COMPUTATIONAL TOXICOLOGY: FRAMEWORK, PARTNERSHIPS, AND PROGRAM DEVELOPMENT

EPA Science Inventory

Computational toxicology is a new research initiative being developed within the Office of Research and Development (ORD) of the US Environmental Protection Agency (EPA). Operationally, it is defined as the application of mathematical and computer models together with molecular c...

Conservative Forgetful Scholars: How People Learn Causal Structure through Sequences of Interventions

ERIC Educational Resources Information Center

Bramley, Neil R.; Lagnado, David A.; Speekenbrink, Maarten

2015-01-01

Interacting with a system is key to uncovering its causal structure. A computational framework for interventional causal learning has been developed over the last decade, but how real causal learners might achieve or approximate the computations entailed by this framework is still poorly understood. Here we describe an interactive computer task in…

A framework for development of an intelligent system for design and manufacturing of stamping dies

NASA Astrophysics Data System (ADS)

Hussein, H. M. A.; Kumar, S.

2014-07-01

An integration of computer aided design (CAD), computer aided process planning (CAPP) and computer aided manufacturing (CAM) is required for development of an intelligent system to design and manufacture stamping dies in sheet metal industries. In this paper, a framework for development of an intelligent system for design and manufacturing of stamping dies is proposed. In the proposed framework, the intelligent system is structured in form of various expert system modules for different activities of design and manufacturing of dies. All system modules are integrated with each other. The proposed system takes its input in form of a CAD file of sheet metal part, and then system modules automate all tasks related to design and manufacturing of stamping dies. Modules are coded using Visual Basic (VB) and developed on the platform of AutoCAD software.

A design automation framework for computational bioenergetics in biological networks.

PubMed

Angione, Claudio; Costanza, Jole; Carapezza, Giovanni; Lió, Pietro; Nicosia, Giuseppe

2013-10-01

The bioenergetic activity of mitochondria can be thoroughly investigated by using computational methods. In particular, in our work we focus on ATP and NADH, namely the metabolites representing the production of energy in the cell. We develop a computational framework to perform an exhaustive investigation at the level of species, reactions, genes and metabolic pathways. The framework integrates several methods implementing the state-of-the-art algorithms for many-objective optimization, sensitivity, and identifiability analysis applied to biological systems. We use this computational framework to analyze three case studies related to the human mitochondria and the algal metabolism of Chlamydomonas reinhardtii, formally described with algebraic differential equations or flux balance analysis. Integrating the results of our framework applied to interacting organelles would provide a general-purpose method for assessing the production of energy in a biological network.

Feasibility Study of a Generalized Framework for Developing Computer-Aided Detection Systems-a New Paradigm.

PubMed

Nemoto, Mitsutaka; Hayashi, Naoto; Hanaoka, Shouhei; Nomura, Yukihiro; Miki, Soichiro; Yoshikawa, Takeharu

2017-10-01

We propose a generalized framework for developing computer-aided detection (CADe) systems whose characteristics depend only on those of the training dataset. The purpose of this study is to show the feasibility of the framework. Two different CADe systems were experimentally developed by a prototype of the framework, but with different training datasets. The CADe systems include four components; preprocessing, candidate area extraction, candidate detection, and candidate classification. Four pretrained algorithms with dedicated optimization/setting methods corresponding to the respective components were prepared in advance. The pretrained algorithms were sequentially trained in the order of processing of the components. In this study, two different datasets, brain MRA with cerebral aneurysms and chest CT with lung nodules, were collected to develop two different types of CADe systems in the framework. The performances of the developed CADe systems were evaluated by threefold cross-validation. The CADe systems for detecting cerebral aneurysms in brain MRAs and for detecting lung nodules in chest CTs were successfully developed using the respective datasets. The framework was shown to be feasible by the successful development of the two different types of CADe systems. The feasibility of this framework shows promise for a new paradigm in the development of CADe systems: development of CADe systems without any lesion specific algorithm designing.

Innovative Science Experiments Using Phoenix

ERIC Educational Resources Information Center

Kumar, B. P. Ajith; Satyanarayana, V. V. V.; Singh, Kundan; Singh, Parmanand

2009-01-01

A simple, flexible and very low cost hardware plus software framework for developing computer-interfaced science experiments is presented. It can be used for developing computer-interfaced science experiments without getting into the details of electronics or computer programming. For developing experiments this is a middle path between…

Improving Conceptual Design for Launch Vehicles

NASA Technical Reports Server (NTRS)

Olds, John R.

1998-01-01

This report summarizes activities performed during the second year of a three year cooperative agreement between NASA - Langley Research Center and Georgia Tech. Year 1 of the project resulted in the creation of a new Cost and Business Assessment Model (CABAM) for estimating the economic performance of advanced reusable launch vehicles including non-recurring costs, recurring costs, and revenue. The current year (second year) activities were focused on the evaluation of automated, collaborative design frameworks (computation architectures or computational frameworks) for automating the design process in advanced space vehicle design. Consistent with NASA's new thrust area in developing and understanding Intelligent Synthesis Environments (ISE), the goals of this year's research efforts were to develop and apply computer integration techniques and near-term computational frameworks for conducting advanced space vehicle design. NASA - Langley (VAB) has taken a lead role in developing a web-based computing architectures within which the designer can interact with disciplinary analysis tools through a flexible web interface. The advantages of this approach are, 1) flexible access to the designer interface through a simple web browser (e.g. Netscape Navigator), 2) ability to include existing 'legacy' codes, and 3) ability to include distributed analysis tools running on remote computers. To date, VAB's internal emphasis has been on developing this test system for the planetary entry mission under the joint Integrated Design System (IDS) program with NASA - Ames and JPL. Georgia Tech's complementary goals this year were to: 1) Examine an alternate 'custom' computational architecture for the three-discipline IDS planetary entry problem to assess the advantages and disadvantages relative to the web-based approach.and 2) Develop and examine a web-based interface and framework for a typical launch vehicle design problem.

A non-voxel-based broad-beam (NVBB) framework for IMRT treatment planning.

PubMed

Lu, Weiguo

2010-12-07

We present a novel framework that enables very large scale intensity-modulated radiation therapy (IMRT) planning in limited computation resources with improvements in cost, plan quality and planning throughput. Current IMRT optimization uses a voxel-based beamlet superposition (VBS) framework that requires pre-calculation and storage of a large amount of beamlet data, resulting in large temporal and spatial complexity. We developed a non-voxel-based broad-beam (NVBB) framework for IMRT capable of direct treatment parameter optimization (DTPO). In this framework, both objective function and derivative are evaluated based on the continuous viewpoint, abandoning 'voxel' and 'beamlet' representations. Thus pre-calculation and storage of beamlets are no longer needed. The NVBB framework has linear complexities (O(N(3))) in both space and time. The low memory, full computation and data parallelization nature of the framework render its efficient implementation on the graphic processing unit (GPU). We implemented the NVBB framework and incorporated it with the TomoTherapy treatment planning system (TPS). The new TPS runs on a single workstation with one GPU card (NVBB-GPU). Extensive verification/validation tests were performed in house and via third parties. Benchmarks on dose accuracy, plan quality and throughput were compared with the commercial TomoTherapy TPS that is based on the VBS framework and uses a computer cluster with 14 nodes (VBS-cluster). For all tests, the dose accuracy of these two TPSs is comparable (within 1%). Plan qualities were comparable with no clinically significant difference for most cases except that superior target uniformity was seen in the NVBB-GPU for some cases. However, the planning time using the NVBB-GPU was reduced many folds over the VBS-cluster. In conclusion, we developed a novel NVBB framework for IMRT optimization. The continuous viewpoint and DTPO nature of the algorithm eliminate the need for beamlets and lead to better plan quality. The computation parallelization on a GPU instead of a computer cluster significantly reduces hardware and service costs. Compared with using the current VBS framework on a computer cluster, the planning time is significantly reduced using the NVBB framework on a single workstation with a GPU card.

Enterprise application architecture development based on DoDAF and TOGAF

NASA Astrophysics Data System (ADS)

Tao, Zhi-Gang; Luo, Yun-Feng; Chen, Chang-Xin; Wang, Ming-Zhe; Ni, Feng

2017-05-01

For the purpose of supporting the design and analysis of enterprise application architecture, here, we report a tailored enterprise application architecture description framework and its corresponding design method. The presented framework can effectively support service-oriented architecting and cloud computing by creating the metadata model based on architecture content framework (ACF), DoDAF metamodel (DM2) and Cloud Computing Modelling Notation (CCMN). The framework also makes an effort to extend and improve the mapping between The Open Group Architecture Framework (TOGAF) application architectural inputs/outputs, deliverables and Department of Defence Architecture Framework (DoDAF)-described models. The roadmap of 52 DoDAF-described models is constructed by creating the metamodels of these described models and analysing the constraint relationship among metamodels. By combining the tailored framework and the roadmap, this article proposes a service-oriented enterprise application architecture development process. Finally, a case study is presented to illustrate the results of implementing the tailored framework in the Southern Base Management Support and Information Platform construction project using the development process proposed by the paper.

Π4U: A high performance computing framework for Bayesian uncertainty quantification of complex models

NASA Astrophysics Data System (ADS)

Hadjidoukas, P. E.; Angelikopoulos, P.; Papadimitriou, C.; Koumoutsakos, P.

2015-03-01

We present Π4U, an extensible framework, for non-intrusive Bayesian Uncertainty Quantification and Propagation (UQ+P) of complex and computationally demanding physical models, that can exploit massively parallel computer architectures. The framework incorporates Laplace asymptotic approximations as well as stochastic algorithms, along with distributed numerical differentiation and task-based parallelism for heterogeneous clusters. Sampling is based on the Transitional Markov Chain Monte Carlo (TMCMC) algorithm and its variants. The optimization tasks associated with the asymptotic approximations are treated via the Covariance Matrix Adaptation Evolution Strategy (CMA-ES). A modified subset simulation method is used for posterior reliability measurements of rare events. The framework accommodates scheduling of multiple physical model evaluations based on an adaptive load balancing library and shows excellent scalability. In addition to the software framework, we also provide guidelines as to the applicability and efficiency of Bayesian tools when applied to computationally demanding physical models. Theoretical and computational developments are demonstrated with applications drawn from molecular dynamics, structural dynamics and granular flow.

Development of a Distributed Parallel Computing Framework to Facilitate Regional/Global Gridded Crop Modeling with Various Scenarios

NASA Astrophysics Data System (ADS)

Jang, W.; Engda, T. A.; Neff, J. C.; Herrick, J.

2017-12-01

Many crop models are increasingly used to evaluate crop yields at regional and global scales. However, implementation of these models across large areas using fine-scale grids is limited by computational time requirements. In order to facilitate global gridded crop modeling with various scenarios (i.e., different crop, management schedule, fertilizer, and irrigation) using the Environmental Policy Integrated Climate (EPIC) model, we developed a distributed parallel computing framework in Python. Our local desktop with 14 cores (28 threads) was used to test the distributed parallel computing framework in Iringa, Tanzania which has 406,839 grid cells. High-resolution soil data, SoilGrids (250 x 250 m), and climate data, AgMERRA (0.25 x 0.25 deg) were also used as input data for the gridded EPIC model. The framework includes a master file for parallel computing, input database, input data formatters, EPIC model execution, and output analyzers. Through the master file for parallel computing, the user-defined number of threads of CPU divides the EPIC simulation into jobs. Then, Using EPIC input data formatters, the raw database is formatted for EPIC input data and the formatted data moves into EPIC simulation jobs. Then, 28 EPIC jobs run simultaneously and only interesting results files are parsed and moved into output analyzers. We applied various scenarios with seven different slopes and twenty-four fertilizer ranges. Parallelized input generators create different scenarios as a list for distributed parallel computing. After all simulations are completed, parallelized output analyzers are used to analyze all outputs according to the different scenarios. This saves significant computing time and resources, making it possible to conduct gridded modeling at regional to global scales with high-resolution data. For example, serial processing for the Iringa test case would require 113 hours, while using the framework developed in this study requires only approximately 6 hours, a nearly 95% reduction in computing time.

A FRAMEWORK FOR FINE-SCALE COMPUTATIONAL FLUID DYNAMICS AIR QUALITY MODELING AND ANALYSIS

EPA Science Inventory

This paper discusses a framework for fine-scale CFD modeling that may be developed to complement the present Community Multi-scale Air Quality (CMAQ) modeling system which itself is a computational fluid dynamics model. A goal of this presentation is to stimulate discussions on w...

WORKSHOP REPORT: COMPUTATIONAL TOXICOLOGY: FRAMEWORK, PARTNERSHIPS, AND PROGRAM DEVELOPMENT, SEPTEMBER 29-30, 2003, RESEARCH TRIANGLE PARK, NORTH CAROLINA

EPA Science Inventory

Computational toxicology is a new research initiative being developed within the Office of Research and Development (ORD) of the US Environmental Protection Agency (EPA). Operationally, it is defined as the application of mathematical and computer models together with molecular c...

New Parallel computing framework for radiation transport codes

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kostin, M.A.; /Michigan State U., NSCL; Mokhov, N.V.

A new parallel computing framework has been developed to use with general-purpose radiation transport codes. The framework was implemented as a C++ module that uses MPI for message passing. The module is significantly independent of radiation transport codes it can be used with, and is connected to the codes by means of a number of interface functions. The framework was integrated with the MARS15 code, and an effort is under way to deploy it in PHITS. Besides the parallel computing functionality, the framework offers a checkpoint facility that allows restarting calculations with a saved checkpoint file. The checkpoint facility canmore » be used in single process calculations as well as in the parallel regime. Several checkpoint files can be merged into one thus combining results of several calculations. The framework also corrects some of the known problems with the scheduling and load balancing found in the original implementations of the parallel computing functionality in MARS15 and PHITS. The framework can be used efficiently on homogeneous systems and networks of workstations, where the interference from the other users is possible.« less

A collaborative computing framework of cloud network and WBSN applied to fall detection and 3-D motion reconstruction.

PubMed

Lai, Chin-Feng; Chen, Min; Pan, Jeng-Shyang; Youn, Chan-Hyun; Chao, Han-Chieh

2014-03-01

As cloud computing and wireless body sensor network technologies become gradually developed, ubiquitous healthcare services prevent accidents instantly and effectively, as well as provides relevant information to reduce related processing time and cost. This study proposes a co-processing intermediary framework integrated cloud and wireless body sensor networks, which is mainly applied to fall detection and 3-D motion reconstruction. In this study, the main focuses includes distributed computing and resource allocation of processing sensing data over the computing architecture, network conditions and performance evaluation. Through this framework, the transmissions and computing time of sensing data are reduced to enhance overall performance for the services of fall events detection and 3-D motion reconstruction.

DOE Office of Scientific and Technical Information (OSTI.GOV)

McCaskey, Alexander J.

Hybrid programming models for beyond-CMOS technologies will prove critical for integrating new computing technologies alongside our existing infrastructure. Unfortunately the software infrastructure required to enable this is lacking or not available. XACC is a programming framework for extreme-scale, post-exascale accelerator architectures that integrates alongside existing conventional applications. It is a pluggable framework for programming languages developed for next-gen computing hardware architectures like quantum and neuromorphic computing. It lets computational scientists efficiently off-load classically intractable work to attached accelerators through user-friendly Kernel definitions. XACC makes post-exascale hybrid programming approachable for domain computational scientists.

Computer-aided drug design at Boehringer Ingelheim

NASA Astrophysics Data System (ADS)

Muegge, Ingo; Bergner, Andreas; Kriegl, Jan M.

2017-03-01

Computer-Aided Drug Design (CADD) is an integral part of the drug discovery endeavor at Boehringer Ingelheim (BI). CADD contributes to the evaluation of new therapeutic concepts, identifies small molecule starting points for drug discovery, and develops strategies for optimizing hit and lead compounds. The CADD scientists at BI benefit from the global use and development of both software platforms and computational services. A number of computational techniques developed in-house have significantly changed the way early drug discovery is carried out at BI. In particular, virtual screening in vast chemical spaces, which can be accessed by combinatorial chemistry, has added a new option for the identification of hits in many projects. Recently, a new framework has been implemented allowing fast, interactive predictions of relevant on and off target endpoints and other optimization parameters. In addition to the introduction of this new framework at BI, CADD has been focusing on the enablement of medicinal chemists to independently perform an increasing amount of molecular modeling and design work. This is made possible through the deployment of MOE as a global modeling platform, allowing computational and medicinal chemists to freely share ideas and modeling results. Furthermore, a central communication layer called the computational chemistry framework provides broad access to predictive models and other computational services.

A conceptual framework for managing clinical processes.

PubMed

Buffone, G J; Moreau, D

1997-01-01

Reengineering of the health care delivery system is underway, as is the transformation of the processes and methods used for recording information describing patient care (i.e., the development of a computer-based record). This report describes the use of object-oriented analysis and design to develop and implement clinical process reengineering as well as the organization of clinical data. In addition, the facility of the proposed framework for implementing workflow computing is discussed.

A Discrete Approximation Framework for Hereditary Systems.

DTIC Science & Technology

1980-05-01

schemes which are included in the general framework and which may be implemented directly on high-speed computing machines are developed. A numerical...an appropriately chosen Hilbert space. We then proceed to develop general approximation schemes for the solutions to the homogeneous AEE which in turn...rich classes of these schemes . In addition, two particular families of approximation schemes included in the general framework are developed and

FPGA-Based High-Performance Embedded Systems for Adaptive Edge Computing in Cyber-Physical Systems: The ARTICo³ Framework.

PubMed

Rodríguez, Alfonso; Valverde, Juan; Portilla, Jorge; Otero, Andrés; Riesgo, Teresa; de la Torre, Eduardo

2018-06-08

Cyber-Physical Systems are experiencing a paradigm shift in which processing has been relocated to the distributed sensing layer and is no longer performed in a centralized manner. This approach, usually referred to as Edge Computing, demands the use of hardware platforms that are able to manage the steadily increasing requirements in computing performance, while keeping energy efficiency and the adaptability imposed by the interaction with the physical world. In this context, SRAM-based FPGAs and their inherent run-time reconfigurability, when coupled with smart power management strategies, are a suitable solution. However, they usually fail in user accessibility and ease of development. In this paper, an integrated framework to develop FPGA-based high-performance embedded systems for Edge Computing in Cyber-Physical Systems is presented. This framework provides a hardware-based processing architecture, an automated toolchain, and a runtime to transparently generate and manage reconfigurable systems from high-level system descriptions without additional user intervention. Moreover, it provides users with support for dynamically adapting the available computing resources to switch the working point of the architecture in a solution space defined by computing performance, energy consumption and fault tolerance. Results show that it is indeed possible to explore this solution space at run time and prove that the proposed framework is a competitive alternative to software-based edge computing platforms, being able to provide not only faster solutions, but also higher energy efficiency for computing-intensive algorithms with significant levels of data-level parallelism.

Framework Programmable Platform for the Advanced Software Development Workstation (FPP/ASDW). Demonstration framework document. Volume 1: Concepts and activity descriptions

NASA Technical Reports Server (NTRS)

Mayer, Richard J.; Blinn, Thomas M.; Dewitte, Paul S.; Crump, John W.; Ackley, Keith A.

1992-01-01

The Framework Programmable Software Development Platform (FPP) is a project aimed at effectively combining tool and data integration mechanisms with a model of the software development process to provide an intelligent integrated software development environment. Guided by the model, this system development framework will take advantage of an integrated operating environment to automate effectively the management of the software development process so that costly mistakes during the development phase can be eliminated. The Advanced Software Development Workstation (ASDW) program is conducting research into development of advanced technologies for Computer Aided Software Engineering (CASE).

A State Cyber Hub Operations Framework

DTIC Science & Technology

2016-06-01

to communicate and sense or interact with their internal states or the external environment. Machine Learning: A type of artificial intelligence that... artificial intelligence , and computational linguistics concerned with the interactions between computers and human (natural) languages. Patching: A piece...formalizing a proof of concept for cyber initiatives and developed frameworks for operationalizing the data and intelligence produced across state

Conceptual Framework for Using Computers to Enhance Employee Engagement in Large Offices

ERIC Educational Resources Information Center

Gill, Rob

2010-01-01

Using computers to engage with staff members on their organization's Employer of Choice (EOC) program as part of a human resource development (HRD) framework can add real value to that organization's reputation. EOC is an evolving principle for Australian business. It reflects the value and importance organizations place on their key stakeholders,…

A configurable distributed high-performance computing framework for satellite's TDI-CCD imaging simulation

NASA Astrophysics Data System (ADS)

Xue, Bo; Mao, Bingjing; Chen, Xiaomei; Ni, Guoqiang

2010-11-01

This paper renders a configurable distributed high performance computing(HPC) framework for TDI-CCD imaging simulation. It uses strategy pattern to adapt multi-algorithms. Thus, this framework help to decrease the simulation time with low expense. Imaging simulation for TDI-CCD mounted on satellite contains four processes: 1) atmosphere leads degradation, 2) optical system leads degradation, 3) electronic system of TDI-CCD leads degradation and re-sampling process, 4) data integration. Process 1) to 3) utilize diversity data-intensity algorithms such as FFT, convolution and LaGrange Interpol etc., which requires powerful CPU. Even uses Intel Xeon X5550 processor, regular series process method takes more than 30 hours for a simulation whose result image size is 1500 * 1462. With literature study, there isn't any mature distributing HPC framework in this field. Here we developed a distribute computing framework for TDI-CCD imaging simulation, which is based on WCF[1], uses Client/Server (C/S) layer and invokes the free CPU resources in LAN. The server pushes the process 1) to 3) tasks to those free computing capacity. Ultimately we rendered the HPC in low cost. In the computing experiment with 4 symmetric nodes and 1 server , this framework reduced about 74% simulation time. Adding more asymmetric nodes to the computing network, the time decreased namely. In conclusion, this framework could provide unlimited computation capacity in condition that the network and task management server are affordable. And this is the brand new HPC solution for TDI-CCD imaging simulation and similar applications.

Assessing collaborative computing: development of the Collaborative-Computing Observation Instrument (C-COI)

NASA Astrophysics Data System (ADS)

Israel, Maya; Wherfel, Quentin M.; Shehab, Saadeddine; Ramos, Evan A.; Metzger, Adam; Reese, George C.

2016-07-01

This paper describes the development, validation, and uses of the Collaborative Computing Observation Instrument (C-COI), a web-based analysis instrument that classifies individual and/or collaborative behaviors of students during computing problem-solving (e.g. coding, programming). The C-COI analyzes data gathered through video and audio screen recording software that captures students' computer screens as they program, and their conversations with their peers or adults. The instrument allows researchers to organize and quantify these data to track behavioral patterns that could be further analyzed for deeper understanding of persistence and/or collaborative interactions. The article provides a rationale for the C-COI including the development of a theoretical framework for measuring collaborative interactions in computer-mediated environments. This theoretical framework relied on the computer-supported collaborative learning literature related to adaptive help seeking, the joint problem-solving space in which collaborative computing occurs, and conversations related to outcomes and products of computational activities. Instrument development and validation also included ongoing advisory board feedback from experts in computer science, collaborative learning, and K-12 computing as well as classroom observations to test out the constructs in the C-COI. These processes resulted in an instrument with rigorous validation procedures and a high inter-rater reliability.

Estimating social carrying capacity through computer simulation modeling: an application to Arches National Park, Utah

Treesearch

Benjamin Wang; Robert E. Manning; Steven R. Lawson; William A. Valliere

2001-01-01

Recent research and management experience has led to several frameworks for defining and managing carrying capacity of national parks and related areas. These frameworks rely on monitoring indicator variables to ensure that standards of quality are maintained. The objective of this study was to develop a computer simulation model to estimate the relationships between...

Crops in silico: A community wide multi-scale computational modeling framework of plant canopies

NASA Astrophysics Data System (ADS)

Srinivasan, V.; Christensen, A.; Borkiewic, K.; Yiwen, X.; Ellis, A.; Panneerselvam, B.; Kannan, K.; Shrivastava, S.; Cox, D.; Hart, J.; Marshall-Colon, A.; Long, S.

2016-12-01

Current crop models predict a looming gap between supply and demand for primary foodstuffs over the next 100 years. While significant yield increases were achieved in major food crops during the early years of the green revolution, the current rates of yield increases are insufficient to meet future projected food demand. Furthermore, with projected reduction in arable land, decrease in water availability, and increasing impacts of climate change on future food production, innovative technologies are required to sustainably improve crop yield. To meet these challenges, we are developing Crops in silico (Cis), a biologically informed, multi-scale, computational modeling framework that can facilitate whole plant simulations of crop systems. The Cis framework is capable of linking models of gene networks, protein synthesis, metabolic pathways, physiology, growth, and development in order to investigate crop response to different climate scenarios and resource constraints. This modeling framework will provide the mechanistic details to generate testable hypotheses toward accelerating directed breeding and engineering efforts to increase future food security. A primary objective for building such a framework is to create synergy among an inter-connected community of biologists and modelers to create a realistic virtual plant. This framework advantageously casts the detailed mechanistic understanding of individual plant processes across various scales in a common scalable framework that makes use of current advances in high performance and parallel computing. We are currently designing a user friendly interface that will make this tool equally accessible to biologists and computer scientists. Critically, this framework will provide the community with much needed tools for guiding future crop breeding and engineering, understanding the emergent implications of discoveries at the molecular level for whole plant behavior, and improved prediction of plant and ecosystem responses to the environment.

A General-purpose Framework for Parallel Processing of Large-scale LiDAR Data

NASA Astrophysics Data System (ADS)

Li, Z.; Hodgson, M.; Li, W.

2016-12-01

Light detection and ranging (LiDAR) technologies have proven efficiency to quickly obtain very detailed Earth surface data for a large spatial extent. Such data is important for scientific discoveries such as Earth and ecological sciences and natural disasters and environmental applications. However, handling LiDAR data poses grand geoprocessing challenges due to data intensity and computational intensity. Previous studies received notable success on parallel processing of LiDAR data to these challenges. However, these studies either relied on high performance computers and specialized hardware (GPUs) or focused mostly on finding customized solutions for some specific algorithms. We developed a general-purpose scalable framework coupled with sophisticated data decomposition and parallelization strategy to efficiently handle big LiDAR data. Specifically, 1) a tile-based spatial index is proposed to manage big LiDAR data in the scalable and fault-tolerable Hadoop distributed file system, 2) two spatial decomposition techniques are developed to enable efficient parallelization of different types of LiDAR processing tasks, and 3) by coupling existing LiDAR processing tools with Hadoop, this framework is able to conduct a variety of LiDAR data processing tasks in parallel in a highly scalable distributed computing environment. The performance and scalability of the framework is evaluated with a series of experiments conducted on a real LiDAR dataset using a proof-of-concept prototype system. The results show that the proposed framework 1) is able to handle massive LiDAR data more efficiently than standalone tools; and 2) provides almost linear scalability in terms of either increased workload (data volume) or increased computing nodes with both spatial decomposition strategies. We believe that the proposed framework provides valuable references on developing a collaborative cyberinfrastructure for processing big earth science data in a highly scalable environment.

CCSI and the role of advanced computing in accelerating the commercial deployment of carbon capture systems

DOE Office of Scientific and Technical Information (OSTI.GOV)

Miller, David; Agarwal, Deborah A.; Sun, Xin

2011-09-01

The Carbon Capture Simulation Initiative is developing state-of-the-art computational modeling and simulation tools to accelerate the commercialization of carbon capture technology. The CCSI Toolset consists of an integrated multi-scale modeling and simulation framework, which includes extensive use of reduced order models (ROMs) and a comprehensive uncertainty quantification (UQ) methodology. This paper focuses on the interrelation among high performance computing, detailed device simulations, ROMs for scale-bridging, UQ and the integration framework.

CCSI and the role of advanced computing in accelerating the commercial deployment of carbon capture systems

DOE Office of Scientific and Technical Information (OSTI.GOV)

Miller, D.; Agarwal, D.; Sun, X.

2011-01-01

The Carbon Capture Simulation Initiative is developing state-of-the-art computational modeling and simulation tools to accelerate the commercialization of carbon capture technology. The CCSI Toolset consists of an integrated multi-scale modeling and simulation framework, which includes extensive use of reduced order models (ROMs) and a comprehensive uncertainty quantification (UQ) methodology. This paper focuses on the interrelation among high performance computing, detailed device simulations, ROMs for scale-bridging, UQ and the integration framework.

Framework and Implementation for Improving Physics Essential Skills via Computer-Based Practice: Vector Math

ERIC Educational Resources Information Center

Mikula, Brendon D.; Heckler, Andrew F.

2017-01-01

We propose a framework for improving accuracy, fluency, and retention of basic skills essential for solving problems relevant to STEM introductory courses, and implement the framework for the case of basic vector math skills over several semesters in an introductory physics course. Using an iterative development process, the framework begins with…

An Evaluation Framework and Comparative Analysis of the Widely Used First Programming Languages

PubMed Central

Farooq, Muhammad Shoaib; Khan, Sher Afzal; Ahmad, Farooq; Islam, Saeed; Abid, Adnan

2014-01-01

Computer programming is the core of computer science curriculum. Several programming languages have been used to teach the first course in computer programming, and such languages are referred to as first programming language (FPL). The pool of programming languages has been evolving with the development of new languages, and from this pool different languages have been used as FPL at different times. Though the selection of an appropriate FPL is very important, yet it has been a controversial issue in the presence of many choices. Many efforts have been made for designing a good FPL, however, there is no ample way to evaluate and compare the existing languages so as to find the most suitable FPL. In this article, we have proposed a framework to evaluate the existing imperative, and object oriented languages for their suitability as an appropriate FPL. Furthermore, based on the proposed framework we have devised a customizable scoring function to compute a quantitative suitability score for a language, which reflects its conformance to the proposed framework. Lastly, we have also evaluated the conformance of the widely used FPLs to the proposed framework, and have also computed their suitability scores. PMID:24586449

An evaluation framework and comparative analysis of the widely used first programming languages.

PubMed

Farooq, Muhammad Shoaib; Khan, Sher Afzal; Ahmad, Farooq; Islam, Saeed; Abid, Adnan

2014-01-01

Computer programming is the core of computer science curriculum. Several programming languages have been used to teach the first course in computer programming, and such languages are referred to as first programming language (FPL). The pool of programming languages has been evolving with the development of new languages, and from this pool different languages have been used as FPL at different times. Though the selection of an appropriate FPL is very important, yet it has been a controversial issue in the presence of many choices. Many efforts have been made for designing a good FPL, however, there is no ample way to evaluate and compare the existing languages so as to find the most suitable FPL. In this article, we have proposed a framework to evaluate the existing imperative, and object oriented languages for their suitability as an appropriate FPL. Furthermore, based on the proposed framework we have devised a customizable scoring function to compute a quantitative suitability score for a language, which reflects its conformance to the proposed framework. Lastly, we have also evaluated the conformance of the widely used FPLs to the proposed framework, and have also computed their suitability scores.

Exposure Control Using Adaptive Multi-Stage Item Bundles.

ERIC Educational Resources Information Center

Luecht, Richard M.

This paper presents a multistage adaptive testing test development paradigm that promises to handle content balancing and other test development needs, psychometric reliability concerns, and item exposure. The bundled multistage adaptive testing (BMAT) framework is a modification of the computer-adaptive sequential testing framework introduced by…

Validation of High-Fidelity CFD/CAA Framework for Launch Vehicle Acoustic Environment Simulation against Scale Model Test Data

NASA Technical Reports Server (NTRS)

Liever, Peter A.; West, Jeffrey S.

2016-01-01

A hybrid Computational Fluid Dynamics and Computational Aero-Acoustics (CFD/CAA) modeling framework has been developed for launch vehicle liftoff acoustic environment predictions. The framework couples the existing highly-scalable NASA production CFD code, Loci/CHEM, with a high-order accurate discontinuous Galerkin solver developed in the same production framework, Loci/THRUST, to accurately resolve and propagate acoustic physics across the entire launch environment. Time-accurate, Hybrid RANS/LES CFD modeling is applied for predicting the acoustic generation physics at the plume source, and a high-order accurate unstructured discontinuous Galerkin (DG) method is employed to propagate acoustic waves away from the source across large distances using high-order accurate schemes. The DG solver is capable of solving 2nd, 3rd, and 4th order Euler solutions for non-linear, conservative acoustic field propagation. Initial application testing and validation has been carried out against high resolution acoustic data from the Ares Scale Model Acoustic Test (ASMAT) series to evaluate the capabilities and production readiness of the CFD/CAA system to resolve the observed spectrum of acoustic frequency content. This paper presents results from this validation and outlines efforts to mature and improve the computational simulation framework.

Computer Simulation of the VASIMR Engine

NASA Technical Reports Server (NTRS)

Garrison, David

2005-01-01

The goal of this project is to develop a magneto-hydrodynamic (MHD) computer code for simulation of the VASIMR engine. This code is designed be easy to modify and use. We achieve this using the Cactus framework, a system originally developed for research in numerical relativity. Since its release, Cactus has become an extremely powerful and flexible open source framework. The development of the code will be done in stages, starting with a basic fluid dynamic simulation and working towards a more complex MHD code. Once developed, this code can be used by students and researchers in order to further test and improve the VASIMR engine.

Towards a Framework to Improve the Quality of Teaching and Learning: Consciousness and Validation in Computer Engineering Science, UCT

ERIC Educational Resources Information Center

Lévano, Marcos; Albornoz, Andrea

2016-01-01

This paper aims to propose a framework to improve the quality in teaching and learning in order to develop good practices to train professionals in the career of computer engineering science. To demonstrate the progress and achievements, our work is based on two principles for the formation of professionals, one based on the model of learning…

Philosophical approaches to the nursing informatics data-information-knowledge-wisdom framework.

PubMed

Matney, Susan; Brewster, Philip J; Sward, Katherine A; Cloyes, Kristin G; Staggers, Nancy

2011-01-01

Although informatics is an important area of nursing inquiry and practice, few scholars have articulated the philosophical foundations of the field or how these translate into practice including the often-cited data, information, knowledge, and wisdom (DIKW) framework. Data, information, and knowledge, often approached through postpositivism, can be exhibited in computer systems. Wisdom aligns with constructivist epistemological perspectives such as Gadamerian hermeneutics. Computer systems can support wisdom development. Wisdom is an important element of the DIKW framework and adds value to the role of nursing informaticists and nursing science.

A Framework for Teaching Software Development Methods

ERIC Educational Resources Information Center

Dubinsky, Yael; Hazzan, Orit

2005-01-01

This article presents a study that aims at constructing a teaching framework for software development methods in higher education. The research field is a capstone project-based course, offered by the Technion's Department of Computer Science, in which Extreme Programming is introduced. The research paradigm is an Action Research that involves…

2D and 3D Multiscale/Multicomponent Modeling of Impact Response of Heterogeneous Energetic Composites

DTIC Science & Technology

2016-06-01

7 Development of Cohesive Finite Element Method (CFEM) Capability ................................7 3D...Cohesive Finite Element Method (CFEM) framework A new scientific framework and technical capability is developed for the computational analyses of...this section should shift from reporting activities to reporting accomplishments. Development of Cohesive Finite Element Method (CFEM) Capability

Framework for architecture-independent run-time reconfigurable applications

NASA Astrophysics Data System (ADS)

Lehn, David I.; Hudson, Rhett D.; Athanas, Peter M.

2000-10-01

Configurable Computing Machines (CCMs) have emerged as a technology with the computational benefits of custom ASICs as well as the flexibility and reconfigurability of general-purpose microprocessors. Significant effort from the research community has focused on techniques to move this reconfigurability from a rapid application development tool to a run-time tool. This requires the ability to change the hardware design while the application is executing and is known as Run-Time Reconfiguration (RTR). Widespread acceptance of run-time reconfigurable custom computing depends upon the existence of high-level automated design tools. Such tools must reduce the designers effort to port applications between different platforms as the architecture, hardware, and software evolves. A Java implementation of a high-level application framework, called Janus, is presented here. In this environment, developers create Java classes that describe the structural behavior of an application. The framework allows hardware and software modules to be freely mixed and interchanged. A compilation phase of the development process analyzes the structure of the application and adapts it to the target platform. Janus is capable of structuring the run-time behavior of an application to take advantage of the memory and computational resources available.

A Computational Framework for Efficient Low Temperature Plasma Simulations

NASA Astrophysics Data System (ADS)

Verma, Abhishek Kumar; Venkattraman, Ayyaswamy

2016-10-01

Over the past years, scientific computing has emerged as an essential tool for the investigation and prediction of low temperature plasmas (LTP) applications which includes electronics, nanomaterial synthesis, metamaterials etc. To further explore the LTP behavior with greater fidelity, we present a computational toolbox developed to perform LTP simulations. This framework will allow us to enhance our understanding of multiscale plasma phenomenon using high performance computing tools mainly based on OpenFOAM FVM distribution. Although aimed at microplasma simulations, the modular framework is able to perform multiscale, multiphysics simulations of physical systems comprises of LTP. Some salient introductory features are capability to perform parallel, 3D simulations of LTP applications on unstructured meshes. Performance of the solver is tested based on numerical results assessing accuracy and efficiency of benchmarks for problems in microdischarge devices. Numerical simulation of microplasma reactor at atmospheric pressure with hemispherical dielectric coated electrodes will be discussed and hence, provide an overview of applicability and future scope of this framework.

A Solution Framework for Environmental Characterization Problems

EPA Science Inventory

This paper describes experiences developing a grid-enabled framework for solving environmental inverse problems. The solution approach taken here couples environmental simulation models with global search methods and requires readily available computational resources of the grid ...

Argonne Simulation Framework for Intelligent Transportation Systems

DOT National Transportation Integrated Search

1996-01-01

A simulation framework has been developed which defines a high-level architecture for a large-scale, comprehensive, scalable simulation of an Intelligent Transportation System (ITS). The simulator is designed to run on parallel computers and distribu...

Session on High Speed Civil Transport Design Capability Using MDO and High Performance Computing

NASA Technical Reports Server (NTRS)

Rehder, Joe

2000-01-01

Since the inception of CAS in 1992, NASA Langley has been conducting research into applying multidisciplinary optimization (MDO) and high performance computing toward reducing aircraft design cycle time. The focus of this research has been the development of a series of computational frameworks and associated applications that increased in capability, complexity, and performance over time. The culmination of this effort is an automated high-fidelity analysis capability for a high speed civil transport (HSCT) vehicle installed on a network of heterogeneous computers with a computational framework built using Common Object Request Broker Architecture (CORBA) and Java. The main focus of the research in the early years was the development of the Framework for Interdisciplinary Design Optimization (FIDO) and associated HSCT applications. While the FIDO effort was eventually halted, work continued on HSCT applications of ever increasing complexity. The current application, HSCT4.0, employs high fidelity CFD and FEM analysis codes. For each analysis cycle, the vehicle geometry and computational grids are updated using new values for design variables. Processes for aeroelastic trim, loads convergence, displacement transfer, stress and buckling, and performance have been developed. In all, a total of 70 processes are integrated in the analysis framework. Many of the key processes include automatic differentiation capabilities to provide sensitivity information that can be used in optimization. A software engineering process was developed to manage this large project. Defining the interactions among 70 processes turned out to be an enormous, but essential, task. A formal requirements document was prepared that defined data flow among processes and subprocesses. A design document was then developed that translated the requirements into actual software design. A validation program was defined and implemented to ensure that codes integrated into the framework produced the same results as their standalone counterparts. Finally, a Commercial Off the Shelf (COTS) configuration management system was used to organize the software development. A computational environment, CJOPT, based on the Common Object Request Broker Architecture, CORBA, and the Java programming language has been developed as a framework for multidisciplinary analysis and Optimization. The environment exploits the parallelisms inherent in the application and distributes the constituent disciplines on machines best suited to their needs. In CJOpt, a discipline code is "wrapped" as an object. An interface to the object identifies the functionality (services) provided by the discipline, defined in Interface Definition Language (IDL) and implemented using Java. The results of using the HSCT4.0 capability are described. A summary of lessons learned is also presented. The use of some of the processes, codes, and techniques by industry are highlighted. The application of the methodology developed in this research to other aircraft are described. Finally, we show how the experience gained is being applied to entirely new vehicles, such as the Reusable Space Transportation System. Additional information is contained in the original.

A computational fluid dynamics simulation framework for ventricular catheter design optimization.

PubMed

Weisenberg, Sofy H; TerMaath, Stephanie C; Barbier, Charlotte N; Hill, Judith C; Killeffer, James A

2017-11-10

OBJECTIVE Cerebrospinal fluid (CSF) shunts are the primary treatment for patients suffering from hydrocephalus. While proven effective in symptom relief, these shunt systems are plagued by high failure rates and often require repeated revision surgeries to replace malfunctioning components. One of the leading causes of CSF shunt failure is obstruction of the ventricular catheter by aggregations of cells, proteins, blood clots, or fronds of choroid plexus that occlude the catheter's small inlet holes or even the full internal catheter lumen. Such obstructions can disrupt CSF diversion out of the ventricular system or impede it entirely. Previous studies have suggested that altering the catheter's fluid dynamics may help to reduce the likelihood of complete ventricular catheter failure caused by obstruction. However, systematic correlation between a ventricular catheter's design parameters and its performance, specifically its likelihood to become occluded, still remains unknown. Therefore, an automated, open-source computational fluid dynamics (CFD) simulation framework was developed for use in the medical community to determine optimized ventricular catheter designs and to rapidly explore parameter influence for a given flow objective. METHODS The computational framework was developed by coupling a 3D CFD solver and an iterative optimization algorithm and was implemented in a high-performance computing environment. The capabilities of the framework were demonstrated by computing an optimized ventricular catheter design that provides uniform flow rates through the catheter's inlet holes, a common design objective in the literature. The baseline computational model was validated using 3D nuclear imaging to provide flow velocities at the inlet holes and through the catheter. RESULTS The optimized catheter design achieved through use of the automated simulation framework improved significantly on previous attempts to reach a uniform inlet flow rate distribution using the standard catheter hole configuration as a baseline. While the standard ventricular catheter design featuring uniform inlet hole diameters and hole spacing has a standard deviation of 14.27% for the inlet flow rates, the optimized design has a standard deviation of 0.30%. CONCLUSIONS This customizable framework, paired with high-performance computing, provides a rapid method of design testing to solve complex flow problems. While a relatively simplified ventricular catheter model was used to demonstrate the framework, the computational approach is applicable to any baseline catheter model, and it is easily adapted to optimize catheters for the unique needs of different patients as well as for other fluid-based medical devices.

A Modeling Framework for Optimal Computational Resource Allocation Estimation: Considering the Trade-offs between Physical Resolutions, Uncertainty and Computational Costs

NASA Astrophysics Data System (ADS)

Moslehi, M.; de Barros, F.; Rajagopal, R.

