO and IOD and hence may be predictable. Despite of the tremendous skill achieved by the state-of-the-art models in predicting such large scale processes, the prediction of monsoon onset variability by the models is still limited to just 2-3 weeks in advance. Using an objective definition of onset in a global coupled ocean-atmosphere model, it is shown that the skillful prediction of onset variability is feasible under seasonal prediction framework. The better representations/simulations of not only the large scale processes but also the synoptic and intraseasonal features during the evolution of monsoon onset are the comprehensions behind skillful simulation of monsoon onset variability. The changes observed in convection, tropospheric circulation and moisture availability prior to and after the onset are evidenced in model simulations, which resulted in high hit rate of early/delay in monsoon onset in the high resolution model.

  10. An expanded framework for the advanced computational testing and simulation toolkit

    Energy Technology Data Exchange (ETDEWEB)

    Marques, Osni A.; Drummond, Leroy A.

    2003-11-09

    The Advanced Computational Testing and Simulation (ACTS) Toolkit is a set of computational tools developed primarily at DOE laboratories and is aimed at simplifying the solution of common and important computational problems. The use of the tools reduces the development time for new codes and the tools provide functionality that might not otherwise be available. This document outlines an agenda for expanding the scope of the ACTS Project based on lessons learned from current activities. Highlights of this agenda include peer-reviewed certification of new tools; finding tools to solve problems that are not currently addressed by the Toolkit; working in collaboration with other software initiatives and DOE computer facilities; expanding outreach efforts; promoting interoperability, further development of the tools; and improving functionality of the ACTS Information Center, among other tasks. The ultimate goal is to make the ACTS tools more widely used and more effective in solving DOE's and the nation's scientific problems through the creation of a reliable software infrastructure for scientific computing.

  11. Imaging Features of Helical Computed Tomography Suggesting Advanced Urothelial Carcinoma Arising from the Pelvocalyceal System

    International Nuclear Information System (INIS)

    Kwak, Kyung Won; Park, Byung Kwan; Kim, Chan Kyo; Lee, Hyun Moo; Choi, Han Y ong

    2008-01-01

    Background: Urothelial carcinoma is the most common malignant tumor arising from the pelvocalyceal system. Helical computed tomography (CT) is probably the best preoperative-stage modality for the determination of treatment plan and prognosis. Purpose: To obtain helical CT imaging features suggesting advanced pelvocalyceal urothelial carcinoma. Material and Methods: Preoperative CT images in 44 patients with pelvocalyceal urothelial carcinoma were retrospectively reviewed and correlated with the pathological examination to determine imaging features suggesting stage III or IV of the disease. Results: Pathological stages revealed stage I in 16, stage II in three, stage III in 17, and stage IV in eight patients. Seven patients had metastatic lymph nodes. CT imaging showed that renal parenchymal invasion, sinus fat invasion, and lymph node metastasis were highly suggestive of advanced urothelial cell carcinoma (P<0.05). Helical CT sensitivity, specificity, and accuracy for advanced pelvocalyceal urothelial carcinoma were 76% (19/25), 84% (16/19), and 80% (35/44), respectively. Conclusion: Preoperative helical CT may suggest imaging features of advanced urothelial carcinoma, influencing treatment plan and patient prognosis, even though its accuracy is not so high

  12. Uncertainty quantification an accelerated course with advanced applications in computational engineering

    CERN Document Server

    Soize, Christian

    2017-01-01

    This book presents the fundamental notions and advanced mathematical tools in the stochastic modeling of uncertainties and their quantification for large-scale computational models in sciences and engineering. In particular, it focuses in parametric uncertainties, and non-parametric uncertainties with applications from the structural dynamics and vibroacoustics of complex mechanical systems, from micromechanics and multiscale mechanics of heterogeneous materials. Resulting from a course developed by the author, the book begins with a description of the fundamental mathematical tools of probability and statistics that are directly useful for uncertainty quantification. It proceeds with a well carried out description of some basic and advanced methods for constructing stochastic models of uncertainties, paying particular attention to the problem of calibrating and identifying a stochastic model of uncertainty when experimental data is available. < This book is intended to be a graduate-level textbook for stu...

  13. Computational mechanics - Advances and trends; Proceedings of the Session - Future directions of Computational Mechanics of the ASME Winter Annual Meeting, Anaheim, CA, Dec. 7-12, 1986

    Science.gov (United States)

    Noor, Ahmed K. (Editor)

    1986-01-01

    The papers contained in this volume provide an overview of the advances made in a number of aspects of computational mechanics, identify some of the anticipated industry needs in this area, discuss the opportunities provided by new hardware and parallel algorithms, and outline some of the current government programs in computational mechanics. Papers are included on advances and trends in parallel algorithms, supercomputers for engineering analysis, material modeling in nonlinear finite-element analysis, the Navier-Stokes computer, and future finite-element software systems.

  14. Advanced scientific computational methods and their applications to nuclear technologies. (4) Overview of scientific computational methods, introduction of continuum simulation methods and their applications (4)

    International Nuclear Information System (INIS)

    Sekimura, Naoto; Okita, Taira

    2006-01-01

    Scientific computational methods have advanced remarkably with the progress of nuclear development. They have played the role of weft connecting each realm of nuclear engineering and then an introductory course of advanced scientific computational methods and their applications to nuclear technologies were prepared in serial form. This is the fourth issue showing the overview of scientific computational methods with the introduction of continuum simulation methods and their applications. Simulation methods on physical radiation effects on materials are reviewed based on the process such as binary collision approximation, molecular dynamics, kinematic Monte Carlo method, reaction rate method and dislocation dynamics. (T. Tanaka)

  15. Enhanced operational safety of BWRs by advanced computer technology and human engineering

    International Nuclear Information System (INIS)

    Tomizawa, T.; Fukumoto, A.; Neda, T.; Toda, Y.; Takizawa, Y.

    1984-01-01

    In BWR nuclear power plants, where unit capacity is increasing and the demand for assured safety is growing, it has become important for the information interface between man and machine to work smoothly. Efforts to improve man-machine communication have been going on for the past ten years in Japan. Computer facilities and colour CRT display systems are amongst the most useful new methods. Advanced computer technology has been applied to operating plants and found to be very helpful for safe operation. A display monitoring system (DMS) is in operation in a 1100 MW(e) BWR plant. A total combination test was successfully completed on the 'plant operation by displayed information and automation' system (PODIA) in February 1983 before shipment to the site. The objective of this test was to verify the improved qualification of the newly developed advanced PODIA man-machine system by this enlarged fabrication test concept. In addition, the development of special graphics displays for the main control room and technical support centre to assist operators in assessing plant safety and diagnosing problems is required to meet post-TMI regulations. For this purpose, a prototype safety parameter display system (called Toshiba SPDS) with two colour CRT displays and a computer (TOSBAC-7/70) was developed in 1981 as an independent safety monitoring system. The PODIA and SPDS are now independent systems, but their combination has been found to be more useful and valuable for nuclear power plant safety. The paper discusses supervisory and operational concepts in the advanced main control room including SPDS, and describes the PODIA and SPDS verification tests including the valuable experience obtained after improvements in the qualification of these systems had been made to satisfactory operational safety levels. (author)

  16. Advanced computer techniques for inverse modeling of electric current in cardiac tissue

    Energy Technology Data Exchange (ETDEWEB)

    Hutchinson, S.A.; Romero, L.A.; Diegert, C.F.

    1996-08-01

    For many years, ECG`s and vector cardiograms have been the tools of choice for non-invasive diagnosis of cardiac conduction problems, such as found in reentrant tachycardia or Wolff-Parkinson-White (WPW) syndrome. Through skillful analysis of these skin-surface measurements of cardiac generated electric currents, a physician can deduce the general location of heart conduction irregularities. Using a combination of high-fidelity geometry modeling, advanced mathematical algorithms and massively parallel computing, Sandia`s approach would provide much more accurate information and thus allow the physician to pinpoint the source of an arrhythmia or abnormal conduction pathway.

  17. DOE Advanced Scientific Computing Advisory Committee (ASCAC) Subcommittee Report on Scientific and Technical Information

    Energy Technology Data Exchange (ETDEWEB)

    Hey, Tony [eScience Institute, University of Washington; Agarwal, Deborah [Lawrence Berkeley National Laboratory; Borgman, Christine [University of California, Los Angeles; Cartaro, Concetta [SLAC National Accelerator Laboratory; Crivelli, Silvia [Lawrence Berkeley National Laboratory; Van Dam, Kerstin Kleese [Pacific Northwest National Laboratory; Luce, Richard [University of Oklahoma; Arjun, Shankar [CADES, Oak Ridge National Laboratory; Trefethen, Anne [University of Oxford; Wade, Alex [Microsoft Research, Microsoft Corporation; Williams, Dean [Lawrence Livermore National Laboratory

    2015-09-04

    The Advanced Scientific Computing Advisory Committee (ASCAC) was charged to form a standing subcommittee to review the Department of Energy’s Office of Scientific and Technical Information (OSTI) and to begin by assessing the quality and effectiveness of OSTI’s recent and current products and services and to comment on its mission and future directions in the rapidly changing environment for scientific publication and data. The Committee met with OSTI staff and reviewed available products, services and other materials. This report summaries their initial findings and recommendations.

  18. Cardiovascular proteomics in the era of big data: experimental and computational advances.

    Science.gov (United States)

    Lam, Maggie P Y; Lau, Edward; Ng, Dominic C M; Wang, Ding; Ping, Peipei

    2016-01-01

    Proteomics plays an increasingly important role in our quest to understand cardiovascular biology. Fueled by analytical and computational advances in the past decade, proteomics applications can now go beyond merely inventorying protein species, and address sophisticated questions on cardiac physiology. The advent of massive mass spectrometry datasets has in turn led to increasing intersection between proteomics and big data science. Here we review new frontiers in technological developments and their applications to cardiovascular medicine. The impact of big data science on cardiovascular proteomics investigations and translation to medicine is highlighted.

  19. Advances in computer applications in radioactive tracer studies of the circulation

    International Nuclear Information System (INIS)

    Wagner, H.N. Jr.; Klingensmith, W.C. III; Knowles, L.G.; Lotter, M.G.; Natarajan, T.K.