2014-12-01

Hydrogeological models that represent flow and transport in subsurface domains are usually large-scale with excessive computational complexity and uncertain characteristics. Uncertainty quantification for predicting flow and transport in heterogeneous formations often entails utilizing a numerical Monte Carlo framework, which repeatedly simulates the model according to a random field representing hydrogeological characteristics of the field. The physical resolution (e.g. grid resolution associated with the physical space) for the simulation is customarily chosen based on recommendations in the literature, independent of the number of Monte Carlo realizations. This practice may lead to either excessive computational burden or inaccurate solutions. We propose an optimization-based methodology that considers the trade-off between the following conflicting objectives: time associated with computational costs, statistical convergence of the model predictions and physical errors corresponding to numerical grid resolution. In this research, we optimally allocate computational resources by developing a modeling framework for the overall error based on a joint statistical and numerical analysis and optimizing the error model subject to a given computational constraint. The derived expression for the overall error explicitly takes into account the joint dependence between the discretization error of the physical space and the statistical error associated with Monte Carlo realizations. The accuracy of the proposed framework is verified in this study by applying it to several computationally extensive examples. Having this framework at hand aims hydrogeologists to achieve the optimum physical and statistical resolutions to minimize the error with a given computational budget. Moreover, the influence of the available computational resources and the geometric properties of the contaminant source zone on the optimum resolutions are investigated. We conclude that the computational cost associated with optimal allocation can be substantially reduced compared with prevalent recommendations in the literature.

A Model-based Framework for Risk Assessment in Human-Computer Controlled Systems

NASA Technical Reports Server (NTRS)

Hatanaka, Iwao

2000-01-01

The rapid growth of computer technology and innovation has played a significant role in the rise of computer automation of human tasks in modem production systems across all industries. Although the rationale for automation has been to eliminate "human error" or to relieve humans from manual repetitive tasks, various computer-related hazards and accidents have emerged as a direct result of increased system complexity attributed to computer automation. The risk assessment techniques utilized for electromechanical systems are not suitable for today's software-intensive systems or complex human-computer controlled systems. This thesis will propose a new systemic model-based framework for analyzing risk in safety-critical systems where both computers and humans are controlling safety-critical functions. A new systems accident model will be developed based upon modem systems theory and human cognitive processes to better characterize system accidents, the role of human operators, and the influence of software in its direct control of significant system functions. Better risk assessments will then be achievable through the application of this new framework to complex human-computer controlled systems.

Cloud Computing Services for Seismic Networks

NASA Astrophysics Data System (ADS)

Olson, Michael

This thesis describes a compositional framework for developing situation awareness applications: applications that provide ongoing information about a user's changing environment. The thesis describes how the framework is used to develop a situation awareness application for earthquakes. The applications are implemented as Cloud computing services connected to sensors and actuators. The architecture and design of the Cloud services are described and measurements of performance metrics are provided. The thesis includes results of experiments on earthquake monitoring conducted over a year. The applications developed by the framework are (1) the CSN---the Community Seismic Network---which uses relatively low-cost sensors deployed by members of the community, and (2) SAF---the Situation Awareness Framework---which integrates data from multiple sources, including the CSN, CISN---the California Integrated Seismic Network, a network consisting of high-quality seismometers deployed carefully by professionals in the CISN organization and spread across Southern California---and prototypes of multi-sensor platforms that include carbon monoxide, methane, dust and radiation sensors.

Moose: An Open-Source Framework to Enable Rapid Development of Collaborative, Multi-Scale, Multi-Physics Simulation Tools

NASA Astrophysics Data System (ADS)

Slaughter, A. E.; Permann, C.; Peterson, J. W.; Gaston, D.; Andrs, D.; Miller, J.

2014-12-01

The Idaho National Laboratory (INL)-developed Multiphysics Object Oriented Simulation Environment (MOOSE; www.mooseframework.org), is an open-source, parallel computational framework for enabling the solution of complex, fully implicit multiphysics systems. MOOSE provides a set of computational tools that scientists and engineers can use to create sophisticated multiphysics simulations. Applications built using MOOSE have computed solutions for chemical reaction and transport equations, computational fluid dynamics, solid mechanics, heat conduction, mesoscale materials modeling, geomechanics, and others. To facilitate the coupling of diverse and highly-coupled physical systems, MOOSE employs the Jacobian-free Newton-Krylov (JFNK) method when solving the coupled nonlinear systems of equations arising in multiphysics applications. The MOOSE framework is written in C++, and leverages other high-quality, open-source scientific software packages such as LibMesh, Hypre, and PETSc. MOOSE uses a "hybrid parallel" model which combines both shared memory (thread-based) and distributed memory (MPI-based) parallelism to ensure efficient resource utilization on a wide range of computational hardware. MOOSE-based applications are inherently modular, which allows for simulation expansion (via coupling of additional physics modules) and the creation of multi-scale simulations. Any application developed with MOOSE supports running (in parallel) any other MOOSE-based application. Each application can be developed independently, yet easily communicate with other applications (e.g., conductivity in a slope-scale model could be a constant input, or a complete phase-field micro-structure simulation) without additional code being written. This method of development has proven effective at INL and expedites the development of sophisticated, sustainable, and collaborative simulation tools.

Models for evaluating the performability of degradable computing systems

NASA Technical Reports Server (NTRS)

Wu, L. T.

1982-01-01

Recent advances in multiprocessor technology established the need for unified methods to evaluate computing systems performance and reliability. In response to this modeling need, a general modeling framework that permits the modeling, analysis and evaluation of degradable computing systems is considered. Within this framework, several user oriented performance variables are identified and shown to be proper generalizations of the traditional notions of system performance and reliability. Furthermore, a time varying version of the model is developed to generalize the traditional fault tree reliability evaluation methods of phased missions.

The Future of Electronic Device Design: Device and Process Simulation Find Intelligence on the World Wide Web

NASA Technical Reports Server (NTRS)

Biegel, Bryan A.

1999-01-01

We are on the path to meet the major challenges ahead for TCAD (technology computer aided design). The emerging computational grid will ultimately solve the challenge of limited computational power. The Modular TCAD Framework will solve the TCAD software challenge once TCAD software developers realize that there is no other way to meet industry's needs. The modular TCAD framework (MTF) also provides the ideal platform for solving the TCAD model challenge by rapid implementation of models in a partial differential solver.

A Bayesian framework for adaptive selection, calibration, and validation of coarse-grained models of atomistic systems

NASA Astrophysics Data System (ADS)

Farrell, Kathryn; Oden, J. Tinsley; Faghihi, Danial

2015-08-01

A general adaptive modeling algorithm for selection and validation of coarse-grained models of atomistic systems is presented. A Bayesian framework is developed to address uncertainties in parameters, data, and model selection. Algorithms for computing output sensitivities to parameter variances, model evidence and posterior model plausibilities for given data, and for computing what are referred to as Occam Categories in reference to a rough measure of model simplicity, make up components of the overall approach. Computational results are provided for representative applications.

A Framework for Safe Composition of Heterogeneous SOA Services in a Pervasive Computing Environment with Resource Constraints

ERIC Educational Resources Information Center

Reyes Alamo, Jose M.

2010-01-01

The Service Oriented Computing (SOC) paradigm, defines services as software artifacts whose implementations are separated from their specifications. Application developers rely on services to simplify the design, reduce the development time and cost. Within the SOC paradigm, different Service Oriented Architectures (SOAs) have been developed.…

Development of a Computer-Based Measure of Listening Comprehension of Science Talk

ERIC Educational Resources Information Center

Lin, Sheau-Wen; Liu, Yu; Chen, Shin-Feng; Wang, Jing-Ru; Kao, Huey-Lien

2015-01-01

The purpose of this study was to develop a computer-based assessment for elementary school students' listening comprehension of science talk within an inquiry-oriented environment. The development procedure had 3 steps: a literature review to define the framework of the test, collecting and identifying key constructs of science talk, and…

Enabling Big Geoscience Data Analytics with a Cloud-Based, MapReduce-Enabled and Service-Oriented Workflow Framework

PubMed Central

Li, Zhenlong; Yang, Chaowei; Jin, Baoxuan; Yu, Manzhu; Liu, Kai; Sun, Min; Zhan, Matthew

2015-01-01

Geoscience observations and model simulations are generating vast amounts of multi-dimensional data. Effectively analyzing these data are essential for geoscience studies. However, the tasks are challenging for geoscientists because processing the massive amount of data is both computing and data intensive in that data analytics requires complex procedures and multiple tools. To tackle these challenges, a scientific workflow framework is proposed for big geoscience data analytics. In this framework techniques are proposed by leveraging cloud computing, MapReduce, and Service Oriented Architecture (SOA). Specifically, HBase is adopted for storing and managing big geoscience data across distributed computers. MapReduce-based algorithm framework is developed to support parallel processing of geoscience data. And service-oriented workflow architecture is built for supporting on-demand complex data analytics in the cloud environment. A proof-of-concept prototype tests the performance of the framework. Results show that this innovative framework significantly improves the efficiency of big geoscience data analytics by reducing the data processing time as well as simplifying data analytical procedures for geoscientists. PMID:25742012

Enabling big geoscience data analytics with a cloud-based, MapReduce-enabled and service-oriented workflow framework.

PubMed

Li, Zhenlong; Yang, Chaowei; Jin, Baoxuan; Yu, Manzhu; Liu, Kai; Sun, Min; Zhan, Matthew

2015-01-01

Geoscience observations and model simulations are generating vast amounts of multi-dimensional data. Effectively analyzing these data are essential for geoscience studies. However, the tasks are challenging for geoscientists because processing the massive amount of data is both computing and data intensive in that data analytics requires complex procedures and multiple tools. To tackle these challenges, a scientific workflow framework is proposed for big geoscience data analytics. In this framework techniques are proposed by leveraging cloud computing, MapReduce, and Service Oriented Architecture (SOA). Specifically, HBase is adopted for storing and managing big geoscience data across distributed computers. MapReduce-based algorithm framework is developed to support parallel processing of geoscience data. And service-oriented workflow architecture is built for supporting on-demand complex data analytics in the cloud environment. A proof-of-concept prototype tests the performance of the framework. Results show that this innovative framework significantly improves the efficiency of big geoscience data analytics by reducing the data processing time as well as simplifying data analytical procedures for geoscientists.

Computer-Simulation Surrogates for Optimization: Application to Trapezoidal Ducts and Axisymmetric Bodies

NASA Technical Reports Server (NTRS)

Otto, John C.; Paraschivoiu, Marius; Yesilyurt, Serhat; Patera, Anthony T.

1995-01-01

Engineering design and optimization efforts using computational systems rapidly become resource intensive. The goal of the surrogate-based approach is to perform a complete optimization with limited resources. In this paper we present a Bayesian-validated approach that informs the designer as to how well the surrogate performs; in particular, our surrogate framework provides precise (albeit probabilistic) bounds on the errors incurred in the surrogate-for-simulation substitution. The theory and algorithms of our computer{simulation surrogate framework are first described. The utility of the framework is then demonstrated through two illustrative examples: maximization of the flowrate of fully developed ow in trapezoidal ducts; and design of an axisymmetric body that achieves a target Stokes drag.

Software Framework for Development of Web-GIS Systems for Analysis of Georeferenced Geophysical Data

NASA Astrophysics Data System (ADS)

Okladnikov, I.; Gordov, E. P.; Titov, A. G.

2011-12-01

Georeferenced datasets (meteorological databases, modeling and reanalysis results, remote sensing products, etc.) are currently actively used in numerous applications including modeling, interpretation and forecast of climatic and ecosystem changes for various spatial and temporal scales. Due to inherent heterogeneity of environmental datasets as well as their size which might constitute up to tens terabytes for a single dataset at present studies in the area of climate and environmental change require a special software support. A dedicated software framework for rapid development of providing such support information-computational systems based on Web-GIS technologies has been created. The software framework consists of 3 basic parts: computational kernel developed using ITTVIS Interactive Data Language (IDL), a set of PHP-controllers run within specialized web portal, and JavaScript class library for development of typical components of web mapping application graphical user interface (GUI) based on AJAX technology. Computational kernel comprise of number of modules for datasets access, mathematical and statistical data analysis and visualization of results. Specialized web-portal consists of web-server Apache, complying OGC standards Geoserver software which is used as a base for presenting cartographical information over the Web, and a set of PHP-controllers implementing web-mapping application logic and governing computational kernel. JavaScript library aiming at graphical user interface development is based on GeoExt library combining ExtJS Framework and OpenLayers software. Based on the software framework an information-computational system for complex analysis of large georeferenced data archives was developed. Structured environmental datasets available for processing now include two editions of NCEP/NCAR Reanalysis, JMA/CRIEPI JRA-25 Reanalysis, ECMWF ERA-40 Reanalysis, ECMWF ERA Interim Reanalysis, MRI/JMA APHRODITE's Water Resources Project Reanalysis, meteorological observational data for the territory of the former USSR for the 20th century, and others. Current version of the system is already involved into a scientific research process. Particularly, recently the system was successfully used for analysis of Siberia climate changes and its impact in the region. The software framework presented allows rapid development of Web-GIS systems for geophysical data analysis thus providing specialists involved into multidisciplinary research projects with reliable and practical instruments for complex analysis of climate and ecosystems changes on global and regional scales. This work is partially supported by RFBR grants #10-07-00547, #11-05-01190, and SB RAS projects 4.31.1.5, 4.31.2.7, 4, 8, 9, 50 and 66.

A multi-GPU real-time dose simulation software framework for lung radiotherapy.

PubMed

Santhanam, A P; Min, Y; Neelakkantan, H; Papp, N; Meeks, S L; Kupelian, P A

2012-09-01

Medical simulation frameworks facilitate both the preoperative and postoperative analysis of the patient's pathophysical condition. Of particular importance is the simulation of radiation dose delivery for real-time radiotherapy monitoring and retrospective analyses of the patient's treatment. In this paper, a software framework tailored for the development of simulation-based real-time radiation dose monitoring medical applications is discussed. A multi-GPU-based computational framework coupled with inter-process communication methods is introduced for simulating the radiation dose delivery on a deformable 3D volumetric lung model and its real-time visualization. The model deformation and the corresponding dose calculation are allocated among the GPUs in a task-specific manner and is performed in a pipelined manner. Radiation dose calculations are computed on two different GPU hardware architectures. The integration of this computational framework with a front-end software layer and back-end patient database repository is also discussed. Real-time simulation of the dose delivered is achieved at once every 120 ms using the proposed framework. With a linear increase in the number of GPU cores, the computational time of the simulation was linearly decreased. The inter-process communication time also improved with an increase in the hardware memory. Variations in the delivered dose and computational speedup for variations in the data dimensions are investigated using D70 and D90 as well as gEUD as metrics for a set of 14 patients. Computational speed-up increased with an increase in the beam dimensions when compared with a CPU-based commercial software while the error in the dose calculation was <1%. Our analyses show that the framework applied to deformable lung model-based radiotherapy is an effective tool for performing both real-time and retrospective analyses.

Validation of High-Fidelity CFD/CAA Framework for Launch Vehicle Acoustic Environment Simulation against Scale Model Test Data

NASA Technical Reports Server (NTRS)

Liever, Peter A.; West, Jeffrey S.; Harris, Robert E.

2016-01-01

A hybrid Computational Fluid Dynamics and Computational Aero-Acoustics (CFD/CAA) modeling framework has been developed for launch vehicle liftoff acoustic environment predictions. The framework couples the existing highly-scalable NASA production CFD code, Loci/CHEM, with a high-order accurate Discontinuous Galerkin solver developed in the same production framework, Loci/THRUST, to accurately resolve and propagate acoustic physics across the entire launch environment. Time-accurate, Hybrid RANS/LES CFD modeling is applied for predicting the acoustic generation physics at the plume source, and a high-order accurate unstructured mesh Discontinuous Galerkin (DG) method is employed to propagate acoustic waves away from the source across large distances using high-order accurate schemes. The DG solver is capable of solving 2nd, 3rd, and 4th order Euler solutions for non-linear, conservative acoustic field propagation. Initial application testing and validation has been carried out against high resolution acoustic data from the Ares Scale Model Acoustic Test (ASMAT) series to evaluate the capabilities and production readiness of the CFD/CAA system to resolve the observed spectrum of acoustic frequency content. This paper presents results from this validation and outlines efforts to mature and improve the computational simulation framework.

A computational framework for automation of point defect calculations

DOE Office of Scientific and Technical Information (OSTI.GOV)

Goyal, Anuj; Gorai, Prashun; Peng, Haowei

We have developed a complete and rigorously validated open-source Python framework to automate point defect calculations using density functional theory. Furthermore, the framework provides an effective and efficient method for defect structure generation, and creation of simple yet customizable workflows to analyze defect calculations. This package provides the capability to compute widely-accepted correction schemes to overcome finite-size effects, including (1) potential alignment, (2) image-charge correction, and (3) band filling correction to shallow defects. Using Si, ZnO and In2O3 as test examples, we demonstrate the package capabilities and validate the methodology.

A computational framework for automation of point defect calculations

DOE PAGES

Goyal, Anuj; Gorai, Prashun; Peng, Haowei; ...

2017-01-13

We have developed a complete and rigorously validated open-source Python framework to automate point defect calculations using density functional theory. Furthermore, the framework provides an effective and efficient method for defect structure generation, and creation of simple yet customizable workflows to analyze defect calculations. This package provides the capability to compute widely-accepted correction schemes to overcome finite-size effects, including (1) potential alignment, (2) image-charge correction, and (3) band filling correction to shallow defects. Using Si, ZnO and In2O3 as test examples, we demonstrate the package capabilities and validate the methodology.

CHAMPION: Intelligent Hierarchical Reasoning Agents for Enhanced Decision Support

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hohimer, Ryan E.; Greitzer, Frank L.; Noonan, Christine F.

2011-11-15

We describe the design and development of an advanced reasoning framework employing semantic technologies, organized within a hierarchy of computational reasoning agents that interpret domain specific information. Designed based on an inspirational metaphor of the pattern recognition functions performed by the human neocortex, the CHAMPION reasoning framework represents a new computational modeling approach that derives invariant knowledge representations through memory-prediction belief propagation processes that are driven by formal ontological language specification and semantic technologies. The CHAMPION framework shows promise for enhancing complex decision making in diverse problem domains including cyber security, nonproliferation and energy consumption analysis.

Cognitive computing and eScience in health and life science research: artificial intelligence and obesity intervention programs.

PubMed

Marshall, Thomas; Champagne-Langabeer, Tiffiany; Castelli, Darla; Hoelscher, Deanna

2017-12-01

To present research models based on artificial intelligence and discuss the concept of cognitive computing and eScience as disruptive factors in health and life science research methodologies. The paper identifies big data as a catalyst to innovation and the development of artificial intelligence, presents a framework for computer-supported human problem solving and describes a transformation of research support models. This framework includes traditional computer support; federated cognition using machine learning and cognitive agents to augment human intelligence; and a semi-autonomous/autonomous cognitive model, based on deep machine learning, which supports eScience. The paper provides a forward view of the impact of artificial intelligence on our human-computer support and research methods in health and life science research. By augmenting or amplifying human task performance with artificial intelligence, cognitive computing and eScience research models are discussed as novel and innovative systems for developing more effective adaptive obesity intervention programs.

Secure and Efficient Regression Analysis Using a Hybrid Cryptographic Framework: Development and Evaluation

PubMed Central

Jiang, Xiaoqian; Aziz, Md Momin Al; Wang, Shuang; Mohammed, Noman

2018-01-01

Background Machine learning is an effective data-driven tool that is being widely used to extract valuable patterns and insights from data. Specifically, predictive machine learning models are very important in health care for clinical data analysis. The machine learning algorithms that generate predictive models often require pooling data from different sources to discover statistical patterns or correlations among different attributes of the input data. The primary challenge is to fulfill one major objective: preserving the privacy of individuals while discovering knowledge from data. Objective Our objective was to develop a hybrid cryptographic framework for performing regression analysis over distributed data in a secure and efficient way. Methods Existing secure computation schemes are not suitable for processing the large-scale data that are used in cutting-edge machine learning applications. We designed, developed, and evaluated a hybrid cryptographic framework, which can securely perform regression analysis, a fundamental machine learning algorithm using somewhat homomorphic encryption and a newly introduced secure hardware component of Intel Software Guard Extensions (Intel SGX) to ensure both privacy and efficiency at the same time. Results Experimental results demonstrate that our proposed method provides a better trade-off in terms of security and efficiency than solely secure hardware-based methods. Besides, there is no approximation error. Computed model parameters are exactly similar to plaintext results. Conclusions To the best of our knowledge, this kind of secure computation model using a hybrid cryptographic framework, which leverages both somewhat homomorphic encryption and Intel SGX, is not proposed or evaluated to this date. Our proposed framework ensures data security and computational efficiency at the same time. PMID:29506966

Secure and Efficient Regression Analysis Using a Hybrid Cryptographic Framework: Development and Evaluation.

PubMed

Sadat, Md Nazmus; Jiang, Xiaoqian; Aziz, Md Momin Al; Wang, Shuang; Mohammed, Noman

2018-03-05

Machine learning is an effective data-driven tool that is being widely used to extract valuable patterns and insights from data. Specifically, predictive machine learning models are very important in health care for clinical data analysis. The machine learning algorithms that generate predictive models often require pooling data from different sources to discover statistical patterns or correlations among different attributes of the input data. The primary challenge is to fulfill one major objective: preserving the privacy of individuals while discovering knowledge from data. Our objective was to develop a hybrid cryptographic framework for performing regression analysis over distributed data in a secure and efficient way. Existing secure computation schemes are not suitable for processing the large-scale data that are used in cutting-edge machine learning applications. We designed, developed, and evaluated a hybrid cryptographic framework, which can securely perform regression analysis, a fundamental machine learning algorithm using somewhat homomorphic encryption and a newly introduced secure hardware component of Intel Software Guard Extensions (Intel SGX) to ensure both privacy and efficiency at the same time. Experimental results demonstrate that our proposed method provides a better trade-off in terms of security and efficiency than solely secure hardware-based methods. Besides, there is no approximation error. Computed model parameters are exactly similar to plaintext results. To the best of our knowledge, this kind of secure computation model using a hybrid cryptographic framework, which leverages both somewhat homomorphic encryption and Intel SGX, is not proposed or evaluated to this date. Our proposed framework ensures data security and computational efficiency at the same time. ©Md Nazmus Sadat, Xiaoqian Jiang, Md Momin Al Aziz, Shuang Wang, Noman Mohammed. Originally published in JMIR Medical Informatics (http://medinform.jmir.org), 05.03.2018.

ICCE/ICCAI 2000 Full & Short Papers (System Design and Development).

ERIC Educational Resources Information Center

2000

This document contains the full and short papers on system design and development from ICCE/ICCAI 2000 (International Conference on Computers in Education/International Conference on Computer-Assisted Instruction) covering the following topics: a code restructuring tool to help scaffold novice programmers; a framework for Internet-based…

A Component-based Programming Model for Composite, Distributed Applications

NASA Technical Reports Server (NTRS)

Eidson, Thomas M.; Bushnell, Dennis M. (Technical Monitor)

2001-01-01

The nature of scientific programming is evolving to larger, composite applications that are composed of smaller element applications. These composite applications are more frequently being targeted for distributed, heterogeneous networks of computers. They are most likely programmed by a group of developers. Software component technology and computational frameworks are being proposed and developed to meet the programming requirements of these new applications. Historically, programming systems have had a hard time being accepted by the scientific programming community. In this paper, a programming model is outlined that attempts to organize the software component concepts and fundamental programming entities into programming abstractions that will be better understood by the application developers. The programming model is designed to support computational frameworks that manage many of the tedious programming details, but also that allow sufficient programmer control to design an accurate, high-performance application.

An esthetics rehabilitation with computer-aided design/ computer-aided manufacturing technology.

PubMed

Mazaro, Josá Vitor Quinelli; de Mello, Caroline Cantieri; Zavanelli, Adriana Cristina; Santiago, Joel Ferreira; Amoroso, Andressa Paschoal; Pellizzer, Eduardo Piza

2014-07-01

This paper describes a case of a rehabilitation involving Computer Aided Design/Computer Aided Manufacturing (CAD-CAM) system in implant supported and dental supported prostheses using zirconia as framework. The CAD-CAM technology has developed considerably over last few years, becoming a reality in dental practice. Among the widely used systems are the systems based on zirconia which demonstrate important physical and mechanical properties of high strength, adequate fracture toughness, biocompatibility and esthetics, and are indicated for unitary prosthetic restorations and posterior and anterior framework. All the modeling was performed by using CAD-CAM system and prostheses were cemented using resin cement best suited for each situation. The rehabilitation of the maxillary arch using zirconia framework demonstrated satisfactory esthetic and functional results after a 12-month control and revealed no biological and technical complications. This article shows the important of use technology CAD/CAM in the manufacture of dental prosthesis and implant-supported.

Efficient and Flexible Climate Analysis with Python in a Cloud-Based Distributed Computing Framework

NASA Astrophysics Data System (ADS)

Gannon, C.

2017-12-01

As climate models become progressively more advanced, and spatial resolution further improved through various downscaling projects, climate projections at a local level are increasingly insightful and valuable. However, the raw size of climate datasets presents numerous hurdles for analysts wishing to develop customized climate risk metrics or perform site-specific statistical analysis. Four Twenty Seven, a climate risk consultancy, has implemented a Python-based distributed framework to analyze large climate datasets in the cloud. With the freedom afforded by efficiently processing these datasets, we are able to customize and continually develop new climate risk metrics using the most up-to-date data. Here we outline our process for using Python packages such as XArray and Dask to evaluate netCDF files in a distributed framework, StarCluster to operate in a cluster-computing environment, cloud computing services to access publicly hosted datasets, and how this setup is particularly valuable for generating climate change indicators and performing localized statistical analysis.

The application of data mining and cloud computing techniques in data-driven models for structural health monitoring

NASA Astrophysics Data System (ADS)

Khazaeli, S.; Ravandi, A. G.; Banerji, S.; Bagchi, A.

2016-04-01

Recently, data-driven models for Structural Health Monitoring (SHM) have been of great interest among many researchers. In data-driven models, the sensed data are processed to determine the structural performance and evaluate the damages of an instrumented structure without necessitating the mathematical modeling of the structure. A framework of data-driven models for online assessment of the condition of a structure has been developed here. The developed framework is intended for automated evaluation of the monitoring data and structural performance by the Internet technology and resources. The main challenges in developing such framework include: (a) utilizing the sensor measurements to estimate and localize the induced damage in a structure by means of signal processing and data mining techniques, and (b) optimizing the computing and storage resources with the aid of cloud services. The main focus in this paper is to demonstrate the efficiency of the proposed framework for real-time damage detection of a multi-story shear-building structure in two damage scenarios (change in mass and stiffness) in various locations. Several features are extracted from the sensed data by signal processing techniques and statistical methods. Machine learning algorithms are deployed to select damage-sensitive features as well as classifying the data to trace the anomaly in the response of the structure. Here, the cloud computing resources from Amazon Web Services (AWS) have been used to implement the proposed framework.

Development of structured ICD-10 and its application to computer-assisted ICD coding.

PubMed

Imai, Takeshi; Kajino, Masayuki; Sato, Megumi; Ohe, Kazuhiko

2010-01-01

This paper presents: (1) a framework of formal representation of ICD10, which functions as a bridge between ontological information and natural language expressions; and (2) a methodology to use formally described ICD10 for computer-assisted ICD coding. First, we analyzed and structurized the meanings of categories in 15 chapters of ICD10. Then we expanded the structured ICD10 (S-ICD10) by adding subordinate concepts and labels derived from Japanese Standard Disease Names. The information model to describe formal representation was refined repeatedly. The resultant model includes 74 types of semantic links. We also developed an ICD coding module based on S-ICD10 and a 'Coding Principle,' which achieved high accuracy (>70%) for four chapters. These results not only demonstrate the basic feasibility of our coding framework but might also inform the development of the information model for formal description framework in the ICD11 revision.

Parallels in Computer-Aided Design Framework and Software Development Environment Efforts.

DTIC Science & Technology

1992-05-01

de - sign kits, and tool and design management frameworks. Also, books about software engineer- ing environments [Long 91] and electronic design...tool integration [Zarrella 90], and agreement upon a universal de - sign automation framework, such as the CAD Framework Initiative (CFI) [Malasky 91...ments: identification, control, status accounting, and audit and review. The paper by Dart ex- tracts 15 CM concepts from existing SDEs and tools

A Framework for Debugging Geoscience Projects in a High Performance Computing Environment

NASA Astrophysics Data System (ADS)

Baxter, C.; Matott, L.

2012-12-01

High performance computing (HPC) infrastructure has become ubiquitous in today's world with the emergence of commercial cloud computing and academic supercomputing centers. Teams of geoscientists, hydrologists and engineers can take advantage of this infrastructure to undertake large research projects - for example, linking one or more site-specific environmental models with soft computing algorithms, such as heuristic global search procedures, to perform parameter estimation and predictive uncertainty analysis, and/or design least-cost remediation systems. However, the size, complexity and distributed nature of these projects can make identifying failures in the associated numerical experiments using conventional ad-hoc approaches both time- consuming and ineffective. To address these problems a multi-tiered debugging framework has been developed. The framework allows for quickly isolating and remedying a number of potential experimental failures, including: failures in the HPC scheduler; bugs in the soft computing code; bugs in the modeling code; and permissions and access control errors. The utility of the framework is demonstrated via application to a series of over 200,000 numerical experiments involving a suite of 5 heuristic global search algorithms and 15 mathematical test functions serving as cheap analogues for the simulation-based optimization of pump-and-treat subsurface remediation systems.

Large-scale structural analysis: The structural analyst, the CSM Testbed and the NAS System

NASA Technical Reports Server (NTRS)

Knight, Norman F., Jr.; Mccleary, Susan L.; Macy, Steven C.; Aminpour, Mohammad A.

1989-01-01

The Computational Structural Mechanics (CSM) activity is developing advanced structural analysis and computational methods that exploit high-performance computers. Methods are developed in the framework of the CSM testbed software system and applied to representative complex structural analysis problems from the aerospace industry. An overview of the CSM testbed methods development environment is presented and some numerical methods developed on a CRAY-2 are described. Selected application studies performed on the NAS CRAY-2 are also summarized.

VisRseq: R-based visual framework for analysis of sequencing data

PubMed Central

2015-01-01

Background Several tools have been developed to enable biologists to perform initial browsing and exploration of sequencing data. However the computational tool set for further analyses often requires significant computational expertise to use and many of the biologists with the knowledge needed to interpret these data must rely on programming experts. Results We present VisRseq, a framework for analysis of sequencing datasets that provides a computationally rich and accessible framework for integrative and interactive analyses without requiring programming expertise. We achieve this aim by providing R apps, which offer a semi-auto generated and unified graphical user interface for computational packages in R and repositories such as Bioconductor. To address the interactivity limitation inherent in R libraries, our framework includes several native apps that provide exploration and brushing operations as well as an integrated genome browser. The apps can be chained together to create more powerful analysis workflows. Conclusions To validate the usability of VisRseq for analysis of sequencing data, we present two case studies performed by our collaborators and report their workflow and insights. PMID:26328469

VisRseq: R-based visual framework for analysis of sequencing data.

PubMed

Younesy, Hamid; Möller, Torsten; Lorincz, Matthew C; Karimi, Mohammad M; Jones, Steven J M

2015-01-01

Several tools have been developed to enable biologists to perform initial browsing and exploration of sequencing data. However the computational tool set for further analyses often requires significant computational expertise to use and many of the biologists with the knowledge needed to interpret these data must rely on programming experts. We present VisRseq, a framework for analysis of sequencing datasets that provides a computationally rich and accessible framework for integrative and interactive analyses without requiring programming expertise. We achieve this aim by providing R apps, which offer a semi-auto generated and unified graphical user interface for computational packages in R and repositories such as Bioconductor. To address the interactivity limitation inherent in R libraries, our framework includes several native apps that provide exploration and brushing operations as well as an integrated genome browser. The apps can be chained together to create more powerful analysis workflows. To validate the usability of VisRseq for analysis of sequencing data, we present two case studies performed by our collaborators and report their workflow and insights.

A Web-based Distributed Voluntary Computing Platform for Large Scale Hydrological Computations

NASA Astrophysics Data System (ADS)

Demir, I.; Agliamzanov, R.

2014-12-01

Distributed volunteer computing can enable researchers and scientist to form large parallel computing environments to utilize the computing power of the millions of computers on the Internet, and use them towards running large scale environmental simulations and models to serve the common good of local communities and the world. Recent developments in web technologies and standards allow client-side scripting languages to run at speeds close to native application, and utilize the power of Graphics Processing Units (GPU). Using a client-side scripting language like JavaScript, we have developed an open distributed computing framework that makes it easy for researchers to write their own hydrologic models, and run them on volunteer computers. Users will easily enable their websites for visitors to volunteer sharing their computer resources to contribute running advanced hydrological models and simulations. Using a web-based system allows users to start volunteering their computational resources within seconds without installing any software. The framework distributes the model simulation to thousands of nodes in small spatial and computational sizes. A relational database system is utilized for managing data connections and queue management for the distributed computing nodes. In this paper, we present a web-based distributed volunteer computing platform to enable large scale hydrological simulations and model runs in an open and integrated environment.

Scout: high-performance heterogeneous computing made simple

DOE Office of Scientific and Technical Information (OSTI.GOV)

Jablin, James; Mc Cormick, Patrick; Herlihy, Maurice

2011-01-26

Researchers must often write their own simulation and analysis software. During this process they simultaneously confront both computational and scientific problems. Current strategies for aiding the generation of performance-oriented programs do not abstract the software development from the science. Furthermore, the problem is becoming increasingly complex and pressing with the continued development of many-core and heterogeneous (CPU-GPU) architectures. To acbieve high performance, scientists must expertly navigate both software and hardware. Co-design between computer scientists and research scientists can alleviate but not solve this problem. The science community requires better tools for developing, optimizing, and future-proofing codes, allowing scientists to focusmore » on their research while still achieving high computational performance. Scout is a parallel programming language and extensible compiler framework targeting heterogeneous architectures. It provides the abstraction required to buffer scientists from the constantly-shifting details of hardware while still realizing higb-performance by encapsulating software and hardware optimization within a compiler framework.« less

Layered Architectures for Quantum Computers and Quantum Repeaters

NASA Astrophysics Data System (ADS)

Jones, Nathan C.

This chapter examines how to organize quantum computers and repeaters using a systematic framework known as layered architecture, where machine control is organized in layers associated with specialized tasks. The framework is flexible and could be used for analysis and comparison of quantum information systems. To demonstrate the design principles in practice, we develop architectures for quantum computers and quantum repeaters based on optically controlled quantum dots, showing how a myriad of technologies must operate synchronously to achieve fault-tolerance. Optical control makes information processing in this system very fast, scalable to large problem sizes, and extendable to quantum communication.

CSDMS2.0: Computational Infrastructure for Community Surface Dynamics Modeling

NASA Astrophysics Data System (ADS)

Syvitski, J. P.; Hutton, E.; Peckham, S. D.; Overeem, I.; Kettner, A.

2012-12-01

The Community Surface Dynamic Modeling System (CSDMS) is an NSF-supported, international and community-driven program that seeks to transform the science and practice of earth-surface dynamics modeling. CSDMS integrates a diverse community of more than 850 geoscientists representing 360 international institutions (academic, government, industry) from 60 countries and is supported by a CSDMS Interagency Committee (22 Federal agencies), and a CSDMS Industrial Consortia (18 companies). CSDMS presently distributes more 200 Open Source models and modeling tools, access to high performance computing clusters in support of developing and running models, and a suite of products for education and knowledge transfer. CSDMS software architecture employs frameworks and services that convert stand-alone models into flexible "plug-and-play" components to be assembled into larger applications. CSDMS2.0 will support model applications within a web browser, on a wider variety of computational platforms, and on other high performance computing clusters to ensure robustness and sustainability of the framework. Conversion of stand-alone models into "plug-and-play" components will employ automated wrapping tools. Methods for quantifying model uncertainty are being adapted as part of the modeling framework. Benchmarking data is being incorporated into the CSDMS modeling framework to support model inter-comparison. Finally, a robust mechanism for ingesting and utilizing semantic mediation databases is being developed within the Modeling Framework. Six new community initiatives are being pursued: 1) an earth - ecosystem modeling initiative to capture ecosystem dynamics and ensuing interactions with landscapes, 2) a geodynamics initiative to investigate the interplay among climate, geomorphology, and tectonic processes, 3) an Anthropocene modeling initiative, to incorporate mechanistic models of human influences, 4) a coastal vulnerability modeling initiative, with emphasis on deltas and their multiple threats and stressors, 5) a continental margin modeling initiative, to capture extreme oceanic and atmospheric events generating turbidity currents in the Gulf of Mexico, and 6) a CZO Focus Research Group, to develop compatibility between CSDMS architecture and protocols and Critical Zone Observatory-developed models and data.

Wasatch: An architecture-proof multiphysics development environment using a Domain Specific Language and graph theory

DOE Office of Scientific and Technical Information (OSTI.GOV)

Saad, Tony; Sutherland, James C.

To address the coding and software challenges of modern hybrid architectures, we propose an approach to multiphysics code development for high-performance computing. This approach is based on using a Domain Specific Language (DSL) in tandem with a directed acyclic graph (DAG) representation of the problem to be solved that allows runtime algorithm generation. When coupled with a large-scale parallel framework, the result is a portable development framework capable of executing on hybrid platforms and handling the challenges of multiphysics applications. In addition, we share our experience developing a code in such an environment – an effort that spans an interdisciplinarymore » team of engineers and computer scientists.« less

Wasatch: An architecture-proof multiphysics development environment using a Domain Specific Language and graph theory

DOE PAGES

Saad, Tony; Sutherland, James C.

2016-05-04

To address the coding and software challenges of modern hybrid architectures, we propose an approach to multiphysics code development for high-performance computing. This approach is based on using a Domain Specific Language (DSL) in tandem with a directed acyclic graph (DAG) representation of the problem to be solved that allows runtime algorithm generation. When coupled with a large-scale parallel framework, the result is a portable development framework capable of executing on hybrid platforms and handling the challenges of multiphysics applications. In addition, we share our experience developing a code in such an environment – an effort that spans an interdisciplinarymore » team of engineers and computer scientists.« less

Strategizing Computer-Supported Collaborative Learning toward Knowledge Building

ERIC Educational Resources Information Center

Mukama, Evode

2010-01-01

The purpose of this paper is to explore how university students can develop knowledge in small task-based groups while acquiring hands-on computer skills. Inspired by the sociocultural perspective, this study presents a theoretical framework on co-construction of knowledge and on computer-supported collaborative learning. The participants were…

Knowledge Acquisition with Static and Animated Pictures in Computer-Based Learning.

ERIC Educational Resources Information Center

Schnotz, Wolfgang; Grzondziel, Harriet

In educational settings, computers provide specific possibilities of visualizing information for instructional purposes. Besides the use of static pictures, computers can present animated pictures which allow exploratory manipulation by the learner and display the dynamic behavior of a system. This paper develops a theoretical framework for…

Metocognitive Support Accelerates Computer Assisted Learning for Novice Programmers

ERIC Educational Resources Information Center

Rum, Siti Nurulain Mohd; Ismail, Maizatul Akmar

2017-01-01

Computer programming is a part of the curriculum in computer science education, and high drop rates for this subject are a universal problem. Development of metacognitive skills, including the conceptual framework provided by socio-cognitive theories that afford reflective thinking, such as actively monitoring, evaluating, and modifying one's…

Arcade: A Web-Java Based Framework for Distributed Computing

NASA Technical Reports Server (NTRS)

Chen, Zhikai; Maly, Kurt; Mehrotra, Piyush; Zubair, Mohammad; Bushnell, Dennis M. (Technical Monitor)

2000-01-01

Distributed heterogeneous environments are being increasingly used to execute a variety of large size simulations and computational problems. We are developing Arcade, a web-based environment to design, execute, monitor, and control distributed applications. These targeted applications consist of independent heterogeneous modules which can be executed on a distributed heterogeneous environment. In this paper we describe the overall design of the system and discuss the prototype implementation of the core functionalities required to support such a framework.

Cooperative fault-tolerant distributed computing U.S. Department of Energy Grant DE-FG02-02ER25537 Final Report

DOE Office of Scientific and Technical Information (OSTI.GOV)

Sunderam, Vaidy S.

2007-01-09

The Harness project has developed novel software frameworks for the execution of high-end simulations in a fault-tolerant manner on distributed resources. The H2O subsystem comprises the kernel of the Harness framework, and controls the key functions of resource management across multiple administrative domains, especially issues of access and allocation. It is based on a “pluggable” architecture that enables the aggregated use of distributed heterogeneous resources for high performance computing. The major contributions of the Harness II project result in significantly enhancing the overall computational productivity of high-end scientific applications by enabling robust, failure-resilient computations on cooperatively pooled resource collections.

Computational Approaches to the Chemical Equilibrium Constant in Protein-ligand Binding.

PubMed

Montalvo-Acosta, Joel José; Cecchini, Marco

2016-12-01

The physiological role played by protein-ligand recognition has motivated the development of several computational approaches to the ligand binding affinity. Some of them, termed rigorous, have a strong theoretical foundation but involve too much computation to be generally useful. Some others alleviate the computational burden by introducing strong approximations and/or empirical calibrations, which also limit their general use. Most importantly, there is no straightforward correlation between the predictive power and the level of approximation introduced. Here, we present a general framework for the quantitative interpretation of protein-ligand binding based on statistical mechanics. Within this framework, we re-derive self-consistently the fundamental equations of some popular approaches to the binding constant and pinpoint the inherent approximations. Our analysis represents a first step towards the development of variants with optimum accuracy/efficiency ratio for each stage of the drug discovery pipeline. © 2016 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

ALFA: The new ALICE-FAIR software framework

NASA Astrophysics Data System (ADS)

Al-Turany, M.; Buncic, P.; Hristov, P.; Kollegger, T.; Kouzinopoulos, C.; Lebedev, A.; Lindenstruth, V.; Manafov, A.; Richter, M.; Rybalchenko, A.; Vande Vyvre, P.; Winckler, N.

2015-12-01

The commonalities between the ALICE and FAIR experiments and their computing requirements led to the development of large parts of a common software framework in an experiment independent way. The FairRoot project has already shown the feasibility of such an approach for the FAIR experiments and extending it beyond FAIR to experiments at other facilities[1, 2]. The ALFA framework is a joint development between ALICE Online- Offline (O2) and FairRoot teams. ALFA is designed as a flexible, elastic system, which balances reliability and ease of development with performance using multi-processing and multithreading. A message- based approach has been adopted; such an approach will support the use of the software on different hardware platforms, including heterogeneous systems. Each process in ALFA assumes limited communication and reliance on other processes. Such a design will add horizontal scaling (multiple processes) to vertical scaling provided by multiple threads to meet computing and throughput demands. ALFA does not dictate any application protocols. Potentially, any content-based processor or any source can change the application protocol. The framework supports different serialization standards for data exchange between different hardware and software languages.

CSM Testbed Development and Large-Scale Structural Applications

NASA Technical Reports Server (NTRS)

Knight, Norman F., Jr.; Gillian, R. E.; Mccleary, Susan L.; Lotts, C. G.; Poole, E. L.; Overman, A. L.; Macy, S. C.

1989-01-01

A research activity called Computational Structural Mechanics (CSM) conducted at the NASA Langley Research Center is described. This activity is developing advanced structural analysis and computational methods that exploit high-performance computers. Methods are developed in the framework of the CSM Testbed software system and applied to representative complex structural analysis problems from the aerospace industry. An overview of the CSM Testbed methods development environment is presented and some new numerical methods developed on a CRAY-2 are described. Selected application studies performed on the NAS CRAY-2 are also summarized.