    1977-01-01

    Advances in computer technology since the last IAEA symposium on medical radionuclide imaging have now made possible a new approach to the study of physiological processes that promise to improve greatly our perception of body functions and structures. We have developed procedures, called ''compressed time imaging'' (CTI), that display serial images obtained over periods of minutes and hours at framing rates of approximately 16 to 60 per minute. At other times, ''real'' or ''expanded time imaging'' is used, depending on the process under study. Designed initially to study the beating heart, such multidimensional time studies are now being extended to the cerebral and other regional circulations, as well as to other organ systems. The improved imaging methods provide a new approach to space and time in the study of physiology and are supplemented by quantitative analysis of data displayed on the television screen of the computer. (author)

  20. Advanced Simulation and Computing Fiscal Year 2016 Implementation Plan, Version 0

    Energy Technology Data Exchange (ETDEWEB)

    McCoy, M. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Archer, B. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Hendrickson, B. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States)

    2015-08-27

    The Stockpile Stewardship Program (SSP) is an integrated technical program for maintaining the safety, surety, and reliability of the U.S. nuclear stockpile. The SSP uses nuclear test data, computational modeling and simulation, and experimental facilities to advance understanding of nuclear weapons. It includes stockpile surveillance, experimental research, development and engineering programs, and an appropriately scaled production capability to support stockpile requirements. This integrated national program requires the continued use of experimental facilities and programs, and the computational capabilities to support these programs. The purpose of this IP is to outline key work requirements to be performed and to control individual work activities within the scope of work. Contractors may not deviate from this plan without a revised WA or subsequent IP.

  1. Review of research on advanced computational science in FY2010-2014

    International Nuclear Information System (INIS)

    2016-03-01

    Research on advanced computational science for nuclear applications, based on 'the plan for meeting the mid-term goal of the Japan Atomic Energy Agency', has been performed at Center for Computational Science and e-Systems (CCSE), Japan Atomic Energy Agency. CCSE established the committee consisting outside experts and authorities which does research evaluation and advices for the assistance of the research and development. This report summarizes the followings. (1) Results of the R and D performed at CCSE in the period of the midterm plan (April 1st, 2010 - March 31st, 2015) (2) Results of the evaluation on the R and D by the committee in the period of the midterm plan (April 1st, 2010 - March 31st, 2015). (author)

  2. Recent advances in transient imaging: A computer graphics and vision perspective

    Directory of Open Access Journals (Sweden)

    Adrian Jarabo

    2017-03-01

    Full Text Available Transient imaging has recently made a huge impact in the computer graphics and computer vision fields. By capturing, reconstructing, or simulating light transport at extreme temporal resolutions, researchers have proposed novel techniques to show movies of light in motion, see around corners, detect objects in highly-scattering media, or infer material properties from a distance, to name a few. The key idea is to leverage the wealth of information in the temporal domain at the pico or nanosecond resolution, information usually lost during the capture-time temporal integration. This paper presents recent advances in this field of transient imaging from a graphics and vision perspective, including capture techniques, analysis, applications and simulation. Keywords: Transient imaging, Ultrafast imaging, Time-of-flight

  3. Integrated Computational Materials Engineering (ICME) for Third Generation Advanced High-Strength Steel Development

    Energy Technology Data Exchange (ETDEWEB)

    Savic, Vesna; Hector, Louis G.; Ezzat, Hesham; Sachdev, Anil K.; Quinn, James; Krupitzer, Ronald; Sun, Xin

    2015-06-01

    This paper presents an overview of a four-year project focused on development of an integrated computational materials engineering (ICME) toolset for third generation advanced high-strength steels (3GAHSS). Following a brief look at ICME as an emerging discipline within the Materials Genome Initiative, technical tasks in the ICME project will be discussed. Specific aims of the individual tasks are multi-scale, microstructure-based material model development using state-of-the-art computational and experimental techniques, forming, toolset assembly, design optimization, integration and technical cost modeling. The integrated approach is initially illustrated using a 980 grade transformation induced plasticity (TRIP) steel, subject to a two-step quenching and partitioning (Q&P) heat treatment, as an example.

  4. Advances in Intelligent Modelling and Simulation Artificial Intelligence-Based Models and Techniques in Scalable Computing

    CERN Document Server

    Khan, Samee; Burczy´nski, Tadeusz

    2012-01-01

    One of the most challenging issues in today’s large-scale computational modeling and design is to effectively manage the complex distributed environments, such as computational clouds, grids, ad hoc, and P2P networks operating under  various  types of users with evolving relationships fraught with  uncertainties. In this context, the IT resources and services usually belong to different owners (institutions, enterprises, or individuals) and are managed by different administrators. Moreover, uncertainties are presented to the system at hand in various forms of information that are incomplete, imprecise, fragmentary, or overloading, which hinders in the full and precise resolve of the evaluation criteria, subsequencing and selection, and the assignment scores. Intelligent scalable systems enable the flexible routing and charging, advanced user interactions and the aggregation and sharing of geographically-distributed resources in modern large-scale systems.   This book presents new ideas, theories, models...

  5. Advanced technique for computing fuel combustion properties in pulverized-fuel fired boilers

    Energy Technology Data Exchange (ETDEWEB)

    Kotler, V.R. (Vsesoyuznyi Teplotekhnicheskii Institut (Russian Federation))

    1992-03-01

    Reviews foreign technical reports on advanced techniques for computing fuel combustion properties in pulverized-fuel fired boilers and analyzes a technique developed by Combustion Engineering, Inc. (USA). Characteristics of 25 fuel types, including 19 grades of coal, are listed along with a diagram of an installation with a drop tube furnace. Characteristics include burn-out intensity curves obtained using thermogravimetric analysis for high-volatile bituminous, semi-bituminous and coking coal. The patented LFP-SKM mathematical model is used to model combustion of a particular fuel under given conditions. The model allows for fuel particle size, air surplus, load, flame height, and portion of air supplied as tertiary blast. Good agreement between computational and experimental data was observed. The method is employed in designing new boilers as well as converting operating boilers to alternative types of fuel. 3 refs.

  6. Advanced management of pipe wall thinning based on prediction-monitor fusion

    International Nuclear Information System (INIS)

    Kojima, Fumio; Uchida, Shunsuke

    2012-01-01

    This article is concerned with pipe wall thinning management system by means of hybrid use of simulation and monitoring. First, the computer-aided simulation for predicting wear rate of piping system is developed based on elucidation of thinning mechanism such as flow-accelerated corrosion (FAC). The accurate prediction of wear rate allows us the useful information on region of interest of inspection. Secondly, several monitoring methods are considered in accordance with interest of inspection. Thirdly, probability of detection (POD) is considered for the reliability of inspection data. The final part of this article is devoted to how to improve safety performance under the hybrid use of predicting and monitoring on the proposed pipe wall management. (author)

  7. Whole Body Computed Tomography with Advanced Imaging Techniques: A Research Tool for Measuring Body Composition in Dogs

    Directory of Open Access Journals (Sweden)

    Dharma Purushothaman

    2013-01-01

    Full Text Available The use of computed tomography (CT to evaluate obesity in canines is limited. Traditional CT image analysis is cumbersome and uses prediction equations that require manual calculations. In order to overcome this, our study investigated the use of advanced image analysis software programs to determine body composition in dogs with an application to canine obesity research. Beagles and greyhounds were chosen for their differences in morphology and propensity to obesity. Whole body CT scans with regular intervals were performed on six beagles and six greyhounds that were subjected to a 28-day weight-gain protocol. The CT images obtained at days 0 and 28 were analyzed using software programs OsiriX, ImageJ, and AutoCAT. The CT scanning technique was able to differentiate bone, lean, and fat tissue in dogs and proved sensitive enough to detect increases in both lean and fat during weight gain over a short period. A significant difference in lean : fat ratio was observed between the two breeds on both days 0 and 28 (P<0.01. Therefore, CT and advanced image analysis proved useful in the current study for the estimation of body composition in dogs and has the potential to be used in canine obesity research.

  8. Advanced scientific computational methods and their applications to nuclear technologies. (3) Introduction of continuum simulation methods and their applications (3)

    International Nuclear Information System (INIS)

    Satake, Shin-ichi; Kunugi, Tomoaki

    2006-01-01

    Scientific computational methods have advanced remarkably with the progress of nuclear development. They have played the role of weft connecting each realm of nuclear engineering and then an introductory course of advanced scientific computational methods and their applications to nuclear technologies were prepared in serial form. This is the third issue showing the introduction of continuum simulation methods and their applications. Spectral methods and multi-interface calculation methods in fluid dynamics are reviewed. (T. Tanaka)

  9. Advances in Predictive Toxicology for Discovery Safety through High Content Screening.

    Science.gov (United States)

    Persson, Mikael; Hornberg, Jorrit J

    2016-12-19

    High content screening enables parallel acquisition of multiple molecular and cellular readouts. In particular the predictive toxicology field has progressed from the advances in high content screening, as more refined end points that report on cellular health can be studied in combination, at the single cell level, and in relatively high throughput. Here, we discuss how high content screening has become an essential tool for Discovery Safety, the discipline that integrates safety and toxicology in the drug discovery process to identify and mitigate safety concerns with the aim to design drug candidates with a superior safety profile. In addition to customized mechanistic assays to evaluate target safety, routine screening assays can be applied to identify risk factors for frequently occurring organ toxicities. We discuss the current state of high content screening assays for hepatotoxicity, cardiotoxicity, neurotoxicity, nephrotoxicity, and genotoxicity, including recent developments and current advances.

  10. Validation of physics and thermalhydraulic computer codes for advanced Candu reactor applications

    International Nuclear Information System (INIS)

    Wren, D.J.; Popov, N.; Snell, V.G.

    2004-01-01

    Atomic Energy of Canada Ltd. (AECL) is developing an Advanced Candu Reactor (ACR) that is an evolutionary advancement of the currently operating Candu 6 reactors. The ACR is being designed to produce electrical power for a capital cost and at a unit-energy cost significantly less than that of the current reactor designs. The ACR retains the modular Candu concept of horizontal fuel channels surrounded by a heavy water moderator. However, ACR uses slightly enriched uranium fuel compared to the natural uranium used in Candu 6. This achieves the twin goals of improved economics (via large reductions in the heavy water moderator volume and replacement of the heavy water coolant with light water coolant) and improved safety. AECL has developed and implemented a software quality assurance program to ensure that its analytical, scientific and design computer codes meet the required standards for software used in safety analyses. Since the basic design of the ACR is equivalent to that of the Candu 6, most of the key phenomena associated with the safety analyses of ACR are common, and the Candu industry standard tool-set of safety analysis codes can be applied to the analysis of the ACR. A systematic assessment of computer code applicability addressing the unique features of the ACR design was performed covering the important aspects of the computer code structure, models, constitutive correlations, and validation database. Arising from this assessment, limited additional requirements for code modifications and extensions to the validation databases have been identified. This paper provides an outline of the AECL software quality assurance program process for the validation of computer codes used to perform physics and thermal-hydraulics safety analyses of the ACR. It describes the additional validation work that has been identified for these codes and the planned, and ongoing, experimental programs to extend the code validation as required to address specific ACR design

  11. Novel computational methods to predict drug–target interactions using graph mining and machine learning approaches

    KAUST Repository

    Olayan, Rawan S.

    2017-12-01

    Computational drug repurposing aims at finding new medical uses for existing drugs. The identification of novel drug-target interactions (DTIs) can be a useful part of such a task. Computational determination of DTIs is a convenient strategy for systematic screening of a large number of drugs in the attempt to identify new DTIs at low cost and with reasonable accuracy. This necessitates development of accurate computational methods that can help focus on the follow-up experimental validation on a smaller number of highly likely targets for a drug. Although many methods have been proposed for computational DTI prediction, they suffer the high false positive prediction rate or they do not predict the effect that drugs exert on targets in DTIs. In this report, first, we present a comprehensive review of the recent progress in the field of DTI prediction from data-centric and algorithm-centric perspectives. The aim is to provide a comprehensive review of computational methods for identifying DTIs, which could help in constructing more reliable methods. Then, we present DDR, an efficient method to predict the existence of DTIs. DDR achieves significantly more accurate results compared to the other state-of-theart methods. As supported by independent evidences, we verified as correct 22 out of the top 25 DDR DTIs predictions. This validation proves the practical utility of DDR, suggesting that DDR can be used as an efficient method to identify 5 correct DTIs. Finally, we present DDR-FE method that predicts the effect types of a drug on its target. On different representative datasets, under various test setups, and using different performance measures, we show that DDR-FE achieves extremely good performance. Using blind test data, we verified as correct 2,300 out of 3,076 DTIs effects predicted by DDR-FE. This suggests that DDR-FE can be used as an efficient method to identify correct effects of a drug on its target.

  12. Prediction of 30-day morbidity after primary cytoreductive surgery for advanced stage ovarian cancer.

    Science.gov (United States)

    Gerestein, C G; Nieuwenhuyzen-de Boer, G M; Eijkemans, M J; Kooi, G S; Burger, C W

    2010-01-01

    Treatment in advanced stage epithelial ovarian cancer (EOC) is based on primary cytoreductive surgery followed by platinum-based chemotherapy. Successful cytoreduction to minimal residual tumour burden is the most important determinant of prognosis. However, extensive surgical procedures to achieve maximal debulking are inevitably associated with postoperative morbidity and mortality. The objective of this study is to determine predictors of 30-day morbidity after primary cytoreductive surgery for advanced stage EOC. All patients in the South Western part of the Netherlands who underwent primary cytoreductive surgery for advanced stage EOC between January 2004 and December 2007 were identified from the Rotterdam Cancer Registry database. All peri- and postoperative complications within 30 days after surgery were registered and classified according to the definitions of the National Surgical Quality Improvement Programme (NSQIP). To investigate independent predictors of 30-day morbidity, a Cox proportional hazards model with backward stepwise elimination was utilised. The identified predictors were entered into a nomogram. Two hundred and ninety-three patients entered the study protocol. Optimal cytoreduction was achieved in 136 (46%) patients. 30-day morbidity was seen in 99 (34%) patients. Postoperative morbidity could be predicted by age (P=0.007; odds ratio [OR] 1.034), WHO performance status (P=0.046; OR 1.757), extent of surgery (P=0.1308; OR=2.101), and operative time (P=0.017; OR 1.007) with an optimism corrected c-statistic of 0.68. 30-day morbidity could be predicted by age, WHO performance status, operative time and extent of surgery. The generated nomogram could be valuable for predicting operative risk in the individual patient.

  13. Predicting which older adults will or will not fall using the Fullerton Advanced Balance scale.

    Science.gov (United States)

    Hernandez, Danielle; Rose, Debra J

    2008-12-01

    The purpose of this study was to determine if the Fullerton Advanced Balance (FAB) scale can predict faller status in a group of independently functioning older adults. A cross-sectional design was used to establish the sensitivity and specificity of the FAB scale to predict faller status based on a retrospective self-reported fall history. For the purpose of this study, a faller was classified as an older adult with a history of 2 or more falls in the previous 12 months. Multipurpose senior centers in an urban community. A sample of independently functioning older adults (N=192; mean age+/-SD, 77+/-6.5 y). Not applicable. FAB scale, a retrospective history of falls. Binary logistic regression analysis indicated that the total FAB scale score could be used to predict faller status (as determined by a retrospective self-reported fall history). In the present sample, the probability of falling increased by 8% with each 1-point decrease in total FAB scale score. Receiver operating characteristic analysis determined that a cut-off score of 25 out of 40 on the FAB scale produced the highest sensitivity (74.6%) and specificity (52.6%) in predicting faller status. Five individual test items on the FAB scale were particularly predictive of faller status and could be combined to form a short version of the scale that may be even more predictive of faller status and require less time to administer. The FAB scale is a predictive measure of faller status when used with independently functioning older adults. A practitioner can be confident in more than 7 out of 10 cases that an older adult who scores 25 or lower on the FAB scale is at high risk for falls and in need of immediate intervention.

  14. Impacts of transient heat transfer modeling on prediction of advanced cladding fracture during LWR LBLOCA

    Energy Technology Data Exchange (ETDEWEB)

    Lee, Youho, E-mail: euo@kaist.ac.kr; Lee, Jeong Ik, E-mail: jeongiklee@kaist.ac.kr; NO, Hee Cheon, E-mail: hcno@kaist.ac.kr

    2016-03-15

    Highlights: • Use of constant heat transfer coefficient for fracture analysis is not sound. • On-time heat transfer coefficient should be used for thermal fracture prediction. • ∼90% of the actual fracture stresses were predicted with the on-time transient h. • Thermal-hydraulic codes can be used to better predict brittle cladding fracture. • Effects of surface oxides on thermal shock fracture should be accounted by h. - Abstract: This study presents the importance of coherency in modeling thermal-hydraulics and mechanical behavior of a solid for an advanced prediction of cladding thermal shock fracture. In water quenching, a solid experiences dynamic heat transfer rate evolutions with phase changes of the fluid over a short quenching period. Yet, such a dynamic change of heat transfer rates has been overlooked in the analysis of thermal shock fracture. In this study, we are presenting quantitative evidence against the prevailing use of a constant heat transfer coefficient for thermal shock fracture analysis in water. We conclude that no single constant heat transfer could suffice to depict the actual stress evolution subject to dynamic fluid phase changes. Use of the surface temperature dependent heat transfer coefficient will remarkably increase predictability of thermal shock fracture of brittle materials. The presented results show a remarkable stress prediction improvement up to 80–90% of the actual stress with the use of the surface temperature dependent heat transfer coefficient. For thermal shock fracture analysis of brittle fuel cladding such as oxidized zirconium-based alloy or silicon carbide during LWR reflood, transient subchannel heat transfer coefficients obtained from a thermal-hydraulics code should be used as input for stress analysis. Such efforts will lead to a fundamental improvement in thermal shock fracture predictability over the current experimental empiricism for cladding fracture analysis during reflood.

  15. Recent advances in the reconstruction of cranio-maxillofacial defects using computer-aided design/computer-aided manufacturing.

    Science.gov (United States)

    Oh, Ji-Hyeon

    2018-12-01

    With the development of computer-aided design/computer-aided manufacturing (CAD/CAM) technology, it has been possible to reconstruct the cranio-maxillofacial defect with more accurate preoperative planning, precise patient-specific implants (PSIs), and shorter operation times. The manufacturing processes include subtractive manufacturing and additive manufacturing and should be selected in consideration of the material type, available technology, post-processing, accuracy, lead time, properties, and surface quality. Materials such as titanium, polyethylene, polyetheretherketone (PEEK), hydroxyapatite (HA), poly-DL-lactic acid (PDLLA), polylactide-co-glycolide acid (PLGA), and calcium phosphate are used. Design methods for the reconstruction of cranio-maxillofacial defects include the use of a pre-operative model printed with pre-operative data, printing a cutting guide or template after virtual surgery, a model after virtual surgery printed with reconstructed data using a mirror image, and manufacturing PSIs by directly obtaining PSI data after reconstruction using a mirror image. By selecting the appropriate design method, manufacturing process, and implant material according to the case, it is possible to obtain a more accurate surgical procedure, reduced operation time, the prevention of various complications that can occur using the traditional method, and predictive results compared to the traditional method.

  16. Traffic Flow Prediction Model for Large-Scale Road Network Based on Cloud Computing

    Directory of Open Access Journals (Sweden)

    Zhaosheng Yang

    2014-01-01

    Full Text Available To increase the efficiency and precision of large-scale road network traffic flow prediction, a genetic algorithm-support vector machine (GA-SVM model based on cloud computing is proposed in this paper, which is based on the analysis of the characteristics and defects of genetic algorithm and support vector machine. In cloud computing environment, firstly, SVM parameters are optimized by the parallel genetic algorithm, and then this optimized parallel SVM model is used to predict traffic flow. On the basis of the traffic flow data of Haizhu District in Guangzhou City, the proposed model was verified and compared with the serial GA-SVM model and parallel GA-SVM model based on MPI (message passing interface. The results demonstrate that the parallel GA-SVM model based on cloud computing has higher prediction accuracy, shorter running time, and higher speedup.

  17. Annual Performance Assessment of Complex Fenestration Systems in Sunny Climates Using Advanced Computer Simulations

    Directory of Open Access Journals (Sweden)

    Chantal Basurto

    2015-12-01

    Full Text Available Complex Fenestration Systems (CFS are advanced daylighting systems that are placed on the upper part of a window to improve the indoor daylight distribution within rooms. Due to their double function of daylight redirection and solar protection, they are considered as a solution to mitigate the unfavorable effects due to the admission of direct sunlight in buildings located in prevailing sunny climates (risk of glare and overheating. Accordingly, an adequate assessment of their performance should include an annual evaluation of the main aspects relevant to the use of daylight in such regions: the indoor illuminance distribution, thermal comfort, and visual comfort of the occupant’s. Such evaluation is possible with the use of computer simulations combined with the bi-directional scattering distribution function (BSDF data of these systems. This study explores the use of available methods to assess the visible and thermal annual performance of five different CFS using advanced computer simulations. To achieve results, an on-site daylight monitoring was carried out in a building located in a predominantly sunny climate location, and the collected data was used to create and calibrate a virtual model used to carry-out the simulations. The results can be employed to select the CFS, which improves visual and thermal interior environment for the occupants.

  18. Advanced in-production hotspot prediction and monitoring with micro-topography

    Science.gov (United States)

    Fanton, P.; Hasan, T.; Lakcher, A.; Le-Gratiet, B.; Prentice, C.; Simiz, J.-G.; La Greca, R.; Depre, L.; Hunsche, S.