The Indispensable Teachers' Guide to Computer Skills. Second Edition.

ERIC Educational Resources Information Center

Johnson, Doug

This book provides a framework of technology skills that can be used for staff development. Part One presents critical components of effective staff development. Part Two describes the basic CODE 77 skills, including basic computer operation, file management, time management, word processing, network and Internet use, graphics and digital images,…

A Framework and Implementation of User Interface and Human-Computer Interaction Instruction

ERIC Educational Resources Information Center

Peslak, Alan

2005-01-01

Researchers have suggested that up to 50 % of the effort in development of information systems is devoted to user interface development (Douglas, Tremaine, Leventhal, Wills, & Manaris, 2002; Myers & Rosson, 1992). Yet little study has been performed on the inclusion of important interface and human-computer interaction topics into a current…

A Framework for Lab Work Management in Mass Courses. Application to Low Level Input/Output without Hardware

ERIC Educational Resources Information Center

Rodriguez, Santiago; Zamorano, Juan; Rosales, Francisco; Dopico, Antonio Garcia; Pedraza, Jose Luis

2007-01-01

This paper describes a complete lab work management framework designed and developed in the authors' department to help teachers to manage the small projects that students are expected to complete as lab assignments during their graduate-level computer engineering studies. The paper focuses on an application example of the framework to a specific…

A Metascalable Computing Framework for Large Spatiotemporal-Scale Atomistic Simulations

DOE Office of Scientific and Technical Information (OSTI.GOV)

Nomura, K; Seymour, R; Wang, W

2009-02-17

A metascalable (or 'design once, scale on new architectures') parallel computing framework has been developed for large spatiotemporal-scale atomistic simulations of materials based on spatiotemporal data locality principles, which is expected to scale on emerging multipetaflops architectures. The framework consists of: (1) an embedded divide-and-conquer (EDC) algorithmic framework based on spatial locality to design linear-scaling algorithms for high complexity problems; (2) a space-time-ensemble parallel (STEP) approach based on temporal locality to predict long-time dynamics, while introducing multiple parallelization axes; and (3) a tunable hierarchical cellular decomposition (HCD) parallelization framework to map these O(N) algorithms onto a multicore cluster based onmore » hybrid implementation combining message passing and critical section-free multithreading. The EDC-STEP-HCD framework exposes maximal concurrency and data locality, thereby achieving: (1) inter-node parallel efficiency well over 0.95 for 218 billion-atom molecular-dynamics and 1.68 trillion electronic-degrees-of-freedom quantum-mechanical simulations on 212,992 IBM BlueGene/L processors (superscalability); (2) high intra-node, multithreading parallel efficiency (nanoscalability); and (3) nearly perfect time/ensemble parallel efficiency (eon-scalability). The spatiotemporal scale covered by MD simulation on a sustained petaflops computer per day (i.e. petaflops {center_dot} day of computing) is estimated as NT = 2.14 (e.g. N = 2.14 million atoms for T = 1 microseconds).« less

Optimal protocols for slowly driven quantum systems.

PubMed

Zulkowski, Patrick R; DeWeese, Michael R

2015-09-01

The design of efficient quantum information processing will rely on optimal nonequilibrium transitions of driven quantum systems. Building on a recently developed geometric framework for computing optimal protocols for classical systems driven in finite time, we construct a general framework for optimizing the average information entropy for driven quantum systems. Geodesics on the parameter manifold endowed with a positive semidefinite metric correspond to protocols that minimize the average information entropy production in finite time. We use this framework to explicitly compute the optimal entropy production for a simple two-state quantum system coupled to a heat bath of bosonic oscillators, which has applications to quantum annealing.

Stochastic hybrid systems for studying biochemical processes.

PubMed

Singh, Abhyudai; Hespanha, João P

2010-11-13

Many protein and mRNA species occur at low molecular counts within cells, and hence are subject to large stochastic fluctuations in copy numbers over time. Development of computationally tractable frameworks for modelling stochastic fluctuations in population counts is essential to understand how noise at the cellular level affects biological function and phenotype. We show that stochastic hybrid systems (SHSs) provide a convenient framework for modelling the time evolution of population counts of different chemical species involved in a set of biochemical reactions. We illustrate recently developed techniques that allow fast computations of the statistical moments of the population count, without having to run computationally expensive Monte Carlo simulations of the biochemical reactions. Finally, we review different examples from the literature that illustrate the benefits of using SHSs for modelling biochemical processes.

Sustainable Supply Chain Design by the P-Graph Framework

EPA Science Inventory

The present work proposes a computer-aided methodology for designing sustainable supply chains in terms of sustainability metrics by resorting to the P-graph framework. The methodology is an outcome of the collaboration between the Office of Research and Development (ORD) of the ...

V&V framework

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hills, Richard G.; Maniaci, David Charles; Naughton, Jonathan W.

2015-09-01

A Verification and Validation (V&V) framework is presented for the development and execution of coordinated modeling and experimental program s to assess the predictive capability of computational models of complex systems through focused, well structured, and formal processes.The elements of the framework are based on established V&V methodology developed by various organizations including the Department of Energy, National Aeronautics and Space Administration, the American Institute of Aeronautics and Astronautics, and the American Society of Mechanical Engineers. Four main topics are addressed: 1) Program planning based on expert elicitation of the modeling physics requirements, 2) experimental design for model assessment, 3)more » uncertainty quantification for experimental observations and computational model simulations, and 4) assessment of the model predictive capability. The audience for this document includes program planners, modelers, experimentalist, V &V specialist, and customers of the modeling results.« less

Resource Aware Intelligent Network Services (RAINS) Final Technical Report

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lehman, Tom; Yang, Xi

The Resource Aware Intelligent Network Services (RAINS) project conducted research and developed technologies in the area of cyber infrastructure resource modeling and computation. The goal of this work was to provide a foundation to enable intelligent, software defined services which spanned the network AND the resources which connect to the network. A Multi-Resource Service Plane (MRSP) was defined, which allows resource owners/managers to locate and place themselves from a topology and service availability perspective within the dynamic networked cyberinfrastructure ecosystem. The MRSP enables the presentation of integrated topology views and computation results which can include resources across the spectrum ofmore » compute, storage, and networks. The RAINS project developed MSRP includes the following key components: i) Multi-Resource Service (MRS) Ontology/Multi-Resource Markup Language (MRML), ii) Resource Computation Engine (RCE), iii) Modular Driver Framework (to allow integration of a variety of external resources). The MRS/MRML is a general and extensible modeling framework that allows for resource owners to model, or describe, a wide variety of resource types. All resources are described using three categories of elements: Resources, Services, and Relationships between the elements. This modeling framework defines a common method for the transformation of cyber infrastructure resources into data in the form of MRML models. In order to realize this infrastructure datification, the RAINS project developed a model based computation system, i.e. “RAINS Computation Engine (RCE)”. The RCE has the ability to ingest, process, integrate, and compute based on automatically generated MRML models. The RCE interacts with the resources thru system drivers which are specific to the type of external network or resource controller. The RAINS project developed a modular and pluggable driver system which facilities a variety of resource controllers to automatically generate, maintain, and distribute MRML based resource descriptions. Once all of the resource topologies are absorbed by the RCE, a connected graph of the full distributed system topology is constructed, which forms the basis for computation and workflow processing. The RCE includes a Modular Computation Element (MCE) framework which allows for tailoring of the computation process to the specific set of resources under control, and the services desired. The input and output of an MCE are both model data based on MRS/MRML ontology and schema. Some of the RAINS project accomplishments include: Development of general and extensible multi-resource modeling framework; Design of a Resource Computation Engine (RCE) system which includes the following key capabilities; Absorb a variety of multi-resource model types and build integrated models; Novel architecture which uses model based communications across the full stack for all Flexible provision of abstract or intent based user facing interfaces; Workflow processing based on model descriptions; Release of the RCE as an open source software; Deployment of RCE in the University of Maryland/Mid-Atlantic Crossroad ScienceDMZ in prototype mode with a plan under way to transition to production; Deployment at the Argonne National Laboratory DTN Facility in prototype mode; Selection of RCE by the DOE SENSE (SDN for End-to-end Networked Science at the Exascale) project as the basis for their orchestration service.« less

Approximations of thermoelastic and viscoelastic control systems

NASA Technical Reports Server (NTRS)

Burns, J. A.; Liu, Z. Y.; Miller, R. E.

1990-01-01

Well-posed models and computational algorithms are developed and analyzed for control of a class of partial differential equations that describe the motions of thermo-viscoelastic structures. An abstract (state space) framework and a general well-posedness result are presented that can be applied to a large class of thermo-elastic and thermo-viscoelastic models. This state space framework is used in the development of a computational scheme to be used in the solution of a linear quadratic regulator (LQR) control problem. A detailed convergence proof is provided for the viscoelastic model and several numerical results are presented to illustrate the theory and to analyze problems for which the theory is incomplete.

International Computer and Information Literacy Study: Assessment Framework

ERIC Educational Resources Information Center

Fraillon, Julian; Schulz, Wolfram; Ainley, John

2013-01-01

The purpose of the International Computer and Information Literacy Study 2013 (ICILS 2013) is to investigate, in a range of countries, the ways in which young people are developing "computer and information literacy" (CIL) to support their capacity to participate in the digital age. To achieve this aim, the study will assess student…

Designing computer learning environments for engineering and computer science: The scaffolded knowledge integration framework

NASA Astrophysics Data System (ADS)

Linn, Marcia C.

1995-06-01

Designing effective curricula for complex topics and incorporating technological tools is an evolving process. One important way to foster effective design is to synthesize successful practices. This paper describes a framework called scaffolded knowledge integration and illustrates how it guided the design of two successful course enhancements in the field of computer science and engineering. One course enhancement, the LISP Knowledge Integration Environment, improved learning and resulted in more gender-equitable outcomes. The second course enhancement, the spatial reasoning environment, addressed spatial reasoning in an introductory engineering course. This enhancement minimized the importance of prior knowledge of spatial reasoning and helped students develop a more comprehensive repertoire of spatial reasoning strategies. Taken together, the instructional research programs reinforce the value of the scaffolded knowledge integration framework and suggest directions for future curriculum reformers.

Integration of a CAD System Into an MDO Framework

NASA Technical Reports Server (NTRS)

Townsend, J. C.; Samareh, J. A.; Weston, R. P.; Zorumski, W. E.

1998-01-01

NASA Langley has developed a heterogeneous distributed computing environment, called the Framework for Inter-disciplinary Design Optimization, or FIDO. Its purpose has been to demonstrate framework technical feasibility and usefulness for optimizing the preliminary design of complex systems and to provide a working environment for testing optimization schemes. Its initial implementation has been for a simplified model of preliminary design of a high-speed civil transport. Upgrades being considered for the FIDO system include a more complete geometry description, required by high-fidelity aerodynamics and structures codes and based on a commercial Computer Aided Design (CAD) system. This report presents the philosophy behind some of the decisions that have shaped the FIDO system and gives a brief case study of the problems and successes encountered in integrating a CAD system into the FEDO framework.

Beyond computer literacy: supporting youth's positive development through technology.

PubMed

Bers, Marina Umaschi

2010-01-01

In a digital era in which technology plays a role in most aspects of a child's life, having the competence and confidence to use computers might be a necessary step, but not a goal in itself. Developing character traits that will serve children to use technology in a safe way to communicate and connect with others, and providing opportunities for children to make a better world through the use of their computational skills, is just as important. The Positive Technological Development framework (PTD), a natural extension of the computer literacy and the technological fluency movements that have influenced the world of educational technology, adds psychosocial, civic, and ethical components to the cognitive ones. PTD examines the developmental tasks of a child growing up in our digital era and provides a model for developing and evaluating technology-rich youth programs. The explicit goal of PTD programs is to support children in the positive uses of technology to lead more fulfilling lives and make the world a better place. This article introduces the concept of PTD and presents examples of the Zora virtual world program for young people that the author developed following this framework.

Designing Energy Supply Chains with the P-graph Framework under Cost Constraints and Sustainability Considerations

EPA Science Inventory

A computer-aided methodology for designing sustainable supply chains is presented using the P-graph framework to develop supply chain structures which are analyzed using cost, the cost of producing electricity, and two sustainability metrics: ecological footprint and emergy. They...

Synthesis of Sustainable Energy Supply Chain by the P-Graph Framework

EPA Science Inventory

The present work proposes a computer-aided methodology for designing sustainable supply chains in terms of sustainability metrics by utilizing the P-graph framework. The methodology is an outcome of the collaboration between the Office of Research and Development (ORD) of the U.S...

Designing Energy Supply Chains with the P-Graph Framework under Cost Constraints andSustainability Considerations

EPA Science Inventory

A computer-aided methodology for designing sustainable supply chains is presented using the P-graph framework to develop supply chain structures which are analyzed using cost, the cost of producing electricity, and two sustainability metrics: ecological footprint and emergy. They...

A biologically consistent hierarchical framework for self-referencing survivalist computation

NASA Astrophysics Data System (ADS)

Cottam, Ron; Ranson, Willy; Vounckx, Roger

2000-05-01

Extensively scaled formally rational hardware and software are indirectly fallible, at the very least through temporal restrictions on the evaluation of their correctness. In addition, the apparent inability of formal rationality to successfully describe living systems as anything other than inanimate structures suggests that the development of self-referencing computational machines will require a different approach. There is currently a strong movement towards the adoption of semiotics as a descriptive medium in theoretical biology. We present a related computational semiosic construction (1, 2) consistent with evolutionary hierarchical emergence (3), which may serve as a framework for implementing anticipatory-oriented survivalist processing in real environments.

A framework for different levels of integration of computational models into web-based virtual patients.

PubMed

Kononowicz, Andrzej A; Narracott, Andrew J; Manini, Simone; Bayley, Martin J; Lawford, Patricia V; McCormack, Keith; Zary, Nabil

2014-01-23

Virtual patients are increasingly common tools used in health care education to foster learning of clinical reasoning skills. One potential way to expand their functionality is to augment virtual patients' interactivity by enriching them with computational models of physiological and pathological processes. The primary goal of this paper was to propose a conceptual framework for the integration of computational models within virtual patients, with particular focus on (1) characteristics to be addressed while preparing the integration, (2) the extent of the integration, (3) strategies to achieve integration, and (4) methods for evaluating the feasibility of integration. An additional goal was to pilot the first investigation of changing framework variables on altering perceptions of integration. The framework was constructed using an iterative process informed by Soft System Methodology. The Virtual Physiological Human (VPH) initiative has been used as a source of new computational models. The technical challenges associated with development of virtual patients enhanced by computational models are discussed from the perspectives of a number of different stakeholders. Concrete design and evaluation steps are discussed in the context of an exemplar virtual patient employing the results of the VPH ARCH project, as well as improvements for future iterations. The proposed framework consists of four main elements. The first element is a list of feasibility features characterizing the integration process from three perspectives: the computational modelling researcher, the health care educationalist, and the virtual patient system developer. The second element included three integration levels: basic, where a single set of simulation outcomes is generated for specific nodes in the activity graph; intermediate, involving pre-generation of simulation datasets over a range of input parameters; advanced, including dynamic solution of the model. The third element is the description of four integration strategies, and the last element consisted of evaluation profiles specifying the relevant feasibility features and acceptance thresholds for specific purposes. The group of experts who evaluated the virtual patient exemplar found higher integration more interesting, but at the same time they were more concerned with the validity of the result. The observed differences were not statistically significant. This paper outlines a framework for the integration of computational models into virtual patients. The opportunities and challenges of model exploitation are discussed from a number of user perspectives, considering different levels of model integration. The long-term aim for future research is to isolate the most crucial factors in the framework and to determine their influence on the integration outcome.

A Framework for Different Levels of Integration of Computational Models Into Web-Based Virtual Patients

PubMed Central

Narracott, Andrew J; Manini, Simone; Bayley, Martin J; Lawford, Patricia V; McCormack, Keith; Zary, Nabil

2014-01-01

Background Virtual patients are increasingly common tools used in health care education to foster learning of clinical reasoning skills. One potential way to expand their functionality is to augment virtual patients’ interactivity by enriching them with computational models of physiological and pathological processes. Objective The primary goal of this paper was to propose a conceptual framework for the integration of computational models within virtual patients, with particular focus on (1) characteristics to be addressed while preparing the integration, (2) the extent of the integration, (3) strategies to achieve integration, and (4) methods for evaluating the feasibility of integration. An additional goal was to pilot the first investigation of changing framework variables on altering perceptions of integration. Methods The framework was constructed using an iterative process informed by Soft System Methodology. The Virtual Physiological Human (VPH) initiative has been used as a source of new computational models. The technical challenges associated with development of virtual patients enhanced by computational models are discussed from the perspectives of a number of different stakeholders. Concrete design and evaluation steps are discussed in the context of an exemplar virtual patient employing the results of the VPH ARCH project, as well as improvements for future iterations. Results The proposed framework consists of four main elements. The first element is a list of feasibility features characterizing the integration process from three perspectives: the computational modelling researcher, the health care educationalist, and the virtual patient system developer. The second element included three integration levels: basic, where a single set of simulation outcomes is generated for specific nodes in the activity graph; intermediate, involving pre-generation of simulation datasets over a range of input parameters; advanced, including dynamic solution of the model. The third element is the description of four integration strategies, and the last element consisted of evaluation profiles specifying the relevant feasibility features and acceptance thresholds for specific purposes. The group of experts who evaluated the virtual patient exemplar found higher integration more interesting, but at the same time they were more concerned with the validity of the result. The observed differences were not statistically significant. Conclusions This paper outlines a framework for the integration of computational models into virtual patients. The opportunities and challenges of model exploitation are discussed from a number of user perspectives, considering different levels of model integration. The long-term aim for future research is to isolate the most crucial factors in the framework and to determine their influence on the integration outcome. PMID:24463466

A General Cross-Layer Cloud Scheduling Framework for Multiple IoT Computer Tasks.

PubMed

Wu, Guanlin; Bao, Weidong; Zhu, Xiaomin; Zhang, Xiongtao

2018-05-23

The diversity of IoT services and applications brings enormous challenges to improving the performance of multiple computer tasks' scheduling in cross-layer cloud computing systems. Unfortunately, the commonly-employed frameworks fail to adapt to the new patterns on the cross-layer cloud. To solve this issue, we design a new computer task scheduling framework for multiple IoT services in cross-layer cloud computing systems. Specifically, we first analyze the features of the cross-layer cloud and computer tasks. Then, we design the scheduling framework based on the analysis and present detailed models to illustrate the procedures of using the framework. With the proposed framework, the IoT services deployed in cross-layer cloud computing systems can dynamically select suitable algorithms and use resources more effectively to finish computer tasks with different objectives. Finally, the algorithms are given based on the framework, and extensive experiments are also given to validate its effectiveness, as well as its superiority.

Tool Integration Framework for Bio-Informatics

DTIC Science & Technology

2007-04-01

Java NetBeans [11] based Integrated Development Environment (IDE) for developing modules and packaging computational tools. The framework is extremely...integrate an Eclipse front-end for Desktop Integration. Eclipse was chosen over Netbeans owing to a higher acceptance, better infrastructure...5.0. This version of Dashboard ran with NetBeans IDE 3.6 requiring Java Runtime 1.4 on a machine with Windows XP. The toolchain is executed by

Security and Cloud Outsourcing Framework for Economic Dispatch

DOE Office of Scientific and Technical Information (OSTI.GOV)

Sarker, Mushfiqur R.; Wang, Jianhui; Li, Zuyi

The computational complexity and problem sizes of power grid applications have increased significantly with the advent of renewable resources and smart grid technologies. The current paradigm of solving these issues consist of inhouse high performance computing infrastructures, which have drawbacks of high capital expenditures, maintenance, and limited scalability. Cloud computing is an ideal alternative due to its powerful computational capacity, rapid scalability, and high cost-effectiveness. A major challenge, however, remains in that the highly confidential grid data is susceptible for potential cyberattacks when outsourced to the cloud. In this work, a security and cloud outsourcing framework is developed for themore » Economic Dispatch (ED) linear programming application. As a result, the security framework transforms the ED linear program into a confidentiality-preserving linear program, that masks both the data and problem structure, thus enabling secure outsourcing to the cloud. Results show that for large grid test cases the performance gain and costs outperforms the in-house infrastructure.« less

Security and Cloud Outsourcing Framework for Economic Dispatch

DOE PAGES

Sarker, Mushfiqur R.; Wang, Jianhui; Li, Zuyi; ...

2017-04-24

The computational complexity and problem sizes of power grid applications have increased significantly with the advent of renewable resources and smart grid technologies. The current paradigm of solving these issues consist of inhouse high performance computing infrastructures, which have drawbacks of high capital expenditures, maintenance, and limited scalability. Cloud computing is an ideal alternative due to its powerful computational capacity, rapid scalability, and high cost-effectiveness. A major challenge, however, remains in that the highly confidential grid data is susceptible for potential cyberattacks when outsourced to the cloud. In this work, a security and cloud outsourcing framework is developed for themore » Economic Dispatch (ED) linear programming application. As a result, the security framework transforms the ED linear program into a confidentiality-preserving linear program, that masks both the data and problem structure, thus enabling secure outsourcing to the cloud. Results show that for large grid test cases the performance gain and costs outperforms the in-house infrastructure.« less

Patient-Specific Simulation of Cardiac Blood Flow From High-Resolution Computed Tomography.

PubMed

Lantz, Jonas; Henriksson, Lilian; Persson, Anders; Karlsson, Matts; Ebbers, Tino

2016-12-01

Cardiac hemodynamics can be computed from medical imaging data, and results could potentially aid in cardiac diagnosis and treatment optimization. However, simulations are often based on simplified geometries, ignoring features such as papillary muscles and trabeculae due to their complex shape, limitations in image acquisitions, and challenges in computational modeling. This severely hampers the use of computational fluid dynamics in clinical practice. The overall aim of this study was to develop a novel numerical framework that incorporated these geometrical features. The model included the left atrium, ventricle, ascending aorta, and heart valves. The framework used image registration to obtain patient-specific wall motion, automatic remeshing to handle topological changes due to the complex trabeculae motion, and a fast interpolation routine to obtain intermediate meshes during the simulations. Velocity fields and residence time were evaluated, and they indicated that papillary muscles and trabeculae strongly interacted with the blood, which could not be observed in a simplified model. The framework resulted in a model with outstanding geometrical detail, demonstrating the feasibility as well as the importance of a framework that is capable of simulating blood flow in physiologically realistic hearts.

Modelling of anisotropic growth in biological tissues. A new approach and computational aspects.

PubMed

Menzel, A

2005-03-01

In this contribution, we develop a theoretical and computational framework for anisotropic growth phenomena. As a key idea of the proposed phenomenological approach, a fibre or rather structural tensor is introduced, which allows the description of transversely isotropic material behaviour. Based on this additional argument, anisotropic growth is modelled via appropriate evolution equations for the fibre while volumetric remodelling is realised by an evolution of the referential density. Both the strength of the fibre as well as the density follow Wolff-type laws. We however elaborate on two different approaches for the evolution of the fibre direction, namely an alignment with respect to strain or with respect to stress. One of the main benefits of the developed framework is therefore the opportunity to address the evolutions of the fibre strength and the fibre direction separately. It is then straightforward to set up appropriate integration algorithms such that the developed framework fits nicely into common, finite element schemes. Finally, several numerical examples underline the applicability of the proposed formulation.

A comprehensive combined experimental and computational framework for pre-clinical wear simulation of total knee replacements.

PubMed

Abdelgaied, A; Fisher, J; Jennings, L M

2018-02-01

A more robust pre-clinical wear simulation framework is required in order to simulate wider and higher ranges of activities, observed in different patient populations such as younger more active patients. Such a framework will help to understand and address the reported higher failure rates for younger and more active patients (National_Joint_Registry, 2016). The current study has developed and validated a comprehensive combined experimental and computational framework for pre-clinical wear simulation of total knee replacements (TKR). The input mechanical (elastic modulus and Poisson's ratio) and wear parameters of the moderately cross-linked ultra-high molecular weight polyethylene (UHMWPE) bearing material were independently measured from experimental studies under realistic test conditions, similar to the loading conditions found in the total knee replacements. The wear predictions from the computational wear simulation were validated against the direct experimental wear measurements for size 3 Sigma curved total knee replacements (DePuy, UK) in an independent experimental wear simulation study under three different daily activities; walking, deep squat, and stairs ascending kinematic conditions. The measured compressive mechanical properties of the moderately cross-linked UHMWPE material were more than 20% lower than that reported in the literature under tensile test conditions. The pin-on-plate wear coefficient of moderately cross-linked UHMWPE was significantly dependant of the contact stress and the degree of cross-shear at the articulating surfaces. The computational wear predictions for the TKR from the current framework were consistent and in a good agreement with the independent full TKR experimental wear simulation measurements, with 0.94 coefficient of determination of the framework. In addition, the comprehensive combined experimental and computational framework was able to explain the complex experimental wear trends from the three different daily activities investigated. Therefore, such a framework can be adopted as a pre-clinical simulation approach to optimise different designs, materials, as well as patient's specific total knee replacements for a range of activities. Copyright © 2017. Published by Elsevier Ltd.

Frameworks Coordinate Scientific Data Management

NASA Technical Reports Server (NTRS)

2012-01-01

Jet Propulsion Laboratory computer scientists developed a unique software framework to help NASA manage its massive amounts of science data. Through a partnership with the Apache Software Foundation of Forest Hill, Maryland, the technology is now available as an open-source solution and is in use by cancer researchers and pediatric hospitals.

Structure, function, and behaviour of computational models in systems biology

PubMed Central

2013-01-01

Background Systems Biology develops computational models in order to understand biological phenomena. The increasing number and complexity of such “bio-models” necessitate computer support for the overall modelling task. Computer-aided modelling has to be based on a formal semantic description of bio-models. But, even if computational bio-models themselves are represented precisely in terms of mathematical expressions their full meaning is not yet formally specified and only described in natural language. Results We present a conceptual framework – the meaning facets – which can be used to rigorously specify the semantics of bio-models. A bio-model has a dual interpretation: On the one hand it is a mathematical expression which can be used in computational simulations (intrinsic meaning). On the other hand the model is related to the biological reality (extrinsic meaning). We show that in both cases this interpretation should be performed from three perspectives: the meaning of the model’s components (structure), the meaning of the model’s intended use (function), and the meaning of the model’s dynamics (behaviour). In order to demonstrate the strengths of the meaning facets framework we apply it to two semantically related models of the cell cycle. Thereby, we make use of existing approaches for computer representation of bio-models as much as possible and sketch the missing pieces. Conclusions The meaning facets framework provides a systematic in-depth approach to the semantics of bio-models. It can serve two important purposes: First, it specifies and structures the information which biologists have to take into account if they build, use and exchange models. Secondly, because it can be formalised, the framework is a solid foundation for any sort of computer support in bio-modelling. The proposed conceptual framework establishes a new methodology for modelling in Systems Biology and constitutes a basis for computer-aided collaborative research. PMID:23721297

plasmaFoam: An OpenFOAM framework for computational plasma physics and chemistry

NASA Astrophysics Data System (ADS)

Venkattraman, Ayyaswamy; Verma, Abhishek Kumar

2016-09-01

As emphasized in the 2012 Roadmap for low temperature plasmas (LTP), scientific computing has emerged as an essential tool for the investigation and prediction of the fundamental physical and chemical processes associated with these systems. While several in-house and commercial codes exist, with each having its own advantages and disadvantages, a common framework that can be developed by researchers from all over the world will likely accelerate the impact of computational studies on advances in low-temperature plasma physics and chemistry. In this regard, we present a finite volume computational toolbox to perform high-fidelity simulations of LTP systems. This framework, primarily based on the OpenFOAM solver suite, allows us to enhance our understanding of multiscale plasma phenomenon by performing massively parallel, three-dimensional simulations on unstructured meshes using well-established high performance computing tools that are widely used in the computational fluid dynamics community. In this talk, we will present preliminary results obtained using the OpenFOAM-based solver suite with benchmark three-dimensional simulations of microplasma devices including both dielectric and plasma regions. We will also discuss the future outlook for the solver suite.

DockScreen: A database of in silico biomolecular interactions to support computational toxicology

EPA Science Inventory

We have developed DockScreen, a database of in silico biomolecular interactions designed to enable rational molecular toxicological insight within a computational toxicology framework. This database is composed of chemical/target (receptor and enzyme) binding scores calculated by...

jInv: A Modular and Scalable Framework for Electromagnetic Inverse Problems

NASA Astrophysics Data System (ADS)

Belliveau, P. T.; Haber, E.

2016-12-01

Inversion is a key tool in the interpretation of geophysical electromagnetic (EM) data. Three-dimensional (3D) EM inversion is very computationally expensive and practical software for inverting large 3D EM surveys must be able to take advantage of high performance computing (HPC) resources. It has traditionally been difficult to achieve those goals in a high level dynamic programming environment that allows rapid development and testing of new algorithms, which is important in a research setting. With those goals in mind, we have developed jInv, a framework for PDE constrained parameter estimation problems. jInv provides optimization and regularization routines, a framework for user defined forward problems, and interfaces to several direct and iterative solvers for sparse linear systems. The forward modeling framework provides finite volume discretizations of differential operators on rectangular tensor product meshes and tetrahedral unstructured meshes that can be used to easily construct forward modeling and sensitivity routines for forward problems described by partial differential equations. jInv is written in the emerging programming language Julia. Julia is a dynamic language targeted at the computational science community with a focus on high performance and native support for parallel programming. We have developed frequency and time-domain EM forward modeling and sensitivity routines for jInv. We will illustrate its capabilities and performance with two synthetic time-domain EM inversion examples. First, in airborne surveys, which use many sources, we achieve distributed memory parallelism by decoupling the forward and inverse meshes and performing forward modeling for each source on small, locally refined meshes. Secondly, we invert grounded source time-domain data from a gradient array style induced polarization survey using a novel time-stepping technique that allows us to compute data from different time-steps in parallel. These examples both show that it is possible to invert large scale 3D time-domain EM datasets within a modular, extensible framework written in a high-level, easy to use programming language.

Advanced computational simulations of water waves interacting with wave energy converters

NASA Astrophysics Data System (ADS)

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.

A Framework for Image-Based Modeling of Acute Myocardial Ischemia Using Intramurally Recorded Extracellular Potentials.

PubMed

Burton, Brett M; Aras, Kedar K; Good, Wilson W; Tate, Jess D; Zenger, Brian; MacLeod, Rob S

2018-05-21

The biophysical basis for electrocardiographic evaluation of myocardial ischemia stems from the notion that ischemic tissues develop, with relative uniformity, along the endocardial aspects of the heart. These injured regions of subendocardial tissue give rise to intramural currents that lead to ST segment deflections within electrocardiogram (ECG) recordings. The concept of subendocardial ischemic regions is often used in clinical practice, providing a simple and intuitive description of ischemic injury; however, such a model grossly oversimplifies the presentation of ischemic disease-inadvertently leading to errors in ECG-based diagnoses. Furthermore, recent experimental studies have brought into question the subendocardial ischemia paradigm suggesting instead a more distributed pattern of tissue injury. These findings come from experiments and so have both the impact and the limitations of measurements from living organisms. Computer models have often been employed to overcome the constraints of experimental approaches and have a robust history in cardiac simulation. To this end, we have developed a computational simulation framework aimed at elucidating the effects of ischemia on measurable cardiac potentials. To validate our framework, we simulated, visualized, and analyzed 226 experimentally derived acute myocardial ischemic events. Simulation outcomes agreed both qualitatively (feature comparison) and quantitatively (correlation, average error, and significance) with experimentally obtained epicardial measurements, particularly under conditions of elevated ischemic stress. Our simulation framework introduces a novel approach to incorporating subject-specific, geometric models and experimental results that are highly resolved in space and time into computational models. We propose this framework as a means to advance the understanding of the underlying mechanisms of ischemic disease while simultaneously putting in place the computational infrastructure necessary to study and improve ischemia models aimed at reducing diagnostic errors in the clinic.

An Optimization Framework for Dynamic Hybrid Energy Systems

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wenbo Du; Humberto E Garcia; Christiaan J.J. Paredis

A computational framework for the efficient analysis and optimization of dynamic hybrid energy systems (HES) is developed. A microgrid system with multiple inputs and multiple outputs (MIMO) is modeled using the Modelica language in the Dymola environment. The optimization loop is implemented in MATLAB, with the FMI Toolbox serving as the interface between the computational platforms. Two characteristic optimization problems are selected to demonstrate the methodology and gain insight into the system performance. The first is an unconstrained optimization problem that optimizes the dynamic properties of the battery, reactor and generator to minimize variability in the HES. The second problemmore » takes operating and capital costs into consideration by imposing linear and nonlinear constraints on the design variables. The preliminary optimization results obtained in this study provide an essential step towards the development of a comprehensive framework for designing HES.« less

A Conceptual Framework for Electronic Socio-Emotional Support for People with Special Needs

ERIC Educational Resources Information Center

Shpigelman, Carmit-Noa; Reiter, Shunit; Weiss, Patrice L.

2009-01-01

In recent years an increasing number of people under psychological distress turn to computer-mediated communication for support. A related development is the increasing number of computer-mediated support groups in which people meet, share interests, and exchange socio-emotional support through text-based messages on computer networks. To date, a…

Effectiveness of an Electronic Performance Support System on Computer Ethics and Ethical Decision-Making Education

ERIC Educational Resources Information Center

Kert, Serhat Bahadir; Uz, Cigdem; Gecu, Zeynep

2014-01-01

This study examined the effectiveness of an electronic performance support system (EPSS) on computer ethics education and the ethical decision-making processes. There were five different phases to this ten month study: (1) Writing computer ethics scenarios, (2) Designing a decision-making framework (3) Developing EPSS software (4) Using EPSS in a…

Multimodal neuroelectric interface development

NASA Technical Reports Server (NTRS)

Trejo, Leonard J.; Wheeler, Kevin R.; Jorgensen, Charles C.; Rosipal, Roman; Clanton, Sam T.; Matthews, Bryan; Hibbs, Andrew D.; Matthews, Robert; Krupka, Michael

2003-01-01

We are developing electromyographic and electroencephalographic methods, which draw control signals for human-computer interfaces from the human nervous system. We have made progress in four areas: 1) real-time pattern recognition algorithms for decoding sequences of forearm muscle activity associated with control gestures; 2) signal-processing strategies for computer interfaces using electroencephalogram (EEG) signals; 3) a flexible computation framework for neuroelectric interface research; and d) noncontact sensors, which measure electromyogram or EEG signals without resistive contact to the body.

Multidisciplinary Environments: A History of Engineering Framework Development

NASA Technical Reports Server (NTRS)

Padula, Sharon L.; Gillian, Ronnie E.

2006-01-01

This paper traces the history of engineering frameworks and their use by Multidisciplinary Design Optimization (MDO) practitioners. The approach is to reference papers that have been presented at one of the ten previous Multidisciplinary Analysis and Optimization (MA&O) conferences. By limiting the search to MA&O papers, the authors can (1) identify the key ideas that led to general purpose MDO frameworks and (2) uncover roadblocks that delayed the development of these ideas. The authors make no attempt to assign credit for revolutionary ideas or to assign blame for missed opportunities. Rather, the goal is to trace the various threads of computer architecture and software framework research and to observe how these threads contributed to the commercial framework products available today.

Scalable and massively parallel Monte Carlo photon transport simulations for heterogeneous computing platforms

NASA Astrophysics Data System (ADS)

Yu, Leiming; Nina-Paravecino, Fanny; Kaeli, David; Fang, Qianqian

2018-01-01

We present a highly scalable Monte Carlo (MC) three-dimensional photon transport simulation platform designed for heterogeneous computing systems. Through the development of a massively parallel MC algorithm using the Open Computing Language framework, this research extends our existing graphics processing unit (GPU)-accelerated MC technique to a highly scalable vendor-independent heterogeneous computing environment, achieving significantly improved performance and software portability. A number of parallel computing techniques are investigated to achieve portable performance over a wide range of computing hardware. Furthermore, multiple thread-level and device-level load-balancing strategies are developed to obtain efficient simulations using multiple central processing units and GPUs.

iTools: a framework for classification, categorization and integration of computational biology resources.

PubMed

Dinov, Ivo D; Rubin, Daniel; Lorensen, William; Dugan, Jonathan; Ma, Jeff; Murphy, Shawn; Kirschner, Beth; Bug, William; Sherman, Michael; Floratos, Aris; Kennedy, David; Jagadish, H V; Schmidt, Jeanette; Athey, Brian; Califano, Andrea; Musen, Mark; Altman, Russ; Kikinis, Ron; Kohane, Isaac; Delp, Scott; Parker, D Stott; Toga, Arthur W

2008-05-28

The advancement of the computational biology field hinges on progress in three fundamental directions--the development of new computational algorithms, the availability of informatics resource management infrastructures and the capability of tools to interoperate and synergize. There is an explosion in algorithms and tools for computational biology, which makes it difficult for biologists to find, compare and integrate such resources. We describe a new infrastructure, iTools, for managing the query, traversal and comparison of diverse computational biology resources. Specifically, iTools stores information about three types of resources--data, software tools and web-services. The iTools design, implementation and resource meta-data content reflect the broad research, computational, applied and scientific expertise available at the seven National Centers for Biomedical Computing. iTools provides a system for classification, categorization and integration of different computational biology resources across space-and-time scales, biomedical problems, computational infrastructures and mathematical foundations. A large number of resources are already iTools-accessible to the community and this infrastructure is rapidly growing. iTools includes human and machine interfaces to its resource meta-data repository. Investigators or computer programs may utilize these interfaces to search, compare, expand, revise and mine meta-data descriptions of existent computational biology resources. We propose two ways to browse and display the iTools dynamic collection of resources. The first one is based on an ontology of computational biology resources, and the second one is derived from hyperbolic projections of manifolds or complex structures onto planar discs. iTools is an open source project both in terms of the source code development as well as its meta-data content. iTools employs a decentralized, portable, scalable and lightweight framework for long-term resource management. We demonstrate several applications of iTools as a framework for integrated bioinformatics. iTools and the complete details about its specifications, usage and interfaces are available at the iTools web page http://iTools.ccb.ucla.edu.

iTools: A Framework for Classification, Categorization and Integration of Computational Biology Resources

PubMed Central

Dinov, Ivo D.; Rubin, Daniel; Lorensen, William; Dugan, Jonathan; Ma, Jeff; Murphy, Shawn; Kirschner, Beth; Bug, William; Sherman, Michael; Floratos, Aris; Kennedy, David; Jagadish, H. V.; Schmidt, Jeanette; Athey, Brian; Califano, Andrea; Musen, Mark; Altman, Russ; Kikinis, Ron; Kohane, Isaac; Delp, Scott; Parker, D. Stott; Toga, Arthur W.

2008-01-01

The advancement of the computational biology field hinges on progress in three fundamental directions – the development of new computational algorithms, the availability of informatics resource management infrastructures and the capability of tools to interoperate and synergize. There is an explosion in algorithms and tools for computational biology, which makes it difficult for biologists to find, compare and integrate such resources. We describe a new infrastructure, iTools, for managing the query, traversal and comparison of diverse computational biology resources. Specifically, iTools stores information about three types of resources–data, software tools and web-services. The iTools design, implementation and resource meta - data content reflect the broad research, computational, applied and scientific expertise available at the seven National Centers for Biomedical Computing. iTools provides a system for classification, categorization and integration of different computational biology resources across space-and-time scales, biomedical problems, computational infrastructures and mathematical foundations. A large number of resources are already iTools-accessible to the community and this infrastructure is rapidly growing. iTools includes human and machine interfaces to its resource meta-data repository. Investigators or computer programs may utilize these interfaces to search, compare, expand, revise and mine meta-data descriptions of existent computational biology resources. We propose two ways to browse and display the iTools dynamic collection of resources. The first one is based on an ontology of computational biology resources, and the second one is derived from hyperbolic projections of manifolds or complex structures onto planar discs. iTools is an open source project both in terms of the source code development as well as its meta-data content. iTools employs a decentralized, portable, scalable and lightweight framework for long-term resource management. We demonstrate several applications of iTools as a framework for integrated bioinformatics. iTools and the complete details about its specifications, usage and interfaces are available at the iTools web page http://iTools.ccb.ucla.edu. PMID:18509477

An Uncertainty Quantification Framework for Prognostics and Condition-Based Monitoring

NASA Technical Reports Server (NTRS)

Sankararaman, Shankar; Goebel, Kai

2014-01-01

This paper presents a computational framework for uncertainty quantification in prognostics in the context of condition-based monitoring of aerospace systems. The different sources of uncertainty and the various uncertainty quantification activities in condition-based prognostics are outlined in detail, and it is demonstrated that the Bayesian subjective approach is suitable for interpreting uncertainty in online monitoring. A state-space model-based framework for prognostics, that can rigorously account for the various sources of uncertainty, is presented. Prognostics consists of two important steps. First, the state of the system is estimated using Bayesian tracking, and then, the future states of the system are predicted until failure, thereby computing the remaining useful life of the system. The proposed framework is illustrated using the power system of a planetary rover test-bed, which is being developed and studied at NASA Ames Research Center.

AnRAD: A Neuromorphic Anomaly Detection Framework for Massive Concurrent Data Streams.

PubMed

Chen, Qiuwen; Luley, Ryan; Wu, Qing; Bishop, Morgan; Linderman, Richard W; Qiu, Qinru

2018-05-01

The evolution of high performance computing technologies has enabled the large-scale implementation of neuromorphic models and pushed the research in computational intelligence into a new era. Among the machine learning applications, unsupervised detection of anomalous streams is especially challenging due to the requirements of detection accuracy and real-time performance. Designing a computing framework that harnesses the growing computing power of the multicore systems while maintaining high sensitivity and specificity to the anomalies is an urgent research topic. In this paper, we propose anomaly recognition and detection (AnRAD), a bioinspired detection framework that performs probabilistic inferences. We analyze the feature dependency and develop a self-structuring method that learns an efficient confabulation network using unlabeled data. This network is capable of fast incremental learning, which continuously refines the knowledge base using streaming data. Compared with several existing anomaly detection approaches, our method provides competitive detection quality. Furthermore, we exploit the massive parallel structure of the AnRAD framework. Our implementations of the detection algorithm on the graphic processing unit and the Xeon Phi coprocessor both obtain substantial speedups over the sequential implementation on general-purpose microprocessor. The framework provides real-time service to concurrent data streams within diversified knowledge contexts, and can be applied to large problems with multiple local patterns. Experimental results demonstrate high computing performance and memory efficiency. For vehicle behavior detection, the framework is able to monitor up to 16000 vehicles (data streams) and their interactions in real time with a single commodity coprocessor, and uses less than 0.2 ms for one testing subject. Finally, the detection network is ported to our spiking neural network simulator to show the potential of adapting to the emerging neuromorphic architectures.

Computational Embryology and Predictive Toxicology of Hypospadias (SOT)

EPA Science Inventory

Hypospadias, one of the most common birth defects in human male infants, is a condition in which the urethral opening is misplaced along ventral aspect of the penis. We developed an Adverse Outcome Pathway (AOP) framework and computer simulation that describes the pathogenesis of...