    2017-03-01

    At 28nm technology node and below, hot spot prediction and process window control across production wafers have become increasingly critical to prevent hotspots from becoming yield-limiting defects. We previously established proof of concept for a systematic approach to identify the most critical pattern locations, i.e. hotspots, in a reticle layout by computational lithography and combining process window characteristics of these patterns with across-wafer process variation data to predict where hotspots may become yield impacting defects [1,2]. The current paper establishes the impact of micro-topography on a 28nm metal layer, and its correlation with hotspot best focus variations across a production chip layout. Detailed topography measurements are obtained from an offline tool, and pattern-dependent best focus (BF) shifts are determined from litho simulations that include mask-3D effects. We also establish hotspot metrology and defect verification by SEM image contour extraction and contour analysis. This enables detection of catastrophic defects as well as quantitative characterization of pattern variability, i.e. local and global CD uniformity, across a wafer to establish hotspot defect and variability maps. Finally, we combine defect prediction and verification capabilities for process monitoring by on-product, guided hotspot metrology, i.e. with sampling locations being determined from the defect prediction model and achieved prediction accuracy (capture rate) around 75%

  19. Proposal of computation chart for general use for diffusion prediction of discharged warm water

    International Nuclear Information System (INIS)

    Wada, Akira; Kadoyu, Masatake

    1976-01-01

    The authors have developed the unique simulation analysis method using the numerical models for the prediction of discharged warm water diffusion. At the present stage, the method is adopted for the precise analysis computation in order to make the prediction of the diffusion of discharged warm water at each survey point, but instead of this method, it is strongly requested that some simple and easy prediction methods should be established. For the purpose of meeting this demand, in this report, the computation chart for general use is given to predict simply the diffusion range of discharged warm water, after classifying the semi-infinite sea region into several flow patterns according to the sea conditions and conducting the systematic simulation analysis with the numerical model of each pattern, respectively. (1) Establishment of the computation conditions: The special sea region was picked up as the area to be investigated, which is semi-infinite facing the outer sea and along the rectilineal coast line from many sea regions surrounding Japan, and from the viewpoint of the flow and the diffusion characteristics, the sea region was classified into three patterns. 51 cases in total various parameters were obtained, and finally the simulation analysis was performed. (2) Drawing up the general use chart: 28 sheets of the computation chart for general use were drawn, which are available for computing the approximate temperature rise caused by the discharged warm water diffusion. The example of Anegasaki Thermal Power Station is given. (Kako, I.)

  20. Computer program for prediction of the deposition of material released from fixed and rotary wing aircraft

    Science.gov (United States)

    Teske, M. E.

    1984-01-01

    This is a user manual for the computer code ""AGDISP'' (AGricultural DISPersal) which has been developed to predict the deposition of material released from fixed and rotary wing aircraft in a single-pass, computationally efficient manner. The formulation of the code is novel in that the mean particle trajectory and the variance about the mean resulting from turbulent fluid fluctuations are simultaneously predicted. The code presently includes the capability of assessing the influence of neutral atmospheric conditions, inviscid wake vortices, particle evaporation, plant canopy and terrain on the deposition pattern.

  1. LiverTox: Advanced QSAR and Toxicogeomic Software for Hepatotoxicity Prediction

    Energy Technology Data Exchange (ETDEWEB)

    Lu, P-Y.; Yuracko, K. (YAHSGS, LLC)

    2011-02-25

    YAHSGS LLC and Oak Ridge National Laboratory (ORNL) established a CRADA in an attempt to develop a predictive system using a pre-existing ORNL computational neural network and wavelets format. This was in the interest of addressing national needs for toxicity prediction system to help overcome the significant drain of resources (money and time) being directed toward developing chemical agents for commerce. The research project has been supported through an STTR mechanism and funded by the National Institute of Environmental Health Sciences beginning Phase I in 2004 (CRADA No. ORNL-04-0688) and extending Phase II through 2007 (ORNL NFE-06-00020). To attempt the research objectives and aims outlined under this CRADA, state-of-the-art computational neural network and wavelet methods were used in an effort to design a predictive toxicity system that used two independent areas on which to base the system’s predictions. These two areas were quantitative structure-activity relationships and gene-expression data obtained from microarrays. A third area, using the new Massively Parallel Signature Sequencing (MPSS) technology to assess gene expression, also was attempted but had to be dropped because the company holding the rights to this promising MPSS technology went out of business. A research-scale predictive toxicity database system called Multi-Intelligent System for Toxicogenomic Applications (MISTA) was developed and its feasibility for use as a predictor of toxicological activity was tested. The fundamental focus of the CRADA was an attempt and effort to operate the MISTA database using the ORNL neural network. This effort indicated the potential that such a fully developed system might be used to assist in predicting such biological endpoints as hepatotoxcity and neurotoxicity. The MISTA/LiverTox approach if eventually fully developed might also be useful for automatic processing of microarray data to predict modes of action. A technical paper describing the

  2. Machine learning and statistical methods for the prediction of maximal oxygen uptake: recent advances

    Directory of Open Access Journals (Sweden)

    Abut F

    2015-08-01

    Full Text Available Fatih Abut, Mehmet Fatih AkayDepartment of Computer Engineering, Çukurova University, Adana, TurkeyAbstract: Maximal oxygen uptake (VO2max indicates how many milliliters of oxygen the body can consume in a state of intense exercise per minute. VO2max plays an important role in both sport and medical sciences for different purposes, such as indicating the endurance capacity of athletes or serving as a metric in estimating the disease risk of a person. In general, the direct measurement of VO2max provides the most accurate assessment of aerobic power. However, despite a high level of accuracy, practical limitations associated with the direct measurement of VO2max, such as the requirement of expensive and sophisticated laboratory equipment or trained staff, have led to the development of various regression models for predicting VO2max. Consequently, a lot of studies have been conducted in the last years to predict VO2max of various target audiences, ranging from soccer athletes, nonexpert swimmers, cross-country skiers to healthy-fit adults, teenagers, and children. Numerous prediction models have been developed using different sets of predictor variables and a variety of machine learning and statistical methods, including support vector machine, multilayer perceptron, general regression neural network, and multiple linear regression. The purpose of this study is to give a detailed overview about the data-driven modeling studies for the prediction of VO2max conducted in recent years and to compare the performance of various VO2max prediction models reported in related literature in terms of two well-known metrics, namely, multiple correlation coefficient (R and standard error of estimate. The survey results reveal that with respect to regression methods used to develop prediction models, support vector machine, in general, shows better performance than other methods, whereas multiple linear regression exhibits the worst performance

  3. Prognostic nomograms for predicting survival and distant metastases in locally advanced rectal cancers.

    Directory of Open Access Journals (Sweden)

    Junjie Peng

    Full Text Available To develop prognostic nomograms for predicting outcomes in patients with locally advanced rectal cancers who do not receive preoperative treatment.A total of 883 patients with stage II-III rectal cancers were retrospectively collected from a single institution. Survival analyses were performed to assess each variable for overall survival (OS, local recurrence (LR and distant metastases (DM. Cox models were performed to develop a predictive model for each endpoint. The performance of model prediction was validated by cross validation and on an independent group of patients.The 5-year LR, DM and OS rates were 22.3%, 32.7% and 63.8%, respectively. Two prognostic nomograms were successfully developed to predict 5-year OS and DM-free survival rates, with c-index of 0.70 (95% CI = [0.66, 0.73] and 0.68 (95% CI = [0.64, 0.72] on the original dataset, and 0.76 (95% CI = [0.67, 0.86] and 0.73 (95% CI = [0.63, 0.83] on the validation dataset, respectively. Factors in our models included age, gender, carcinoembryonic antigen value, tumor location, T stage, N stage, metastatic lymph nodes ratio, adjuvant chemotherapy and chemoradiotherapy. Predicted by our nomogram, substantial variability in terms of 5-year OS and DM-free survival was observed within each TNM stage category.The prognostic nomograms integrated demographic and clinicopathological factors to account for tumor and patient heterogeneity, and thereby provided a more individualized outcome prognostication. Our individualized prediction nomograms could help patients with preoperatively under-staged rectal cancer about their postoperative treatment strategies and follow-up protocols.

  4. Advancement in Watershed Modelling Using Dynamic Lateral and Longitudinal Sediment (Dis)connectivity Prediction

    Science.gov (United States)

    Mahoney, D. T.; al Aamery, N. M. H.; Fox, J.

    2017-12-01

    The authors find that sediment (dis)connectivity has seldom taken precedence within watershed models, and the present study advances this modeling framework and applies the modeling within a bedrock-controlled system. Sediment (dis)connectivity, defined as the detachment and transport of sediment from source to sink between geomorphic zones, is a major control on sediment transport. Given the availability of high resolution geospatial data, coupling sediment connectivity concepts within sediment prediction models offers an approach to simulate sediment sources and pathways within a watershed's sediment cascade. Bedrock controlled catchments are potentially unique due to the presence of rock outcrops causing longitudinal impedance to sediment transport pathways in turn impacting the longitudinal distribution of the energy gradient responsible for conveying sediment. Therefore, the authors were motivated by the need to formulate a sediment transport model that couples sediment (dis)connectivity knowledge to predict sediment flux for bedrock controlled catchments. A watershed-scale sediment transport model was formulated that incorporates sediment (dis)connectivity knowledge collected via field reconnaissance and predicts sediment flux through coupling with the Partheniades equation and sediment continuity model. Sediment (dis)connectivity was formulated by coupling probabilistic upland lateral connectivity prediction with instream longitudinal connectivity assessments via discretization of fluid and sediment pathways. Flux predictions from the upland lateral connectivity model served as an input to the instream longitudinal connectivity model. Disconnectivity in the instream model was simulated via the discretization of stream reaches due to barriers such as bedrock outcroppings and man-made check dams. The model was tested for a bedrock controlled catchment in Kentucky, USA for which extensive historic water and sediment flux data was available. Predicted sediment

  5. Hidden Hearing Loss and Computational Models of the Auditory Pathway: Predicting Speech Intelligibility Decline

    Science.gov (United States)

    2016-11-28

    Title: Hidden Hearing Loss and Computational Models of the Auditory Pathway: Predicting Speech Intelligibility Decline Christopher J. Smalt...representation of speech intelligibility in noise. The auditory-periphery model of Zilany et al. (JASA 2009,2014) is used to make predictions of...auditory nerve (AN) responses to speech stimuli under a variety of difficult listening conditions. The resulting cochlear neurogram, a spectrogram

  6. Three-dimensional computed tomographic volumetry precisely predicts the postoperative pulmonary function.

    Science.gov (United States)

    Kobayashi, Keisuke; Saeki, Yusuke; Kitazawa, Shinsuke; Kobayashi, Naohiro; Kikuchi, Shinji; Goto, Yukinobu; Sakai, Mitsuaki; Sato, Yukio

    2017-11-01

    It is important to accurately predict the patient's postoperative pulmonary function. The aim of this study was to compare the accuracy of predictions of the postoperative residual pulmonary function obtained with three-dimensional computed tomographic (3D-CT) volumetry with that of predictions obtained with the conventional segment-counting method. Fifty-three patients scheduled to undergo lung cancer resection, pulmonary function tests, and computed tomography were enrolled in this study. The postoperative residual pulmonary function was predicted based on the segment-counting and 3D-CT volumetry methods. The predicted postoperative values were compared with the results of postoperative pulmonary function tests. Regarding the linear correlation coefficients between the predicted postoperative values and the measured values, those obtained using the 3D-CT volumetry method tended to be higher than those acquired using the segment-counting method. In addition, the variations between the predicted and measured values were smaller with the 3D-CT volumetry method than with the segment-counting method. These results were more obvious in COPD patients than in non-COPD patients. Our findings suggested that the 3D-CT volumetry was able to predict the residual pulmonary function more accurately than the segment-counting method, especially in patients with COPD. This method might lead to the selection of appropriate candidates for surgery among patients with a marginal pulmonary function.