Development of software for computing forming information using a component based approach

NASA Astrophysics Data System (ADS)

Ko, Kwang Hee; Park, Jiing Seo; Kim, Jung; Kim, Young Bum; Shin, Jong Gye

2009-12-01

In shipbuilding industry, the manufacturing technology> has advanced at an unprecedented pace for the last decade. As a result, many automatic systems for cutting, welding, etc. have been developed and employed in the manufacturing process and accordingly the productivity has been increased drastically. Despite such improvement in the manufacturing technology', however, development of an automatic system for fabricating a curved hull plate remains at the beginning stage since hardware and software for the automation of the curved hull fabrication process should be developed differently depending on the dimensions of plates, forming methods and manufacturing processes of each shipyard. To deal with this problem, it is necessary> to create a "plug-in ''framework, which can adopt various kinds of hardware and software to construct a full automatic fabrication system. In this paper, a frame-work for automatic fabrication of curved hull plates is proposed, which consists of four components and related software. In particular the software module for computing fabrication information is developed by using the ooCBD development methodology; which can interface with other hardware and software with minimum effort. Examples of the proposed framework applied to medium and large shipyards are presented.

The WHATs and HOWs of maturing computational and software engineering skills in Russian higher education institutions

NASA Astrophysics Data System (ADS)

Semushin, I. V.; Tsyganova, J. V.; Ugarov, V. V.; Afanasova, A. I.

2018-05-01

Russian higher education institutions' tradition of teaching large-enrolled classes is impairing student striving for individual prominence, one-upmanship, and hopes for originality. Intending to converting these drawbacks into benefits, a Project-Centred Education Model (PCEM) has been introduced to deliver Computational Mathematics and Information Science courses. The model combines a Frontal Competitive Approach and a Project-Driven Learning (PDL) framework. The PDL framework has been developed by stating and solving three design problems: (i) enhance the diversity of project assignments on specific computation methods algorithmic approaches, (ii) balance similarity and dissimilarity of the project assignments, and (iii) develop a software assessment tool suitable for evaluating the technological maturity of students' project deliverables and thus reducing instructor's workload and possible overlook. The positive experience accumulated over 15 years shows that implementing the PCEM keeps students motivated to strive for success in rising to higher levels of their computational and software engineering skills.

A dynamic water-quality modeling framework for the Neuse River estuary, North Carolina

USGS Publications Warehouse

Bales, Jerad D.; Robbins, Jeanne C.

1999-01-01

As a result of fish kills in the Neuse River estuary in 1995, nutrient reduction strategies were developed for point and nonpoint sources in the basin. However, because of the interannual variability in the natural system and the resulting complex hydrologic-nutrient inter- actions, it is difficult to detect through a short-term observational program the effects of management activities on Neuse River estuary water quality and aquatic health. A properly constructed water-quality model can be used to evaluate some of the potential effects of manage- ment actions on estuarine water quality. Such a model can be used to predict estuarine response to present and proposed nutrient strategies under the same set of meteorological and hydrologic conditions, thus removing the vagaries of weather and streamflow from the analysis. A two-dimensional, laterally averaged hydrodynamic and water-quality modeling framework was developed for the Neuse River estuary by using previously collected data. Development of the modeling framework consisted of (1) computational grid development, (2) assembly of data for model boundary conditions and model testing, (3) selection of initial values of model parameters, and (4) limited model testing. The model domain extends from Streets Ferry to Oriental, N.C., includes seven lateral embayments that have continual exchange with the main- stem of the estuary, three point-source discharges, and three tributary streams. Thirty-five computational segments represent the mainstem of the estuary, and the entire framework contains a total of 60 computa- tional segments. Each computational cell is 0.5 meter thick; segment lengths range from 500 meters to 7,125 meters. Data that were used to develop the modeling framework were collected during March through October 1991 and represent the most comprehensive data set available prior to 1997. Most of the data were collected by the North Carolina Division of Water Quality, the University of North Carolina Institute of Marine Sciences, and the U.S. Geological Survey. Limitations in the modeling framework were clearly identified. These limitations formed the basis for a set of suggestions to refine the Neuse River estuary water-quality model.

Development of solute transport models in YMPYRÄ framework to simulate solute migration in military shooting and training areas

NASA Astrophysics Data System (ADS)

Warsta, L.; Karvonen, T.

2017-12-01

There are currently 25 shooting and training areas in Finland managed by The Finnish Defence Forces (FDF), where military activities can cause contamination of open waters and groundwater reservoirs. In the YMPYRÄ project, a computer software framework is being developed that combines existing open environmental data and proprietary information collected by FDF with computational models to investigate current and prevent future environmental problems. A data centric philosophy is followed in the development of the system, i.e. the models are updated and extended to handle available data from different areas. The results generated by the models are summarized as easily understandable flow and risk maps that can be opened in GIS programs and used in environmental assessments by experts. Substances investigated with the system include explosives and metals such as lead, and both surface and groundwater dominated areas can be simulated. The YMPYRÄ framework is composed of a three dimensional soil and groundwater flow model, several solute transport models and an uncertainty assessment system. Solute transport models in the framework include particle based, stream tube and finite volume based approaches. The models can be used to simulate solute dissolution from source area, transport in the unsaturated layers to groundwater and finally migration in groundwater to water extraction wells and springs. The models can be used to simulate advection, dispersion, equilibrium adsorption on soil particles, solubility and dissolution from solute phase and dendritic solute decay chains. Correct numerical solutions were confirmed by comparing results to analytical 1D and 2D solutions and by comparing the numerical solutions to each other. The particle based and stream tube type solute transport models were useful as they could complement the traditional finite volume based approach which in certain circumstances produced numerical dispersion due to piecewise solution of the governing equations in computational grids and included computationally intensive and in some cases unstable iterative solutions. The YMPYRÄ framework is being developed by WaterHope, Gain Oy, and SITO Oy consulting companies and funded by FDF.

Architecutres, Models, Algorithms, and Software Tools for Configurable Computing

DTIC Science & Technology

2000-03-06

and J.G. Nash. The gated interconnection network for dynamic programming. Plenum, 1988 . [18] Ju wook Jang, Heonchul Park, and Viktor K. Prasanna. A ...Sep. 1997. [2] C. Ebeling, D. C. Cronquist , P. Franklin and C. Fisher, "RaPiD - A configurable computing architecture for compute-intensive...ABSTRACT (Maximum 200 words) The Models, Algorithms, and Architectures for Reconfigurable Computing (MAARC) project developed a sound framework for

An Integrated Data-Driven Strategy for Safe-by-Design Nanoparticles: The FP7 MODERN Project.

PubMed

Brehm, Martin; Kafka, Alexander; Bamler, Markus; Kühne, Ralph; Schüürmann, Gerrit; Sikk, Lauri; Burk, Jaanus; Burk, Peeter; Tamm, Tarmo; Tämm, Kaido; Pokhrel, Suman; Mädler, Lutz; Kahru, Anne; Aruoja, Villem; Sihtmäe, Mariliis; Scott-Fordsmand, Janeck; Sorensen, Peter B; Escorihuela, Laura; Roca, Carlos P; Fernández, Alberto; Giralt, Francesc; Rallo, Robert

2017-01-01

The development and implementation of safe-by-design strategies is key for the safe development of future generations of nanotechnology enabled products. The safety testing of the huge variety of nanomaterials that can be synthetized is unfeasible due to time and cost constraints. Computational modeling facilitates the implementation of alternative testing strategies in a time and cost effective way. The development of predictive nanotoxicology models requires the use of high quality experimental data on the structure, physicochemical properties and bioactivity of nanomaterials. The FP7 Project MODERN has developed and evaluated the main components of a computational framework for the evaluation of the environmental and health impacts of nanoparticles. This chapter describes each of the elements of the framework including aspects related to data generation, management and integration; development of nanodescriptors; establishment of nanostructure-activity relationships; identification of nanoparticle categories; hazard ranking and risk assessment.

Computational Thinking in High School Science Classrooms: Exploring the Science "Framework" and "NGSS"

ERIC Educational Resources Information Center

Sneider, Cary; Stephenson, Chris; Schafer, Bruce; Flick, Larry

2014-01-01

A "Framework for K-12 Science Education" identified eight practices as "essential elements of the K-12 science and engineering curriculum" (NRC 2012, p. 49). Most of the practices, such as Developing and Using Models, Planning and Carrying Out Investigations, and Analyzing and Interpreting Data, are well known among science…

The "Day in the Life of a Teenage Hobo" Project: Integrating Technology with Shneiderman's Collect-Relate-Create- Donate Framework

ERIC Educational Resources Information Center

Reich, Justin; Daccord, Thomas

2009-01-01

Used wisely, academic technology empowers students to take responsibility for their own learning. "In Leonardo's Laptop," Ben Shneiderman provides teachers with a powerful framework, "Collect-Relate-Create-Donate" (CRCD), for designing student-centered learning opportunities using computers. Shneiderman developed his model by…

A Framework for Understanding Physics Students' Computational Modeling Practices

NASA Astrophysics Data System (ADS)

Lunk, Brandon Robert

With the growing push to include computational modeling in the physics classroom, we are faced with the need to better understand students' computational modeling practices. While existing research on programming comprehension explores how novices and experts generate programming algorithms, little of this discusses how domain content knowledge, and physics knowledge in particular, can influence students' programming practices. In an effort to better understand this issue, I have developed a framework for modeling these practices based on a resource stance towards student knowledge. A resource framework models knowledge as the activation of vast networks of elements called "resources." Much like neurons in the brain, resources that become active can trigger cascading events of activation throughout the broader network. This model emphasizes the connectivity between knowledge elements and provides a description of students' knowledge base. Together with resources resources, the concepts of "epistemic games" and "frames" provide a means for addressing the interaction between content knowledge and practices. Although this framework has generally been limited to describing conceptual and mathematical understanding, it also provides a means for addressing students' programming practices. In this dissertation, I will demonstrate this facet of a resource framework as well as fill in an important missing piece: a set of epistemic games that can describe students' computational modeling strategies. The development of this theoretical framework emerged from the analysis of video data of students generating computational models during the laboratory component of a Matter & Interactions: Modern Mechanics course. Student participants across two semesters were recorded as they worked in groups to fix pre-written computational models that were initially missing key lines of code. Analysis of this video data showed that the students' programming practices were highly influenced by their existing physics content knowledge, particularly their knowledge of analytic procedures. While this existing knowledge was often applied in inappropriate circumstances, the students were still able to display a considerable amount of understanding of the physics content and of analytic solution procedures. These observations could not be adequately accommodated by the existing literature of programming comprehension. In extending the resource framework to the task of computational modeling, I model students' practices in terms of three important elements. First, a knowledge base includes re- sources for understanding physics, math, and programming structures. Second, a mechanism for monitoring and control describes students' expectations as being directed towards numerical, analytic, qualitative or rote solution approaches and which can be influenced by the problem representation. Third, a set of solution approaches---many of which were identified in this study---describe what aspects of the knowledge base students use and how they use that knowledge to enact their expectations. This framework allows us as researchers to track student discussions and pinpoint the source of difficulties. This work opens up many avenues of potential research. First, this framework gives researchers a vocabulary for extending Resource Theory to other domains of instruction, such as modeling how physics students use graphs. Second, this framework can be used as the basis for modeling expert physicists' programming practices. Important instructional implications also follow from this research. Namely, as we broaden the use of computational modeling in the physics classroom, our instructional practices should focus on helping students understand the step-by-step nature of programming in contrast to the already salient analytic procedures.

GiPSi:a framework for open source/open architecture software development for organ-level surgical simulation.

PubMed

Cavuşoğlu, M Cenk; Göktekin, Tolga G; Tendick, Frank

2006-04-01

This paper presents the architectural details of an evolving open source/open architecture software framework for developing organ-level surgical simulations. Our goal is to facilitate shared development of reusable models, to accommodate heterogeneous models of computation, and to provide a framework for interfacing multiple heterogeneous models. The framework provides an application programming interface for interfacing dynamic models defined over spatial domains. It is specifically designed to be independent of the specifics of the modeling methods used, and therefore facilitates seamless integration of heterogeneous models and processes. Furthermore, each model has separate geometries for visualization, simulation, and interfacing, allowing the model developer to choose the most natural geometric representation for each case. Input/output interfaces for visualization and haptics for real-time interactive applications have also been provided.

Computational rationality: linking mechanism and behavior through bounded utility maximization.

PubMed

Lewis, Richard L; Howes, Andrew; Singh, Satinder

2014-04-01

We propose a framework for including information-processing bounds in rational analyses. It is an application of bounded optimality (Russell & Subramanian, 1995) to the challenges of developing theories of mechanism and behavior. The framework is based on the idea that behaviors are generated by cognitive mechanisms that are adapted to the structure of not only the environment but also the mind and brain itself. We call the framework computational rationality to emphasize the incorporation of computational mechanism into the definition of rational action. Theories are specified as optimal program problems, defined by an adaptation environment, a bounded machine, and a utility function. Such theories yield different classes of explanation, depending on the extent to which they emphasize adaptation to bounds, and adaptation to some ecology that differs from the immediate local environment. We illustrate this variation with examples from three domains: visual attention in a linguistic task, manual response ordering, and reasoning. We explore the relation of this framework to existing "levels" approaches to explanation, and to other optimality-based modeling approaches. Copyright © 2014 Cognitive Science Society, Inc.

Software Engineering Support of the Third Round of Scientific Grand Challenge Investigations: Earth System Modeling Software Framework Survey

NASA Technical Reports Server (NTRS)

Talbot, Bryan; Zhou, Shu-Jia; Higgins, Glenn; Zukor, Dorothy (Technical Monitor)

2002-01-01

One of the most significant challenges in large-scale climate modeling, as well as in high-performance computing in other scientific fields, is that of effectively integrating many software models from multiple contributors. A software framework facilitates the integration task, both in the development and runtime stages of the simulation. Effective software frameworks reduce the programming burden for the investigators, freeing them to focus more on the science and less on the parallel communication implementation. while maintaining high performance across numerous supercomputer and workstation architectures. This document surveys numerous software frameworks for potential use in Earth science modeling. Several frameworks are evaluated in depth, including Parallel Object-Oriented Methods and Applications (POOMA), Cactus (from (he relativistic physics community), Overture, Goddard Earth Modeling System (GEMS), the National Center for Atmospheric Research Flux Coupler, and UCLA/UCB Distributed Data Broker (DDB). Frameworks evaluated in less detail include ROOT, Parallel Application Workspace (PAWS), and Advanced Large-Scale Integrated Computational Environment (ALICE). A host of other frameworks and related tools are referenced in this context. The frameworks are evaluated individually and also compared with each other.

GeoFramework: A Modeling Framework for Solid Earth Geophysics

NASA Astrophysics Data System (ADS)

Gurnis, M.; Aivazis, M.; Tromp, J.; Tan, E.; Thoutireddy, P.; Liu, Q.; Choi, E.; Dicaprio, C.; Chen, M.; Simons, M.; Quenette, S.; Appelbe, B.; Aagaard, B.; Williams, C.; Lavier, L.; Moresi, L.; Law, H.

2003-12-01

As data sets in geophysics become larger and of greater relevance to other earth science disciplines, and as earth science becomes more interdisciplinary in general, modeling tools are being driven in new directions. There is now a greater need to link modeling codes to one another, link modeling codes to multiple datasets, and to make modeling software available to non modeling specialists. Coupled with rapid progress in computer hardware (including the computational speed afforded by massively parallel computers), progress in numerical algorithms, and the introduction of software frameworks, these lofty goals of merging software in geophysics are now possible. The GeoFramework project, a collaboration between computer scientists and geoscientists, is a response to these needs and opportunities. GeoFramework is based on and extends Pyre, a Python-based modeling framework, recently developed to link solid (Lagrangian) and fluid (Eulerian) models, as well as mesh generators, visualization packages, and databases, with one another for engineering applications. The utility and generality of Pyre as a general purpose framework in science is now being recognized. Besides its use in engineering and geophysics, it is also being used in particle physics and astronomy. Geology and geophysics impose their own unique requirements on software frameworks which are not generally available in existing frameworks and so there is a need for research in this area. One of the special requirements is the way Lagrangian and Eulerian codes will need to be linked in time and space within a plate tectonics context. GeoFramework has grown beyond its initial goal of linking a limited number of exiting codes together. The following codes are now being reengineered within the context of Pyre: Tecton, 3-D FE Visco-elastic code for lithospheric relaxation; CitComS, a code for spherical mantle convection; SpecFEM3D, a SEM code for global and regional seismic waves; eqsim, a FE code for dynamic earthquake rupture; SNAC, a developing 3-D coded based on the FLAC method for visco-elastoplastic deformation; SNARK, a 3-D FE-PIC method for viscoplastic deformation; and gPLATES an open source paleogeographic/plate tectonics modeling package. We will demonstrate how codes can be linked with themselves, such as a regional and global model of mantle convection and a visco-elastoplastic representation of the crust within viscous mantle flow. Finally, we will describe how http://GeoFramework.org has become a distribution site for a suite of modeling software in geophysics.

The Computational and Neural Basis of Cognitive Control: Charted Territory and New Frontiers

ERIC Educational Resources Information Center

Botvinick, Matthew M.; Cohen, Jonathan D.

2014-01-01

Cognitive control has long been one of the most active areas of computational modeling work in cognitive science. The focus on computational models as a medium for specifying and developing theory predates the PDP books, and cognitive control was not one of the areas on which they focused. However, the framework they provided has injected work on…

Cartographic Modeling: Computer-assisted Analysis of Spatially Defined Neighborhoods

NASA Technical Reports Server (NTRS)

Berry, J. K.; Tomlin, C. D.

1982-01-01

Cartographic models addressing a wide variety of applications are composed of fundamental map processing operations. These primitive operations are neither data base nor application-specific. By organizing the set of operations into a mathematical-like structure, the basis for a generalized cartographic modeling framework can be developed. Among the major classes of primitive operations are those associated with reclassifying map categories, overlaying maps, determining distance and connectivity, and characterizing cartographic neighborhoods. The conceptual framework of cartographic modeling is established and techniques for characterizing neighborhoods are used as a means of demonstrating some of the more sophisticated procedures of computer-assisted map analysis. A cartographic model for assessing effective roundwood supply is briefly described as an example of a computer analysis. Most of the techniques described have been implemented as part of the map analysis package developed at the Yale School of Forestry and Environmental Studies.

Computational Aspects of Data Assimilation and the ESMF

NASA Technical Reports Server (NTRS)

daSilva, A.

2003-01-01

The scientific challenge of developing advanced data assimilation applications is a daunting task. Independently developed components may have incompatible interfaces or may be written in different computer languages. The high-performance computer (HPC) platforms required by numerically intensive Earth system applications are complex, varied, rapidly evolving and multi-part systems themselves. Since the market for high-end platforms is relatively small, there is little robust middleware available to buffer the modeler from the difficulties of HPC programming. To complicate matters further, the collaborations required to develop large Earth system applications often span initiatives, institutions and agencies, involve geoscience, software engineering, and computer science communities, and cross national borders.The Earth System Modeling Framework (ESMF) project is a concerted response to these challenges. Its goal is to increase software reuse, interoperability, ease of use and performance in Earth system models through the use of a common software framework, developed in an open manner by leaders in the modeling community. The ESMF addresses the technical and to some extent the cultural - aspects of Earth system modeling, laying the groundwork for addressing the more difficult scientific aspects, such as the physical compatibility of components, in the future. In this talk we will discuss the general philosophy and architecture of the ESMF, focussing on those capabilities useful for developing advanced data assimilation applications.

A Communication-Optimal Framework for Contracting Distributed Tensors

DOE Office of Scientific and Technical Information (OSTI.GOV)

Rajbhandari, Samyam; NIkam, Akshay; Lai, Pai-Wei

Tensor contractions are extremely compute intensive generalized matrix multiplication operations encountered in many computational science fields, such as quantum chemistry and nuclear physics. Unlike distributed matrix multiplication, which has been extensively studied, limited work has been done in understanding distributed tensor contractions. In this paper, we characterize distributed tensor contraction algorithms on torus networks. We develop a framework with three fundamental communication operators to generate communication-efficient contraction algorithms for arbitrary tensor contractions. We show that for a given amount of memory per processor, our framework is communication optimal for all tensor contractions. We demonstrate performance and scalability of our frameworkmore » on up to 262,144 cores of BG/Q supercomputer using five tensor contraction examples.« less

Online SVT Commissioning and Monitoring using a Service-Oriented Architecture Framework

NASA Astrophysics Data System (ADS)

Ruger, Justin; Gotra, Yuri; Weygand, Dennis; Ziegler, Veronique; Heddle, David; Gore, David

2014-03-01

Silicon Vertex Tracker detectors are devices used in high energy experiments for precision measurement of charged tracks close to the collision point. Early detection of faulty hardware is essential and therefore code development of monitoring and commissioning software is essential. The computing framework for the CLAS12 experiment at Jefferson Lab is a service-oriented architecture that allows efficient data-flow from one service to another through loose coupling. I will present the strategy and development of services for the CLAS12 Silicon Tracker data monitoring and commissioning within this framework, as well as preliminary results using test data.

Using computer simulations to facilitate conceptual understanding of electromagnetic induction

NASA Astrophysics Data System (ADS)

Lee, Yu-Fen

This study investigated the use of computer simulations to facilitate conceptual understanding in physics. The use of computer simulations in the present study was grounded in a conceptual framework drawn from findings related to the use of computer simulations in physics education. To achieve the goal of effective utilization of computers for physics education, I first reviewed studies pertaining to computer simulations in physics education categorized by three different learning frameworks and studies comparing the effects of different simulation environments. My intent was to identify the learning context and factors for successful use of computer simulations in past studies and to learn from the studies which did not obtain a significant result. Based on the analysis of reviewed literature, I proposed effective approaches to integrate computer simulations in physics education. These approaches are consistent with well established education principles such as those suggested by How People Learn (Bransford, Brown, Cocking, Donovan, & Pellegrino, 2000). The research based approaches to integrated computer simulations in physics education form a learning framework called Concept Learning with Computer Simulations (CLCS) in the current study. The second component of this study was to examine the CLCS learning framework empirically. The participants were recruited from a public high school in Beijing, China. All participating students were randomly assigned to two groups, the experimental (CLCS) group and the control (TRAD) group. Research based computer simulations developed by the physics education research group at University of Colorado at Boulder were used to tackle common conceptual difficulties in learning electromagnetic induction. While interacting with computer simulations, CLCS students were asked to answer reflective questions designed to stimulate qualitative reasoning and explanation. After receiving model reasoning online, students were asked to submit their revised answers electronically. Students in the TRAD group were not granted access to the CLCS material and followed their normal classroom routine. At the end of the study, both the CLCS and TRAD students took a post-test. Questions on the post-test were divided into "what" questions, "how" questions, and an open response question. Analysis of students' post-test performance showed mixed results. While the TRAD students scored higher on the "what" questions, the CLCS students scored higher on the "how" questions and the one open response questions. This result suggested that more TRAD students knew what kinds of conditions may or may not cause electromagnetic induction without understanding how electromagnetic induction works. Analysis of the CLCS students' learning also suggested that frequent disruption and technical trouble might pose threats to the effectiveness of the CLCS learning framework. Despite the mixed results of students' post-test performance, the CLCS learning framework revealed some limitations to promote conceptual understanding in physics. Improvement can be made by providing students with background knowledge necessary to understand model reasoning and incorporating the CLCS learning framework with other learning frameworks to promote integration of various physics concepts. In addition, the reflective questions in the CLCS learning framework may be refined to better address students' difficulties. Limitations of the study, as well as suggestions for future research, are also presented in this study.

A Design for Computationally Enabled Analyses Supporting the Pre-Intervention Analytical Framework (PIAF)

DTIC Science & Technology

2015-06-01

public release; distribution is unlimited. The US Army Engineer Research and Development Center (ERDC) solves the nation’s toughest engineering and...Framework (PIAF) Timothy K. Perkins and Chris C. Rewerts Construction Engineering Research Laboratory U.S. Army Engineer Research and Development Center...Prepared for U.S. Army Corps of Engineers Washington, DC 20314-1000 Under Project P2 335530, “Cultural Reasoning and Ethnographic Analysis for the

URDME: a modular framework for stochastic simulation of reaction-transport processes in complex geometries.

PubMed

Drawert, Brian; Engblom, Stefan; Hellander, Andreas

2012-06-22

Experiments in silico using stochastic reaction-diffusion models have emerged as an important tool in molecular systems biology. Designing computational software for such applications poses several challenges. Firstly, realistic lattice-based modeling for biological applications requires a consistent way of handling complex geometries, including curved inner- and outer boundaries. Secondly, spatiotemporal stochastic simulations are computationally expensive due to the fast time scales of individual reaction- and diffusion events when compared to the biological phenomena of actual interest. We therefore argue that simulation software needs to be both computationally efficient, employing sophisticated algorithms, yet in the same time flexible in order to meet present and future needs of increasingly complex biological modeling. We have developed URDME, a flexible software framework for general stochastic reaction-transport modeling and simulation. URDME uses Unstructured triangular and tetrahedral meshes to resolve general geometries, and relies on the Reaction-Diffusion Master Equation formalism to model the processes under study. An interface to a mature geometry and mesh handling external software (Comsol Multiphysics) provides for a stable and interactive environment for model construction. The core simulation routines are logically separated from the model building interface and written in a low-level language for computational efficiency. The connection to the geometry handling software is realized via a Matlab interface which facilitates script computing, data management, and post-processing. For practitioners, the software therefore behaves much as an interactive Matlab toolbox. At the same time, it is possible to modify and extend URDME with newly developed simulation routines. Since the overall design effectively hides the complexity of managing the geometry and meshes, this means that newly developed methods may be tested in a realistic setting already at an early stage of development. In this paper we demonstrate, in a series of examples with high relevance to the molecular systems biology community, that the proposed software framework is a useful tool for both practitioners and developers of spatial stochastic simulation algorithms. Through the combined efforts of algorithm development and improved modeling accuracy, increasingly complex biological models become feasible to study through computational methods. URDME is freely available at http://www.urdme.org.

A WPS Based Architecture for Climate Data Analytic Services (CDAS) at NASA

NASA Astrophysics Data System (ADS)

Maxwell, T. P.; McInerney, M.; Duffy, D.; Carriere, L.; Potter, G. L.; Doutriaux, C.

2015-12-01

Faced with unprecedented growth in the Big Data domain of climate science, NASA has developed the Climate Data Analytic Services (CDAS) framework. This framework enables scientists to execute trusted and tested analysis operations in a high performance environment close to the massive data stores at NASA. The data is accessed in standard (NetCDF, HDF, etc.) formats in a POSIX file system and processed using trusted climate data analysis tools (ESMF, CDAT, NCO, etc.). The framework is structured as a set of interacting modules allowing maximal flexibility in deployment choices. The current set of module managers include: Staging Manager: Runs the computation locally on the WPS server or remotely using tools such as celery or SLURM. Compute Engine Manager: Runs the computation serially or distributed over nodes using a parallelization framework such as celery or spark. Decomposition Manger: Manages strategies for distributing the data over nodes. Data Manager: Handles the import of domain data from long term storage and manages the in-memory and disk-based caching architectures. Kernel manager: A kernel is an encapsulated computational unit which executes a processor's compute task. Each kernel is implemented in python exploiting existing analysis packages (e.g. CDAT) and is compatible with all CDAS compute engines and decompositions. CDAS services are accessed via a WPS API being developed in collaboration with the ESGF Compute Working Team to support server-side analytics for ESGF. The API can be executed using either direct web service calls, a python script or application, or a javascript-based web application. Client packages in python or javascript contain everything needed to make CDAS requests. The CDAS architecture brings together the tools, data storage, and high-performance computing required for timely analysis of large-scale data sets, where the data resides, to ultimately produce societal benefits. It is is currently deployed at NASA in support of the Collaborative REAnalysis Technical Environment (CREATE) project, which centralizes numerous global reanalysis datasets onto a single advanced data analytics platform. This service permits decision makers to investigate climate changes around the globe, inspect model trends, compare multiple reanalysis datasets, and variability.

Noise in Neuronal and Electronic Circuits: A General Modeling Framework and Non-Monte Carlo Simulation Techniques.

PubMed

Kilinc, Deniz; Demir, Alper

2017-08-01

The brain is extremely energy efficient and remarkably robust in what it does despite the considerable variability and noise caused by the stochastic mechanisms in neurons and synapses. Computational modeling is a powerful tool that can help us gain insight into this important aspect of brain mechanism. A deep understanding and computational design tools can help develop robust neuromorphic electronic circuits and hybrid neuroelectronic systems. In this paper, we present a general modeling framework for biological neuronal circuits that systematically captures the nonstationary stochastic behavior of ion channels and synaptic processes. In this framework, fine-grained, discrete-state, continuous-time Markov chain models of both ion channels and synaptic processes are treated in a unified manner. Our modeling framework features a mechanism for the automatic generation of the corresponding coarse-grained, continuous-state, continuous-time stochastic differential equation models for neuronal variability and noise. Furthermore, we repurpose non-Monte Carlo noise analysis techniques, which were previously developed for analog electronic circuits, for the stochastic characterization of neuronal circuits both in time and frequency domain. We verify that the fast non-Monte Carlo analysis methods produce results with the same accuracy as computationally expensive Monte Carlo simulations. We have implemented the proposed techniques in a prototype simulator, where both biological neuronal and analog electronic circuits can be simulated together in a coupled manner.

A Software Rejuvenation Framework for Distributed Computing

NASA Technical Reports Server (NTRS)

Chau, Savio

2009-01-01

A performability-oriented conceptual framework for software rejuvenation has been constructed as a means of increasing levels of reliability and performance in distributed stateful computing. As used here, performability-oriented signifies that the construction of the framework is guided by the concept of analyzing the ability of a given computing system to deliver services with gracefully degradable performance. The framework is especially intended to support applications that involve stateful replicas of server computers.

A New Biogeochemical Computational Framework Integrated within the Community Land Model

NASA Astrophysics Data System (ADS)

Fang, Y.; Li, H.; Liu, C.; Huang, M.; Leung, L.

2012-12-01

Terrestrial biogeochemical processes, particularly carbon cycle dynamics, have been shown to significantly influence regional and global climate changes. Modeling terrestrial biogeochemical processes within the land component of Earth System Models such as the Community Land model (CLM), however, faces three major challenges: 1) extensive efforts in modifying modeling structures and rewriting computer programs to incorporate biogeochemical processes with increasing complexity, 2) expensive computational cost to solve the governing equations due to numerical stiffness inherited from large variations in the rates of biogeochemical processes, and 3) lack of an efficient framework to systematically evaluate various mathematical representations of biogeochemical processes. To address these challenges, we introduce a new computational framework to incorporate biogeochemical processes into CLM, which consists of a new biogeochemical module with a generic algorithm and reaction database. New and updated biogeochemical processes can be incorporated into CLM without significant code modification. To address the stiffness issue, algorithms and criteria will be developed to identify fast processes, which will be replaced with algebraic equations and decoupled from slow processes. This framework can serve as a generic and user-friendly platform to test out different mechanistic process representations and datasets and gain new insight on the behavior of the terrestrial ecosystems in response to climate change in a systematic way.

Task-based image quality assessment in radiation therapy: initial characterization and demonstration with CT simulation images

NASA Astrophysics Data System (ADS)

Dolly, Steven R.; Anastasio, Mark A.; Yu, Lifeng; Li, Hua

2017-03-01

In current radiation therapy practice, image quality is still assessed subjectively or by utilizing physically-based metrics. Recently, a methodology for objective task-based image quality (IQ) assessment in radiation therapy was proposed by Barrett et al.1 In this work, we present a comprehensive implementation and evaluation of this new IQ assessment methodology. A modular simulation framework was designed to perform an automated, computer-simulated end-to-end radiation therapy treatment. A fully simulated framework was created that utilizes new learning-based stochastic object models (SOM) to obtain known organ boundaries, generates a set of images directly from the numerical phantoms created with the SOM, and automates the image segmentation and treatment planning steps of a radiation therapy work ow. By use of this computational framework, therapeutic operating characteristic (TOC) curves can be computed and the area under the TOC curve (AUTOC) can be employed as a figure-of-merit to guide optimization of different components of the treatment planning process. The developed computational framework is employed to optimize X-ray CT pre-treatment imaging. We demonstrate that use of the radiation therapy-based-based IQ measures lead to different imaging parameters than obtained by use of physical-based measures.

Integration of hybrid wireless networks in cloud services oriented enterprise information systems

NASA Astrophysics Data System (ADS)

Li, Shancang; Xu, Lida; Wang, Xinheng; Wang, Jue

2012-05-01

This article presents a hybrid wireless network integration scheme in cloud services-based enterprise information systems (EISs). With the emerging hybrid wireless networks and cloud computing technologies, it is necessary to develop a scheme that can seamlessly integrate these new technologies into existing EISs. By combining the hybrid wireless networks and computing in EIS, a new framework is proposed, which includes frontend layer, middle layer and backend layers connected to IP EISs. Based on a collaborative architecture, cloud services management framework and process diagram are presented. As a key feature, the proposed approach integrates access control functionalities within the hybrid framework that provide users with filtered views on available cloud services based on cloud service access requirements and user security credentials. In future work, we will implement the proposed framework over SwanMesh platform by integrating the UPnP standard into an enterprise information system.

A Validation Framework for the Long Term Preservation of High Energy Physics Data

NASA Astrophysics Data System (ADS)

Ozerov, Dmitri; South, David M.

2014-06-01

The study group on data preservation in high energy physics, DPHEP, is moving to a new collaboration structure, which will focus on the implementation of preservation projects, such as those described in the group's large scale report published in 2012. One such project is the development of a validation framework, which checks the compatibility of evolving computing environments and technologies with the experiments software for as long as possible, with the aim of substantially extending the lifetime of the analysis software, and hence of the usability of the data. The framework is designed to automatically test and validate the software and data of an experiment against changes and upgrades to the computing environment, as well as changes to the experiment software itself. Technically, this is realised using a framework capable of hosting a number of virtual machine images, built with different configurations of operating systems and the relevant software, including any necessary external dependencies.

Abilities and Affordances: Factors Influencing Successful Child-Tablet Communication

ERIC Educational Resources Information Center

Dubé, Adam K.; McEwen, Rhonda N.

2017-01-01

Using Luhmann's communication theory and affordance theories, we develop a framework to examine how kindergarten-grade 2 students interact with tablet computers. We assessed whether cognitive ability and device configuration influence how successfully children use tablet computers. We found that children's limited ability to direct their cognitive…

Use of a Computer Simulation To Develop Mental Simulations for Understanding Relative Motion Concepts.

ERIC Educational Resources Information Center

Monaghan, James M.; Clement, John

1999-01-01

Presents evidence for students' qualitative and quantitative difficulties with apparently simple one-dimensional relative-motion problems, students' spontaneous visualization of relative-motion problems, the visualizations facilitating solution of these problems, and students' memories of the online computer simulation used as a framework for…

Computer Technology Standards of Learning for Virginia's Public Schools

ERIC Educational Resources Information Center

Virginia Department of Education, 2005

2005-01-01

The Computer/Technology Standards of Learning identify and define the progressive development of essential knowledge and skills necessary for students to access, evaluate, use, and create information using technology. They provide a framework for technology literacy and demonstrate a progression from physical manipulation skills for the use of…

A Framework for the Specification of the Semantics and the Dynamics of Instructional Applications

ERIC Educational Resources Information Center

Buendia-Garcia, Felix; Diaz, Paloma

2003-01-01

An instructional application consists of a set of resources and activities to implement interacting, interrelated, and structured experiences oriented towards achieving specific educational objectives. The development of computer-based instructional applications has to follow a well defined process, so models for computer-based instructional…

eMZed: an open source framework in Python for rapid and interactive development of LC/MS data analysis workflows.

PubMed

Kiefer, Patrick; Schmitt, Uwe; Vorholt, Julia A

2013-04-01

The Python-based, open-source eMZed framework was developed for mass spectrometry (MS) users to create tailored workflows for liquid chromatography (LC)/MS data analysis. The goal was to establish a unique framework with comprehensive basic functionalities that are easy to apply and allow for the extension and modification of the framework in a straightforward manner. eMZed supports the iterative development and prototyping of individual evaluation strategies by providing a computing environment and tools for inspecting and modifying underlying LC/MS data. The framework specifically addresses non-expert programmers, as it requires only basic knowledge of Python and relies largely on existing successful open-source software, e.g. OpenMS. The framework eMZed and its documentation are freely available at http://emzed.biol.ethz.ch/. eMZed is published under the GPL 3.0 license, and an online discussion group is available at https://groups.google.com/group/emzed-users. Supplementary data are available at Bioinformatics online.

Parallelized multi–graphics processing unit framework for high-speed Gabor-domain optical coherence microscopy

PubMed Central

Tankam, Patrice; Santhanam, Anand P.; Lee, Kye-Sung; Won, Jungeun; Canavesi, Cristina; Rolland, Jannick P.

2014-01-01

Abstract. Gabor-domain optical coherence microscopy (GD-OCM) is a volumetric high-resolution technique capable of acquiring three-dimensional (3-D) skin images with histological resolution. Real-time image processing is needed to enable GD-OCM imaging in a clinical setting. We present a parallelized and scalable multi-graphics processing unit (GPU) computing framework for real-time GD-OCM image processing. A parallelized control mechanism was developed to individually assign computation tasks to each of the GPUs. For each GPU, the optimal number of amplitude-scans (A-scans) to be processed in parallel was selected to maximize GPU memory usage and core throughput. We investigated five computing architectures for computational speed-up in processing 1000×1000 A-scans. The proposed parallelized multi-GPU computing framework enables processing at a computational speed faster than the GD-OCM image acquisition, thereby facilitating high-speed GD-OCM imaging in a clinical setting. Using two parallelized GPUs, the image processing of a 1×1×0.6  mm3 skin sample was performed in about 13 s, and the performance was benchmarked at 6.5 s with four GPUs. This work thus demonstrates that 3-D GD-OCM data may be displayed in real-time to the examiner using parallelized GPU processing. PMID:24695868

Parallelized multi-graphics processing unit framework for high-speed Gabor-domain optical coherence microscopy.

PubMed

Tankam, Patrice; Santhanam, Anand P; Lee, Kye-Sung; Won, Jungeun; Canavesi, Cristina; Rolland, Jannick P

2014-07-01

Gabor-domain optical coherence microscopy (GD-OCM) is a volumetric high-resolution technique capable of acquiring three-dimensional (3-D) skin images with histological resolution. Real-time image processing is needed to enable GD-OCM imaging in a clinical setting. We present a parallelized and scalable multi-graphics processing unit (GPU) computing framework for real-time GD-OCM image processing. A parallelized control mechanism was developed to individually assign computation tasks to each of the GPUs. For each GPU, the optimal number of amplitude-scans (A-scans) to be processed in parallel was selected to maximize GPU memory usage and core throughput. We investigated five computing architectures for computational speed-up in processing 1000×1000 A-scans. The proposed parallelized multi-GPU computing framework enables processing at a computational speed faster than the GD-OCM image acquisition, thereby facilitating high-speed GD-OCM imaging in a clinical setting. Using two parallelized GPUs, the image processing of a 1×1×0.6  mm3 skin sample was performed in about 13 s, and the performance was benchmarked at 6.5 s with four GPUs. This work thus demonstrates that 3-D GD-OCM data may be displayed in real-time to the examiner using parallelized GPU processing.

Analytical modeling and feasibility study of a multi-GPU cloud-based server (MGCS) framework for non-voxel-based dose calculations.

PubMed

Neylon, J; Min, Y; Kupelian, P; Low, D A; Santhanam, A

2017-04-01

In this paper, a multi-GPU cloud-based server (MGCS) framework is presented for dose calculations, exploring the feasibility of remote computing power for parallelization and acceleration of computationally and time intensive radiotherapy tasks in moving toward online adaptive therapies. An analytical model was developed to estimate theoretical MGCS performance acceleration and intelligently determine workload distribution. Numerical studies were performed with a computing setup of 14 GPUs distributed over 4 servers interconnected by a 1 Gigabits per second (Gbps) network. Inter-process communication methods were optimized to facilitate resource distribution and minimize data transfers over the server interconnect. The analytically predicted computation time predicted matched experimentally observations within 1-5 %. MGCS performance approached a theoretical limit of acceleration proportional to the number of GPUs utilized when computational tasks far outweighed memory operations. The MGCS implementation reproduced ground-truth dose computations with negligible differences, by distributing the work among several processes and implemented optimization strategies. The results showed that a cloud-based computation engine was a feasible solution for enabling clinics to make use of fast dose calculations for advanced treatment planning and adaptive radiotherapy. The cloud-based system was able to exceed the performance of a local machine even for optimized calculations, and provided significant acceleration for computationally intensive tasks. Such a framework can provide access to advanced technology and computational methods to many clinics, providing an avenue for standardization across institutions without the requirements of purchasing, maintaining, and continually updating hardware.

New statistical scission-point model to predict fission fragment observables

NASA Astrophysics Data System (ADS)

Lemaître, Jean-François; Panebianco, Stefano; Sida, Jean-Luc; Hilaire, Stéphane; Heinrich, Sophie

2015-09-01

The development of high performance computing facilities makes possible a massive production of nuclear data in a full microscopic framework. Taking advantage of the individual potential calculations of more than 7000 nuclei, a new statistical scission-point model, called SPY, has been developed. It gives access to the absolute available energy at the scission point, which allows the use of a parameter-free microcanonical statistical description to calculate the distributions and the mean values of all fission observables. SPY uses the richness of microscopy in a rather simple theoretical framework, without any parameter except the scission-point definition, to draw clear answers based on perfect knowledge of the ingredients involved in the model, with very limited computing cost.

Reusable Component Model Development Approach for Parallel and Distributed Simulation

PubMed Central

Zhu, Feng; Yao, Yiping; Chen, Huilong; Yao, Feng

2014-01-01

Model reuse is a key issue to be resolved in parallel and distributed simulation at present. However, component models built by different domain experts usually have diversiform interfaces, couple tightly, and bind with simulation platforms closely. As a result, they are difficult to be reused across different simulation platforms and applications. To address the problem, this paper first proposed a reusable component model framework. Based on this framework, then our reusable model development approach is elaborated, which contains two phases: (1) domain experts create simulation computational modules observing three principles to achieve their independence; (2) model developer encapsulates these simulation computational modules with six standard service interfaces to improve their reusability. The case study of a radar model indicates that the model developed using our approach has good reusability and it is easy to be used in different simulation platforms and applications. PMID:24729751

A Framework for the Development of Context-Adaptable User Interfaces for Ubiquitous Computing Systems.

PubMed

Varela, Gervasio; Paz-Lopez, Alejandro; Becerra, Jose A; Duro, Richard

2016-07-07

This paper addresses the problem of developing user interfaces for Ubiquitous Computing (UC) and Ambient Intelligence (AmI) systems. These kind of systems are expected to provide a natural user experience, considering interaction modalities adapted to the user abilities and preferences and using whatever interaction devices are present in the environment. These interaction devices are not necessarily known at design time. The task is quite complicated due to the variety of devices and technologies, and the diversity of scenarios, and it usually burdens the developer with the need to create many different UIs in order to consider the foreseeable user-environment combinations. Here, we propose an UI abstraction framework for UC and AmI systems that effectively improves the portability of those systems between different environments and for different users. It allows developers to design and implement a single UI capable of being deployed with different devices and modalities regardless the physical location.