  7. Free energy minimization to predict RNA secondary structures and computational RNA design.

    Science.gov (United States)

    Churkin, Alexander; Weinbrand, Lina; Barash, Danny

    2015-01-01

    Determining the RNA secondary structure from sequence data by computational predictions is a long-standing problem. Its solution has been approached in two distinctive ways. If a multiple sequence alignment of a collection of homologous sequences is available, the comparative method uses phylogeny to determine conserved base pairs that are more likely to form as a result of billions of years of evolution than by chance. In the case of single sequences, recursive algorithms that compute free energy structures by using empirically derived energy parameters have been developed. This latter approach of RNA folding prediction by energy minimization is widely used to predict RNA secondary structure from sequence. For a significant number of RNA molecules, the secondary structure of the RNA molecule is indicative of its function and its computational prediction by minimizing its free energy is important for its functional analysis. A general method for free energy minimization to predict RNA secondary structures is dynamic programming, although other optimization methods have been developed as well along with empirically derived energy parameters. In this chapter, we introduce and illustrate by examples the approach of free energy minimization to predict RNA secondary structures.

  8. Advances in the operation of the DIII-D neutral beam computer systems

    International Nuclear Information System (INIS)

    Phillips, J.C.; Busath, J.L.; Penaflor, B.G.; Piglowski, D.; Kellman, D.H.; Chiu, H.K.; Hong, R.M.

    1998-02-01

    The DIII-D neutral beam system routinely provides up to 20 MW of deuterium neutral beam heating in support of experiments on the DIII-D tokamak, and is a critical part of the DIII-D physics experimental program. The four computer systems previously used to control neutral beam operation and data acquisition were designed and implemented in the late 1970's and used on DIII and DIII-D from 1981--1996. By comparison to modern standards, they had become expensive to maintain, slow and cumbersome, making it difficult to implement improvements. Most critical of all, they were not networked computers. During the 1997 experimental campaign, these systems were replaced with new Unix compliant hardware and, for the most part, commercially available software. This paper describes operational experience with the new neutral beam computer systems, and new advances made possible by using features not previously available. These include retention and access to historical data, an asynchronously fired ''rules'' base, and a relatively straightforward programming interface. Methods and principles for extending the availability of data beyond the scope of the operator consoles will be discussed

  9. Development of a computer code for dynamic analysis of the primary circuit of advanced reactors

    Energy Technology Data Exchange (ETDEWEB)

    Rocha, Jussie Soares da; Lira, Carlos A.B.O.; Magalhaes, Mardson A. de Sa, E-mail: cabol@ufpe.b [Universidade Federal de Pernambuco (DEN/UFPE), Recife, PE (Brazil). Dept. de Energia Nuclear

    2011-07-01

    Currently, advanced reactors are being developed, seeking for enhanced safety, better performance and low environmental impacts. Reactor designs must follow several steps and numerous tests before a conceptual project could be certified. In this sense, computational tools become indispensable in the preparation of such projects. Thus, this study aimed at the development of a computational tool for thermal-hydraulic analysis by coupling two computer codes to evaluate the influence of transients caused by pressure variations and flow surges in the region of the primary circuit of IRIS reactor between the core and the pressurizer. For the simulation, it was used a situation of 'insurge', characterized by the entry of water in the pressurizer, due to the expansion of the refrigerant in the primary circuit. This expansion was represented by a pressure disturbance in step form, through the block 'step' of SIMULINK, thus enabling the transient startup. The results showed that the dynamic tool, obtained through the coupling of the codes, generated very satisfactory responses within model limitations, preserving the most important phenomena in the process. (author)

  10. Development of a computer code for dynamic analysis of the primary circuit of advanced reactors

    International Nuclear Information System (INIS)

    Rocha, Jussie Soares da; Lira, Carlos A.B.O.; Magalhaes, Mardson A. de Sa

    2011-01-01

    Currently, advanced reactors are being developed, seeking for enhanced safety, better performance and low environmental impacts. Reactor designs must follow several steps and numerous tests before a conceptual project could be certified. In this sense, computational tools become indispensable in the preparation of such projects. Thus, this study aimed at the development of a computational tool for thermal-hydraulic analysis by coupling two computer codes to evaluate the influence of transients caused by pressure variations and flow surges in the region of the primary circuit of IRIS reactor between the core and the pressurizer. For the simulation, it was used a situation of 'insurge', characterized by the entry of water in the pressurizer, due to the expansion of the refrigerant in the primary circuit. This expansion was represented by a pressure disturbance in step form, through the block 'step' of SIMULINK, thus enabling the transient startup. The results showed that the dynamic tool, obtained through the coupling of the codes, generated very satisfactory responses within model limitations, preserving the most important phenomena in the process. (author)

  11. Frequency of reporting and predictive factors for anxiety and depression in patients with advanced cancer.

    Science.gov (United States)

    Salvo, N; Zeng, L; Zhang, L; Leung, M; Khan, L; Presutti, R; Nguyen, J; Holden, L; Culleton, S; Chow, E

    2012-03-01

    The prevalence of anxiety and depression in patients with advanced cancer has been reported to be on average 25% and to significantly affect patients' quality of life. Despite high prevalence rates, these disorders remain underdiagnosed and undertreated. The purpose of our study was to examine the self-report rates of anxiety and depression with the Edmonton Symptom Assessment System (ESAS) and to assess the predictive factors for these reports in cancer patients with metastatic disease. Consecutive patients who attended the Rapid Response Radiotherapy Program (RRRP) completed the ESAS as well as baseline demographic information. Ordinal logistic regression analysis was used to determine factors that significantly predicted anxiety and/or depression. Pearson χ(2) was used to test goodness-of-fit for categorical variables and established whether or not an observed frequency distribution differed from a predicted frequency distribution. A univariate analysis was conducted first and those variables with a P valueanalysis. A score test was used to test the proportional odds assumption. In total, 1439 patients seen in the RRRP between January 1999 and October 2009 completed ESAS questionnaires. Fifty-five per cent of patients reported at least mild symptoms of depression and 65% reported at least mild anxiety. In the univariate analysis, patients who were female, who had a lower performance status score, or primary lung cancer were more likely to report depressed and anxious feelings. Primary prostate cancer patients were significantly less likely to report depression and anxiety. Patients referred for spinal cord compression were significantly less depressed. The multivariate models showed that younger patients were significantly more anxious than older patients and females reported more anxiety than males. Patients who reported higher feelings of nausea, tiredness, drowsiness, dyspnoea, and worse appetite and overall well-being on the ESAS tool were more likely to

  12. Simulation and high performance computing-Building a predictive capability for fusion

    International Nuclear Information System (INIS)

    Strand, P.I.; Coelho, R.; Coster, D.; Eriksson, L.-G.; Imbeaux, F.; Guillerminet, Bernard

    2010-01-01

    The Integrated Tokamak Modelling Task Force (ITM-TF) is developing an infrastructure where the validation needs, as being formulated in terms of multi-device data access and detailed physics comparisons aiming for inclusion of synthetic diagnostics in the simulation chain, are key components. As the activity and the modelling tools are aimed for general use, although focused on ITER plasmas, a device independent approach to data transport and a standardized approach to data management (data structures, naming, and access) is being developed in order to allow cross-validation between different fusion devices using a single toolset. Extensive work has already gone into, and is continuing to go into, the development of standardized descriptions of the data (Consistent Physical Objects). The longer term aim is a complete simulation platform which is expected to last and be extended in different ways for the coming 30 years. The technical underpinning is therefore of vital importance. In particular the platform needs to be extensible and open-ended to be able to take full advantage of not only today's most advanced technologies but also be able to marshal future developments. As a full level comprehensive prediction of ITER physics rapidly becomes expensive in terms of computing resources, the simulation framework needs to be able to use both grid and HPC computing facilities. Hence data access and code coupling technologies are required to be available for a heterogeneous, possibly distributed, environment. The developments in this area are pursued in a separate project-EUFORIA (EU Fusion for ITER Applications) which is providing about 15 professional person year (ppy) per annum from 14 different institutes. The range and size of the activity is not only technically challenging but is providing some unique management challenges in that a large and geographically distributed team (a truly pan-European set of researchers) need to be coordinated on a fairly detailed

  13. Towards pattern generation and chaotic series prediction with photonic reservoir computers

    Science.gov (United States)

    Antonik, Piotr; Hermans, Michiel; Duport, François; Haelterman, Marc; Massar, Serge

    2016-03-01

    Reservoir Computing is a bio-inspired computing paradigm for processing time dependent signals that is particularly well suited for analog implementations. Our team has demonstrated several photonic reservoir computers with performance comparable to digital algorithms on a series of benchmark tasks such as channel equalisation and speech recognition. Recently, we showed that our opto-electronic reservoir computer could be trained online with a simple gradient descent algorithm programmed on an FPGA chip. This setup makes it in principle possible to feed the output signal back into the reservoir, and thus highly enrich the dynamics of the system. This will allow to tackle complex prediction tasks in hardware, such as pattern generation and chaotic and financial series prediction, which have so far only been studied in digital implementations. Here we report simulation results of our opto-electronic setup with an FPGA chip and output feedback applied to pattern generation and Mackey-Glass chaotic series prediction. The simulations take into account the major aspects of our experimental setup. We find that pattern generation can be easily implemented on the current setup with very good results. The Mackey-Glass series prediction task is more complex and requires a large reservoir and more elaborate training algorithm. With these adjustments promising result are obtained, and we now know what improvements are needed to match previously reported numerical results. These simulation results will serve as basis of comparison for experiments we will carry out in the coming months.

  14. Role of computer graphics in space telerobotics - Preview and predictive displays

    Science.gov (United States)

    Bejczy, Antal K.; Venema, Steven; Kim, Won S.

    1991-01-01

    The application of computer graphics in space telerobotics research and development work is briefly reviewed and illustrated by specific examples implemented in real time operation. The applications are discussed under the following four major categories: preview displays, predictive displays, sensor data displays, and control system status displays.

  15. Computer code to predict the heat of explosion of high energy materials

    International Nuclear Information System (INIS)

    Muthurajan, H.; Sivabalan, R.; Pon Saravanan, N.; Talawar, M.B.

    2009-01-01

    The computational approach to the thermochemical changes involved in the process of explosion of a high energy materials (HEMs) vis-a-vis its molecular structure aids a HEMs chemist/engineers to predict the important thermodynamic parameters such as heat of explosion of the HEMs. Such a computer-aided design will be useful in predicting the performance of a given HEM as well as in conceiving futuristic high energy molecules that have significant potential in the field of explosives and propellants. The software code viz., LOTUSES developed by authors predicts various characteristics of HEMs such as explosion products including balanced explosion reactions, density of HEMs, velocity of detonation, CJ pressure, etc. The new computational approach described in this paper allows the prediction of heat of explosion (ΔH e ) without any experimental data for different HEMs, which are comparable with experimental results reported in literature. The new algorithm which does not require any complex input parameter is incorporated in LOTUSES (version 1.5) and the results are presented in this paper. The linear regression analysis of all data point yields the correlation coefficient R 2 = 0.9721 with a linear equation y = 0.9262x + 101.45. The correlation coefficient value 0.9721 reveals that the computed values are in good agreement with experimental values and useful for rapid hazard assessment of energetic materials

  16. Prediction of intramuscular fat levels in Texel lamb loins using X-ray computed tomography scanning.

    Science.gov (United States)

    Clelland, N; Bunger, L; McLean, K A; Conington, J; Maltin, C; Knott, S; Lambe, N R

    2014-10-01

    For the consumer, tenderness, juiciness and flavour are often described as the most important factors for meat eating quality, all of which have a close association with intramuscular fat (IMF). X-ray computed tomography (CT) can measure fat, muscle and bone volumes and weights, in vivo in sheep and CT predictions of carcass composition have been used in UK sheep breeding programmes over the last few decades. This study aimed to determine the most accurate combination of CT variables to predict IMF percentage of M. longissimus lumborum in Texel lambs. As expected, predicted carcass fat alone accounted for a moderate amount of the variation (R(2)=0.51) in IMF. Prediction accuracies were significantly improved (Adj R(2)>0.65) using information on fat and muscle densities measured from three CT reference scans, showing that CT can provide an accurate prediction of IMF in the loin of purebred Texel sheep. Copyright © 2014. Published by Elsevier Ltd.

  17. THE INTEGRATED USE OF COMPUTATIONAL CHEMISTRY, SCANNING PROBE MICROSCOPY, AND VIRTUAL REALITY TO PREDICT THE CHEMICAL REACTIVITY OF ENVIRONMENTAL SURFACES

    Science.gov (United States)

    In the last decade three new techniques scanning probe microscopy (SPM), virtual reality (YR) and computational chemistry ave emerged with the combined capability of a priori predicting the chemically reactivity of environmental surfaces. Computational chemistry provides the cap...

  18. Advances in Rosetta structure prediction for difficult molecular-replacement problems

    International Nuclear Information System (INIS)

    DiMaio, Frank

    2013-01-01

    Modeling advances using Rosetta structure prediction to aid in solving difficult molecular-replacement problems are discussed. Recent work has shown the effectiveness of structure-prediction methods in solving difficult molecular-replacement problems. The Rosetta protein structure modeling suite can aid in the solution of difficult molecular-replacement problems using templates from 15 to 25% sequence identity; Rosetta refinement guided by noisy density has consistently led to solved structures where other methods fail. In this paper, an overview of the use of Rosetta for these difficult molecular-replacement problems is provided and new modeling developments that further improve model quality are described. Several variations to the method are introduced that significantly reduce the time needed to generate a model and the sampling required to improve the starting template. The improvements are benchmarked on a set of nine difficult cases and it is shown that this improved method obtains consistently better models in less running time. Finally, strategies for best using Rosetta to solve difficult molecular-replacement problems are presented and future directions for the role of structure-prediction methods in crystallography are discussed

  19. Predicting Relapse among Young Adults: Psychometric Validation of the Advanced Warning of Relapse (AWARE) Scale

    Science.gov (United States)

    Kelly, John F.; Hoeppner, Bettina B.; Urbanoski, Karen A.; Slaymaker, Valerie

    2011-01-01

    Objective Failure to maintain abstinence despite incurring severe harm is perhaps the key defining feature of addiction. Relapse prevention strategies have been developed to attenuate this propensity to relapse, but predicting who will, and who will not, relapse has stymied attempts to more efficiently tailor treatments according to relapse risk profile. Here we examine the psychometric properties of a promising relapse risk measure - the Advance WArning of RElapse scale (AWARE) scale (Miller and Harris, 2000) in an understudied but clinically important sample of young adults. Method Inpatient youth (N=303; Age 18-24; 26% female) completed the AWARE scale and the Brief Symptom Inventory-18 (BSI) at the end of residential treatment, and at 1-, 3-, and 6-months following discharge. Internal and convergent validity was tested for each of these four timepoints using confirmatory factor analysis and correlations (with BSI scores). Predictive validity was tested for relapse 1, 3, and 6 months following discharge, as was incremental utility, where AWARE scores were used as predictors of any substance use while controlling for treatment entry substance use severity and having spent time in a controlled environment following treatment. Results Confirmatory factor analysis revealed a single, internally consistent, 25-item factor that demonstrated convergent validity and predicted subsequent relapse alone and when controlling for other important relapse risk predictors. Conclusions The AWARE scale may be a useful and efficient clinical tool for assessing short-term relapse risk among young people and, thus, could serve to enhance the effectiveness of relapse prevention efforts. PMID:21700396

  20. Predicting relapse among young adults: psychometric validation of the Advanced WArning of RElapse (AWARE) scale.

    Science.gov (United States)

    Kelly, John F; Hoeppner, Bettina B; Urbanoski, Karen A; Slaymaker, Valerie

    2011-10-01

    Failure to maintain abstinence despite incurring severe harm is perhaps the key defining feature of addiction. Relapse prevention strategies have been developed to attenuate this propensity to relapse, but predicting who will, and who will not, relapse has stymied attempts to more efficiently tailor treatments according to relapse risk profile. Here we examine the psychometric properties of a promising relapse risk measure-the Advance WArning of RElapse (AWARE) scale (Miller & Harris, 2000) in an understudied but clinically important sample of young adults. Inpatient youth (N=303; Ages 18-24; 26% female) completed the AWARE scale and the Brief Symptom Inventory-18 (BSI) at the end of residential treatment, and at 1-, 3-, and 6-months following discharge. Internal and convergent validity was tested for each of these four timepoints using confirmatory factor analysis and correlations (with BSI scores). Predictive validity was tested for relapse 1, 3, and 6 months following discharge, as was incremental utility, where AWARE scores were used as predictors of any substance use while controlling for treatment entry substance use severity and having spent time in a controlled environment following treatment. Confirmatory factor analysis revealed a single, internally consistent, 25-item factor that demonstrated convergent validity and predicted subsequent relapse alone and when controlling for other important relapse risk predictors. The AWARE scale may be a useful and efficient clinical tool for assessing short-term relapse risk among young people and, thus, could serve to enhance the effectiveness of relapse prevention efforts. Copyright © 2011 Elsevier Ltd. All rights reserved.

  1. Multiple-Swarm Ensembles: Improving the Predictive Power and Robustness of Predictive Models and Its Use in Computational Biology.

    Science.gov (United States)

    Alves, Pedro; Liu, Shuang; Wang, Daifeng; Gerstein, Mark

    2018-01-01

    Machine learning is an integral part of computational biology, and has already shown its use in various applications, such as prognostic tests. In the last few years in the non-biological machine learning community, ensembling techniques have shown their power in data mining competitions such as the Netflix challenge; however, such methods have not found wide use in computational biology. In this work, we endeavor to show how ensembling techniques can be applied to practical problems, including problems in the field of bioinformatics, and how they often outperform other machine learning techniques in both predictive power and robustness. Furthermore, we develop a methodology of ensembling, Multi-Swarm Ensemble (MSWE) by using multiple particle swarm optimizations and demonstrate its ability to further enhance the performance of ensembles.

  2. Computer programs for capital cost estimation, lifetime economic performance simulation, and computation of cost indexes for laser fusion and other advanced technology facilities

    International Nuclear Information System (INIS)

    Pendergrass, J.H.

    1978-01-01

    Three FORTRAN programs, CAPITAL, VENTURE, and INDEXER, have been developed to automate computations used in assessing the economic viability of proposed or conceptual laser fusion and other advanced-technology facilities, as well as conventional projects. The types of calculations performed by these programs are, respectively, capital cost estimation, lifetime economic performance simulation, and computation of cost indexes. The codes permit these three topics to be addressed with considerable sophistication commensurate with user requirements and available data

  3. In silico toxicology: computational methods for the prediction of chemical toxicity

    KAUST Repository

    Raies, Arwa B.; Bajic, Vladimir B.

    2016-01-01

    Determining the toxicity of chemicals is necessary to identify their harmful effects on humans, animals, plants, or the environment. It is also one of the main steps in drug design. Animal models have been used for a long time for toxicity testing. However, in vivo animal tests are constrained by time, ethical considerations, and financial burden. Therefore, computational methods for estimating the toxicity of chemicals are considered useful. In silico toxicology is one type of toxicity assessment that uses computational methods to analyze, simulate, visualize, or predict the toxicity of chemicals. In silico toxicology aims to complement existing toxicity tests to predict toxicity, prioritize chemicals, guide toxicity tests, and minimize late-stage failures in drugs design. There are various methods for generating models to predict toxicity endpoints. We provide a comprehensive overview, explain, and compare the strengths and weaknesses of the existing modeling methods and algorithms for toxicity prediction with a particular (but not exclusive) emphasis on computational tools that can implement these methods and refer to expert systems that deploy the prediction models. Finally, we briefly review a number of new research directions in in silico toxicology and provide recommendations for designing in silico models.

  4. In silico toxicology: computational methods for the prediction of chemical toxicity

    KAUST Repository

    Raies, Arwa B.