Relational Databases: A Transparent Framework for Encouraging Biology Students to Think Informatically

ERIC Educational Resources Information Center

Rice, Michael; Gladstone, William; Weir, Michael

2004-01-01

We discuss how relational databases constitute an ideal framework for representing and analyzing large-scale genomic data sets in biology. As a case study, we describe a Drosophila splice-site database that we recently developed at Wesleyan University for use in research and teaching. The database stores data about splice sites computed by a…

An Investigation of the Artifacts and Process of Constructing Computers Games about Environmental Science in a Fifth Grade Classroom

ERIC Educational Resources Information Center

Baytak, Ahmet; Land, Susan M.

2011-01-01

This study employed a case study design (Yin, "Case study research, design and methods," 2009) to investigate the processes used by 5th graders to design and develop computer games within the context of their environmental science unit, using the theoretical framework of "constructionism." Ten fifth graders designed computer games using "Scratch"…

EarthCube - Earth System Bridge: Spanning Scientific Communities with Interoperable Modeling Frameworks

NASA Astrophysics Data System (ADS)

Peckham, S. D.; DeLuca, C.; Gochis, D. J.; Arrigo, J.; Kelbert, A.; Choi, E.; Dunlap, R.

2014-12-01

In order to better understand and predict environmental hazards of weather/climate, ecology and deep earth processes, geoscientists develop and use physics-based computational models. These models are used widely both in academic and federal communities. Because of the large effort required to develop and test models, there is widespread interest in component-based modeling, which promotes model reuse and simplified coupling to tackle problems that often cross discipline boundaries. In component-based modeling, the goal is to make relatively small changes to models that make it easy to reuse them as "plug-and-play" components. Sophisticated modeling frameworks exist to rapidly couple these components to create new composite models. They allow component models to exchange variables while accommodating different programming languages, computational grids, time-stepping schemes, variable names and units. Modeling frameworks have arisen in many modeling communities. CSDMS (Community Surface Dynamics Modeling System) serves the academic earth surface process dynamics community, while ESMF (Earth System Modeling Framework) serves many federal Earth system modeling projects. Others exist in both the academic and federal domains and each satisfies design criteria that are determined by the community they serve. While they may use different interface standards or semantic mediation strategies, they share fundamental similarities. The purpose of the Earth System Bridge project is to develop mechanisms for interoperability between modeling frameworks, such as the ability to share a model or service component. This project has three main goals: (1) Develop a Framework Description Language (ES-FDL) that allows modeling frameworks to be described in a standard way so that their differences and similarities can be assessed. (2) Demonstrate that if a model is augmented with a framework-agnostic Basic Model Interface (BMI), then simple, universal adapters can go from BMI to a modeling framework's native component interface. (3) Create semantic mappings between modeling frameworks that support semantic mediation. This third goal involves creating a crosswalk between the CF Standard Names and the CSDMS Standard Names (a set of naming conventions). This talk will summarize progress towards these goals.

Safety Metrics for Human-Computer Controlled Systems

NASA Technical Reports Server (NTRS)

Leveson, Nancy G; Hatanaka, Iwao

2000-01-01

The rapid growth of computer technology and innovation has played a significant role in the rise of computer automation of human tasks in modem production systems across all industries. Although the rationale for automation has been to eliminate "human error" or to relieve humans from manual repetitive tasks, various computer-related hazards and accidents have emerged as a direct result of increased system complexity attributed to computer automation. The risk assessment techniques utilized for electromechanical systems are not suitable for today's software-intensive systems or complex human-computer controlled systems.This thesis will propose a new systemic model-based framework for analyzing risk in safety-critical systems where both computers and humans are controlling safety-critical functions. A new systems accident model will be developed based upon modem systems theory and human cognitive processes to better characterize system accidents, the role of human operators, and the influence of software in its direct control of significant system functions Better risk assessments will then be achievable through the application of this new framework to complex human-computer controlled systems.

A Framework to Improve Energy Efficient Behaviour at Home through Activity and Context Monitoring

PubMed Central

García, Óscar; Alonso, Ricardo S.; Corchado, Juan M.

2017-01-01

Real-time Localization Systems have been postulated as one of the most appropriated technologies for the development of applications that provide customized services. These systems provide us with the ability to locate and trace users and, among other features, they help identify behavioural patterns and habits. Moreover, the implementation of policies that will foster energy saving in homes is a complex task that involves the use of this type of systems. Although there are multiple proposals in this area, the implementation of frameworks that combine technologies and use Social Computing to influence user behaviour have not yet reached any significant savings in terms of energy. In this work, the CAFCLA framework (Context-Aware Framework for Collaborative Learning Applications) is used to develop a recommendation system for home users. The proposed system integrates a Real-Time Localization System and Wireless Sensor Networks, making it possible to develop applications that work under the umbrella of Social Computing. The implementation of an experimental use case aided efficient energy use, achieving savings of 17%. Moreover, the conducted case study pointed to the possibility of attaining good energy consumption habits in the long term. This can be done thanks to the system’s real time and historical localization, tracking and contextual data, based on which customized recommendations are generated. PMID:28758987

Development of a Flexible Framework for Hypersonic Navier-Stoke Space Shuttle Orbiter Meshes

NASA Technical Reports Server (NTRS)

Alter, Stephen J.; Reuthler, James J.; McDaniel, Ryan D.

2004-01-01

A flexible framework constructing block structured volume grids for hypersonic Navier-Strokes flow simulations was developed for the analysis of the Shuttle Orbiter Columbia. The development of the framework, which was partially basedon the requirements of the primary flow solvers used resulted in an ability to directly correlate solutions contributed by participating groups on a common surface mesh. A foundation was built through the assessment of differences between differnt solvers, which provided confidence for independent assessment of other damage scenarios by team members. The framework draws on the experience of NASA Langley and NASA Ames Research Centers in structured grid generation, and consists of a grid generation, and consist of a grid generation process implemented through a division of responsibilities. The nominal division of labor consisted of NASA Johnson Space Center coordinating the damage scenarios to be analyzed by the Aerothermodynamics Columbia Accident Investigation (ACAI) team, Ames developing the surface grids that described the computational volume about the Orbiter, and Langley improving grid quality of Ames generated data and constructing the final computational volume grids. Distributing the work among the participant in th ACAI team resulted in significantl less time required to construct complete meshes than possible by any individual participant. The approach demonstrated that the One-NASA grid generation team could sustain the demand of for five new meshes to explore new damage scenarios within an aggressive time-line.

Dynamic Vision for Control

DTIC Science & Technology

2006-07-27

unlimited 13. SUPPLEMENTARY NOTES 14. ABSTRACT The goal of this project was to develop analytical and computational tools to make vision a Viable sensor for...vision.ucla. edu July 27, 2006 Abstract The goal of this project was to develop analytical and computational tools to make vision a viable sensor for the ... sensors . We have proposed the framework of stereoscopic segmentation where multiple images of the same obejcts were jointly processed to extract geometry

Near real-time, on-the-move software PED using VPEF

NASA Astrophysics Data System (ADS)

Green, Kevin; Geyer, Chris; Burnette, Chris; Agarwal, Sanjeev; Swett, Bruce; Phan, Chung; Deterline, Diane

2015-05-01

The scope of the Micro-Cloud for Operational, Vehicle-Based EO-IR Reconnaissance System (MOVERS) development effort, managed by the Night Vision and Electronic Sensors Directorate (NVESD), is to develop, integrate, and demonstrate new sensor technologies and algorithms that improve improvised device/mine detection using efficient and effective exploitation and fusion of sensor data and target cues from existing and future Route Clearance Package (RCP) sensor systems. Unfortunately, the majority of forward looking Full Motion Video (FMV) and computer vision processing, exploitation, and dissemination (PED) algorithms are often developed using proprietary, incompatible software. This makes the insertion of new algorithms difficult due to the lack of standardized processing chains. In order to overcome these limitations, EOIR developed the Government off-the-shelf (GOTS) Video Processing and Exploitation Framework (VPEF) to be able to provide standardized interfaces (e.g., input/output video formats, sensor metadata, and detected objects) for exploitation software and to rapidly integrate and test computer vision algorithms. EOIR developed a vehicle-based computing framework within the MOVERS and integrated it with VPEF. VPEF was further enhanced for automated processing, detection, and publishing of detections in near real-time, thus improving the efficiency and effectiveness of RCP sensor systems.

A survey of artificial immune system based intrusion detection.

PubMed

Yang, Hua; Li, Tao; Hu, Xinlei; Wang, Feng; Zou, Yang

2014-01-01

In the area of computer security, Intrusion Detection (ID) is a mechanism that attempts to discover abnormal access to computers by analyzing various interactions. There is a lot of literature about ID, but this study only surveys the approaches based on Artificial Immune System (AIS). The use of AIS in ID is an appealing concept in current techniques. This paper summarizes AIS based ID methods from a new view point; moreover, a framework is proposed for the design of AIS based ID Systems (IDSs). This framework is analyzed and discussed based on three core aspects: antibody/antigen encoding, generation algorithm, and evolution mode. Then we collate the commonly used algorithms, their implementation characteristics, and the development of IDSs into this framework. Finally, some of the future challenges in this area are also highlighted.

A Computational Framework for Automation of Point Defect Calculations

NASA Astrophysics Data System (ADS)

Goyal, Anuj; Gorai, Prashun; Peng, Haowei; Lany, Stephan; Stevanovic, Vladan; National Renewable Energy Laboratory, Golden, Colorado 80401 Collaboration

A complete and rigorously validated open-source Python framework to automate point defect calculations using density functional theory has been developed. The framework provides an effective and efficient method for defect structure generation, and creation of simple yet customizable workflows to analyze defect calculations. The package provides the capability to compute widely accepted correction schemes to overcome finite-size effects, including (1) potential alignment, (2) image-charge correction, and (3) band filling correction to shallow defects. Using Si, ZnO and In2O3as test examples, we demonstrate the package capabilities and validate the methodology. We believe that a robust automated tool like this will enable the materials by design community to assess the impact of point defects on materials performance. National Renewable Energy Laboratory, Golden, Colorado 80401.

Recent developments in the CCP-EM software suite.

PubMed

Burnley, Tom; Palmer, Colin M; Winn, Martyn

2017-06-01

As part of its remit to provide computational support to the cryo-EM community, the Collaborative Computational Project for Electron cryo-Microscopy (CCP-EM) has produced a software framework which enables easy access to a range of programs and utilities. The resulting software suite incorporates contributions from different collaborators by encapsulating them in Python task wrappers, which are then made accessible via a user-friendly graphical user interface as well as a command-line interface suitable for scripting. The framework includes tools for project and data management. An overview of the design of the framework is given, together with a survey of the functionality at different levels. The current CCP-EM suite has particular strength in the building and refinement of atomic models into cryo-EM reconstructions, which is described in detail.

Recent developments in the CCP-EM software suite

PubMed Central

Burnley, Tom

2017-01-01

As part of its remit to provide computational support to the cryo-EM community, the Collaborative Computational Project for Electron cryo-Microscopy (CCP-EM) has produced a software framework which enables easy access to a range of programs and utilities. The resulting software suite incorporates contributions from different collaborators by encapsulating them in Python task wrappers, which are then made accessible via a user-friendly graphical user interface as well as a command-line interface suitable for scripting. The framework includes tools for project and data management. An overview of the design of the framework is given, together with a survey of the functionality at different levels. The current CCP-EM suite has particular strength in the building and refinement of atomic models into cryo-EM reconstructions, which is described in detail. PMID:28580908

An automated and integrated framework for dust storm detection based on ogc web processing services

NASA Astrophysics Data System (ADS)

Xiao, F.; Shea, G. Y. K.; Wong, M. S.; Campbell, J.

2014-11-01

Dust storms are known to have adverse effects on public health. Atmospheric dust loading is also one of the major uncertainties in global climatic modelling as it is known to have a significant impact on the radiation budget and atmospheric stability. The complexity of building scientific dust storm models is coupled with the scientific computation advancement, ongoing computing platform development, and the development of heterogeneous Earth Observation (EO) networks. It is a challenging task to develop an integrated and automated scheme for dust storm detection that combines Geo-Processing frameworks, scientific models and EO data together to enable the dust storm detection and tracking processes in a dynamic and timely manner. This study develops an automated and integrated framework for dust storm detection and tracking based on the Web Processing Services (WPS) initiated by Open Geospatial Consortium (OGC). The presented WPS framework consists of EO data retrieval components, dust storm detecting and tracking component, and service chain orchestration engine. The EO data processing component is implemented based on OPeNDAP standard. The dust storm detecting and tracking component combines three earth scientific models, which are SBDART model (for computing aerosol optical depth (AOT) of dust particles), WRF model (for simulating meteorological parameters) and HYSPLIT model (for simulating the dust storm transport processes). The service chain orchestration engine is implemented based on Business Process Execution Language for Web Service (BPEL4WS) using open-source software. The output results, including horizontal and vertical AOT distribution of dust particles as well as their transport paths, were represented using KML/XML and displayed in Google Earth. A serious dust storm, which occurred over East Asia from 26 to 28 Apr 2012, is used to test the applicability of the proposed WPS framework. Our aim here is to solve a specific instance of a complex EO data and scientific model integration problem by using a framework and scientific workflow approach together. The experimental result shows that this newly automated and integrated framework can be used to give advance near real-time warning of dust storms, for both environmental authorities and public. The methods presented in this paper might be also generalized to other types of Earth system models, leading to improved ease of use and flexibility.

A mathematical model and computational framework for three-dimensional chondrocyte cell growth in a porous tissue scaffold placed inside a bi-directional flow perfusion bioreactor.

PubMed

Shakhawath Hossain, Md; Bergstrom, D J; Chen, X B

2015-12-01

The in vitro chondrocyte cell culture for cartilage tissue regeneration in a perfusion bioreactor is a complex process. Mathematical modeling and computational simulation can provide important insights into the culture process, which would be helpful for selecting culture conditions to improve the quality of the developed tissue constructs. However, simulation of the cell culture process is a challenging task due to the complicated interaction between the cells and local fluid flow and nutrient transport inside the complex porous scaffolds. In this study, a mathematical model and computational framework has been developed to simulate the three-dimensional (3D) cell growth in a porous scaffold placed inside a bi-directional flow perfusion bioreactor. The model was developed by taking into account the two-way coupling between the cell growth and local flow field and associated glucose concentration, and then used to perform a resolved-scale simulation based on the lattice Boltzmann method (LBM). The simulation predicts the local shear stress, glucose concentration, and 3D cell growth inside the porous scaffold for a period of 30 days of cell culture. The predicted cell growth rate was in good overall agreement with the experimental results available in the literature. This study demonstrates that the bi-directional flow perfusion culture system can enhance the homogeneity of the cell growth inside the scaffold. The model and computational framework developed is capable of providing significant insight into the culture process, thus providing a powerful tool for the design and optimization of the cell culture process. © 2015 Wiley Periodicals, Inc.

ClimateSpark: An in-memory distributed computing framework for big climate data analytics

NASA Astrophysics Data System (ADS)

Hu, Fei; Yang, Chaowei; Schnase, John L.; Duffy, Daniel Q.; Xu, Mengchao; Bowen, Michael K.; Lee, Tsengdar; Song, Weiwei

2018-06-01

The unprecedented growth of climate data creates new opportunities for climate studies, and yet big climate data pose a grand challenge to climatologists to efficiently manage and analyze big data. The complexity of climate data content and analytical algorithms increases the difficulty of implementing algorithms on high performance computing systems. This paper proposes an in-memory, distributed computing framework, ClimateSpark, to facilitate complex big data analytics and time-consuming computational tasks. Chunking data structure improves parallel I/O efficiency, while a spatiotemporal index is built for the chunks to avoid unnecessary data reading and preprocessing. An integrated, multi-dimensional, array-based data model (ClimateRDD) and ETL operations are developed to address big climate data variety by integrating the processing components of the climate data lifecycle. ClimateSpark utilizes Spark SQL and Apache Zeppelin to develop a web portal to facilitate the interaction among climatologists, climate data, analytic operations and computing resources (e.g., using SQL query and Scala/Python notebook). Experimental results show that ClimateSpark conducts different spatiotemporal data queries/analytics with high efficiency and data locality. ClimateSpark is easily adaptable to other big multiple-dimensional, array-based datasets in various geoscience domains.

A New Framework for Effective and Efficient Global Sensitivity Analysis of Earth and Environmental Systems Models

NASA Astrophysics Data System (ADS)

Razavi, Saman; Gupta, Hoshin

2015-04-01

Earth and Environmental Systems (EES) models are essential components of research, development, and decision-making in science and engineering disciplines. With continuous advances in understanding and computing power, such models are becoming more complex with increasingly more factors to be specified (model parameters, forcings, boundary conditions, etc.). To facilitate better understanding of the role and importance of different factors in producing the model responses, the procedure known as 'Sensitivity Analysis' (SA) can be very helpful. Despite the availability of a large body of literature on the development and application of various SA approaches, two issues continue to pose major challenges: (1) Ambiguous Definition of Sensitivity - Different SA methods are based in different philosophies and theoretical definitions of sensitivity, and can result in different, even conflicting, assessments of the underlying sensitivities for a given problem, (2) Computational Cost - The cost of carrying out SA can be large, even excessive, for high-dimensional problems and/or computationally intensive models. In this presentation, we propose a new approach to sensitivity analysis that addresses the dual aspects of 'effectiveness' and 'efficiency'. By effective, we mean achieving an assessment that is both meaningful and clearly reflective of the objective of the analysis (the first challenge above), while by efficiency we mean achieving statistically robust results with minimal computational cost (the second challenge above). Based on this approach, we develop a 'global' sensitivity analysis framework that efficiently generates a newly-defined set of sensitivity indices that characterize a range of important properties of metric 'response surfaces' encountered when performing SA on EES models. Further, we show how this framework embraces, and is consistent with, a spectrum of different concepts regarding 'sensitivity', and that commonly-used SA approaches (e.g., Sobol, Morris, etc.) are actually limiting cases of our approach under specific conditions. Multiple case studies are used to demonstrate the value of the new framework. The results show that the new framework provides a fundamental understanding of the underlying sensitivities for any given problem, while requiring orders of magnitude fewer model runs.

Pedagogical Content Knowledge in Teaching Material

ERIC Educational Resources Information Center

Saeli, Mara; Perrenet, Jacob; Jochems, Wim M. G.; Zwaneveld, Bert

2012-01-01

The scope of this article is to understand to what extent Computer Science teachers can find support for their Pedagogical Content Knowledge (PCK) in teaching material. We report the results of a study in which PCK is used as framework to develop a research instrument to examine three high school computer science textbooks, with special focus on…

An Empirical Generative Framework for Computational Modeling of Language Acquisition

ERIC Educational Resources Information Center

Waterfall, Heidi R.; Sandbank, Ben; Onnis, Luca; Edelman, Shimon

2010-01-01

This paper reports progress in developing a computer model of language acquisition in the form of (1) a generative grammar that is (2) algorithmically learnable from realistic corpus data, (3) viable in its large-scale quantitative performance and (4) psychologically real. First, we describe new algorithmic methods for unsupervised learning of…

The Design and Evaluation of Teaching Experiments in Computer Science.

ERIC Educational Resources Information Center

Forcheri, Paola; Molfino, Maria Teresa

1992-01-01

Describes a relational model that was developed to provide a framework for the design and evaluation of teaching experiments for the introduction of computer science in secondary schools in Italy. Teacher training is discussed, instructional materials are considered, and use of the model for the evaluation process is described. (eight references)…

Application of Psychological Theories in Agent-Based Modeling: The Case of the Theory of Planned Behavior.

PubMed

Scalco, Andrea; Ceschi, Andrea; Sartori, Riccardo

2018-01-01

It is likely that computer simulations will assume a greater role in the next future to investigate and understand reality (Rand & Rust, 2011). Particularly, agent-based models (ABMs) represent a method of investigation of social phenomena that blend the knowledge of social sciences with the advantages of virtual simulations. Within this context, the development of algorithms able to recreate the reasoning engine of autonomous virtual agents represents one of the most fragile aspects and it is indeed crucial to establish such models on well-supported psychological theoretical frameworks. For this reason, the present work discusses the application case of the theory of planned behavior (TPB; Ajzen, 1991) in the context of agent-based modeling: It is argued that this framework might be helpful more than others to develop a valid representation of human behavior in computer simulations. Accordingly, the current contribution considers issues related with the application of the model proposed by the TPB inside computer simulations and suggests potential solutions with the hope to contribute to shorten the distance between the fields of psychology and computer science.

PROTO-PLASM: parallel language for adaptive and scalable modelling of biosystems.

PubMed

Bajaj, Chandrajit; DiCarlo, Antonio; Paoluzzi, Alberto

2008-09-13

This paper discusses the design goals and the first developments of PROTO-PLASM, a novel computational environment to produce libraries of executable, combinable and customizable computer models of natural and synthetic biosystems, aiming to provide a supporting framework for predictive understanding of structure and behaviour through multiscale geometric modelling and multiphysics simulations. Admittedly, the PROTO-PLASM platform is still in its infancy. Its computational framework--language, model library, integrated development environment and parallel engine--intends to provide patient-specific computational modelling and simulation of organs and biosystem, exploiting novel functionalities resulting from the symbolic combination of parametrized models of parts at various scales. PROTO-PLASM may define the model equations, but it is currently focused on the symbolic description of model geometry and on the parallel support of simulations. Conversely, CellML and SBML could be viewed as defining the behavioural functions (the model equations) to be used within a PROTO-PLASM program. Here we exemplify the basic functionalities of PROTO-PLASM, by constructing a schematic heart model. We also discuss multiscale issues with reference to the geometric and physical modelling of neuromuscular junctions.

Computational Sensing and in vitro Classification of GMOs and Biomolecular Events

DTIC Science & Technology

2008-12-01

COMPUTATIONAL SENSING AND IN VITRO CLASSIFICATION OF GMOs AND BIOMOLECULAR EVENTS Elebeoba May1∗, Miler T. Lee2†, Patricia Dolan1, Paul Crozier1...modified organisms ( GMOs ) in the pres- ence of non-lethal agents. Using an information and coding- theoretic framework we develop a de novo method for...high through- put screening, distinguishing genetically modified organisms ( GMOs ), molecular computing, differentiating biological mark- ers

Managing Computer Systems Development: Understanding the Human and Technological Imperatives.

DTIC Science & Technology

1985-06-01

for their organization’s use? How can they predict tle impact of future systems ca their management control capabilities ? Cf equal importance is the...commercial organizations discovered that there was only a limited capability of interaction between various types of computers. These organizations were...Viewed together, these three interrelated subsystems, EDP, MIS, and DSS, establish the framework of an overall systems capability known as a Computer

Data Structures for Extreme Scale Computing

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kahan, Simon

As computing problems of national importance grow, the government meets the increased demand by funding the development of ever larger systems. The overarching goal of the work supported in part by this grant is to increase efficiency of programming and performing computations on these large computing systems. In past work, we have demonstrated that some of these computations once thought to require expensive hardware designs and/or complex, special-purpose programming may be executed efficiently on low-cost commodity cluster computing systems using a general-purpose “latency-tolerant” programming framework. One important developed application of the ideas underlying this framework is graph database technology supportingmore » social network pattern matching used by US intelligence agencies to more quickly identify potential terrorist threats. This database application has been spun out by the Pacific Northwest National Laboratory, a Department of Energy Laboratory, into a commercial start-up, Trovares Inc. We explore an alternative application of the same underlying ideas to a well-studied challenge arising in engineering: solving unstructured sparse linear equations. Solving these equations is key to predicting the behavior of large electronic circuits before they are fabricated. Predicting that behavior ahead of fabrication means that designs can optimized and errors corrected ahead of the expense of manufacture.« less

Automatic and accurate reconstruction of distal humerus contours through B-Spline fitting based on control polygon deformation.

PubMed

Mostafavi, Kamal; Tutunea-Fatan, O Remus; Bordatchev, Evgueni V; Johnson, James A

2014-12-01

The strong advent of computer-assisted technologies experienced by the modern orthopedic surgery prompts for the expansion of computationally efficient techniques to be built on the broad base of computer-aided engineering tools that are readily available. However, one of the common challenges faced during the current developmental phase continues to remain the lack of reliable frameworks to allow a fast and precise conversion of the anatomical information acquired through computer tomography to a format that is acceptable to computer-aided engineering software. To address this, this study proposes an integrated and automatic framework capable to extract and then postprocess the original imaging data to a common planar and closed B-Spline representation. The core of the developed platform relies on the approximation of the discrete computer tomography data by means of an original two-step B-Spline fitting technique based on successive deformations of the control polygon. In addition to its rapidity and robustness, the developed fitting technique was validated to produce accurate representations that do not deviate by more than 0.2 mm with respect to alternate representations of the bone geometry that were obtained through different-contact-based-data acquisition or data processing methods. © IMechE 2014.

A Buyer Behaviour Framework for the Development and Design of Software Agents in E-Commerce.

ERIC Educational Resources Information Center

Sproule, Susan; Archer, Norm

2000-01-01

Software agents are computer programs that run in the background and perform tasks autonomously as delegated by the user. This paper blends models from marketing research and findings from the field of decision support systems to build a framework for the design of software agents to support in e-commerce buying applications. (Contains 35…

Nektar++: An open-source spectral/ hp element framework

NASA Astrophysics Data System (ADS)

Cantwell, C. D.; Moxey, D.; Comerford, A.; Bolis, A.; Rocco, G.; Mengaldo, G.; De Grazia, D.; Yakovlev, S.; Lombard, J.-E.; Ekelschot, D.; Jordi, B.; Xu, H.; Mohamied, Y.; Eskilsson, C.; Nelson, B.; Vos, P.; Biotto, C.; Kirby, R. M.; Sherwin, S. J.

2015-07-01

Nektar++ is an open-source software framework designed to support the development of high-performance scalable solvers for partial differential equations using the spectral/ hp element method. High-order methods are gaining prominence in several engineering and biomedical applications due to their improved accuracy over low-order techniques at reduced computational cost for a given number of degrees of freedom. However, their proliferation is often limited by their complexity, which makes these methods challenging to implement and use. Nektar++ is an initiative to overcome this limitation by encapsulating the mathematical complexities of the underlying method within an efficient C++ framework, making the techniques more accessible to the broader scientific and industrial communities. The software supports a variety of discretisation techniques and implementation strategies, supporting methods research as well as application-focused computation, and the multi-layered structure of the framework allows the user to embrace as much or as little of the complexity as they need. The libraries capture the mathematical constructs of spectral/ hp element methods, while the associated collection of pre-written PDE solvers provides out-of-the-box application-level functionality and a template for users who wish to develop solutions for addressing questions in their own scientific domains.

Interventional radiology virtual simulator for liver biopsy.

PubMed

Villard, P F; Vidal, F P; ap Cenydd, L; Holbrey, R; Pisharody, S; Johnson, S; Bulpitt, A; John, N W; Bello, F; Gould, D

2014-03-01

Training in Interventional Radiology currently uses the apprenticeship model, where clinical and technical skills of invasive procedures are learnt during practice in patients. This apprenticeship training method is increasingly limited by regulatory restrictions on working hours, concerns over patient risk through trainees' inexperience and the variable exposure to case mix and emergencies during training. To address this, we have developed a computer-based simulation of visceral needle puncture procedures. A real-time framework has been built that includes: segmentation, physically based modelling, haptics rendering, pseudo-ultrasound generation and the concept of a physical mannequin. It is the result of a close collaboration between different universities, involving computer scientists, clinicians, clinical engineers and occupational psychologists. The technical implementation of the framework is a robust and real-time simulation environment combining a physical platform and an immersive computerized virtual environment. The face, content and construct validation have been previously assessed, showing the reliability and effectiveness of this framework, as well as its potential for teaching visceral needle puncture. A simulator for ultrasound-guided liver biopsy has been developed. It includes functionalities and metrics extracted from cognitive task analysis. This framework can be useful during training, particularly given the known difficulties in gaining significant practice of core skills in patients.

How Adverse Outcome Pathways Can Aid the Development and Use of Computational Prediction Models for Regulatory Toxicology

PubMed Central

Aladjov, Hristo; Ankley, Gerald; Byrne, Hugh J.; de Knecht, Joop; Heinzle, Elmar; Klambauer, Günter; Landesmann, Brigitte; Luijten, Mirjam; MacKay, Cameron; Maxwell, Gavin; Meek, M. E. (Bette); Paini, Alicia; Perkins, Edward; Sobanski, Tomasz; Villeneuve, Dan; Waters, Katrina M.; Whelan, Maurice

2017-01-01

Efforts are underway to transform regulatory toxicology and chemical safety assessment from a largely empirical science based on direct observation of apical toxicity outcomes in whole organism toxicity tests to a predictive one in which outcomes and risk are inferred from accumulated mechanistic understanding. The adverse outcome pathway (AOP) framework provides a systematic approach for organizing knowledge that may support such inference. Likewise, computational models of biological systems at various scales provide another means and platform to integrate current biological understanding to facilitate inference and extrapolation. We argue that the systematic organization of knowledge into AOP frameworks can inform and help direct the design and development of computational prediction models that can further enhance the utility of mechanistic and in silico data for chemical safety assessment. This concept was explored as part of a workshop on AOP-Informed Predictive Modeling Approaches for Regulatory Toxicology held September 24–25, 2015. Examples of AOP-informed model development and its application to the assessment of chemicals for skin sensitization and multiple modes of endocrine disruption are provided. The role of problem formulation, not only as a critical phase of risk assessment, but also as guide for both AOP and complementary model development is described. Finally, a proposal for actively engaging the modeling community in AOP-informed computational model development is made. The contents serve as a vision for how AOPs can be leveraged to facilitate development of computational prediction models needed to support the next generation of chemical safety assessment. PMID:27994170

Implementation and performance of FDPS: a framework for developing parallel particle simulation codes

NASA Astrophysics Data System (ADS)

Iwasawa, Masaki; Tanikawa, Ataru; Hosono, Natsuki; Nitadori, Keigo; Muranushi, Takayuki; Makino, Junichiro

2016-08-01

We present the basic idea, implementation, measured performance, and performance model of FDPS (Framework for Developing Particle Simulators). FDPS is an application-development framework which helps researchers to develop simulation programs using particle methods for large-scale distributed-memory parallel supercomputers. A particle-based simulation program for distributed-memory parallel computers needs to perform domain decomposition, exchange of particles which are not in the domain of each computing node, and gathering of the particle information in other nodes which are necessary for interaction calculation. Also, even if distributed-memory parallel computers are not used, in order to reduce the amount of computation, algorithms such as the Barnes-Hut tree algorithm or the Fast Multipole Method should be used in the case of long-range interactions. For short-range interactions, some methods to limit the calculation to neighbor particles are required. FDPS provides all of these functions which are necessary for efficient parallel execution of particle-based simulations as "templates," which are independent of the actual data structure of particles and the functional form of the particle-particle interaction. By using FDPS, researchers can write their programs with the amount of work necessary to write a simple, sequential and unoptimized program of O(N2) calculation cost, and yet the program, once compiled with FDPS, will run efficiently on large-scale parallel supercomputers. A simple gravitational N-body program can be written in around 120 lines. We report the actual performance of these programs and the performance model. The weak scaling performance is very good, and almost linear speed-up was obtained for up to the full system of the K computer. The minimum calculation time per timestep is in the range of 30 ms (N = 107) to 300 ms (N = 109). These are currently limited by the time for the calculation of the domain decomposition and communication necessary for the interaction calculation. We discuss how we can overcome these bottlenecks.

Development of a Dynamically Configurable,Object-Oriented Framework for Distributed, Multi-modal Computational Aerospace Systems Simulation

NASA Technical Reports Server (NTRS)

Afjeh, Abdollah A.; Reed, John A.

2003-01-01

This research is aimed at developing a neiv and advanced simulation framework that will significantly improve the overall efficiency of aerospace systems design and development. This objective will be accomplished through an innovative integration of object-oriented and Web-based technologies ivith both new and proven simulation methodologies. The basic approach involves Ihree major areas of research: Aerospace system and component representation using a hierarchical object-oriented component model which enables the use of multimodels and enforces component interoperability. Collaborative software environment that streamlines the process of developing, sharing and integrating aerospace design and analysis models. . Development of a distributed infrastructure which enables Web-based exchange of models to simplify the collaborative design process, and to support computationally intensive aerospace design and analysis processes. Research for the first year dealt with the design of the basic architecture and supporting infrastructure, an initial implementation of that design, and a demonstration of its application to an example aircraft engine system simulation.

An Efficient Finite Element Framework to Assess Flexibility Performances of SMA Self-Expandable Carotid Artery Stents

PubMed Central

Ferraro, Mauro; Auricchio, Ferdinando; Boatti, Elisa; Scalet, Giulia; Conti, Michele; Morganti, Simone; Reali, Alessandro

2015-01-01

Computer-based simulations are nowadays widely exploited for the prediction of the mechanical behavior of different biomedical devices. In this aspect, structural finite element analyses (FEA) are currently the preferred computational tool to evaluate the stent response under bending. This work aims at developing a computational framework based on linear and higher order FEA to evaluate the flexibility of self-expandable carotid artery stents. In particular, numerical simulations involving large deformations and inelastic shape memory alloy constitutive modeling are performed, and the results suggest that the employment of higher order FEA allows accurately representing the computational domain and getting a better approximation of the solution with a widely-reduced number of degrees of freedom with respect to linear FEA. Moreover, when buckling phenomena occur, higher order FEA presents a superior capability of reproducing the nonlinear local effects related to buckling phenomena. PMID:26184329

Computational Models of Anterior Cingulate Cortex: At the Crossroads between Prediction and Effort.

PubMed

Vassena, Eliana; Holroyd, Clay B; Alexander, William H

2017-01-01

In the last two decades the anterior cingulate cortex (ACC) has become one of the most investigated areas of the brain. Extensive neuroimaging evidence suggests countless functions for this region, ranging from conflict and error coding, to social cognition, pain and effortful control. In response to this burgeoning amount of data, a proliferation of computational models has tried to characterize the neurocognitive architecture of ACC. Early seminal models provided a computational explanation for a relatively circumscribed set of empirical findings, mainly accounting for EEG and fMRI evidence. More recent models have focused on ACC's contribution to effortful control. In parallel to these developments, several proposals attempted to explain within a single computational framework a wider variety of empirical findings that span different cognitive processes and experimental modalities. Here we critically evaluate these modeling attempts, highlighting the continued need to reconcile the array of disparate ACC observations within a coherent, unifying framework.

Architecture of a framework for providing information services for public transport.

PubMed

García, Carmelo R; Pérez, Ricardo; Lorenzo, Alvaro; Quesada-Arencibia, Alexis; Alayón, Francisco; Padrón, Gabino

2012-01-01

This paper presents OnRoute, a framework for developing and running ubiquitous software that provides information services to passengers of public transportation, including payment systems and on-route guidance services. To achieve a high level of interoperability, accessibility and context awareness, OnRoute uses the ubiquitous computing paradigm. To guarantee the quality of the software produced, the reliable software principles used in critical contexts, such as automotive systems, are also considered by the framework. The main components of its architecture (run-time, system services, software components and development discipline) and how they are deployed in the transportation network (stations and vehicles) are described in this paper. Finally, to illustrate the use of OnRoute, the development of a guidance service for travellers is explained.

CyberMedVPS: visual programming for development of simulators.

PubMed

Morais, Aline M; Machado, Liliane S

2011-01-01

Computer applications based on Virtual Reality (VR) has been outstanding in training and teaching in the medical filed due to their ability to simulate realistic in which users can practice skills and decision making in different situations. But was realized in these frameworks a hard interaction of non-programmers users. Based on this problematic will be shown the CyberMedVPS, a graphical module which implement Visual Programming concepts to solve an interaction trouble. Frameworks to develop such simulators are available but their use demands knowledge of programming. Based on this problematic will be shown the CyberMedVPS, a graphical module for the CyberMed framework, which implements Visual Programming concepts to allow the development of simulators by non-programmers professionals of the medical field.

Simulating motivated cognition

NASA Technical Reports Server (NTRS)

Gevarter, William B.

1991-01-01

A research effort to develop a sophisticated computer model of human behavior is described. A computer framework of motivated cognition was developed. Motivated cognition focuses on the motivations or affects that provide the context and drive in human cognition and decision making. A conceptual architecture of the human decision-making approach from the perspective of information processing in the human brain is developed in diagrammatic form. A preliminary version of such a diagram is presented. This architecture is then used as a vehicle for successfully constructing a computer program simulation Dweck and Leggett's findings that relate how an individual's implicit theories orient them toward particular goals, with resultant cognitions, affects, and behavior.

Framework for emotional mobile computation for creating entertainment experience

NASA Astrophysics Data System (ADS)

Lugmayr, Artur R.

2007-02-01

Ambient media are media, which are manifesting in the natural environment of the consumer. The perceivable borders between the media and the context, where the media is used are getting more and more blurred. The consumer is moving through a digital space of services throughout his daily life. As we are developing towards an experience society, the central point in the development of services is the creation of a consumer experience. This paper reviews possibilities and potentials of the creation of entertainment experiences with mobile phone platforms. It reviews sensor network capable of acquiring consumer behavior data, interactivity strategies, psychological models for emotional computation on mobile phones, and lays the foundations of a nomadic experience society. The paper rounds up with a presentation of several different possible service scenarios in the field of entertainment and leisure computation on mobiles. The goal of this paper is to present a framework and evaluation of possibilities of applying sensor technology on mobile platforms to create an increasing consumer entertainment experience.

Instrumentino: An Open-Source Software for Scientific Instruments.

PubMed

Koenka, Israel Joel; Sáiz, Jorge; Hauser, Peter C

2015-01-01

Scientists often need to build dedicated computer-controlled experimental systems. For this purpose, it is becoming common to employ open-source microcontroller platforms, such as the Arduino. These boards and associated integrated software development environments provide affordable yet powerful solutions for the implementation of hardware control of transducers and acquisition of signals from detectors and sensors. It is, however, a challenge to write programs that allow interactive use of such arrangements from a personal computer. This task is particularly complex if some of the included hardware components are connected directly to the computer and not via the microcontroller. A graphical user interface framework, Instrumentino, was therefore developed to allow the creation of control programs for complex systems with minimal programming effort. By writing a single code file, a powerful custom user interface is generated, which enables the automatic running of elaborate operation sequences and observation of acquired experimental data in real time. The framework, which is written in Python, allows extension by users, and is made available as an open source project.

A Systems Engineering Framework for Implementing a Security and Critical Patch Management Process in Diverse Environments (Academic Departments' Workstations)

NASA Astrophysics Data System (ADS)

Mohammadi, Hadi

Use of the Patch Vulnerability Management (PVM) process should be seriously considered for any networked computing system. The PVM process prevents the operating system (OS) and software applications from being attacked due to security vulnerabilities, which lead to system failures and critical data leakage. The purpose of this research is to create and design a Security and Critical Patch Management Process (SCPMP) framework based on Systems Engineering (SE) principles. This framework will assist Information Technology Department Staff (ITDS) to reduce IT operating time and costs and mitigate the risk of security and vulnerability attacks. Further, this study evaluates implementation of the SCPMP in the networked computing systems of an academic environment in order to: 1. Meet patch management requirements by applying SE principles. 2. Reduce the cost of IT operations and PVM cycles. 3. Improve the current PVM methodologies to prevent networked computing systems from becoming the targets of security vulnerability attacks. 4. Embed a Maintenance Optimization Tool (MOT) in the proposed framework. The MOT allows IT managers to make the most practicable choice of methods for deploying and installing released patches and vulnerability remediation. In recent years, there has been a variety of frameworks for security practices in every networked computing system to protect computer workstations from becoming compromised or vulnerable to security attacks, which can expose important information and critical data. I have developed a new mechanism for implementing PVM for maximizing security-vulnerability maintenance, protecting OS and software packages, and minimizing SCPMP cost. To increase computing system security in any diverse environment, particularly in academia, one must apply SCPMP. I propose an optimal maintenance policy that will allow ITDS to measure and estimate the variation of PVM cycles based on their department's requirements. My results demonstrate that MOT optimizes the process of implementing SCPMP in academic workstations.

Unified Computational Methods for Regression Analysis of Zero-Inflated and Bound-Inflated Data

PubMed Central

Yang, Yan; Simpson, Douglas

2010-01-01

Bounded data with excess observations at the boundary are common in many areas of application. Various individual cases of inflated mixture models have been studied in the literature for bound-inflated data, yet the computational methods have been developed separately for each type of model. In this article we use a common framework for computing these models, and expand the range of models for both discrete and semi-continuous data with point inflation at the lower boundary. The quasi-Newton and EM algorithms are adapted and compared for estimation of model parameters. The numerical Hessian and generalized Louis method are investigated as means for computing standard errors after optimization. Correlated data are included in this framework via generalized estimating equations. The estimation of parameters and effectiveness of standard errors are demonstrated through simulation and in the analysis of data from an ultrasound bioeffect study. The unified approach enables reliable computation for a wide class of inflated mixture models and comparison of competing models. PMID:20228950

Multidisciplinary Optimization Branch Experience Using iSIGHT Software

NASA Technical Reports Server (NTRS)

Padula, S. L.; Korte, J. J.; Dunn, H. J.; Salas, A. O.

1999-01-01

The Multidisciplinary Optimization (MDO) Branch at NASA Langley is investigating frameworks for supporting multidisciplinary analysis and optimization research. A framework provides software and system services to integrate computational tasks and allows the researcher to concentrate more on the application and less on the programming details. A framework also provides a common working environment and a full range of optimization tools, and so increases the productivity of multidisciplinary research teams. Finally, a framework enables staff members to develop applications for use by disciplinary experts in other organizations. This year, the MDO Branch has gained experience with the iSIGHT framework. This paper describes experiences with four aerospace applications, including: (1) reusable launch vehicle sizing, (2) aerospike nozzle design, (3) low-noise rotorcraft trajectories, and (4) acoustic liner design. Brief overviews of each problem are provided, including the number and type of disciplinary codes and computation time estimates. In addition, the optimization methods, objective functions, design variables, and constraints are described for each problem. For each case, discussions on the advantages and disadvantages of using the iSIGHT framework are provided as well as notes on the ease of use of various advanced features and suggestions for areas of improvement.

Stability-Constrained Aerodynamic Shape Optimization with Applications to Flying Wings

NASA Astrophysics Data System (ADS)

Mader, Charles Alexander

A set of techniques is developed that allows the incorporation of flight dynamics metrics as an additional discipline in a high-fidelity aerodynamic optimization. Specifically, techniques for including static stability constraints and handling qualities constraints in a high-fidelity aerodynamic optimization are demonstrated. These constraints are developed from stability derivative information calculated using high-fidelity computational fluid dynamics (CFD). Two techniques are explored for computing the stability derivatives from CFD. One technique uses an automatic differentiation adjoint technique (ADjoint) to efficiently and accurately compute a full set of static and dynamic stability derivatives from a single steady solution. The other technique uses a linear regression method to compute the stability derivatives from a quasi-unsteady time-spectral CFD solution, allowing for the computation of static, dynamic and transient stability derivatives. Based on the characteristics of the two methods, the time-spectral technique is selected for further development, incorporated into an optimization framework, and used to conduct stability-constrained aerodynamic optimization. This stability-constrained optimization framework is then used to conduct an optimization study of a flying wing configuration. This study shows that stability constraints have a significant impact on the optimal design of flying wings and that, while static stability constraints can often be satisfied by modifying the airfoil profiles of the wing, dynamic stability constraints can require a significant change in the planform of the aircraft in order for the constraints to be satisfied.