    2016-01-06

    Determining the toxicity of chemicals is necessary to identify their harmful effects on humans, animals, plants, or the environment. It is also one of the main steps in drug design. Animal models have been used for a long time for toxicity testing. However, in vivo animal tests are constrained by time, ethical considerations, and financial burden. Therefore, computational methods for estimating the toxicity of chemicals are considered useful. In silico toxicology is one type of toxicity assessment that uses computational methods to analyze, simulate, visualize, or predict the toxicity of chemicals. In silico toxicology aims to complement existing toxicity tests to predict toxicity, prioritize chemicals, guide toxicity tests, and minimize late-stage failures in drugs design. There are various methods for generating models to predict toxicity endpoints. We provide a comprehensive overview, explain, and compare the strengths and weaknesses of the existing modeling methods and algorithms for toxicity prediction with a particular (but not exclusive) emphasis on computational tools that can implement these methods and refer to expert systems that deploy the prediction models. Finally, we briefly review a number of new research directions in in silico toxicology and provide recommendations for designing in silico models.

  5. Use of computer-assisted prediction of toxic effects of chemical substances

    International Nuclear Information System (INIS)

    Simon-Hettich, Brigitte; Rothfuss, Andreas; Steger-Hartmann, Thomas

    2006-01-01

    The current revision of the European policy for the evaluation of chemicals (REACH) has lead to a controversy with regard to the need of additional animal safety testing. To avoid increases in animal testing but also to save time and resources, alternative in silico or in vitro tests for the assessment of toxic effects of chemicals are advocated. The draft of the original document issued in 29th October 2003 by the European Commission foresees the use of alternative methods but does not give further specification on which methods should be used. Computer-assisted prediction models, so-called predictive tools, besides in vitro models, will likely play an essential role in the proposed repertoire of 'alternative methods'. The current discussion has urged the Advisory Committee of the German Toxicology Society to present its position on the use of predictive tools in toxicology. Acceptable prediction models already exist for those toxicological endpoints which are based on well-understood mechanism, such as mutagenicity and skin sensitization, whereas mechanistically more complex endpoints such as acute, chronic or organ toxicities currently cannot be satisfactorily predicted. A potential strategy to assess such complex toxicities will lie in their dissection into models for the different steps or pathways leading to the final endpoint. Integration of these models should result in a higher predictivity. Despite these limitations, computer-assisted prediction tools already today play a complementary role for the assessment of chemicals for which no data is available or for which toxicological testing is impractical due to the lack of availability of sufficient compounds for testing. Furthermore, predictive tools offer support in the screening and the subsequent prioritization of compound for further toxicological testing, as expected within the scope of the European REACH program. This program will also lead to the collection of high-quality data which will broaden the

  6. Comparison of the Berg Balance Scale and Fullerton Advanced Balance Scale to predict falls in community-dwelling adults.

    Science.gov (United States)

    Jeon, Yong-Jin; Kim, Gyoung-Mo

    2017-02-01

    [Purpose] The purpose of this study was to investigate and compare the predictive properties of Berg Balance Scale and Fullerton Advanced Balance Scales, in a group of independently-functioning community dwelling older adults. [Subjects and Methods] Ninety-seven community-dwelling older adults (male=39, female=58) who were capable of walking independently on assessment were included in this study. A binary logistic regression analysis of the Berg Balance Scale and Fullerton Advanced Balance Scale scores was used to investigate a predictive model for fall risk. A receiver operating characteristic analysis was conducted for each, to determine the cut-off for optimal levels of sensitivity and specificity. [Results] The overall prediction success rate was 89.7%; the total Berg Balance Scale and Fullerton Advanced Balance Scale scores were significant in predicting fall risk. Receiver operating characteristic analysis determined that a cut-off score of 40 out of 56 on the Berg Balance Scale produced the highest sensitivity (0.82) and specificity (0.67), and a cut-off score of 22 out of 40 on the Fullerton Advanced Balance Scale produced the highest sensitivity (0.85) and specificity (0.65) in predicting faller status. [Conclusion] The Berg Balance Scale and Fullerton Advanced Balance Scales can predict fall risk, when used for independently-functioning community-dwelling older adults.

  7. Advanced Scientific Computing Research Network Requirements: ASCR Network Requirements Review Final Report

    Energy Technology Data Exchange (ETDEWEB)

    Bacon, Charles [Argonne National Lab. (ANL), Argonne, IL (United States); Bell, Greg [ESnet, Berkeley, CA (United States); Canon, Shane [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Dart, Eli [ESnet, Berkeley, CA (United States); Dattoria, Vince [Dept. of Energy (DOE), Washington DC (United States). Office of Science. Advanced Scientific Computing Research (ASCR); Goodwin, Dave [Dept. of Energy (DOE), Washington DC (United States). Office of Science. Advanced Scientific Computing Research (ASCR); Lee, Jason [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Hicks, Susan [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Holohan, Ed [Argonne National Lab. (ANL), Argonne, IL (United States); Klasky, Scott [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Lauzon, Carolyn [Dept. of Energy (DOE), Washington DC (United States). Office of Science. Advanced Scientific Computing Research (ASCR); Rogers, Jim [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Shipman, Galen [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Skinner, David [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Tierney, Brian [ESnet, Berkeley, CA (United States)

    2013-03-08

    The Energy Sciences Network (ESnet) is the primary provider of network connectivity for the U.S. Department of Energy (DOE) Office of Science (SC), the single largest supporter of basic research in the physical sciences in the United States. In support of SC programs, ESnet regularly updates and refreshes its understanding of the networking requirements of the instruments, facilities, scientists, and science programs that it serves. This focus has helped ESnet to be a highly successful enabler of scientific discovery for over 25 years. In October 2012, ESnet and the Office of Advanced Scientific Computing Research (ASCR) of the DOE SC organized a review to characterize the networking requirements of the programs funded by the ASCR program office. The requirements identified at the review are summarized in the Findings section, and are described in more detail in the body of the report.

  8. Radical decomposition of 2,4-dinitrotoluene (DNT at conditions of advanced oxidation. Computational study

    Directory of Open Access Journals (Sweden)

    Liudmyla K. Sviatenko

    2016-12-01

    Full Text Available At the present time one of the main remediation technologies for such environmental pollutant as 2,4-dinitrotoluene (DNT is advanced oxidation processes (AOPs. Since hydroxyl radical is the most common active species for AOPs, in particular for Fenton oxidation, the study modeled mechanism of interaction between DNT and hydroxyl radical at SMD(Pauling/M06-2X/6-31+G(d,p level. Computed results allow to suggest the most energetically favourable pathway for the process. DNT decomposition consists of sequential hydrogen abstractions and hydroxyl attachments passing through 2,4-dinitrobenzyl alcohol, 2,4-dinitrobenzaldehyde, and 2,4-dinitrobenzoic acid. Further replacement of nitro- and carboxyl groups by hydroxyl leads to 2,4-dihydroxybenzoic acid and 2,4-dinitrophenol, respectively. Reaction intermediates and products are experimentally confirmed. Mostly of reaction steps have low energy barriers, some steps are diffusion controlled. The whole process is highly exothermic.

  9. Advanced neural network-based computational schemes for robust fault diagnosis

    CERN Document Server

    Mrugalski, Marcin

    2014-01-01

    The present book is devoted to problems of adaptation of artificial neural networks to robust fault diagnosis schemes. It presents neural networks-based modelling and estimation techniques used for designing robust fault diagnosis schemes for non-linear dynamic systems. A part of the book focuses on fundamental issues such as architectures of dynamic neural networks, methods for designing of neural networks and fault diagnosis schemes as well as the importance of robustness. The book is of a tutorial value and can be perceived as a good starting point for the new-comers to this field. The book is also devoted to advanced schemes of description of neural model uncertainty. In particular, the methods of computation of neural networks uncertainty with robust parameter estimation are presented. Moreover, a novel approach for system identification with the state-space GMDH neural network is delivered. All the concepts described in this book are illustrated by both simple academic illustrative examples and practica...

  10. Experiences with the ACPMAPS (Advanced Computer Program Multiple Array Processor System) 50 GFLOP system

    International Nuclear Information System (INIS)

    Fischler, M.

    1992-10-01

    The Fermilab Computer R ampersand D and Theory departments have for several years collaborated on a multi-GFLOP (recently upgraded to 50 GFLOP) system for lattice gauge calculations. The primary emphasis is on flexibility and ease of algorithm development. This system (ACPMAPS) has been in use for some time, allowing theorists to produce QCD results with relevance for the analysis of experimental data. We present general observations about benefits of such a scientist-oriented system, and summarize some of the advances recently made. We also discuss what was discovered about features needed in a useful algorithm exploration platform. These lessons can be applied to the design and evaluation of future massively parallel systems (commercial or otherwise)

  11. Computer-aided and predictive models for design of controlled release of pesticides

    DEFF Research Database (Denmark)

    Suné, Nuria Muro; Gani, Rafiqul

    2004-01-01

    In the field of pesticide controlled release technology, a computer based model that can predict the delivery of the Active Ingredient (AI) from fabricated units is important for purposes of product design and marketing. A model for the release of an M from a microcapsule device is presented...... in this paper, together with a specific case study application to highlight its scope and significance. The paper also addresses the need for predictive models and proposes a computer aided modelling framework for achieving it through the development and introduction of reliable and predictive constitutive...... models. A group-contribution based model for one of the constitutive variables (AI solubility in polymers) is presented together with examples of application and validation....

  12. Prediction of the Thermal Conductivity of Refrigerants by Computational Methods and Artificial Neural Network.

    Science.gov (United States)

    Ghaderi, Forouzan; Ghaderi, Amir H; Ghaderi, Noushin; Najafi, Bijan

    2017-01-01

    Background: The thermal conductivity of fluids can be calculated by several computational methods. However, these methods are reliable only at the confined levels of density, and there is no specific computational method for calculating thermal conductivity in the wide ranges of density. Methods: In this paper, two methods, an Artificial Neural Network (ANN) approach and a computational method established upon the Rainwater-Friend theory, were used to predict the value of thermal conductivity in all ranges of density. The thermal conductivity of six refrigerants, R12, R14, R32, R115, R143, and R152 was predicted by these methods and the effectiveness of models was specified and compared. Results: The results show that the computational method is a usable method for predicting thermal conductivity at low levels of density. However, the efficiency of this model is considerably reduced in the mid-range of density. It means that this model cannot be used at density levels which are higher than 6. On the other hand, the ANN approach is a reliable method for thermal conductivity prediction in all ranges of density. The best accuracy of ANN is achieved when the number of units is increased in the hidden layer. Conclusion: The results of the computational method indicate that the regular dependence between thermal conductivity and density at higher densities is eliminated. It can develop a nonlinear problem. Therefore, analytical approaches are not able to predict thermal conductivity in wide ranges of density. Instead, a nonlinear approach such as, ANN is a valuable method for this purpose.