Barriers and facilitators to electronic documentation in a rural hospital.

PubMed

Whittaker, Alice A; Aufdenkamp, Marilee; Tinley, Susan

2009-01-01

The purpose of the study was to explore nurses' perceptions of barriers and facilitators to adoption of an electronic health record (EHR) in a rural Midwestern hospital. This study was a qualitative, descriptive design. The Staggers and Parks Nurse-Computer Interaction Framework was used to guide directed content analysis. Eleven registered nurses from oncology and medical-surgical units were interviewed using three semistructured interview questions. Predetermined codes and operational definitions were developed from the Staggers and Parks framework. Narrative data were analyzed by each member of the research team and group consensus on coding was reached through group discussions. Participants were able to identify computer-related, nurse-related, and contextual barriers and facilitators to implementation of EHR. In addition, two distinct patterns of perceptions and acceptance were identified. The Staggers and Parks Nurse-Computer Interaction framework was found to be useful in identifying computer, nurse, and contextual characteristics that act as facilitators or barriers to adoption of an EHR system. Acceptance and use of an EHR are enhanced when barriers are managed and facilitators are supported. Understanding and management of facilitators and barriers to EHR adoption may impact nurses' ability to provide and document nursing care.

Towards Test Driven Development for Computational Science with pFUnit

NASA Technical Reports Server (NTRS)

Rilee, Michael L.; Clune, Thomas L.

2014-01-01

Developers working in Computational Science & Engineering (CSE)/High Performance Computing (HPC) must contend with constant change due to advances in computing technology and science. Test Driven Development (TDD) is a methodology that mitigates software development risks due to change at the cost of adding comprehensive and continuous testing to the development process. Testing frameworks tailored for CSE/HPC, like pFUnit, can lower the barriers to such testing, yet CSE software faces unique constraints foreign to the broader software engineering community. Effective testing of numerical software requires a comprehensive suite of oracles, i.e., use cases with known answers, as well as robust estimates for the unavoidable numerical errors associated with implementation with finite-precision arithmetic. At first glance these concerns often seem exceedingly challenging or even insurmountable for real-world scientific applications. However, we argue that this common perception is incorrect and driven by (1) a conflation between model validation and software verification and (2) the general tendency in the scientific community to develop relatively coarse-grained, large procedures that compound numerous algorithmic steps.We believe TDD can be applied routinely to numerical software if developers pursue fine-grained implementations that permit testing, neatly side-stepping concerns about needing nontrivial oracles as well as the accumulation of errors. We present an example of a successful, complex legacy CSE/HPC code whose development process shares some aspects with TDD, which we contrast with current and potential capabilities. A mix of our proposed methodology and framework support should enable everyday use of TDD by CSE-expert developers.

GPU-based ultra-fast dose calculation using a finite size pencil beam model.

PubMed

Gu, Xuejun; Choi, Dongju; Men, Chunhua; Pan, Hubert; Majumdar, Amitava; Jiang, Steve B

2009-10-21

Online adaptive radiation therapy (ART) is an attractive concept that promises the ability to deliver an optimal treatment in response to the inter-fraction variability in patient anatomy. However, it has yet to be realized due to technical limitations. Fast dose deposit coefficient calculation is a critical component of the online planning process that is required for plan optimization of intensity-modulated radiation therapy (IMRT). Computer graphics processing units (GPUs) are well suited to provide the requisite fast performance for the data-parallel nature of dose calculation. In this work, we develop a dose calculation engine based on a finite-size pencil beam (FSPB) algorithm and a GPU parallel computing framework. The developed framework can accommodate any FSPB model. We test our implementation in the case of a water phantom and the case of a prostate cancer patient with varying beamlet and voxel sizes. All testing scenarios achieved speedup ranging from 200 to 400 times when using a NVIDIA Tesla C1060 card in comparison with a 2.27 GHz Intel Xeon CPU. The computational time for calculating dose deposition coefficients for a nine-field prostate IMRT plan with this new framework is less than 1 s. This indicates that the GPU-based FSPB algorithm is well suited for online re-planning for adaptive radiotherapy.

PNNL Data-Intensive Computing for a Smarter Energy Grid

ScienceCinema

Carol Imhoff; Zhenyu (Henry) Huang; Daniel Chavarria

2017-12-09

The Middleware for Data-Intensive Computing (MeDICi) Integration Framework, an integrated platform to solve data analysis and processing needs, supports PNNL research on the U.S. electric power grid. MeDICi is enabling development of visualizations of grid operations and vulnerabilities, with goal of near real-time analysis to aid operators in preventing and mitigating grid failures.

Comparing Students' Scratch Skills with Their Computational Thinking Skills in Terms of Different Variables

ERIC Educational Resources Information Center

Oluk, Ali; Korkmaz, Özgen

2016-01-01

This study aimed to compare 5th graders' scores obtained from Scratch projects developed in the framework of Information Technologies and Software classes via Dr Scratch web tool with the scores obtained from Computational Thinking Levels Scale and to examine this comparison in terms of different variables. Correlational research model was…

Counterfactuals and Causal Models: Introduction to the Special Issue

ERIC Educational Resources Information Center

Sloman, Steven A.

2013-01-01

Judea Pearl won the 2010 Rumelhart Prize in computational cognitive science due to his seminal contributions to the development of Bayes nets and causal Bayes nets, frameworks that are central to multiple domains of the computational study of mind. At the heart of the causal Bayes nets formalism is the notion of a counterfactual, a representation…

Do Clouds Compute? A Framework for Estimating the Value of Cloud Computing

NASA Astrophysics Data System (ADS)

Klems, Markus; Nimis, Jens; Tai, Stefan

On-demand provisioning of scalable and reliable compute services, along with a cost model that charges consumers based on actual service usage, has been an objective in distributed computing research and industry for a while. Cloud Computing promises to deliver on this objective: consumers are able to rent infrastructure in the Cloud as needed, deploy applications and store data, and access them via Web protocols on a pay-per-use basis. The acceptance of Cloud Computing, however, depends on the ability for Cloud Computing providers and consumers to implement a model for business value co-creation. Therefore, a systematic approach to measure costs and benefits of Cloud Computing is needed. In this paper, we discuss the need for valuation of Cloud Computing, identify key components, and structure these components in a framework. The framework assists decision makers in estimating Cloud Computing costs and to compare these costs to conventional IT solutions. We demonstrate by means of representative use cases how our framework can be applied to real world scenarios.

The Hartree-Fock calculation of the magnetic properties of molecular solutes

NASA Astrophysics Data System (ADS)

Cammi, R.

1998-08-01

In this paper we set the formal bases for the calculation of the magnetic susceptibility and of the nuclear magnetic shielding tensors for molecular solutes described within the framework of the polarizable continuum model (PCM). The theory has been developed at self-consistent field (SCF) level and adapted to be used within the framework of some of the computational procedures of larger use, i.e., the gauge invariant atomic orbital method (GIAO) and the continuous set gauge transformation method (CSGT). The numerical results relative to the magnetizabilities and chemical shielding of acetonitrile and nitrometane in various solvents computed with the PCM-CSGT method are also presented.

Unified Framework for Development, Deployment and Robust Testing of Neuroimaging Algorithms

PubMed Central

Joshi, Alark; Scheinost, Dustin; Okuda, Hirohito; Belhachemi, Dominique; Murphy, Isabella; Staib, Lawrence H.; Papademetris, Xenophon

2011-01-01

Developing both graphical and command-line user interfaces for neuroimaging algorithms requires considerable effort. Neuroimaging algorithms can meet their potential only if they can be easily and frequently used by their intended users. Deployment of a large suite of such algorithms on multiple platforms requires consistency of user interface controls, consistent results across various platforms and thorough testing. We present the design and implementation of a novel object-oriented framework that allows for rapid development of complex image analysis algorithms with many reusable components and the ability to easily add graphical user interface controls. Our framework also allows for simplified yet robust nightly testing of the algorithms to ensure stability and cross platform interoperability. All of the functionality is encapsulated into a software object requiring no separate source code for user interfaces, testing or deployment. This formulation makes our framework ideal for developing novel, stable and easy-to-use algorithms for medical image analysis and computer assisted interventions. The framework has been both deployed at Yale and released for public use in the open source multi-platform image analysis software—BioImage Suite (bioimagesuite.org). PMID:21249532

A novel framework of tissue membrane systems for image fusion.

PubMed

Zhang, Zulin; Yi, Xinzhong; Peng, Hong

2014-01-01

This paper proposes a tissue membrane system-based framework to deal with the optimal image fusion problem. A spatial domain fusion algorithm is given, and a tissue membrane system of multiple cells is used as its computing framework. Based on the multicellular structure and inherent communication mechanism of the tissue membrane system, an improved velocity-position model is developed. The performance of the fusion framework is studied with comparison of several traditional fusion methods as well as genetic algorithm (GA)-based and differential evolution (DE)-based spatial domain fusion methods. Experimental results show that the proposed fusion framework is superior or comparable to the other methods and can be efficiently used for image fusion.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Farrell, Kathryn, E-mail: kfarrell@ices.utexas.edu; Oden, J. Tinsley, E-mail: oden@ices.utexas.edu; Faghihi, Danial, E-mail: danial@ices.utexas.edu

A general adaptive modeling algorithm for selection and validation of coarse-grained models of atomistic systems is presented. A Bayesian framework is developed to address uncertainties in parameters, data, and model selection. Algorithms for computing output sensitivities to parameter variances, model evidence and posterior model plausibilities for given data, and for computing what are referred to as Occam Categories in reference to a rough measure of model simplicity, make up components of the overall approach. Computational results are provided for representative applications.

A Survey of Artificial Immune System Based Intrusion Detection

PubMed Central

Li, Tao; Hu, Xinlei; Wang, Feng; Zou, Yang

2014-01-01

In the area of computer security, Intrusion Detection (ID) is a mechanism that attempts to discover abnormal access to computers by analyzing various interactions. There is a lot of literature about ID, but this study only surveys the approaches based on Artificial Immune System (AIS). The use of AIS in ID is an appealing concept in current techniques. This paper summarizes AIS based ID methods from a new view point; moreover, a framework is proposed for the design of AIS based ID Systems (IDSs). This framework is analyzed and discussed based on three core aspects: antibody/antigen encoding, generation algorithm, and evolution mode. Then we collate the commonly used algorithms, their implementation characteristics, and the development of IDSs into this framework. Finally, some of the future challenges in this area are also highlighted. PMID:24790549

A Parallel Framework with Block Matrices of a Discrete Fourier Transform for Vector-Valued Discrete-Time Signals.

PubMed

Soto-Quiros, Pablo

2015-01-01

This paper presents a parallel implementation of a kind of discrete Fourier transform (DFT): the vector-valued DFT. The vector-valued DFT is a novel tool to analyze the spectra of vector-valued discrete-time signals. This parallel implementation is developed in terms of a mathematical framework with a set of block matrix operations. These block matrix operations contribute to analysis, design, and implementation of parallel algorithms in multicore processors. In this work, an implementation and experimental investigation of the mathematical framework are performed using MATLAB with the Parallel Computing Toolbox. We found that there is advantage to use multicore processors and a parallel computing environment to minimize the high execution time. Additionally, speedup increases when the number of logical processors and length of the signal increase.

Structure simulation with calculated NMR parameters - integrating COSMOS into the CCPN framework.

PubMed

Schneider, Olaf; Fogh, Rasmus H; Sternberg, Ulrich; Klenin, Konstantin; Kondov, Ivan

2012-01-01

The Collaborative Computing Project for NMR (CCPN) has build a software framework consisting of the CCPN data model (with APIs) for NMR related data, the CcpNmr Analysis program and additional tools like CcpNmr FormatConverter. The open architecture allows for the integration of external software to extend the abilities of the CCPN framework with additional calculation methods. Recently, we have carried out the first steps for integrating our software Computer Simulation of Molecular Structures (COSMOS) into the CCPN framework. The COSMOS-NMR force field unites quantum chemical routines for the calculation of molecular properties with a molecular mechanics force field yielding the relative molecular energies. COSMOS-NMR allows introducing NMR parameters as constraints into molecular mechanics calculations. The resulting infrastructure will be made available for the NMR community. As a first application we have tested the evaluation of calculated protein structures using COSMOS-derived 13C Cα and Cβ chemical shifts. In this paper we give an overview of the methodology and a roadmap for future developments and applications.

A New Mathematical Framework for Design Under Uncertainty

DTIC Science & Technology

2016-05-05

blending multiple information sources via auto-regressive stochastic modeling. A computationally efficient machine learning framework is developed based on...sion and machine learning approaches; see Fig. 1. This will lead to a comprehensive description of system performance with less uncertainty than in the...Bayesian optimization of super-cavitating hy- drofoils The goal of this study is to demonstrate the capabilities of statistical learning and

GISpark: A Geospatial Distributed Computing Platform for Spatiotemporal Big Data

NASA Astrophysics Data System (ADS)

Wang, S.; Zhong, E.; Wang, E.; Zhong, Y.; Cai, W.; Li, S.; Gao, S.

2016-12-01

Geospatial data are growing exponentially because of the proliferation of cost effective and ubiquitous positioning technologies such as global remote-sensing satellites and location-based devices. Analyzing large amounts of geospatial data can provide great value for both industrial and scientific applications. Data- and compute- intensive characteristics inherent in geospatial big data increasingly pose great challenges to technologies of data storing, computing and analyzing. Such challenges require a scalable and efficient architecture that can store, query, analyze, and visualize large-scale spatiotemporal data. Therefore, we developed GISpark - a geospatial distributed computing platform for processing large-scale vector, raster and stream data. GISpark is constructed based on the latest virtualized computing infrastructures and distributed computing architecture. OpenStack and Docker are used to build multi-user hosting cloud computing infrastructure for GISpark. The virtual storage systems such as HDFS, Ceph, MongoDB are combined and adopted for spatiotemporal data storage management. Spark-based algorithm framework is developed for efficient parallel computing. Within this framework, SuperMap GIScript and various open-source GIS libraries can be integrated into GISpark. GISpark can also integrated with scientific computing environment (e.g., Anaconda), interactive computing web applications (e.g., Jupyter notebook), and machine learning tools (e.g., TensorFlow/Orange). The associated geospatial facilities of GISpark in conjunction with the scientific computing environment, exploratory spatial data analysis tools, temporal data management and analysis systems make up a powerful geospatial computing tool. GISpark not only provides spatiotemporal big data processing capacity in the geospatial field, but also provides spatiotemporal computational model and advanced geospatial visualization tools that deals with other domains related with spatial property. We tested the performance of the platform based on taxi trajectory analysis. Results suggested that GISpark achieves excellent run time performance in spatiotemporal big data applications.

BCILAB: a platform for brain-computer interface development

NASA Astrophysics Data System (ADS)

Kothe, Christian Andreas; Makeig, Scott

2013-10-01

Objective. The past two decades have seen dramatic progress in our ability to model brain signals recorded by electroencephalography, functional near-infrared spectroscopy, etc., and to derive real-time estimates of user cognitive state, response, or intent for a variety of purposes: to restore communication by the severely disabled, to effect brain-actuated control and, more recently, to augment human-computer interaction. Continuing these advances, largely achieved through increases in computational power and methods, requires software tools to streamline the creation, testing, evaluation and deployment of new data analysis methods. Approach. Here we present BCILAB, an open-source MATLAB-based toolbox built to address the need for the development and testing of brain-computer interface (BCI) methods by providing an organized collection of over 100 pre-implemented methods and method variants, an easily extensible framework for the rapid prototyping of new methods, and a highly automated framework for systematic testing and evaluation of new implementations. Main results. To validate and illustrate the use of the framework, we present two sample analyses of publicly available data sets from recent BCI competitions and from a rapid serial visual presentation task. We demonstrate the straightforward use of BCILAB to obtain results compatible with the current BCI literature. Significance. The aim of the BCILAB toolbox is to provide the BCI community a powerful toolkit for methods research and evaluation, thereby helping to accelerate the pace of innovation in the field, while complementing the existing spectrum of tools for real-time BCI experimentation, deployment and use.

Applications integration in a hybrid cloud computing environment: modelling and platform

NASA Astrophysics Data System (ADS)

Li, Qing; Wang, Ze-yuan; Li, Wei-hua; Li, Jun; Wang, Cheng; Du, Rui-yang

2013-08-01

With the development of application services providers and cloud computing, more and more small- and medium-sized business enterprises use software services and even infrastructure services provided by professional information service companies to replace all or part of their information systems (ISs). These information service companies provide applications, such as data storage, computing processes, document sharing and even management information system services as public resources to support the business process management of their customers. However, no cloud computing service vendor can satisfy the full functional IS requirements of an enterprise. As a result, enterprises often have to simultaneously use systems distributed in different clouds and their intra enterprise ISs. Thus, this article presents a framework to integrate applications deployed in public clouds and intra ISs. A run-time platform is developed and a cross-computing environment process modelling technique is also developed to improve the feasibility of ISs under hybrid cloud computing environments.

Software platform for managing the classification of error- related potentials of observers

NASA Astrophysics Data System (ADS)

Asvestas, P.; Ventouras, E.-C.; Kostopoulos, S.; Sidiropoulos, K.; Korfiatis, V.; Korda, A.; Uzunolglu, A.; Karanasiou, I.; Kalatzis, I.; Matsopoulos, G.

2015-09-01

Human learning is partly based on observation. Electroencephalographic recordings of subjects who perform acts (actors) or observe actors (observers), contain a negative waveform in the Evoked Potentials (EPs) of the actors that commit errors and of observers who observe the error-committing actors. This waveform is called the Error-Related Negativity (ERN). Its detection has applications in the context of Brain-Computer Interfaces. The present work describes a software system developed for managing EPs of observers, with the aim of classifying them into observations of either correct or incorrect actions. It consists of an integrated platform for the storage, management, processing and classification of EPs recorded during error-observation experiments. The system was developed using C# and the following development tools and frameworks: MySQL, .NET Framework, Entity Framework and Emgu CV, for interfacing with the machine learning library of OpenCV. Up to six features can be computed per EP recording per electrode. The user can select among various feature selection algorithms and then proceed to train one of three types of classifiers: Artificial Neural Networks, Support Vector Machines, k-nearest neighbour. Next the classifier can be used for classifying any EP curve that has been inputted to the database.

GIAnT - Generic InSAR Analysis Toolbox

NASA Astrophysics Data System (ADS)

Agram, P.; Jolivet, R.; Riel, B. V.; Simons, M.; Doin, M.; Lasserre, C.; Hetland, E. A.

2012-12-01

We present a computing framework for studying the spatio-temporal evolution of ground deformation from interferometric synthetic aperture radar (InSAR) data. Several open-source tools including Repeat Orbit Interferometry PACkage (ROI-PAC) and InSAR Scientific Computing Environment (ISCE) from NASA-JPL, and Delft Object-oriented Repeat Interferometric Software (DORIS), have enabled scientists to generate individual interferograms from raw radar data with relative ease. Numerous computational techniques and algorithms that reduce phase information from multiple interferograms to a deformation time-series have been developed and verified over the past decade. However, the sharing and direct comparison of products from multiple processing approaches has been hindered by - 1) absence of simple standards for sharing of estimated time-series products, 2) use of proprietary software tools with license restrictions and 3) the closed source nature of the exact implementation of many of these algorithms. We have developed this computing framework to address all of the above issues. We attempt to take the first steps towards creating a community software repository for InSAR time-series analysis. To date, we have implemented the short baseline subset algorithm (SBAS), NSBAS and multi-scale interferometric time-series (MInTS) in this framework and the associated source code is included in the GIAnT distribution. A number of the associated routines have been optimized for performance and scalability with large data sets. Some of the new features in our processing framework are - 1) the use of daily solutions from continuous GPS stations to correct for orbit errors, 2) the use of meteorological data sets to estimate the tropospheric delay screen and 3) a data-driven bootstrapping approach to estimate the uncertainties associated with estimated time-series products. We are currently working on incorporating tidal load corrections for individual interferograms and propagation of noise covariance models through the processing chain for robust estimation of uncertainties in the deformation estimates. We will demonstrate the ease of use of our framework with results ranging from regional scale analysis around Long Valley, CA and Parkfield, CA to continental scale analysis in Western South America. We will also present preliminary results from a new time-series approach that simultaneously estimates deformation over the complete spatial domain at all time epochs on a distributed computing platform. GIAnT has been developed entirely using open source tools and uses Python as the underlying platform. We build on the extensive numerical (NumPy) and scientific (SciPy) computing Python libraries to develop an object-oriented, flexible and modular framework for time-series InSAR applications. The toolbox is currently configured to work with outputs from ROI-PAC, ISCE and DORIS, but can easily be extended to support products from other SAR/InSAR processors. The toolbox libraries include support for hierarchical data format (HDF5) memory mapped files, parallel processing with Python's multi-processing module and support for many convex optimization solvers like CSDP, CVXOPT etc. An extensive set of routines to deal with ASCII and XML files has also been included for controlling the processing parameters.

Computational Modeling for Enhancing Soft Tissue Image Guided Surgery: An Application in Neurosurgery.

PubMed

Miga, Michael I

2016-01-01

With the recent advances in computing, the opportunities to translate computational models to more integrated roles in patient treatment are expanding at an exciting rate. One area of considerable development has been directed towards correcting soft tissue deformation within image guided neurosurgery applications. This review captures the efforts that have been undertaken towards enhancing neuronavigation by the integration of soft tissue biomechanical models, imaging and sensing technologies, and algorithmic developments. In addition, the review speaks to the evolving role of modeling frameworks within surgery and concludes with some future directions beyond neurosurgical applications.

Parallelization of fine-scale computation in Agile Multiscale Modelling Methodology

NASA Astrophysics Data System (ADS)

Macioł, Piotr; Michalik, Kazimierz

2016-10-01

Nowadays, multiscale modelling of material behavior is an extensively developed area. An important obstacle against its wide application is high computational demands. Among others, the parallelization of multiscale computations is a promising solution. Heterogeneous multiscale models are good candidates for parallelization, since communication between sub-models is limited. In this paper, the possibility of parallelization of multiscale models based on Agile Multiscale Methodology framework is discussed. A sequential, FEM based macroscopic model has been combined with concurrently computed fine-scale models, employing a MatCalc thermodynamic simulator. The main issues, being investigated in this work are: (i) the speed-up of multiscale models with special focus on fine-scale computations and (ii) on decreasing the quality of computations enforced by parallel execution. Speed-up has been evaluated on the basis of Amdahl's law equations. The problem of `delay error', rising from the parallel execution of fine scale sub-models, controlled by the sequential macroscopic sub-model is discussed. Some technical aspects of combining third-party commercial modelling software with an in-house multiscale framework and a MPI library are also discussed.

Learning Resources and Technology. A Guide to Program Development.

ERIC Educational Resources Information Center

Connecticut State Dept. of Education, Hartford.

This guide provides a framework to assist all Connecticut school districts in planning effective learning resources centers and educational technology programs capable of providing: a well developed library media component; shared instructional design responsibilities; reading for enrichment; integration of computers into instruction; distance…

A Framework for the Development of Context-Adaptable User Interfaces for Ubiquitous Computing Systems

PubMed Central

Varela, Gervasio; Paz-Lopez, Alejandro; Becerra, Jose A.; Duro, Richard

2016-01-01

This paper addresses the problem of developing user interfaces for Ubiquitous Computing (UC) and Ambient Intelligence (AmI) systems. These kind of systems are expected to provide a natural user experience, considering interaction modalities adapted to the user abilities and preferences and using whatever interaction devices are present in the environment. These interaction devices are not necessarily known at design time. The task is quite complicated due to the variety of devices and technologies, and the diversity of scenarios, and it usually burdens the developer with the need to create many different UIs in order to consider the foreseeable user-environment combinations. Here, we propose an UI abstraction framework for UC and AmI systems that effectively improves the portability of those systems between different environments and for different users. It allows developers to design and implement a single UI capable of being deployed with different devices and modalities regardless the physical location. PMID:27399711

Vertical marginal gap evaluation of conventional cast and computer numeric controlled-milled titanium full-arch implant-supported frameworks.

PubMed

Alfadda, Sara A

2014-01-01

To use a novel approach to measure the amount of vertical marginal gap in computer numeric controlled (CNC)-milled titanium frameworks and conventional cast frameworks. Ten cast frameworks were fabricated on the mandibular master casts of 10 patients. Then, 10 CNC-milled titanium frameworks were fabricated by laser scanning the cast frameworks. The vertical marginal gap was measured and analyzed using the Contura-G2 coordinate measuring machine and special computer software. The CNC-milled titanium frameworks showed an overall reduced mean vertical gap compared with the cast frameworks in all five analogs. This difference was highly statistically significant in the distal analogs. The largest mean gap in the cast framework was recorded in the most distal analogs, and the least amount was in the middle analog. Neither of the two types of frameworks provided a completely gap-free superstructure. The CNCmilled titanium frameworks showed a significantly smaller vertical marginal gap than the cast frameworks.

Aorta: a management layer for mobile peer-to-peer massive multiplayer games

NASA Astrophysics Data System (ADS)

Edlich, Stefan; Hoerning, Henrik; Brunnert, Andreas; Hoerning, Reidar

2005-03-01

The development of massive multiplayer games (MMPGs) for personal computers is based on a wide range of frameworks and technologies. In contrast, MMPG development for cell phones lacks the availability of framework support. We present Aorta as a multi-purpose lightweight MIDP 2.0 framework to support the transparent and equal API usage of peer-to-peer communication via http, IP and Bluetooth. Special experiments, such as load-tests on Nokia 6600s, have been carried out with Bluetooth support in using a server-as-client architecture to create ad-hoc networks by using piconet functionalities. Additionally, scatternet functionalities, which will be supported in upcoming devices, have been tested in a simulated environment on more than 12 cell phones. The core of the Aorta framework is the Etherlobby, which manages connections, peers, the game lobby, game policies and much more. The framework itself was developed to enable the fast development of mobile games, regardless of the distance between users, which might be within the schoolyard or much further away. The earliest market-ready application shown here is a multimedia game for cell phones utilizing all of the frameworks features. This game, called Micromonster, acts as platform for developer tests, as well as providing valuable information about interface usability and user acceptance.

Node Resource Manager: A Distributed Computing Software Framework Used for Solving Geophysical Problems

NASA Astrophysics Data System (ADS)

Lawry, B. J.; Encarnacao, A.; Hipp, J. R.; Chang, M.; Young, C. J.

2011-12-01

With the rapid growth of multi-core computing hardware, it is now possible for scientific researchers to run complex, computationally intensive software on affordable, in-house commodity hardware. Multi-core CPUs (Central Processing Unit) and GPUs (Graphics Processing Unit) are now commonplace in desktops and servers. Developers today have access to extremely powerful hardware that enables the execution of software that could previously only be run on expensive, massively-parallel systems. It is no longer cost-prohibitive for an institution to build a parallel computing cluster consisting of commodity multi-core servers. In recent years, our research team has developed a distributed, multi-core computing system and used it to construct global 3D earth models using seismic tomography. Traditionally, computational limitations forced certain assumptions and shortcuts in the calculation of tomographic models; however, with the recent rapid growth in computational hardware including faster CPU's, increased RAM, and the development of multi-core computers, we are now able to perform seismic tomography, 3D ray tracing and seismic event location using distributed parallel algorithms running on commodity hardware, thereby eliminating the need for many of these shortcuts. We describe Node Resource Manager (NRM), a system we developed that leverages the capabilities of a parallel computing cluster. NRM is a software-based parallel computing management framework that works in tandem with the Java Parallel Processing Framework (JPPF, http://www.jppf.org/), a third party library that provides a flexible and innovative way to take advantage of modern multi-core hardware. NRM enables multiple applications to use and share a common set of networked computers, regardless of their hardware platform or operating system. Using NRM, algorithms can be parallelized to run on multiple processing cores of a distributed computing cluster of servers and desktops, which results in a dramatic speedup in execution time. NRM is sufficiently generic to support applications in any domain, as long as the application is parallelizable (i.e., can be subdivided into multiple individual processing tasks). At present, NRM has been effective in decreasing the overall runtime of several algorithms: 1) the generation of a global 3D model of the compressional velocity distribution in the Earth using tomographic inversion, 2) the calculation of the model resolution matrix, model covariance matrix, and travel time uncertainty for the aforementioned velocity model, and 3) the correlation of waveforms with archival data on a massive scale for seismic event detection. Sandia National Laboratories is a multi-program laboratory managed and operated by Sandia Corporation, a wholly owned subsidiary of Lockheed Martin Corporation, for the U.S. Department of Energy's National Nuclear Security Administration under contract DE-AC04-94AL85000.

ProFUSO: Business process and ontology-based framework to develop ubiquitous computing support systems for chronic patients' management.

PubMed

Jimenez-Molina, Angel; Gaete-Villegas, Jorge; Fuentes, Javier

2018-06-01

New advances in telemedicine, ubiquitous computing, and artificial intelligence have supported the emergence of more advanced applications and support systems for chronic patients. This trend addresses the important problem of chronic illnesses, highlighted by multiple international organizations as a core issue in future healthcare. Despite the myriad of exciting new developments, each application and system is designed and implemented for specific purposes and lacks the flexibility to support different healthcare concerns. Some of the known problems of such developments are the integration issues between applications and existing healthcare systems, the reusability of technical knowledge in the creation of new and more sophisticated systems and the usage of data gathered from multiple sources in the generation of new knowledge. This paper proposes a framework for the development of chronic disease support systems and applications as an answer to these shortcomings. Through this framework our pursuit is to create a common ground methodology upon which new developments can be created and easily integrated to provide better support to chronic patients, medical staff and other relevant participants. General requirements are inferred for any support system from the primary attention process of chronic patients by the Business Process Management Notation. Numerous technical approaches are proposed to design a general architecture that considers the medical organizational requirements in the treatment of a patient. A framework is presented for any application in support of chronic patients and evaluated by a case study to test the applicability and pertinence of the solution. Copyright © 2018 Elsevier Inc. All rights reserved.

How Adverse Outcome Pathways Can Aid the Development and Use of Computational Prediction Models for Regulatory Toxicology.

PubMed

Wittwehr, Clemens; Aladjov, Hristo; Ankley, Gerald; Byrne, Hugh J; de Knecht, Joop; Heinzle, Elmar; Klambauer, Günter; Landesmann, Brigitte; Luijten, Mirjam; MacKay, Cameron; Maxwell, Gavin; Meek, M E Bette; Paini, Alicia; Perkins, Edward; Sobanski, Tomasz; Villeneuve, Dan; Waters, Katrina M; Whelan, Maurice

2017-02-01

Efforts are underway to transform regulatory toxicology and chemical safety assessment from a largely empirical science based on direct observation of apical toxicity outcomes in whole organism toxicity tests to a predictive one in which outcomes and risk are inferred from accumulated mechanistic understanding. The adverse outcome pathway (AOP) framework provides a systematic approach for organizing knowledge that may support such inference. Likewise, computational models of biological systems at various scales provide another means and platform to integrate current biological understanding to facilitate inference and extrapolation. We argue that the systematic organization of knowledge into AOP frameworks can inform and help direct the design and development of computational prediction models that can further enhance the utility of mechanistic and in silico data for chemical safety assessment. This concept was explored as part of a workshop on AOP-Informed Predictive Modeling Approaches for Regulatory Toxicology held September 24-25, 2015. Examples of AOP-informed model development and its application to the assessment of chemicals for skin sensitization and multiple modes of endocrine disruption are provided. The role of problem formulation, not only as a critical phase of risk assessment, but also as guide for both AOP and complementary model development is described. Finally, a proposal for actively engaging the modeling community in AOP-informed computational model development is made. The contents serve as a vision for how AOPs can be leveraged to facilitate development of computational prediction models needed to support the next generation of chemical safety assessment. © The Author 2016. Published by Oxford University Press on behalf of the Society of Toxicology.

Architecture of a Framework for Providing Information Services for Public Transport

PubMed Central

García, Carmelo R.; Pérez, Ricardo; Lorenzo, Álvaro; Quesada-Arencibia, Alexis; Alayón, Francisco; Padrón, Gabino

2012-01-01

This paper presents OnRoute, a framework for developing and running ubiquitous software that provides information services to passengers of public transportation, including payment systems and on-route guidance services. To achieve a high level of interoperability, accessibility and context awareness, OnRoute uses the ubiquitous computing paradigm. To guarantee the quality of the software produced, the reliable software principles used in critical contexts, such as automotive systems, are also considered by the framework. The main components of its architecture (run-time, system services, software components and development discipline) and how they are deployed in the transportation network (stations and vehicles) are described in this paper. Finally, to illustrate the use of OnRoute, the development of a guidance service for travellers is explained. PMID:22778585

Developments and Validations of Fully Coupled CFD and Practical Vortex Transport Method for High-Fidelity Wake Modeling in Fixed and Rotary Wing Applications

NASA Technical Reports Server (NTRS)

Anusonti-Inthra, Phuriwat

2010-01-01

A novel Computational Fluid Dynamics (CFD) coupling framework using a conventional Reynolds-Averaged Navier-Stokes (BANS) solver to resolve the near-body flow field and a Particle-based Vorticity Transport Method (PVTM) to predict the evolution of the far field wake is developed, refined, and evaluated for fixed and rotary wing cases. For the rotary wing case, the RANS/PVTM modules are loosely coupled to a Computational Structural Dynamics (CSD) module that provides blade motion and vehicle trim information. The PVTM module is refined by the addition of vortex diffusion, stretching, and reorientation models as well as an efficient memory model. Results from the coupled framework are compared with several experimental data sets (a fixed-wing wind tunnel test and a rotary-wing hover test).

A new approach to the design of information systems for foodservice management in health care facilities.

PubMed

Matthews, M E; Norback, J P

1984-06-01

An organizational framework for integrating foodservice data into an information system for management decision making is presented. The framework involves the application to foodservice of principles developed by the disciplines of managerial economics and accounting, mathematics, computer science, and information systems. The first step is to conceptualize a foodservice system from an input-output perspective, in which inputs are units of resources available to managers and outputs are servings of menu items. Next, methods of full cost accounting, from the management accounting literature, are suggested as a mechanism for developing and assigning costs of using resources within a foodservice operation. Then matrix multiplication is used to illustrate types of information that matrix data structures could make available for management planning and control when combined with a conversational mode of computer programming.

Development of an Aeroelastic Modeling Capability for Transient Nozzle Side Load Analysis

NASA Technical Reports Server (NTRS)

Wang, Ten-See; Zhao, Xiang; Zhang, Sijun; Chen, Yen-Sen

2013-01-01

Lateral nozzle forces are known to cause severe structural damage to any new rocket engine in development during test. While three-dimensional, transient, turbulent, chemically reacting computational fluid dynamics methodology has been demonstrated to capture major side load physics with rigid nozzles, hot-fire tests often show nozzle structure deformation during major side load events, leading to structural damages if structural strengthening measures were not taken. The modeling picture is incomplete without the capability to address the two-way responses between the structure and fluid. The objective of this study is to develop a coupled aeroelastic modeling capability by implementing the necessary structural dynamics component into an anchored computational fluid dynamics methodology. The computational fluid dynamics component is based on an unstructured-grid, pressure-based computational fluid dynamics formulation, while the computational structural dynamics component is developed in the framework of modal analysis. Transient aeroelastic nozzle startup analyses of the Block I Space Shuttle Main Engine at sea level were performed. The computed results from the aeroelastic nozzle modeling are presented.

A discrete mechanics framework for real time virtual surgical simulations with application to virtual laparoscopic nephrectomy.

PubMed

Zhou, Xiangmin; Zhang, Nan; Sha, Desong; Shen, Yunhe; Tamma, Kumar K; Sweet, Robert

2009-01-01

The inability to render realistic soft-tissue behavior in real time has remained a barrier to face and content aspects of validity for many virtual reality surgical training systems. Biophysically based models are not only suitable for training purposes but also for patient-specific clinical applications, physiological modeling and surgical planning. When considering the existing approaches for modeling soft tissue for virtual reality surgical simulation, the computer graphics-based approach lacks predictive capability; the mass-spring model (MSM) based approach lacks biophysically realistic soft-tissue dynamic behavior; and the finite element method (FEM) approaches fail to meet the real-time requirement. The present development stems from physics fundamental thermodynamic first law; for a space discrete dynamic system directly formulates the space discrete but time continuous governing equation with embedded material constitutive relation and results in a discrete mechanics framework which possesses a unique balance between the computational efforts and the physically realistic soft-tissue dynamic behavior. We describe the development of the discrete mechanics framework with focused attention towards a virtual laparoscopic nephrectomy application.

An efficient and accurate framework for calculating lattice thermal conductivity of solids: AFLOW—AAPL Automatic Anharmonic Phonon Library

NASA Astrophysics Data System (ADS)

Plata, Jose J.; Nath, Pinku; Usanmaz, Demet; Carrete, Jesús; Toher, Cormac; de Jong, Maarten; Asta, Mark; Fornari, Marco; Nardelli, Marco Buongiorno; Curtarolo, Stefano

2017-10-01

One of the most accurate approaches for calculating lattice thermal conductivity, , is solving the Boltzmann transport equation starting from third-order anharmonic force constants. In addition to the underlying approximations of ab-initio parameterization, two main challenges are associated with this path: high computational costs and lack of automation in the frameworks using this methodology, which affect the discovery rate of novel materials with ad-hoc properties. Here, the Automatic Anharmonic Phonon Library (AAPL) is presented. It efficiently computes interatomic force constants by making effective use of crystal symmetry analysis, it solves the Boltzmann transport equation to obtain , and allows a fully integrated operation with minimum user intervention, a rational addition to the current high-throughput accelerated materials development framework AFLOW. An "experiment vs. theory" study of the approach is shown, comparing accuracy and speed with respect to other available packages, and for materials characterized by strong electron localization and correlation. Combining AAPL with the pseudo-hybrid functional ACBN0 is possible to improve accuracy without increasing computational requirements.

A FSI computational framework for vascular physiopathology: A novel flow-tissue multiscale strategy.

PubMed

Bianchi, Daniele; Monaldo, Elisabetta; Gizzi, Alessio; Marino, Michele; Filippi, Simonetta; Vairo, Giuseppe

2017-09-01

A novel fluid-structure computational framework for vascular applications is herein presented. It is developed by combining the double multi-scale nature of vascular physiopathology in terms of both tissue properties and blood flow. Addressing arterial tissues, they are modelled via a nonlinear multiscale constitutive rationale, based only on parameters having a clear histological and biochemical meaning. Moreover, blood flow is described by coupling a three-dimensional fluid domain (undergoing physiological inflow conditions) with a zero-dimensional model, which allows to reproduce the influence of the downstream vasculature, furnishing a realistic description of the outflow proximal pressure. The fluid-structure interaction is managed through an explicit time-marching approach, able to accurately describe tissue nonlinearities within each computational step for the fluid problem. A case study associated to a patient-specific aortic abdominal aneurysmatic geometry is numerically investigated, highlighting advantages gained from the proposed multiscale strategy, as well as showing soundness and effectiveness of the established framework for assessing useful clinical quantities and risk indexes. Copyright © 2017 IPEM. Published by Elsevier Ltd. All rights reserved.

Reconstructing constructivism: causal models, Bayesian learning mechanisms, and the theory theory.

PubMed

Gopnik, Alison; Wellman, Henry M

2012-11-01

We propose a new version of the "theory theory" grounded in the computational framework of probabilistic causal models and Bayesian learning. Probabilistic models allow a constructivist but rigorous and detailed approach to cognitive development. They also explain the learning of both more specific causal hypotheses and more abstract framework theories. We outline the new theoretical ideas, explain the computational framework in an intuitive and nontechnical way, and review an extensive but relatively recent body of empirical results that supports these ideas. These include new studies of the mechanisms of learning. Children infer causal structure from statistical information, through their own actions on the world and through observations of the actions of others. Studies demonstrate these learning mechanisms in children from 16 months to 4 years old and include research on causal statistical learning, informal experimentation through play, and imitation and informal pedagogy. They also include studies of the variability and progressive character of intuitive theory change, particularly theory of mind. These studies investigate both the physical and the psychological and social domains. We conclude with suggestions for further collaborative projects between developmental and computational cognitive scientists.

Framework for Intelligent Teaching and Training Systems -- A Study of Systems

ERIC Educational Resources Information Center

Graf von Malotky, Nikolaj Troels; Martens, Alke

2016-01-01

Intelligent Tutoring System are state of the art in eLearning since the late 1980s. The earliest system have been developed in teams of psychologists and computer scientists, with the goal to investigate learning processes and, later on with the goal to intelligently support teaching and training with computers. Over the years, the eLearning hype…

A Conceptual Review of Research on the Pathological Use of Computers, Video Games, and the Internet

ERIC Educational Resources Information Center

Sim, Timothy; Gentile, Douglas A.; Bricolo, Francesco; Serpelloni, Giovanni; Gulamoydeen, Farah

2012-01-01

Preliminary research studies suggest that some people who use computer, video games, and the Internet heavily develop dysfunctional symptoms, often referred to in the popular press as an "addiction." Although several studies have measured various facets of this issue, there has been no common framework within which to view these studies. This…

A computational framework for supporting environmental-climate-energy decision-making

EPA Science Inventory

GLIMPSE is a effort in which the U.S. EPA Office of Research and Development is developing tools to support long-term, coordinated environmental, climate, and energy planning. The purpose of this presentation is to discuss the underlying science questions; provide an overview of ...

A framework for multi-stakeholder decision-making and ...

EPA Pesticide Factsheets

We propose a decision-making framework to compute compromise solutions that balance conflicting priorities of multiple stakeholders on multiple objectives. In our setting, we shape the stakeholder dis-satisfaction distribution by solving a conditional-value-at-risk (CVaR) minimization problem. The CVaR problem is parameterized by a probability level that shapes the tail of the dissatisfaction distribution. The proposed approach allows us to compute a family of compromise solutions and generalizes multi-stakeholder settings previously proposed in the literature that minimize average and worst-case dissatisfactions. We use the concept of the CVaR norm to give a geometric interpretation to this problem +and use the properties of this norm to prove that the CVaR minimization problem yields Pareto optimal solutions for any choice of the probability level. We discuss a broad range of potential applications of the framework that involve complex decision-making processes. We demonstrate the developments using a biowaste facility location case study in which we seek to balance stakeholder priorities on transportation, safety, water quality, and capital costs. This manuscript describes the methodology of a new decision-making framework that computes compromise solutions that balance conflicting priorities of multiple stakeholders on multiple objectives as needed for SHC Decision Science and Support Tools project. A biowaste facility location is employed as the case study

Framework and implementation for improving physics essential skills via computer-based practice: Vector math

NASA Astrophysics Data System (ADS)

Mikula, Brendon D.; Heckler, Andrew F.

2017-06-01

We propose a framework for improving accuracy, fluency, and retention of basic skills essential for solving problems relevant to STEM introductory courses, and implement the framework for the case of basic vector math skills over several semesters in an introductory physics course. Using an iterative development process, the framework begins with a careful identification of target skills and the study of specific student difficulties with these skills. It then employs computer-based instruction, immediate feedback, mastery grading, and well-researched principles from cognitive psychology such as interleaved training sequences and distributed practice. We implemented this with more than 1500 students over 2 semesters. Students completed the mastery practice for an average of about 13 min /week , for a total of about 2-3 h for the whole semester. Results reveal large (>1 SD ) pretest to post-test gains in accuracy in vector skills, even compared to a control group, and these gains were retained at least 2 months after practice. We also find evidence of improved fluency, student satisfaction, and that awarding regular course credit results in higher participation and higher learning gains than awarding extra credit. In all, we find that simple computer-based mastery practice is an effective and efficient way to improve a set of basic and essential skills for introductory physics.

An open-source job management framework for parameter-space exploration: OACIS

NASA Astrophysics Data System (ADS)

Murase, Y.; Uchitane, T.; Ito, N.

2017-11-01

We present an open-source software framework for parameter-space exporation, named OACIS, which is useful to manage vast amount of simulation jobs and results in a systematic way. Recent development of high-performance computers enabled us to explore parameter spaces comprehensively, however, in such cases, manual management of the workflow is practically impossible. OACIS is developed aiming at reducing the cost of these repetitive tasks when conducting simulations by automating job submissions and data management. In this article, an overview of OACIS as well as a getting started guide are presented.

Framework Resources Multiply Computing Power

NASA Technical Reports Server (NTRS)

2010-01-01

As an early proponent of grid computing, Ames Research Center awarded Small Business Innovation Research (SBIR) funding to 3DGeo Development Inc., of Santa Clara, California, (now FusionGeo Inc., of The Woodlands, Texas) to demonstrate a virtual computer environment that linked geographically dispersed computer systems over the Internet to help solve large computational problems. By adding to an existing product, FusionGeo enabled access to resources for calculation- or data-intensive applications whenever and wherever they were needed. Commercially available as Accelerated Imaging and Modeling, the product is used by oil companies and seismic service companies, which require large processing and data storage capacities.

Fault Injection Campaign for a Fault Tolerant Duplex Framework

NASA Technical Reports Server (NTRS)

Sacco, Gian Franco; Ferraro, Robert D.; von llmen, Paul; Rennels, Dave A.

2007-01-01

Fault tolerance is an efficient approach adopted to avoid or reduce the damage of a system failure. In this work we present the results of a fault injection campaign we conducted on the Duplex Framework (DF). The DF is a software developed by the UCLA group [1, 2] that uses a fault tolerant approach and allows to run two replicas of the same process on two different nodes of a commercial off-the-shelf (COTS) computer cluster. A third process running on a different node, constantly monitors the results computed by the two replicas, and eventually restarts the two replica processes if an inconsistency in their computation is detected. This approach is very cost efficient and can be adopted to control processes on spacecrafts where the fault rate produced by cosmic rays is not very high.

Impact of information and communication technology on child health.

PubMed

Woo, Eugenia Hc; White, Peter; Lai, Christopher Wk

2016-06-01

This article provides a general framework for understanding the use of information and communication technology in education and discusses the impact of computer usage on students' health and development. Potential beneficial and harmful effects of computer use by children are discussed. Early epidemiological and laboratory studies have indicated that children are at least of similar risk of developing musculoskeletal and vision problems as adults, and musculoskeletal and visual health problems developed in childhood are likely to persist into adulthood. This article, therefore, aims to provide a reflection on the deficits of existing policy and recommendations for child-specific guidelines in computer use. © 2016 Paediatrics and Child Health Division (The Royal Australasian College of Physicians).

Improving Fidelity of Launch Vehicle Liftoff Acoustic Simulations

NASA Technical Reports Server (NTRS)

Liever, Peter; West, Jeff

2016-01-01

Launch vehicles experience high acoustic loads during ignition and liftoff affected by the interaction of rocket plume generated acoustic waves with launch pad structures. Application of highly parallelized Computational Fluid Dynamics (CFD) analysis tools optimized for application on the NAS computer systems such as the Loci/CHEM program now enable simulation of time-accurate, turbulent, multi-species plume formation and interaction with launch pad geometry and capture the generation of acoustic noise at the source regions in the plume shear layers and impingement regions. These CFD solvers are robust in capturing the acoustic fluctuations, but they are too dissipative to accurately resolve the propagation of the acoustic waves throughout the launch environment domain along the vehicle. A hybrid Computational Fluid Dynamics and Computational Aero-Acoustics (CFD/CAA) modeling framework has been developed to improve such liftoff acoustic environment predictions. The framework combines the existing highly-scalable NASA production CFD code, Loci/CHEM, with a high-order accurate discontinuous Galerkin (DG) solver, Loci/THRUST, developed in the same computational framework. Loci/THRUST employs a low dissipation, high-order, unstructured DG method to accurately propagate acoustic waves away from the source regions across large distances. The DG solver is currently capable of solving up to 4th order solutions for non-linear, conservative acoustic field propagation. Higher order boundary conditions are implemented to accurately model the reflection and refraction of acoustic waves on launch pad components. The DG solver accepts generalized unstructured meshes, enabling efficient application of common mesh generation tools for CHEM and THRUST simulations. The DG solution is coupled with the CFD solution at interface boundaries placed near the CFD acoustic source regions. Both simulations are executed simultaneously with coordinated boundary condition data exchange.

Autonomic Computing for Spacecraft Ground Systems

NASA Technical Reports Server (NTRS)

Li, Zhenping; Savkli, Cetin; Jones, Lori

2007-01-01

Autonomic computing for spacecraft ground systems increases the system reliability and reduces the cost of spacecraft operations and software maintenance. In this paper, we present an autonomic computing solution for spacecraft ground systems at NASA Goddard Space Flight Center (GSFC), which consists of an open standard for a message oriented architecture referred to as the GMSEC architecture (Goddard Mission Services Evolution Center), and an autonomic computing tool, the Criteria Action Table (CAT). This solution has been used in many upgraded ground systems for NASA 's missions, and provides a framework for developing solutions with higher autonomic maturity.

Coalescent: an open-science framework for importance sampling in coalescent theory.

PubMed

Tewari, Susanta; Spouge, John L

2015-01-01

Background. In coalescent theory, computer programs often use importance sampling to calculate likelihoods and other statistical quantities. An importance sampling scheme can exploit human intuition to improve statistical efficiency of computations, but unfortunately, in the absence of general computer frameworks on importance sampling, researchers often struggle to translate new sampling schemes computationally or benchmark against different schemes, in a manner that is reliable and maintainable. Moreover, most studies use computer programs lacking a convenient user interface or the flexibility to meet the current demands of open science. In particular, current computer frameworks can only evaluate the efficiency of a single importance sampling scheme or compare the efficiencies of different schemes in an ad hoc manner. Results. We have designed a general framework (http://coalescent.sourceforge.net; language: Java; License: GPLv3) for importance sampling that computes likelihoods under the standard neutral coalescent model of a single, well-mixed population of constant size over time following infinite sites model of mutation. The framework models the necessary core concepts, comes integrated with several data sets of varying size, implements the standard competing proposals, and integrates tightly with our previous framework for calculating exact probabilities. For a given dataset, it computes the likelihood and provides the maximum likelihood estimate of the mutation parameter. Well-known benchmarks in the coalescent literature validate the accuracy of the framework. The framework provides an intuitive user interface with minimal clutter. For performance, the framework switches automatically to modern multicore hardware, if available. It runs on three major platforms (Windows, Mac and Linux). Extensive tests and coverage make the framework reliable and maintainable. Conclusions. In coalescent theory, many studies of computational efficiency consider only effective sample size. Here, we evaluate proposals in the coalescent literature, to discover that the order of efficiency among the three importance sampling schemes changes when one considers running time as well as effective sample size. We also describe a computational technique called "just-in-time delegation" available to improve the trade-off between running time and precision by constructing improved importance sampling schemes from existing ones. Thus, our systems approach is a potential solution to the "2(8) programs problem" highlighted by Felsenstein, because it provides the flexibility to include or exclude various features of similar coalescent models or importance sampling schemes.

Implementing vertex dynamics models of cell populations in biology within a consistent computational framework.

PubMed

Fletcher, Alexander G; Osborne, James M; Maini, Philip K; Gavaghan, David J

2013-11-01

The dynamic behaviour of epithelial cell sheets plays a central role during development, growth, disease and wound healing. These processes occur as a result of cell adhesion, migration, division, differentiation and death, and involve multiple processes acting at the cellular and molecular level. Computational models offer a useful means by which to investigate and test hypotheses about these processes, and have played a key role in the study of cell-cell interactions. However, the necessarily complex nature of such models means that it is difficult to make accurate comparison between different models, since it is often impossible to distinguish between differences in behaviour that are due to the underlying model assumptions, and those due to differences in the in silico implementation of the model. In this work, an approach is described for the implementation of vertex dynamics models, a discrete approach that represents each cell by a polygon (or polyhedron) whose vertices may move in response to forces. The implementation is undertaken in a consistent manner within a single open source computational framework, Chaste, which comprises fully tested, industrial-grade software that has been developed using an agile approach. This framework allows one to easily change assumptions regarding force generation and cell rearrangement processes within these models. The versatility and generality of this framework is illustrated using a number of biological examples. In each case we provide full details of all technical aspects of our model implementations, and in some cases provide extensions to make the models more generally applicable. Copyright © 2013 Elsevier Ltd. All rights reserved.

Using Frameworks in a Government Contracting Environment: Case Study at the NASA Center for Computational Sciences

NASA Technical Reports Server (NTRS)

McGalliard, James

2008-01-01

A viewgraph describing the use of multiple frameworks by NASA, GSA, and U.S. Government agencies is presented. The contents include: 1) Federal Systems Integration and Management Center (FEDSIM) and NASA Center for Computational Sciences (NCCS) Environment; 2) Ruling Frameworks; 3) Implications; and 4) Reconciling Multiple Frameworks.

Development of an Aeroelastic Modeling Capability for Transient Nozzle Side Load Analysis

NASA Technical Reports Server (NTRS)

Wang, Ten-See; Zhao, Xiang; Zhang, Sijun; Chen, Yen-Sen

2013-01-01

Lateral nozzle forces are known to cause severe structural damage to any new rocket engine in development. Currently there is no fully coupled computational tool to analyze this fluid/structure interaction process. The objective of this study was to develop a fully coupled aeroelastic modeling capability to describe the fluid/structure interaction process during the transient nozzle operations. The aeroelastic model composes of three components: the computational fluid dynamics component based on an unstructured-grid, pressure-based computational fluid dynamics formulation, the computational structural dynamics component developed in the framework of modal analysis, and the fluid-structural interface component. The developed aeroelastic model was applied to the transient nozzle startup process of the Space Shuttle Main Engine at sea level. The computed nozzle side loads and the axial nozzle wall pressure profiles from the aeroelastic nozzle are compared with those of the published rigid nozzle results, and the impact of the fluid/structure interaction on nozzle side loads is interrogated and presented.

E-learning for healthcare students: developing the communities of practice framework.

PubMed

Moule, Pam

2006-05-01

This paper presents research considering whether healthcare students were able to develop characteristics of communities of practice when engaged in an online module. Little is known about whether the communities of practice framework can be applied to online learning, with no previous consideration of its potential use within healthcare education. Using a case study approach the research, completed in 2004, had two phases. A questionnaire was administered to a group of 109 healthcare students to gain information on which to base sampling for the subsequent phase. Phase 2 employed three strands of data collection: five students completed an online diary, the online interactions of seven students were captured on a discussion board and three students were interviewed. Data were analysed using a form of pattern matching. Students were able to develop essential elements of communities of practice: mutual engagement, joint enterprise and shared repertoire, though this was not uniformly seen. Particular issues emerged for the online community, including enabling access to the online environment to support mutual engagement. The development of trust was also threatened by difficulties of presenting identities online. Joint enterprise was hampered by the online situation, although the virtual classroom proved essential for supporting endeavour. Not all students were committed to their groups. There was some evidence of group members developing shared repertoire, as routines of group working emerged. Professional understanding and computer skills were also enhanced. The framework can be applied to supporting online learning internationally amongst students and has applicability to professional groups. Those intending to employ the framework should ensure that students can gain access to the community and have the computer skills to engage. Course design should be considered to ensure support for developing the essential components of communities of practice.

Foundational Tools for Petascale Computing

DOE Office of Scientific and Technical Information (OSTI.GOV)

Miller, Barton

2014-05-19

The Paradyn project has a history of developing algorithms, techniques, and software that push the cutting edge of tool technology for high-end computing systems. Under this funding, we are working on a three-year agenda to make substantial new advances in support of new and emerging Petascale systems. The overall goal for this work is to address the steady increase in complexity of these petascale systems. Our work covers two key areas: (1) The analysis, instrumentation and control of binary programs. Work in this area falls under the general framework of the Dyninst API tool kits. (2) Infrastructure for building toolsmore » and applications at extreme scale. Work in this area falls under the general framework of the MRNet scalability framework. Note that work done under this funding is closely related to work done under a contemporaneous grant, “High-Performance Energy Applications and Systems”, SC0004061/FG02-10ER25972, UW PRJ36WV.« less

RE-PLAN: An Extensible Software Architecture to Facilitate Disaster Response Planning

PubMed Central

O’Neill, Martin; Mikler, Armin R.; Indrakanti, Saratchandra; Tiwari, Chetan; Jimenez, Tamara

2014-01-01

Computational tools are needed to make data-driven disaster mitigation planning accessible to planners and policymakers without the need for programming or GIS expertise. To address this problem, we have created modules to facilitate quantitative analyses pertinent to a variety of different disaster scenarios. These modules, which comprise the REsponse PLan ANalyzer (RE-PLAN) framework, may be used to create tools for specific disaster scenarios that allow planners to harness large amounts of disparate data and execute computational models through a point-and-click interface. Bio-E, a user-friendly tool built using this framework, was designed to develop and analyze the feasibility of ad hoc clinics for treating populations following a biological emergency event. In this article, the design and implementation of the RE-PLAN framework are described, and the functionality of the modules used in the Bio-E biological emergency mitigation tool are demonstrated. PMID:25419503

An ovine in vivo framework for tracheobronchial stent analysis.

PubMed

McGrath, Donnacha J; Thiebes, Anja Lena; Cornelissen, Christian G; O'Shea, Mary B; O'Brien, Barry; Jockenhoevel, Stefan; Bruzzi, Mark; McHugh, Peter E

2017-10-01

Tracheobronchial stents are most commonly used to restore patency to airways stenosed by tumour growth. Currently all tracheobronchial stents are associated with complications such as stent migration, granulation tissue formation, mucous plugging and stent strut fracture. The present work develops a computational framework to evaluate tracheobronchial stent designs in vivo. Pressurised computed tomography is used to create a biomechanical lung model which takes into account the in vivo stress state, global lung deformation and local loading from pressure variation. Stent interaction with the airway is then evaluated for a number of loading conditions including normal breathing, coughing and ventilation. Results of the analysis indicate that three of the major complications associated with tracheobronchial stents can potentially be analysed with this framework, which can be readily applied to the human case. Airway deformation caused by lung motion is shown to have a significant effect on stent mechanical performance, including implications for stent migration, granulation formation and stent fracture.

Development and Application of a Numerical Framework for Improving Building Foundation Heat Transfer Calculations

NASA Astrophysics Data System (ADS)

Kruis, Nathanael J. F.

Heat transfer from building foundations varies significantly in all three spatial dimensions and has important dynamic effects at all timescales, from one hour to several years. With the additional consideration of moisture transport, ground freezing, evapotranspiration, and other physical phenomena, the estimation of foundation heat transfer becomes increasingly sophisticated and computationally intensive to the point where accuracy must be compromised for reasonable computation time. The tools currently available to calculate foundation heat transfer are often either too limited in their capabilities to draw meaningful conclusions or too sophisticated to use in common practices. This work presents Kiva, a new foundation heat transfer computational framework. Kiva provides a flexible environment for testing different numerical schemes, initialization methods, spatial and temporal discretizations, and geometric approximations. Comparisons within this framework provide insight into the balance of computation speed and accuracy relative to highly detailed reference solutions. The accuracy and computational performance of six finite difference numerical schemes are verified against established IEA BESTEST test cases for slab-on-grade heat conduction. Of the schemes tested, the Alternating Direction Implicit (ADI) scheme demonstrates the best balance between accuracy, performance, and numerical stability. Kiva features four approaches of initializing soil temperatures for an annual simulation. A new accelerated initialization approach is shown to significantly reduce the required years of presimulation. Methods of approximating three-dimensional heat transfer within a representative two-dimensional context further improve computational performance. A new approximation called the boundary layer adjustment method is shown to improve accuracy over other established methods with a negligible increase in computation time. This method accounts for the reduced heat transfer from concave foundation shapes, which has not been adequately addressed to date. Within the Kiva framework, three-dimensional heat transfer that can require several days to simulate is approximated in two-dimensions in a matter of seconds while maintaining a mean absolute deviation within 3%.

Computer-aided pulmonary image analysis in small animal models

DOE Office of Scientific and Technical Information (OSTI.GOV)

Xu, Ziyue; Mansoor, Awais; Mollura, Daniel J.

Purpose: To develop an automated pulmonary image analysis framework for infectious lung diseases in small animal models. Methods: The authors describe a novel pathological lung and airway segmentation method for small animals. The proposed framework includes identification of abnormal imaging patterns pertaining to infectious lung diseases. First, the authors’ system estimates an expected lung volume by utilizing a regression function between total lung capacity and approximated rib cage volume. A significant difference between the expected lung volume and the initial lung segmentation indicates the presence of severe pathology, and invokes a machine learning based abnormal imaging pattern detection system next.more » The final stage of the proposed framework is the automatic extraction of airway tree for which new affinity relationships within the fuzzy connectedness image segmentation framework are proposed by combining Hessian and gray-scale morphological reconstruction filters. Results: 133 CT scans were collected from four different studies encompassing a wide spectrum of pulmonary abnormalities pertaining to two commonly used small animal models (ferret and rabbit). Sensitivity and specificity were greater than 90% for pathological lung segmentation (average dice similarity coefficient > 0.9). While qualitative visual assessments of airway tree extraction were performed by the participating expert radiologists, for quantitative evaluation the authors validated the proposed airway extraction method by using publicly available EXACT’09 data set. Conclusions: The authors developed a comprehensive computer-aided pulmonary image analysis framework for preclinical research applications. The proposed framework consists of automatic pathological lung segmentation and accurate airway tree extraction. The framework has high sensitivity and specificity; therefore, it can contribute advances in preclinical research in pulmonary diseases.« less

Proof-of-Concept Demonstrations for Computation-Based Human Reliability Analysis. Modeling Operator Performance During Flooding Scenarios

DOE Office of Scientific and Technical Information (OSTI.GOV)

Joe, Jeffrey Clark; Boring, Ronald Laurids; Herberger, Sarah Elizabeth Marie

The United States (U.S.) Department of Energy (DOE) Light Water Reactor Sustainability (LWRS) program has the overall objective to help sustain the existing commercial nuclear power plants (NPPs). To accomplish this program objective, there are multiple LWRS “pathways,” or research and development (R&D) focus areas. One LWRS focus area is called the Risk-Informed Safety Margin and Characterization (RISMC) pathway. Initial efforts under this pathway to combine probabilistic and plant multi-physics models to quantify safety margins and support business decisions also included HRA, but in a somewhat simplified manner. HRA experts at Idaho National Laboratory (INL) have been collaborating with othermore » experts to develop a computational HRA approach, called the Human Unimodel for Nuclear Technology to Enhance Reliability (HUNTER), for inclusion into the RISMC framework. The basic premise of this research is to leverage applicable computational techniques, namely simulation and modeling, to develop and then, using RAVEN as a controller, seamlessly integrate virtual operator models (HUNTER) with 1) the dynamic computational MOOSE runtime environment that includes a full-scope plant model, and 2) the RISMC framework PRA models already in use. The HUNTER computational HRA approach is a hybrid approach that leverages past work from cognitive psychology, human performance modeling, and HRA, but it is also a significant departure from existing static and even dynamic HRA methods. This report is divided into five chapters that cover the development of an external flooding event test case and associated statistical modeling considerations.« less

Earth Science Computational Architecture for Multi-disciplinary Investigations

NASA Astrophysics Data System (ADS)

Parker, J. W.; Blom, R.; Gurrola, E.; Katz, D.; Lyzenga, G.; Norton, C.

2005-12-01

Understanding the processes underlying Earth's deformation and mass transport requires a non-traditional, integrated, interdisciplinary, approach dependent on multiple space and ground based data sets, modeling, and computational tools. Currently, details of geophysical data acquisition, analysis, and modeling largely limit research to discipline domain experts. Interdisciplinary research requires a new computational architecture that is optimized to perform complex data processing of multiple solid Earth science data types in a user-friendly environment. A web-based computational framework is being developed and integrated with applications for automatic interferometric radar processing, and models for high-resolution deformation & gravity, forward models of viscoelastic mass loading over short wavelengths & complex time histories, forward-inverse codes for characterizing surface loading-response over time scales of days to tens of thousands of years, and inversion of combined space magnetic & gravity fields to constrain deep crustal and mantle properties. This framework combines an adaptation of the QuakeSim distributed services methodology with the Pyre framework for multiphysics development. The system uses a three-tier architecture, with a middle tier server that manages user projects, available resources, and security. This ensures scalability to very large networks of collaborators. Users log into a web page and have a personal project area, persistently maintained between connections, for each application. Upon selection of an application and host from a list of available entities, inputs may be uploaded or constructed from web forms and available data archives, including gravity, GPS and imaging radar data. The user is notified of job completion and directed to results posted via URLs. Interdisciplinary work is supported through easy availability of all applications via common browsers, application tutorials and reference guides, and worked examples with visual response. At the platform level, multi-physics application development and workflow are available in the enriched environment of the Pyre framework. Advantages for combining separate expert domains include: multiple application components efficiently interact through Python shared libraries, investigators may nimbly swap models and try new parameter values, and a rich array of common tools are inherent in the Pyre system. The first four specific investigations to use this framework are: Gulf Coast subsidence: understanding of partitioning between compaction, subsidence and growth faulting; Gravity & deformation of a layered spherical earth model due to large earthquakes; Rift setting of Lake Vostok, Antarctica; and global ice mass changes.

Transportation Impact Evaluation System

DOT National Transportation Integrated Search

1979-11-01

This report specifies a framework for spatial analysis and the general modelling steps required. It also suggests available urban and regional data sources, along with some typical existing urban and regional models. The goal is to develop a computer...

A novel medical image data-based multi-physics simulation platform for computational life sciences.

PubMed

Neufeld, Esra; Szczerba, Dominik; Chavannes, Nicolas; Kuster, Niels

2013-04-06

Simulating and modelling complex biological systems in computational life sciences requires specialized software tools that can perform medical image data-based modelling, jointly visualize the data and computational results, and handle large, complex, realistic and often noisy anatomical models. The required novel solvers must provide the power to model the physics, biology and physiology of living tissue within the full complexity of the human anatomy (e.g. neuronal activity, perfusion and ultrasound propagation). A multi-physics simulation platform satisfying these requirements has been developed for applications including device development and optimization, safety assessment, basic research, and treatment planning. This simulation platform consists of detailed, parametrized anatomical models, a segmentation and meshing tool, a wide range of solvers and optimizers, a framework for the rapid development of specialized and parallelized finite element method solvers, a visualization toolkit-based visualization engine, a Python scripting interface for customized applications, a coupling framework, and more. Core components are cross-platform compatible and use open formats. Several examples of applications are presented: hyperthermia cancer treatment planning, tumour growth modelling, evaluating the magneto-haemodynamic effect as a biomarker and physics-based morphing of anatomical models.

Computational and experimental investigation of free vibration and flutter of bridge decks

NASA Astrophysics Data System (ADS)

Helgedagsrud, Tore A.; Bazilevs, Yuri; Mathisen, Kjell M.; Øiseth, Ole A.

2018-06-01

A modified rigid-object formulation is developed, and employed as part of the fluid-object interaction modeling framework from Akkerman et al. (J Appl Mech 79(1):010905, 2012. https://doi.org/10.1115/1.4005072) to simulate free vibration and flutter of long-span bridges subjected to strong winds. To validate the numerical methodology, companion wind tunnel experiments have been conducted. The results show that the computational framework captures very precisely the aeroelastic behavior in terms of aerodynamic stiffness, damping and flutter characteristics. Considering its relative simplicity and accuracy, we conclude from our study that the proposed free-vibration simulation technique is a valuable tool in engineering design of long-span bridges.

Towards a cyber-physical era: soft computing framework based multi-sensor array for water quality monitoring

NASA Astrophysics Data System (ADS)

Bhardwaj, Jyotirmoy; Gupta, Karunesh K.; Gupta, Rajiv

2018-02-01

New concepts and techniques are replacing traditional methods of water quality parameter measurement systems. This paper introduces a cyber-physical system (CPS) approach for water quality assessment in a distribution network. Cyber-physical systems with embedded sensors, processors and actuators can be designed to sense and interact with the water environment. The proposed CPS is comprised of sensing framework integrated with five different water quality parameter sensor nodes and soft computing framework for computational modelling. Soft computing framework utilizes the applications of Python for user interface and fuzzy sciences for decision making. Introduction of multiple sensors in a water distribution network generates a huge number of data matrices, which are sometimes highly complex, difficult to understand and convoluted for effective decision making. Therefore, the proposed system framework also intends to simplify the complexity of obtained sensor data matrices and to support decision making for water engineers through a soft computing framework. The target of this proposed research is to provide a simple and efficient method to identify and detect presence of contamination in a water distribution network using applications of CPS.

A comparison of fit of CNC-milled titanium and zirconia frameworks to implants.

PubMed

Abduo, Jaafar; Lyons, Karl; Waddell, Neil; Bennani, Vincent; Swain, Michael

2012-05-01

Computer numeric controlled (CNC) milling was proven to be predictable method to fabricate accurately fitting implant titanium frameworks. However, no data are available regarding the fit of CNC-milled implant zirconia frameworks. To compare the precision of fit of implant frameworks milled from titanium and zirconia and relate it to peri-implant strain development after framework fixation. A partially edentulous epoxy resin models received two Branemark implants in the areas of the lower left second premolar and second molar. From this model, 10 identical frameworks were fabricated by mean of CNC milling. Half of them were made from titanium and the other half from zirconia. Strain gauges were mounted close to the implants to qualitatively and quantitatively assess strain development as a result of framework fitting. In addition, the fit of the framework implant interface was measured using an optical microscope, when only one screw was tightened (passive fit) and when all screws were tightened (vertical fit). The data was statistically analyzed using the Mann-Whitney test. All frameworks produced measurable amounts of peri-implant strain. The zirconia frameworks produced significantly less strain than titanium. Combining the qualitative and quantitative information indicates that the implants were under vertical displacement rather than horizontal. The vertical fit was similar for zirconia (3.7 µm) and titanium (3.6 µm) frameworks; however, the zirconia frameworks exhibited a significantly finer passive fit (5.5 µm) than titanium frameworks (13.6 µm). CNC milling produced zirconia and titanium frameworks with high accuracy. The difference between the two materials in terms of fit is expected to be of minimal clinical significance. The strain developed around the implants was more related to the framework fit rather than framework material. © 2011 Wiley Periodicals, Inc.

Computer Software Training and HRD: What Are the Critical Issues?

ERIC Educational Resources Information Center

Altemeyer, Brad

2005-01-01

The paper explores critical issues for HRD practice from a parsonian framework across the HRD legs of organizational development, adult learning, and training and development. Insights into the critical issues emerge from this approach. Identifying successful transfer of training to be critical for organizational, group, and individual success.…

A Hardware-Accelerated Quantum Monte Carlo framework (HAQMC) for N-body systems

NASA Astrophysics Data System (ADS)

Gothandaraman, Akila; Peterson, Gregory D.; Warren, G. Lee; Hinde, Robert J.; Harrison, Robert J.

2009-12-01

Interest in the study of structural and energetic properties of highly quantum clusters, such as inert gas clusters has motivated the development of a hardware-accelerated framework for Quantum Monte Carlo simulations. In the Quantum Monte Carlo method, the properties of a system of atoms, such as the ground-state energies, are averaged over a number of iterations. Our framework is aimed at accelerating the computations in each iteration of the QMC application by offloading the calculation of properties, namely energy and trial wave function, onto reconfigurable hardware. This gives a user the capability to run simulations for a large number of iterations, thereby reducing the statistical uncertainty in the properties, and for larger clusters. This framework is designed to run on the Cray XD1 high performance reconfigurable computing platform, which exploits the coarse-grained parallelism of the processor along with the fine-grained parallelism of the reconfigurable computing devices available in the form of field-programmable gate arrays. In this paper, we illustrate the functioning of the framework, which can be used to calculate the energies for a model cluster of helium atoms. In addition, we present the capabilities of the framework that allow the user to vary the chemical identities of the simulated atoms. Program summaryProgram title: Hardware Accelerated Quantum Monte Carlo (HAQMC) Catalogue identifier: AEEP_v1_0 Program summary URL:http://cpc.cs.qub.ac.uk/summaries/AEEP_v1_0.html Program obtainable from: CPC Program Library, Queen's University, Belfast, N. Ireland Licensing provisions: Standard CPC licence, http://cpc.cs.qub.ac.uk/licence/licence.html No. of lines in distributed program, including test data, etc.: 691 537 No. of bytes in distributed program, including test data, etc.: 5 031 226 Distribution format: tar.gz Programming language: C/C++ for the QMC application, VHDL and Xilinx 8.1 ISE/EDK tools for FPGA design and development Computer: Cray XD1 consisting of a dual-core, dualprocessor AMD Opteron 2.2 GHz with a Xilinx Virtex-4 (V4LX160) or Xilinx Virtex-II Pro (XC2VP50) FPGA per node. We use the compute node with the Xilinx Virtex-4 FPGA Operating system: Red Hat Enterprise Linux OS Has the code been vectorised or parallelized?: Yes Classification: 6.1 Nature of problem: Quantum Monte Carlo is a practical method to solve the Schrödinger equation for large many-body systems and obtain the ground-state properties of such systems. This method involves the sampling of a number of configurations of atoms and averaging the properties of the configurations over a number of iterations. We are interested in applying the QMC method to obtain the energy and other properties of highly quantum clusters, such as inert gas clusters. Solution method: The proposed framework provides a combined hardware-software approach, in which the QMC simulation is performed on the host processor, with the computationally intensive functions such as energy and trial wave function computations mapped onto the field-programmable gate array (FPGA) logic device attached as a co-processor to the host processor. We perform the QMC simulation for a number of iterations as in the case of our original software QMC approach, to reduce the statistical uncertainty of the results. However, our proposed HAQMC framework accelerates each iteration of the simulation, by significantly reducing the time taken to calculate the ground-state properties of the configurations of atoms, thereby accelerating the overall QMC simulation. We provide a generic interpolation framework that can be extended to study a variety of pure and doped atomic clusters, irrespective of the chemical identities of the atoms. For the FPGA implementation of the properties, we use a two-region approach for accurately computing the properties over the entire domain, employ deep pipelines and fixed-point for all our calculations guaranteeing the accuracy required for our simulation.

Electrodiffusion: a continuum modeling framework for biomolecular systems with realistic spatiotemporal resolution.

PubMed

Lu, Benzhuo; Zhou, Y C; Huber, Gary A; Bond, Stephen D; Holst, Michael J; McCammon, J Andrew

2007-10-07

A computational framework is presented for the continuum modeling of cellular biomolecular diffusion influenced by electrostatic driving forces. This framework is developed from a combination of state-of-the-art numerical methods, geometric meshing, and computer visualization tools. In particular, a hybrid of (adaptive) finite element and boundary element methods is adopted to solve the Smoluchowski equation (SE), the Poisson equation (PE), and the Poisson-Nernst-Planck equation (PNPE) in order to describe electrodiffusion processes. The finite element method is used because of its flexibility in modeling irregular geometries and complex boundary conditions. The boundary element method is used due to the convenience of treating the singularities in the source charge distribution and its accurate solution to electrostatic problems on molecular boundaries. Nonsteady-state diffusion can be studied using this framework, with the electric field computed using the densities of charged small molecules and mobile ions in the solvent. A solution for mesh generation for biomolecular systems is supplied, which is an essential component for the finite element and boundary element computations. The uncoupled Smoluchowski equation and Poisson-Boltzmann equation are considered as special cases of the PNPE in the numerical algorithm, and therefore can be solved in this framework as well. Two types of computations are reported in the results: stationary PNPE and time-dependent SE or Nernst-Planck equations solutions. A biological application of the first type is the ionic density distribution around a fragment of DNA determined by the equilibrium PNPE. The stationary PNPE with nonzero flux is also studied for a simple model system, and leads to an observation that the interference on electrostatic field of the substrate charges strongly affects the reaction rate coefficient. The second is a time-dependent diffusion process: the consumption of the neurotransmitter acetylcholine by acetylcholinesterase, determined by the SE and a single uncoupled solution of the Poisson-Boltzmann equation. The electrostatic effects, counterion compensation, spatiotemporal distribution, and diffusion-controlled reaction kinetics are analyzed and different methods are compared.

Best practices for assessing ocean health in multiple contexts using tailorable frameworks

PubMed Central

Pacheco, Erich J.; Best, Benjamin D.; Scarborough, Courtney; Longo, Catherine; Katona, Steven K.; Halpern, Benjamin S.

2015-01-01

Marine policy is increasingly calling for maintaining or restoring healthy oceans while human activities continue to intensify. Thus, successful prioritization and management of competing objectives requires a comprehensive assessment of the current state of the ocean. Unfortunately, assessment frameworks to define and quantify current ocean state are often site-specific, limited to a few ocean components, and difficult to reproduce in different geographies or even through time, limiting spatial or temporal comparisons as well as the potential for shared learning. Ideally, frameworks should be tailorable to accommodate use in disparate locations and contexts, removing the need to develop frameworks de novo and allowing efforts to focus on the assessments themselves to advise action. Here, we present some of our experiences using the Ocean Health Index (OHI) framework, a tailorable and repeatable approach that measures health of coupled human-ocean ecosystems in different contexts by accommodating differences in local environmental characteristics, cultural priorities, and information availability and quality. Since its development in 2012, eleven assessments using the OHI framework have been completed at global, national, and regional scales, four of which have been led by independent academic or government groups. We have found the following to be best practices for conducting assessments: Incorporate key characteristics and priorities into the assessment framework design before gathering information; Strategically define spatial boundaries to balance information availability and decision-making scales; Maintain the key characteristics and priorities of the assessment framework regardless of information limitations; and Document and share the assessment process, methods, and tools. These best practices are relevant to most ecosystem assessment processes, but also provide tangible guidance for assessments using the OHI framework. These recommendations also promote transparency around which decisions were made and why, reproducibility through access to detailed methods and computational code, repeatability via the ability to modify methods and computational code, and ease of communication to wide audiences, all of which are critical for any robust assessment process. PMID:26713251

Best practices for assessing ocean health in multiple contexts using tailorable frameworks.

PubMed

Lowndes, Julia S Stewart; Pacheco, Erich J; Best, Benjamin D; Scarborough, Courtney; Longo, Catherine; Katona, Steven K; Halpern, Benjamin S

2015-01-01

Marine policy is increasingly calling for maintaining or restoring healthy oceans while human activities continue to intensify. Thus, successful prioritization and management of competing objectives requires a comprehensive assessment of the current state of the ocean. Unfortunately, assessment frameworks to define and quantify current ocean state are often site-specific, limited to a few ocean components, and difficult to reproduce in different geographies or even through time, limiting spatial or temporal comparisons as well as the potential for shared learning. Ideally, frameworks should be tailorable to accommodate use in disparate locations and contexts, removing the need to develop frameworks de novo and allowing efforts to focus on the assessments themselves to advise action. Here, we present some of our experiences using the Ocean Health Index (OHI) framework, a tailorable and repeatable approach that measures health of coupled human-ocean ecosystems in different contexts by accommodating differences in local environmental characteristics, cultural priorities, and information availability and quality. Since its development in 2012, eleven assessments using the OHI framework have been completed at global, national, and regional scales, four of which have been led by independent academic or government groups. We have found the following to be best practices for conducting assessments: Incorporate key characteristics and priorities into the assessment framework design before gathering information; Strategically define spatial boundaries to balance information availability and decision-making scales; Maintain the key characteristics and priorities of the assessment framework regardless of information limitations; and Document and share the assessment process, methods, and tools. These best practices are relevant to most ecosystem assessment processes, but also provide tangible guidance for assessments using the OHI framework. These recommendations also promote transparency around which decisions were made and why, reproducibility through access to detailed methods and computational code, repeatability via the ability to modify methods and computational code, and ease of communication to wide audiences, all of which are critical for any robust assessment process.

Towards a Framework for Evolvable Network Design

NASA Astrophysics Data System (ADS)

Hassan, Hoda; Eltarras, Ramy; Eltoweissy, Mohamed

The layered Internet architecture that had long guided network design and protocol engineering was an “interconnection architecture” defining a framework for interconnecting networks rather than a model for generic network structuring and engineering. We claim that the approach of abstracting the network in terms of an internetwork hinders the thorough understanding of the network salient characteristics and emergent behavior resulting in impeding design evolution required to address extreme scale, heterogeneity, and complexity. This paper reports on our work in progress that aims to: 1) Investigate the problem space in terms of the factors and decisions that influenced the design and development of computer networks; 2) Sketch the core principles for designing complex computer networks; and 3) Propose a model and related framework for building evolvable, adaptable and self organizing networks We will adopt a bottom up strategy primarily focusing on the building unit of the network model, which we call the “network cell”. The model is inspired by natural complex systems. A network cell is intrinsically capable of specialization, adaptation and evolution. Subsequently, we propose CellNet; a framework for evolvable network design. We outline scenarios for using the CellNet framework to enhance legacy Internet protocol stack.

Development Context Driven Change Awareness and Analysis Framework

NASA Technical Reports Server (NTRS)

Sarma, Anita; Branchaud, Josh; Dwyer, Matthew B.; Person, Suzette; Rungta, Neha

2014-01-01

Recent work on workspace monitoring allows conflict prediction early in the development process, however, these approaches mostly use syntactic differencing techniques to compare different program versions. In contrast, traditional change-impact analysis techniques analyze related versions of the program only after the code has been checked into the master repository. We propose a novel approach, De- CAF (Development Context Analysis Framework), that leverages the development context to scope a change impact analysis technique. The goal is to characterize the impact of each developer on other developers in the team. There are various client applications such as task prioritization, early conflict detection, and providing advice on testing that can benefit from such a characterization. The DeCAF framework leverages information from the development context to bound the iDiSE change impact analysis technique to analyze only the parts of the code base that are of interest. Bounding the analysis can enable DeCAF to efficiently compute the impact of changes using a combination of program dependence and symbolic execution based approaches.

Development Context Driven Change Awareness and Analysis Framework

NASA Technical Reports Server (NTRS)

Sarma, Anita; Branchaud, Josh; Dwyer, Matthew B.; Person, Suzette; Rungta, Neha; Wang, Yurong; Elbaum, Sebastian

2014-01-01

Recent work on workspace monitoring allows conflict prediction early in the development process, however, these approaches mostly use syntactic differencing techniques to compare different program versions. In contrast, traditional change-impact analysis techniques analyze related versions of the program only after the code has been checked into the master repository. We propose a novel approach, DeCAF (Development Context Analysis Framework), that leverages the development context to scope a change impact analysis technique. The goal is to characterize the impact of each developer on other developers in the team. There are various client applications such as task prioritization, early conflict detection, and providing advice on testing that can benefit from such a characterization. The DeCAF framework leverages information from the development context to bound the iDiSE change impact analysis technique to analyze only the parts of the code base that are of interest. Bounding the analysis can enable DeCAF to efficiently compute the impact of changes using a combination of program dependence and symbolic execution based approaches.

S3DB core: a framework for RDF generation and management in bioinformatics infrastructures

PubMed Central

2010-01-01

Background Biomedical research is set to greatly benefit from the use of semantic web technologies in the design of computational infrastructure. However, beyond well defined research initiatives, substantial issues of data heterogeneity, source distribution, and privacy currently stand in the way towards the personalization of Medicine. Results A computational framework for bioinformatic infrastructure was designed to deal with the heterogeneous data sources and the sensitive mixture of public and private data that characterizes the biomedical domain. This framework consists of a logical model build with semantic web tools, coupled with a Markov process that propagates user operator states. An accompanying open source prototype was developed to meet a series of applications that range from collaborative multi-institution data acquisition efforts to data analysis applications that need to quickly traverse complex data structures. This report describes the two abstractions underlying the S3DB-based infrastructure, logical and numerical, and discusses its generality beyond the immediate confines of existing implementations. Conclusions The emergence of the "web as a computer" requires a formal model for the different functionalities involved in reading and writing to it. The S3DB core model proposed was found to address the design criteria of biomedical computational infrastructure, such as those supporting large scale multi-investigator research, clinical trials, and molecular epidemiology. PMID:20646315

The semiotics of medical image Segmentation.

PubMed

Baxter, John S H; Gibson, Eli; Eagleson, Roy; Peters, Terry M

2018-02-01

As the interaction between clinicians and computational processes increases in complexity, more nuanced mechanisms are required to describe how their communication is mediated. Medical image segmentation in particular affords a large number of distinct loci for interaction which can act on a deep, knowledge-driven level which complicates the naive interpretation of the computer as a symbol processing machine. Using the perspective of the computer as dialogue partner, we can motivate the semiotic understanding of medical image segmentation. Taking advantage of Peircean semiotic traditions and new philosophical inquiry into the structure and quality of metaphors, we can construct a unified framework for the interpretation of medical image segmentation as a sign exchange in which each sign acts as an interface metaphor. This allows for a notion of finite semiosis, described through a schematic medium, that can rigorously describe how clinicians and computers interpret the signs mediating their interaction. Altogether, this framework provides a unified approach to the understanding and development of medical image segmentation interfaces. Copyright © 2017 Elsevier B.V. All rights reserved.

Integrating computational methods to retrofit enzymes to synthetic pathways.

PubMed

Brunk, Elizabeth; Neri, Marilisa; Tavernelli, Ivano; Hatzimanikatis, Vassily; Rothlisberger, Ursula

2012-02-01

Microbial production of desired compounds provides an efficient framework for the development of renewable energy resources. To be competitive to traditional chemistry, one requirement is to utilize the full capacity of the microorganism to produce target compounds with high yields and turnover rates. We use integrated computational methods to generate and quantify the performance of novel biosynthetic routes that contain highly optimized catalysts. Engineering a novel reaction pathway entails addressing feasibility on multiple levels, which involves handling the complexity of large-scale biochemical networks while respecting the critical chemical phenomena at the atomistic scale. To pursue this multi-layer challenge, our strategy merges knowledge-based metabolic engineering methods with computational chemistry methods. By bridging multiple disciplines, we provide an integral computational framework that could accelerate the discovery and implementation of novel biosynthetic production routes. Using this approach, we have identified and optimized a novel biosynthetic route for the production of 3HP from pyruvate. Copyright © 2011 Wiley Periodicals, Inc.