  13. TRAC-PF1: an advanced best-estimate computer program for pressurized water reactor analysis

    International Nuclear Information System (INIS)

    Liles, D.R.; Mahaffy, J.H.

    1984-02-01

    The Transient Reactor Analysis Code (TRAC) is being developed at the Los Alamos National Laboratory to provide advanced best-estimate predictions of postulated accidents in light water reactors. The TRAC-PF1 program provides this capability for pressurized water reactors and for many thermal-hydraulic experimental facilities. The code features either a one-dimensional or a three-dimensional treatment of the pressure vessel and its associated internals; a two-phase, two-fluid nonequilibrium hydrodynamics model with a noncondensable gas field; flow-regime-dependent constitutive equation treatment; optional reflood tracking capability for both bottom flood and falling-film quench fronts; and consistent treatment of entire accident sequences including the generation of consistent initial conditions. This report describes the thermal-hydraulic models and the numerical solution methods used in the code. Detailed programming and user information also are provided

  14. Computational Efficient Upscaling Methodology for Predicting Thermal Conductivity of Nuclear Waste forms

    International Nuclear Information System (INIS)

    Li, Dongsheng; Sun, Xin; Khaleel, Mohammad A.

    2011-01-01

    This study evaluated different upscaling methods to predict thermal conductivity in loaded nuclear waste form, a heterogeneous material system. The efficiency and accuracy of these methods were compared. Thermal conductivity in loaded nuclear waste form is an important property specific to scientific researchers, in waste form Integrated performance and safety code (IPSC). The effective thermal conductivity obtained from microstructure information and local thermal conductivity of different components is critical in predicting the life and performance of waste form during storage. How the heat generated during storage is directly related to thermal conductivity, which in turn determining the mechanical deformation behavior, corrosion resistance and aging performance. Several methods, including the Taylor model, Sachs model, self-consistent model, and statistical upscaling models were developed and implemented. Due to the absence of experimental data, prediction results from finite element method (FEM) were used as reference to determine the accuracy of different upscaling models. Micrographs from different loading of nuclear waste were used in the prediction of thermal conductivity. Prediction results demonstrated that in term of efficiency, boundary models (Taylor and Sachs model) are better than self consistent model, statistical upscaling method and FEM. Balancing the computation resource and accuracy, statistical upscaling is a computational efficient method in predicting effective thermal conductivity for nuclear waste form.

  15. A computational environment for long-term multi-feature and multi-algorithm seizure prediction.

    Science.gov (United States)

    Teixeira, C A; Direito, B; Costa, R P; Valderrama, M; Feldwisch-Drentrup, H; Nikolopoulos, S; Le Van Quyen, M; Schelter, B; Dourado, A

    2010-01-01

    The daily life of epilepsy patients is constrained by the possibility of occurrence of seizures. Until now, seizures cannot be predicted with sufficient sensitivity and specificity. Most of the seizure prediction studies have been focused on a small number of patients, and frequently assuming unrealistic hypothesis. This paper adopts the view that for an appropriate development of reliable predictors one should consider long-term recordings and several features and algorithms integrated in one software tool. A computational environment, based on Matlab (®), is presented, aiming to be an innovative tool for seizure prediction. It results from the need of a powerful and flexible tool for long-term EEG/ECG analysis by multiple features and algorithms. After being extracted, features can be subjected to several reduction and selection methods, and then used for prediction. The predictions can be conducted based on optimized thresholds or by applying computational intelligence methods. One important aspect is the integrated evaluation of the seizure prediction characteristic of the developed predictors.

  16. Improving Computational Efficiency of Prediction in Model-Based Prognostics Using the Unscented Transform

    Science.gov (United States)

    Daigle, Matthew John; Goebel, Kai Frank

    2010-01-01

    Model-based prognostics captures system knowledge in the form of physics-based models of components, and how they fail, in order to obtain accurate predictions of end of life (EOL). EOL is predicted based on the estimated current state distribution of a component and expected profiles of future usage. In general, this requires simulations of the component using the underlying models. In this paper, we develop a simulation-based prediction methodology that achieves computational efficiency by performing only the minimal number of simulations needed in order to accurately approximate the mean and variance of the complete EOL distribution. This is performed through the use of the unscented transform, which predicts the means and covariances of a distribution passed through a nonlinear transformation. In this case, the EOL simulation acts as that nonlinear transformation. In this paper, we review the unscented transform, and describe how this concept is applied to efficient EOL prediction. As a case study, we develop a physics-based model of a solenoid valve, and perform simulation experiments to demonstrate improved computational efficiency without sacrificing prediction accuracy.

  17. Government Cloud Computing Policies: Potential Opportunities for Advancing Military Biomedical Research.

    Science.gov (United States)

    Lebeda, Frank J; Zalatoris, Jeffrey J; Scheerer, Julia B

    2018-02-07

    indicated that the security infrastructure in cloud services may be more compliant with the Health Insurance Portability and Accountability Act of 1996 regulations than traditional methods. To gauge the DoD's adoption of cloud technologies proposed metrics included cost factors, ease of use, automation, availability, accessibility, security, and policy compliance. Since 2009, plans and policies were developed for the use of cloud technology to help consolidate and reduce the number of data centers which were expected to reduce costs, improve environmental factors, enhance information technology security, and maintain mission support for service members. Cloud technologies were also expected to improve employee efficiency and productivity. Federal cloud computing policies within the last decade also offered increased opportunities to advance military healthcare. It was assumed that these opportunities would benefit consumers of healthcare and health science data by allowing more access to centralized cloud computer facilities to store, analyze, search and share relevant data, to enhance standardization, and to reduce potential duplications of effort. We recommend that cloud computing be considered by DoD biomedical researchers for increasing connectivity, presumably by facilitating communications and data sharing, among the various intra- and extramural laboratories. We also recommend that policies and other guidances be updated to include developing additional metrics that will help stakeholders evaluate the above mentioned assumptions and expectations. Published by Oxford University Press on behalf of the Association of Military Surgeons of the United States 2018. This work is written by (a) US Government employee(s) and is in the public domain in the US.

  18. COMPUTING

    CERN Multimedia

    I. Fisk

    2011-01-01

    Introduction CMS distributed computing system performed well during the 2011 start-up. The events in 2011 have more pile-up and are more complex than last year; this results in longer reconstruction times and harder events to simulate. Significant increases in computing capacity were delivered in April for all computing tiers, and the utilisation and load is close to the planning predictions. All computing centre tiers performed their expected functionalities. Heavy-Ion Programme The CMS Heavy-Ion Programme had a very strong showing at the Quark Matter conference. A large number of analyses were shown. The dedicated heavy-ion reconstruction facility at the Vanderbilt Tier-2 is still involved in some commissioning activities, but is available for processing and analysis. Facilities and Infrastructure Operations Facility and Infrastructure operations have been active with operations and several important deployment tasks. Facilities participated in the testing and deployment of WMAgent and WorkQueue+Request...

  19. Derivation and External Validation of Prediction Models for Advanced Chronic Kidney Disease Following Acute Kidney Injury.

    Science.gov (United States)

    James, Matthew T; Pannu, Neesh; Hemmelgarn, Brenda R; Austin, Peter C; Tan, Zhi; McArthur, Eric; Manns, Braden J; Tonelli, Marcello; Wald, Ron; Quinn, Robert R; Ravani, Pietro; Garg, Amit X

    2017-11-14

    Some patients will develop chronic kidney disease after a hospitalization with acute kidney injury; however, no risk-prediction tools have been developed to identify high-risk patients requiring follow-up. To derive and validate predictive models for progression of acute kidney injury to advanced chronic kidney disease. Data from 2 population-based cohorts of patients with a prehospitalization estimated glomerular filtration rate (eGFR) of more than 45 mL/min/1.73 m2 and who had survived hospitalization with acute kidney injury (defined by a serum creatinine increase during hospitalization > 0.3 mg/dL or > 50% of their prehospitalization baseline), were used to derive and validate multivariable prediction models. The risk models were derived from 9973 patients hospitalized in Alberta, Canada (April 2004-March 2014, with follow-up to March 2015). The risk models were externally validated with data from a cohort of 2761 patients hospitalized in Ontario, Canada (June 2004-March 2012, with follow-up to March 2013). Demographic, laboratory, and comorbidity variables measured prior to discharge. Advanced chronic kidney disease was defined by a sustained reduction in eGFR less than 30 mL/min/1.73 m2 for at least 3 months during the year after discharge. All participants were followed up for up to 1 year. The participants (mean [SD] age, 66 [15] years in the derivation and internal validation cohorts and 69 [11] years in the external validation cohort; 40%-43% women per cohort) had a mean (SD) baseline serum creatinine level of 1.0 (0.2) mg/dL and more than 20% had stage 2 or 3 acute kidney injury. Advanced chronic kidney disease developed in 408 (2.7%) of 9973 patients in the derivation cohort and 62 (2.2%) of 2761 patients in the external validation cohort. In the derivation cohort, 6 variables were independently associated with the outcome: older age, female sex, higher baseline serum creatinine value, albuminuria, greater severity of acute kidney injury, and higher

  20. Integrating Crop Growth Models with Whole Genome Prediction through Approximate Bayesian Computation.

    Directory of Open Access Journals (Sweden)

    Frank Technow

    Full Text Available Genomic selection, enabled by whole genome prediction (WGP methods, is revolutionizing plant breeding. Existing WGP methods have been shown to deliver accurate predictions in the most common settings, such as prediction of across environment performance for traits with additive gene effects. However, prediction of traits with non-additive gene effects and prediction of genotype by environment interaction (G×E, continues to be challenging. Previous attempts to increase prediction accuracy for these particularly difficult tasks employed prediction methods that are purely statistical in nature. Augmenting the statistical methods with biological knowledge has been largely overlooked thus far. Crop growth models (CGMs attempt to represent the impact of functional relationships between plant physiology and the environment in the formation of yield and similar output traits of interest. Thus, they can explain the impact of G×E and certain types of non-additive gene effects on the expressed phenotype. Approximate Bayesian computation (ABC, a novel and powerful computational procedure, allows the incorporation of CGMs directly into the estimation of whole genome marker effects in WGP. Here we provide a proof of concept study for this novel approach and demonstrate its use with synthetic data sets. We show that this novel approach can be considerably more accurate than the benchmark WGP method GBLUP in predicting performance in environments represented in the estimation set as well as in previously unobserved environments for traits determined by non-additive gene effects. We conclude that this proof of concept demonstrates that using ABC for incorporating biological knowledge in the form of CGMs into WGP is a very promising and novel approach to improving prediction accuracy for some of the most challenging scenarios in plant breeding and applied genetics.