Computational psychiatry

PubMed Central

Montague, P. Read; Dolan, Raymond J.; Friston, Karl J.; Dayan, Peter

2013-01-01

Computational ideas pervade many areas of science and have an integrative explanatory role in neuroscience and cognitive science. However, computational depictions of cognitive function have had surprisingly little impact on the way we assess mental illness because diseases of the mind have not been systematically conceptualized in computational terms. Here, we outline goals and nascent efforts in the new field of computational psychiatry, which seeks to characterize mental dysfunction in terms of aberrant computations over multiple scales. We highlight early efforts in this area that employ reinforcement learning and game theoretic frameworks to elucidate decision-making in health and disease. Looking forwards, we emphasize a need for theory development and large-scale computational phenotyping in human subjects. PMID:22177032

Elementary School Students' Science Talk Ability in Inquiry-Oriented Settings in Taiwan: Test Development, Verification, and Performance Benchmarks

ERIC Educational Resources Information Center

Lin, Sheau-Wen; Liu, Yu; Chen, Shin-Feng; Wang, Jing-Ru; Kao, Huey-Lien

2016-01-01

The purpose of this study was to develop a computer-based measure of elementary students' science talk and to report students' benchmarks. The development procedure had three steps: defining the framework of the test, collecting and identifying key reference sets of science talk, and developing and verifying the science talk instrument. The…

A GPU-Parallelized Eigen-Based Clutter Filter Framework for Ultrasound Color Flow Imaging.

PubMed

Chee, Adrian J Y; Yiu, Billy Y S; Yu, Alfred C H

2017-01-01

Eigen-filters with attenuation response adapted to clutter statistics in color flow imaging (CFI) have shown improved flow detection sensitivity in the presence of tissue motion. Nevertheless, its practical adoption in clinical use is not straightforward due to the high computational cost for solving eigendecompositions. Here, we provide a pedagogical description of how a real-time computing framework for eigen-based clutter filtering can be developed through a single-instruction, multiple data (SIMD) computing approach that can be implemented on a graphical processing unit (GPU). Emphasis is placed on the single-ensemble-based eigen-filtering approach (Hankel singular value decomposition), since it is algorithmically compatible with GPU-based SIMD computing. The key algebraic principles and the corresponding SIMD algorithm are explained, and annotations on how such algorithm can be rationally implemented on the GPU are presented. Real-time efficacy of our framework was experimentally investigated on a single GPU device (GTX Titan X), and the computing throughput for varying scan depths and slow-time ensemble lengths was studied. Using our eigen-processing framework, real-time video-range throughput (24 frames/s) can be attained for CFI frames with full view in azimuth direction (128 scanlines), up to a scan depth of 5 cm ( λ pixel axial spacing) for slow-time ensemble length of 16 samples. The corresponding CFI image frames, with respect to the ones derived from non-adaptive polynomial regression clutter filtering, yielded enhanced flow detection sensitivity in vivo, as demonstrated in a carotid imaging case example. These findings indicate that the GPU-enabled eigen-based clutter filtering can improve CFI flow detection performance in real time.

Numerical propulsion system simulation

NASA Technical Reports Server (NTRS)

Lytle, John K.; Remaklus, David A.; Nichols, Lester D.

1990-01-01

The cost of implementing new technology in aerospace propulsion systems is becoming prohibitively expensive. One of the major contributors to the high cost is the need to perform many large scale system tests. Extensive testing is used to capture the complex interactions among the multiple disciplines and the multiple components inherent in complex systems. The objective of the Numerical Propulsion System Simulation (NPSS) is to provide insight into these complex interactions through computational simulations. This will allow for comprehensive evaluation of new concepts early in the design phase before a commitment to hardware is made. It will also allow for rapid assessment of field-related problems, particularly in cases where operational problems were encountered during conditions that would be difficult to simulate experimentally. The tremendous progress taking place in computational engineering and the rapid increase in computing power expected through parallel processing make this concept feasible within the near future. However it is critical that the framework for such simulations be put in place now to serve as a focal point for the continued developments in computational engineering and computing hardware and software. The NPSS concept which is described will provide that framework.

Network Community Detection based on the Physarum-inspired Computational Framework.

PubMed

Gao, Chao; Liang, Mingxin; Li, Xianghua; Zhang, Zili; Wang, Zhen; Zhou, Zhili

2016-12-13

Community detection is a crucial and essential problem in the structure analytics of complex networks, which can help us understand and predict the characteristics and functions of complex networks. Many methods, ranging from the optimization-based algorithms to the heuristic-based algorithms, have been proposed for solving such a problem. Due to the inherent complexity of identifying network structure, how to design an effective algorithm with a higher accuracy and a lower computational cost still remains an open problem. Inspired by the computational capability and positive feedback mechanism in the wake of foraging process of Physarum, which is a large amoeba-like cell consisting of a dendritic network of tube-like pseudopodia, a general Physarum-based computational framework for community detection is proposed in this paper. Based on the proposed framework, the inter-community edges can be identified from the intra-community edges in a network and the positive feedback of solving process in an algorithm can be further enhanced, which are used to improve the efficiency of original optimization-based and heuristic-based community detection algorithms, respectively. Some typical algorithms (e.g., genetic algorithm, ant colony optimization algorithm, and Markov clustering algorithm) and real-world datasets have been used to estimate the efficiency of our proposed computational framework. Experiments show that the algorithms optimized by Physarum-inspired computational framework perform better than the original ones, in terms of accuracy and computational cost. Moreover, a computational complexity analysis verifies the scalability of our framework.

Tensor scale-based fuzzy connectedness image segmentation

NASA Astrophysics Data System (ADS)

Saha, Punam K.; Udupa, Jayaram K.

2003-05-01

Tangible solutions to image segmentation are vital in many medical imaging applications. Toward this goal, a framework based on fuzzy connectedness was developed in our laboratory. A fundamental notion called "affinity" - a local fuzzy hanging togetherness relation on voxels - determines the effectiveness of this segmentation framework in real applications. In this paper, we introduce the notion of "tensor scale" - a recently developed local morphometric parameter - in affinity definition and study its effectiveness. Although, our previous notion of "local scale" using the spherical model successfully incorporated local structure size into affinity and resulted in measureable improvements in segmentation results, a major limitation of the previous approach was that it ignored local structural orientation and anisotropy. The current approach of using tensor scale in affinity computation allows an effective utilization of local size, orientation, and ansiotropy in a unified manner. Tensor scale is used for computing both the homogeneity- and object-feature-based components of affinity. Preliminary results of the proposed method on several medical images and computer generated phantoms of realistic shapes are presented. Further extensions of this work are discussed.

Conservative forgetful scholars: How people learn causal structure through sequences of interventions.

PubMed

Bramley, Neil R; Lagnado, David A; Speekenbrink, Maarten

2015-05-01

Interacting with a system is key to uncovering its causal structure. A computational framework for interventional causal learning has been developed over the last decade, but how real causal learners might achieve or approximate the computations entailed by this framework is still poorly understood. Here we describe an interactive computer task in which participants were incentivized to learn the structure of probabilistic causal systems through free selection of multiple interventions. We develop models of participants' intervention choices and online structure judgments, using expected utility gain, probability gain, and information gain and introducing plausible memory and processing constraints. We find that successful participants are best described by a model that acts to maximize information (rather than expected score or probability of being correct); that forgets much of the evidence received in earlier trials; but that mitigates this by being conservative, preferring structures consistent with earlier stated beliefs. We explore 2 heuristics that partly explain how participants might be approximating these models without explicitly representing or updating a hypothesis space. (c) 2015 APA, all rights reserved).

Model Diagnostics for the Department of Energy's Accelerated Climate Modeling for Energy (ACME) Project

NASA Astrophysics Data System (ADS)

Smith, B.

2015-12-01

In 2014, eight Department of Energy (DOE) national laboratories, four academic institutions, one company, and the National Centre for Atmospheric Research combined forces in a project called Accelerated Climate Modeling for Energy (ACME) with the goal to speed Earth system model development for climate and energy. Over the planned 10-year span, the project will conduct simulations and modeling on DOE's most powerful high-performance computing systems at Oak Ridge, Argonne, and Lawrence Berkeley Leadership Compute Facilities. A key component of the ACME project is the development of an interactive test bed for the advanced Earth system model. Its execution infrastructure will accelerate model development and testing cycles. The ACME Workflow Group is leading the efforts to automate labor-intensive tasks, provide intelligent support for complex tasks and reduce duplication of effort through collaboration support. As part of this new workflow environment, we have created a diagnostic, metric, and intercomparison Python framework, called UVCMetrics, to aid in the testing-to-production execution of the ACME model. The framework exploits similarities among different diagnostics to compactly support diagnosis of new models. It presently focuses on atmosphere and land but is designed to support ocean and sea ice model components as well. This framework is built on top of the existing open-source software framework known as the Ultrascale Visualization Climate Data Analysis Tools (UV-CDAT). Because of its flexible framework design, scientists and modelers now can generate thousands of possible diagnostic outputs. These diagnostics can compare model runs, compare model vs. observation, or simply verify a model is physically realistic. Additional diagnostics are easily integrated into the framework, and our users have already added several. Diagnostics can be generated, viewed, and manipulated from the UV-CDAT graphical user interface, Python command line scripts and programs, and web browsers. The framework is designed to be scalable to large datasets, yet easy to use and familiar to scientists using previous tools. Integration in the ACME overall user interface facilitates data publication, further analysis, and quick feedback to model developers and scientists making component or coupled model runs.

A stochastic hybrid systems based framework for modeling dependent failure processes

PubMed Central

Fan, Mengfei; Zeng, Zhiguo; Zio, Enrico; Kang, Rui; Chen, Ying

2017-01-01

In this paper, we develop a framework to model and analyze systems that are subject to dependent, competing degradation processes and random shocks. The degradation processes are described by stochastic differential equations, whereas transitions between the system discrete states are triggered by random shocks. The modeling is, then, based on Stochastic Hybrid Systems (SHS), whose state space is comprised of a continuous state determined by stochastic differential equations and a discrete state driven by stochastic transitions and reset maps. A set of differential equations are derived to characterize the conditional moments of the state variables. System reliability and its lower bounds are estimated from these conditional moments, using the First Order Second Moment (FOSM) method and Markov inequality, respectively. The developed framework is applied to model three dependent failure processes from literature and a comparison is made to Monte Carlo simulations. The results demonstrate that the developed framework is able to yield an accurate estimation of reliability with less computational costs compared to traditional Monte Carlo-based methods. PMID:28231313

A stochastic hybrid systems based framework for modeling dependent failure processes.

PubMed

Fan, Mengfei; Zeng, Zhiguo; Zio, Enrico; Kang, Rui; Chen, Ying

2017-01-01

In this paper, we develop a framework to model and analyze systems that are subject to dependent, competing degradation processes and random shocks. The degradation processes are described by stochastic differential equations, whereas transitions between the system discrete states are triggered by random shocks. The modeling is, then, based on Stochastic Hybrid Systems (SHS), whose state space is comprised of a continuous state determined by stochastic differential equations and a discrete state driven by stochastic transitions and reset maps. A set of differential equations are derived to characterize the conditional moments of the state variables. System reliability and its lower bounds are estimated from these conditional moments, using the First Order Second Moment (FOSM) method and Markov inequality, respectively. The developed framework is applied to model three dependent failure processes from literature and a comparison is made to Monte Carlo simulations. The results demonstrate that the developed framework is able to yield an accurate estimation of reliability with less computational costs compared to traditional Monte Carlo-based methods.

Onyx-Advanced Aeropropulsion Simulation Framework Created

NASA Technical Reports Server (NTRS)

Reed, John A.

2001-01-01

The Numerical Propulsion System Simulation (NPSS) project at the NASA Glenn Research Center is developing a new software environment for analyzing and designing aircraft engines and, eventually, space transportation systems. Its purpose is to dramatically reduce the time, effort, and expense necessary to design and test jet engines by creating sophisticated computer simulations of an aerospace object or system (refs. 1 and 2). Through a university grant as part of that effort, researchers at the University of Toledo have developed Onyx, an extensible Java-based (Sun Micro-systems, Inc.), objectoriented simulation framework, to investigate how advanced software design techniques can be successfully applied to aeropropulsion system simulation (refs. 3 and 4). The design of Onyx's architecture enables users to customize and extend the framework to add new functionality or adapt simulation behavior as required. It exploits object-oriented technologies, such as design patterns, domain frameworks, and software components, to develop a modular system in which users can dynamically replace components with others having different functionality.

A Probabilistic Risk Assessment of Groundwater-Related Risks at Excavation Sites

NASA Astrophysics Data System (ADS)

Jurado, A.; de Gaspari, F.; Vilarrasa, V.; Sanchez-Vila, X.; Fernandez-Garcia, D.; Tartakovsky, D. M.; Bolster, D.

2010-12-01

Excavation sites such as those associated with the construction of subway lines, railways and highway tunnels are hazardous places, posing risks to workers, machinery and surrounding buildings. Many of these risks can be groundwater related. In this work we develop a general framework based on a probabilistic risk assessment (PRA) to quantify such risks. This approach is compatible with standard PRA practices and it employs many well-developed risk analysis tools, such as fault trees. The novelty and computational challenges of the proposed approach stem from the reliance on stochastic differential equations, rather than reliability databases, to compute the probabilities of basic events. The general framework is applied to a specific case study in Spain. It is used to estimate and minimize risks for a potential construction site of an underground station for the new subway line in the Barcelona metropolitan area.

Riemannian geometry of Hamiltonian chaos: hints for a general theory.

PubMed

Cerruti-Sola, Monica; Ciraolo, Guido; Franzosi, Roberto; Pettini, Marco

2008-10-01

We aim at assessing the validity limits of some simplifying hypotheses that, within a Riemmannian geometric framework, have provided an explanation of the origin of Hamiltonian chaos and have made it possible to develop a method of analytically computing the largest Lyapunov exponent of Hamiltonian systems with many degrees of freedom. Therefore, a numerical hypotheses testing has been performed for the Fermi-Pasta-Ulam beta model and for a chain of coupled rotators. These models, for which analytic computations of the largest Lyapunov exponents have been carried out in the mentioned Riemannian geometric framework, appear as paradigmatic examples to unveil the reason why the main hypothesis of quasi-isotropy of the mechanical manifolds sometimes breaks down. The breakdown is expected whenever the topology of the mechanical manifolds is nontrivial. This is an important step forward in view of developing a geometric theory of Hamiltonian chaos of general validity.

An integrated computational tool for precipitation simulation

NASA Astrophysics Data System (ADS)

Cao, W.; Zhang, F.; Chen, S.-L.; Zhang, C.; Chang, Y. A.

2011-07-01

Computer aided materials design is of increasing interest because the conventional approach solely relying on experimentation is no longer viable within the constraint of available resources. Modeling of microstructure and mechanical properties during precipitation plays a critical role in understanding the behavior of materials and thus accelerating the development of materials. Nevertheless, an integrated computational tool coupling reliable thermodynamic calculation, kinetic simulation, and property prediction of multi-component systems for industrial applications is rarely available. In this regard, we are developing a software package, PanPrecipitation, under the framework of integrated computational materials engineering to simulate precipitation kinetics. It is seamlessly integrated with the thermodynamic calculation engine, PanEngine, to obtain accurate thermodynamic properties and atomic mobility data necessary for precipitation simulation.

Content-based histopathology image retrieval using CometCloud.

PubMed

Qi, Xin; Wang, Daihou; Rodero, Ivan; Diaz-Montes, Javier; Gensure, Rebekah H; Xing, Fuyong; Zhong, Hua; Goodell, Lauri; Parashar, Manish; Foran, David J; Yang, Lin

2014-08-26

The development of digital imaging technology is creating extraordinary levels of accuracy that provide support for improved reliability in different aspects of the image analysis, such as content-based image retrieval, image segmentation, and classification. This has dramatically increased the volume and rate at which data are generated. Together these facts make querying and sharing non-trivial and render centralized solutions unfeasible. Moreover, in many cases this data is often distributed and must be shared across multiple institutions requiring decentralized solutions. In this context, a new generation of data/information driven applications must be developed to take advantage of the national advanced cyber-infrastructure (ACI) which enable investigators to seamlessly and securely interact with information/data which is distributed across geographically disparate resources. This paper presents the development and evaluation of a novel content-based image retrieval (CBIR) framework. The methods were tested extensively using both peripheral blood smears and renal glomeruli specimens. The datasets and performance were evaluated by two pathologists to determine the concordance. The CBIR algorithms that were developed can reliably retrieve the candidate image patches exhibiting intensity and morphological characteristics that are most similar to a given query image. The methods described in this paper are able to reliably discriminate among subtle staining differences and spatial pattern distributions. By integrating a newly developed dual-similarity relevance feedback module into the CBIR framework, the CBIR results were improved substantially. By aggregating the computational power of high performance computing (HPC) and cloud resources, we demonstrated that the method can be successfully executed in minutes on the Cloud compared to weeks using standard computers. In this paper, we present a set of newly developed CBIR algorithms and validate them using two different pathology applications, which are regularly evaluated in the practice of pathology. Comparative experimental results demonstrate excellent performance throughout the course of a set of systematic studies. Additionally, we present and evaluate a framework to enable the execution of these algorithms across distributed resources. We show how parallel searching of content-wise similar images in the dataset significantly reduces the overall computational time to ensure the practical utility of the proposed CBIR algorithms.

Phase 1: Definition of intercity transportation comparison framework. Volume 1: Summary. [operations research of passenger and freight transporatation systems

NASA Technical Reports Server (NTRS)

1978-01-01

A unified framework for comparing intercity passenger and freight transportation systems is presented. Composite measures for cost, service/demand, energy, and environmental impact were determined. A set of 14 basic measures were articulated to form the foundation for computing the composite measures. A parameter dependency diagram, constructed to explicitly interrelate the composite and basic measures is discussed. Ground rules and methodology for developing the values of the basic measures are provided and the use of the framework with existing cost and service data is illustrated for various freight systems.

Real-time long term measurement using integrated framework for ubiquitous smart monitoring

NASA Astrophysics Data System (ADS)

Heo, Gwanghee; Lee, Giu; Lee, Woosang; Jeon, Joonryong; Kim, Pil-Joong

2007-04-01

Ubiquitous monitoring combining internet technologies and wireless communication is one of the most promising technologies of infrastructure health monitoring against the natural of man-made hazards. In this paper, an integrated framework of the ubiquitous monitoring is developed for real-time long term measurement in internet environment. This framework develops a wireless sensor system based on Bluetooth technology and sends measured acceleration data to the host computer through TCP/IP protocol. And it is also designed to respond to the request of web user on real time basis. In order to verify this system, real time monitoring tests are carried out on a prototype self-anchored suspension bridge. Also, wireless measurement system is analyzed to estimate its sensing capacity and evaluate its performance for monitoring purpose. Based on the evaluation, this paper proposes the effective strategies for integrated framework in order to detect structural deficiencies and to design an early warning system.

Modeling Complex Biological Flows in Multi-Scale Systems using the APDEC Framework

DOE Office of Scientific and Technical Information (OSTI.GOV)

Trebotich, D

We have developed advanced numerical algorithms to model biological fluids in multiscale flow environments using the software framework developed under the SciDAC APDEC ISIC. The foundation of our computational effort is an approach for modeling DNA-laden fluids as ''bead-rod'' polymers whose dynamics are fully coupled to an incompressible viscous solvent. The method is capable of modeling short range forces and interactions between particles using soft potentials and rigid constraints. Our methods are based on higher-order finite difference methods in complex geometry with adaptivity, leveraging algorithms and solvers in the APDEC Framework. Our Cartesian grid embedded boundary approach to incompressible viscousmore » flow in irregular geometries has also been interfaced to a fast and accurate level-sets method within the APDEC Framework for extracting surfaces from volume renderings of medical image data and used to simulate cardio-vascular and pulmonary flows in critical anatomies.« less

Modeling complex biological flows in multi-scale systems using the APDEC framework

NASA Astrophysics Data System (ADS)

Trebotich, David

2006-09-01

We have developed advanced numerical algorithms to model biological fluids in multiscale flow environments using the software framework developed under the SciDAC APDEC ISIC. The foundation of our computational effort is an approach for modeling DNA laden fluids as ''bead-rod'' polymers whose dynamics are fully coupled to an incompressible viscous solvent. The method is capable of modeling short range forces and interactions between particles using soft potentials and rigid constraints. Our methods are based on higher-order finite difference methods in complex geometry with adaptivity, leveraging algorithms and solvers in the APDEC Framework. Our Cartesian grid embedded boundary approach to incompressible viscous flow in irregular geometries has also been interfaced to a fast and accurate level-sets method within the APDEC Framework for extracting surfaces from volume renderings of medical image data and used to simulate cardio-vascular and pulmonary flows in critical anatomies.

An empirical generative framework for computational modeling of language acquisition.

PubMed

Waterfall, Heidi R; Sandbank, Ben; Onnis, Luca; Edelman, Shimon

2010-06-01

This paper reports progress in developing a computer model of language acquisition in the form of (1) a generative grammar that is (2) algorithmically learnable from realistic corpus data, (3) viable in its large-scale quantitative performance and (4) psychologically real. First, we describe new algorithmic methods for unsupervised learning of generative grammars from raw CHILDES data and give an account of the generative performance of the acquired grammars. Next, we summarize findings from recent longitudinal and experimental work that suggests how certain statistically prominent structural properties of child-directed speech may facilitate language acquisition. We then present a series of new analyses of CHILDES data indicating that the desired properties are indeed present in realistic child-directed speech corpora. Finally, we suggest how our computational results, behavioral findings, and corpus-based insights can be integrated into a next-generation model aimed at meeting the four requirements of our modeling framework.

Software life cycle methodologies and environments

NASA Technical Reports Server (NTRS)

Fridge, Ernest

1991-01-01

Products of this project will significantly improve the quality and productivity of Space Station Freedom Program software processes by: improving software reliability and safety; and broadening the range of problems that can be solved with computational solutions. Projects brings in Computer Aided Software Engineering (CASE) technology for: Environments such as Engineering Script Language/Parts Composition System (ESL/PCS) application generator, Intelligent User Interface for cost avoidance in setting up operational computer runs, Framework programmable platform for defining process and software development work flow control, Process for bringing CASE technology into an organization's culture, and CLIPS/CLIPS Ada language for developing expert systems; and methodologies such as Method for developing fault tolerant, distributed systems and a method for developing systems for common sense reasoning and for solving expert systems problems when only approximate truths are known.

Aeroelastic Modeling of a Nozzle Startup Transient

NASA Technical Reports Server (NTRS)

Wang, Ten-See; Zhao, Xiang; Zhang, Sijun; Chen, Yen-Sen

2014-01-01

Lateral nozzle forces are known to cause severe structural damage to any new rocket engine in development during test. While three-dimensional, transient, turbulent, chemically reacting computational fluid dynamics methodology has been demonstrated to capture major side load physics with rigid nozzles, hot-fire tests often show nozzle structure deformation during major side load events, leading to structural damages if structural strengthening measures were not taken. The modeling picture is incomplete without the capability to address the two-way responses between the structure and fluid. The objective of this study is to develop a tightly coupled aeroelastic modeling algorithm by implementing the necessary structural dynamics component into an anchored computational fluid dynamics methodology. The computational fluid dynamics component is based on an unstructured-grid, pressure-based computational fluid dynamics formulation, while the computational structural dynamics component is developed under the framework of modal analysis. Transient aeroelastic nozzle startup analyses at sea level were performed, and the computed transient nozzle fluid-structure interaction physics presented,

The Earth Data Analytic Services (EDAS) Framework

NASA Astrophysics Data System (ADS)

Maxwell, T. P.; Duffy, D.

2017-12-01

Faced with unprecedented growth in earth data volume and demand, NASA has developed the Earth Data Analytic Services (EDAS) framework, a high performance big data analytics framework built on Apache Spark. This framework enables scientists to execute data processing workflows combining common analysis operations close to the massive data stores at NASA. The data is accessed in standard (NetCDF, HDF, etc.) formats in a POSIX file system and processed using vetted earth data analysis tools (ESMF, CDAT, NCO, etc.). EDAS utilizes a dynamic caching architecture, a custom distributed array framework, and a streaming parallel in-memory workflow for efficiently processing huge datasets within limited memory spaces with interactive response times. EDAS services are accessed via a WPS API being developed in collaboration with the ESGF Compute Working Team to support server-side analytics for ESGF. The API can be accessed using direct web service calls, a Python script, a Unix-like shell client, or a JavaScript-based web application. New analytic operations can be developed in Python, Java, or Scala (with support for other languages planned). Client packages in Python, Java/Scala, or JavaScript contain everything needed to build and submit EDAS requests. The EDAS architecture brings together the tools, data storage, and high-performance computing required for timely analysis of large-scale data sets, where the data resides, to ultimately produce societal benefits. It is is currently deployed at NASA in support of the Collaborative REAnalysis Technical Environment (CREATE) project, which centralizes numerous global reanalysis datasets onto a single advanced data analytics platform. This service enables decision makers to compare multiple reanalysis datasets and investigate trends, variability, and anomalies in earth system dynamics around the globe.

A modular approach to large-scale design optimization of aerospace systems

NASA Astrophysics Data System (ADS)

Hwang, John T.

Gradient-based optimization and the adjoint method form a synergistic combination that enables the efficient solution of large-scale optimization problems. Though the gradient-based approach struggles with non-smooth or multi-modal problems, the capability to efficiently optimize up to tens of thousands of design variables provides a valuable design tool for exploring complex tradeoffs and finding unintuitive designs. However, the widespread adoption of gradient-based optimization is limited by the implementation challenges for computing derivatives efficiently and accurately, particularly in multidisciplinary and shape design problems. This thesis addresses these difficulties in two ways. First, to deal with the heterogeneity and integration challenges of multidisciplinary problems, this thesis presents a computational modeling framework that solves multidisciplinary systems and computes their derivatives in a semi-automated fashion. This framework is built upon a new mathematical formulation developed in this thesis that expresses any computational model as a system of algebraic equations and unifies all methods for computing derivatives using a single equation. The framework is applied to two engineering problems: the optimization of a nanosatellite with 7 disciplines and over 25,000 design variables; and simultaneous allocation and mission optimization for commercial aircraft involving 330 design variables, 12 of which are integer variables handled using the branch-and-bound method. In both cases, the framework makes large-scale optimization possible by reducing the implementation effort and code complexity. The second half of this thesis presents a differentiable parametrization of aircraft geometries and structures for high-fidelity shape optimization. Existing geometry parametrizations are not differentiable, or they are limited in the types of shape changes they allow. This is addressed by a novel parametrization that smoothly interpolates aircraft components, providing differentiability. An unstructured quadrilateral mesh generation algorithm is also developed to automate the creation of detailed meshes for aircraft structures, and a mesh convergence study is performed to verify that the quality of the mesh is maintained as it is refined. As a demonstration, high-fidelity aerostructural analysis is performed for two unconventional configurations with detailed structures included, and aerodynamic shape optimization is applied to the truss-braced wing, which finds and eliminates a shock in the region bounded by the struts and the wing.

eScience for molecular-scale simulations and the eMinerals project.

PubMed

Salje, E K H; Artacho, E; Austen, K F; Bruin, R P; Calleja, M; Chappell, H F; Chiang, G-T; Dove, M T; Frame, I; Goodwin, A L; Kleese van Dam, K; Marmier, A; Parker, S C; Pruneda, J M; Todorov, I T; Trachenko, K; Tyer, R P; Walker, A M; White, T O H

2009-03-13

We review the work carried out within the eMinerals project to develop eScience solutions that facilitate a new generation of molecular-scale simulation work. Technological developments include integration of compute and data systems, developing of collaborative frameworks and new researcher-friendly tools for grid job submission, XML data representation, information delivery, metadata harvesting and metadata management. A number of diverse science applications will illustrate how these tools are being used for large parameter-sweep studies, an emerging type of study for which the integration of computing, data and collaboration is essential.

Development and experimental assessment of a numerical modelling code to aid the design of profile extrusion cooling tools

NASA Astrophysics Data System (ADS)

Carneiro, O. S.; Rajkumar, A.; Fernandes, C.; Ferrás, L. L.; Habla, F.; Nóbrega, J. M.

2017-10-01

On the extrusion of thermoplastic profiles, upon the forming stage that takes place in the extrusion die, the profile must be cooled in a metallic calibrator. This stage must be done at a high rate, to assure increased productivity, but avoiding the development of high temperature gradients, in order to minimize the level of induced thermal residual stresses. In this work, we present a new coupled numerical solver, developed in the framework of the OpenFOAM® computational library, that computes the temperature distribution in both domains simultaneously (metallic calibrator and plastic profile), whose implementation aimed the minimization of the computational time. The new solver was experimentally assessed with an industrial case study.

Manufacturing Magic and Computational Creativity

PubMed Central

Williams, Howard; McOwan, Peter W.

2016-01-01

This paper describes techniques in computational creativity, blending mathematical modeling and psychological insight, to generate new magic tricks. The details of an explicit computational framework capable of creating new magic tricks are summarized, and evaluated against a range of contemporary theories about what constitutes a creative system. To allow further development of the proposed system we situate this approach to the generation of magic in the wider context of other areas of application in computational creativity in performance arts. We show how approaches in these domains could be incorporated to enhance future magic generation systems, and critically review possible future applications of such magic generating computers. PMID:27375533

Semantic Web Services Challenge, Results from the First Year. Series: Semantic Web And Beyond, Volume 8.

NASA Astrophysics Data System (ADS)

Petrie, C.; Margaria, T.; Lausen, H.; Zaremba, M.

Explores trade-offs among existing approaches. Reveals strengths and weaknesses of proposed approaches, as well as which aspects of the problem are not yet covered. Introduces software engineering approach to evaluating semantic web services. Service-Oriented Computing is one of the most promising software engineering trends because of the potential to reduce the programming effort for future distributed industrial systems. However, only a small part of this potential rests on the standardization of tools offered by the web services stack. The larger part of this potential rests upon the development of sufficient semantics to automate service orchestration. Currently there are many different approaches to semantic web service descriptions and many frameworks built around them. A common understanding, evaluation scheme, and test bed to compare and classify these frameworks in terms of their capabilities and shortcomings, is necessary to make progress in developing the full potential of Service-Oriented Computing. The Semantic Web Services Challenge is an open source initiative that provides a public evaluation and certification of multiple frameworks on common industrially-relevant problem sets. This edited volume reports on the first results in developing common understanding of the various technologies intended to facilitate the automation of mediation, choreography and discovery for Web Services using semantic annotations. Semantic Web Services Challenge: Results from the First Year is designed for a professional audience composed of practitioners and researchers in industry. Professionals can use this book to evaluate SWS technology for their potential practical use. The book is also suitable for advanced-level students in computer science.

Methodological Framework for World Health Organization Estimates of the Global Burden of Foodborne Disease

PubMed Central

Devleesschauwer, Brecht; Haagsma, Juanita A.; Angulo, Frederick J.; Bellinger, David C.; Cole, Dana; Döpfer, Dörte; Fazil, Aamir; Fèvre, Eric M.; Gibb, Herman J.; Hald, Tine; Kirk, Martyn D.; Lake, Robin J.; Maertens de Noordhout, Charline; Mathers, Colin D.; McDonald, Scott A.; Pires, Sara M.; Speybroeck, Niko; Thomas, M. Kate; Torgerson, Paul R.; Wu, Felicia; Havelaar, Arie H.; Praet, Nicolas

2015-01-01

Background The Foodborne Disease Burden Epidemiology Reference Group (FERG) was established in 2007 by the World Health Organization to estimate the global burden of foodborne diseases (FBDs). This paper describes the methodological framework developed by FERG's Computational Task Force to transform epidemiological information into FBD burden estimates. Methods and Findings The global and regional burden of 31 FBDs was quantified, along with limited estimates for 5 other FBDs, using Disability-Adjusted Life Years in a hazard- and incidence-based approach. To accomplish this task, the following workflow was defined: outline of disease models and collection of epidemiological data; design and completion of a database template; development of an imputation model; identification of disability weights; probabilistic burden assessment; and estimating the proportion of the disease burden by each hazard that is attributable to exposure by food (i.e., source attribution). All computations were performed in R and the different functions were compiled in the R package 'FERG'. Traceability and transparency were ensured by sharing results and methods in an interactive way with all FERG members throughout the process. Conclusions We developed a comprehensive framework for estimating the global burden of FBDs, in which methodological simplicity and transparency were key elements. All the tools developed have been made available and can be translated into a user-friendly national toolkit for studying and monitoring food safety at the local level. PMID:26633883

A tuned mesh-generation strategy for image representation based on data-dependent triangulation.

PubMed

Li, Ping; Adams, Michael D

2013-05-01

A mesh-generation framework for image representation based on data-dependent triangulation is proposed. The proposed framework is a modified version of the frameworks of Rippa and Garland and Heckbert that facilitates the development of more effective mesh-generation methods. As the proposed framework has several free parameters, the effects of different choices of these parameters on mesh quality are studied, leading to the recommendation of a particular set of choices for these parameters. A mesh-generation method is then introduced that employs the proposed framework with these best parameter choices. This method is demonstrated to produce meshes of higher quality (both in terms of squared error and subjectively) than those generated by several competing approaches, at a relatively modest computational and memory cost.

Simulation framework for intelligent transportation systems

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ewing, T.; Doss, E.; Hanebutte, U.

1996-10-01

A simulation framework has been developed for a large-scale, comprehensive, scaleable simulation of an Intelligent Transportation System (ITS). The simulator is designed for running on parallel computers and distributed (networked) computer systems, but can run on standalone workstations for smaller simulations. The simulator currently models instrumented smart vehicles with in-vehicle navigation units capable of optimal route planning and Traffic Management Centers (TMC). The TMC has probe vehicle tracking capabilities (display position and attributes of instrumented vehicles), and can provide two-way interaction with traffic to provide advisories and link times. Both the in-vehicle navigation module and the TMC feature detailed graphicalmore » user interfaces to support human-factors studies. Realistic modeling of variations of the posted driving speed are based on human factors studies that take into consideration weather, road conditions, driver personality and behavior, and vehicle type. The prototype has been developed on a distributed system of networked UNIX computers but is designed to run on parallel computers, such as ANL`s IBM SP-2, for large-scale problems. A novel feature of the approach is that vehicles are represented by autonomous computer processes which exchange messages with other processes. The vehicles have a behavior model which governs route selection and driving behavior, and can react to external traffic events much like real vehicles. With this approach, the simulation is scaleable to take advantage of emerging massively parallel processor (MPP) systems.« less

A hierarchical competing systems model of the emergence and early development of executive function

PubMed Central

Marcovitch, Stuart; Zelazo, Philip David

2010-01-01

The hierarchical competing systems model (HCSM) provides a framework for understanding the emergence and early development of executive function – the cognitive processes underlying the conscious control of behavior – in the context of search for hidden objects. According to this model, behavior is determined by the joint influence of a developmentally invariant habit system and a conscious representational system that becomes increasingly influential as children develop. This article describes a computational formalization of the HCSM, reviews behavioral and computational research consistent with the model, and suggests directions for future research on the development of executive function. PMID:19120405

Framework for computationally efficient optimal irrigation scheduling using ant colony optimization

USDA-ARS?s Scientific Manuscript database

A general optimization framework is introduced with the overall goal of reducing search space size and increasing the computational efficiency of evolutionary algorithm application for optimal irrigation scheduling. The framework achieves this goal by representing the problem in the form of a decisi...

SURF's Up: An Outline of an Innovative Framework for Teaching Mental Computation to Students in the Early Years of Schooling

ERIC Educational Resources Information Center

Russo, James

2015-01-01

In this article James Russo presents the Strategies, Understanding, Reading and Fast Facts Framework (SURF) for mental computation. He explains how this framework can be used to deepen mathematical understanding and build mental flexibility.

Toxicology ontology perspectives.

PubMed

Hardy, Barry; Apic, Gordana; Carthew, Philip; Clark, Dominic; Cook, David; Dix, Ian; Escher, Sylvia; Hastings, Janna; Heard, David J; Jeliazkova, Nina; Judson, Philip; Matis-Mitchell, Sherri; Mitic, Dragana; Myatt, Glenn; Shah, Imran; Spjuth, Ola; Tcheremenskaia, Olga; Toldo, Luca; Watson, David; White, Andrew; Yang, Chihae

2012-01-01

The field of predictive toxicology requires the development of open, public, computable, standardized toxicology vocabularies and ontologies to support the applications required by in silico, in vitro, and in vivo toxicology methods and related analysis and reporting activities. In this article we review ontology developments based on a set of perspectives showing how ontologies are being used in predictive toxicology initiatives and applications. Perspectives on resources and initiatives reviewed include OpenTox, eTOX, Pistoia Alliance, ToxWiz, Virtual Liver, EU-ADR, BEL, ToxML, and Bioclipse. We also review existing ontology developments in neighboring fields that can contribute to establishing an ontological framework for predictive toxicology. A significant set of resources is already available to provide a foundation for an ontological framework for 21st century mechanistic-based toxicology research. Ontologies such as ToxWiz provide a basis for application to toxicology investigations, whereas other ontologies under development in the biological, chemical, and biomedical communities could be incorporated in an extended future framework. OpenTox has provided a semantic web framework for the implementation of such ontologies into software applications and linked data resources. Bioclipse developers have shown the benefit of interoperability obtained through ontology by being able to link their workbench application with remote OpenTox web services. Although these developments are promising, an increased international coordination of efforts is greatly needed to develop a more unified, standardized, and open toxicology ontology framework.

EPA GEOBOOK

EPA Science Inventory

The EPA GeoBook is a computer application that resembles a notebook with pages of information on the Southeastern Ecological Framework, a powerpoint presentation, a short video and a map viewer. It was developed to forge partnerships with local, state and federal partners to work...

Towards an interactive electromechanical model of the heart

PubMed Central

Talbot, Hugo; Marchesseau, Stéphanie; Duriez, Christian; Sermesant, Maxime; Cotin, Stéphane; Delingette, Hervé

2013-01-01

In this work, we develop an interactive framework for rehearsal of and training in cardiac catheter ablation, and for planning cardiac resynchronization therapy. To this end, an interactive and real-time electrophysiology model of the heart is developed to fit patient-specific data. The proposed interactive framework relies on two main contributions. First, an efficient implementation of cardiac electrophysiology is proposed, using the latest graphics processing unit computing techniques. Second, a mechanical simulation is then coupled to the electrophysiological signals to produce realistic motion of the heart. We demonstrate that pathological mechanical and electrophysiological behaviour can be simulated. PMID:24427533

Integrating Science and Mathematics Curricula Using Computer Mediated Communications: A Vygotskian Perspective.

ERIC Educational Resources Information Center

Charnitski, Christina Wotell; Harvey, Francis A.

This paper presents the theories of L.S. Vygotsky as a conceptual framework for implementing instruction that supports concept development and promotes higher level thinking skills in students. Three major components (i.e., language, scientific and spontaneous concepts, and the zone of proximal development) of Vygotsky's socio-cultural-historical…

A Biologically Informed Framework for the Analysis of the PPAR Signaling Pathway using a Bayesian Network

EPA Science Inventory

The US EPA’s ToxCastTM program seeks to combine advances in high-throughput screening technology with methodologies from statistics and computer science to develop high-throughput decision support tools for assessing chemical hazard and risk. To develop new methods of analysis of...

Framework to parameterize and validate APEX to support deployment of the nutrient tracking tool

USDA-ARS?s Scientific Manuscript database

The Agricultural Policy Environmental eXtender (APEX) model is the scientific basis for the Nutrient Tracking Tool (NTT). NTT is an enhanced version of the Nitrogen Trading Tool, a user-friendly web-based computer program originally developed by the USDA. NTT was developed to estimate reductions in...

Pre-Service Teachers' TPACK Development and Conceptions through a TPACK-Based Course

ERIC Educational Resources Information Center

Durdu, Levent; Dag, Funda

2017-01-01

This study examines pre-service teachers' Technological Pedagogical Content Knowledge (TPACK) development and analyses their conceptions of learning and teaching with technology. With this aim in mind, researchers designed and implemented a computer-based mathematics course based on a TPACK framework. As a research methodology, a parallel mixed…

Microsoft C#.NET program and electromagnetic depth sounding for large loop source

NASA Astrophysics Data System (ADS)

Prabhakar Rao, K.; Ashok Babu, G.

2009-07-01

A program, in the C# (C Sharp) language with Microsoft.NET Framework, is developed to compute the normalized vertical magnetic field of a horizontal rectangular loop source placed on the surface of an n-layered earth. The field can be calculated either inside or outside the loop. Five C# classes with member functions in each class are, designed to compute the kernel, Hankel transform integral, coefficients for cubic spline interpolation between computed values and the normalized vertical magnetic field. The program computes the vertical magnetic field in the frequency domain using the integral expressions evaluated by a combination of straightforward numerical integration and the digital filter technique. The code utilizes different object-oriented programming (OOP) features. It finally computes the amplitude and phase of the normalized vertical magnetic field. The computed results are presented for geometric and parametric soundings. The code is developed in Microsoft.NET visual studio 2003 and uses various system class libraries.

Computational discovery of metal-organic frameworks with high gas deliverable capacity

NASA Astrophysics Data System (ADS)

Bao, Yi

Metal-organic frameworks (MOFs) are a rapidly emerging class of nanoporous materials with largely tunable chemistry and diverse applications in gas storage, gas purification, catalysis, sensing and drug delivery. Efforts have been made to develop new MOFs with desirable properties both experimentally and computationally for decades. To guide experimental synthesis, we here develop a computational methodology to explore MOFs with high gas deliverable capacity. This de novo design procedure applies known chemical reactions, considers synthesizability and geometric requirements of organic linkers, and efficiently evolves a population of MOFs to optimize a desirable property. We identify 48 MOFs with higher methane deliverable capacity at 65-5.8 bar condition than the MOF-5 reference in nine networks. In a more comprehensive work, we predict two sets of MOFs with high methane deliverable capacity at a 65-5.8 bar loading-delivery condition or a 35-5.8 bar loading-delivery condition. We also optimize a set of MOFs with high methane accessible internal surface area to investigate the relationship between deliverable capacities and internal surface area. This methodology can be extended to MOFs with multiple types of linkers and multiple SBUs. Flexibile MOFs may allow for sophisticated heat management strategies and also provide higher gas deliverable capacity than rigid frameworks. We investigate flexible MOFs, such as MIL-53 families, and Fe(bdp) and Co(bdp) analogs, to understand the structural phase transition of frameworks and the resulting influence on heat of adsorption. Challenges of simulating a system with a flexible host structure and incoming guest molecules are discussed. Preliminary results from isotherm simulation using the hybrid MC/MD simulation scheme on MIL-53(Cr) are presented. Suggestions for proceeding to understand the free energy profile of flexible MOFs are provided.

A multi-fidelity framework for physics based rotor blade simulation and optimization

NASA Astrophysics Data System (ADS)

Collins, Kyle Brian

New helicopter rotor designs are desired that offer increased efficiency, reduced vibration, and reduced noise. Rotor Designers in industry need methods that allow them to use the most accurate simulation tools available to search for these optimal designs. Computer based rotor analysis and optimization have been advanced by the development of industry standard codes known as "comprehensive" rotorcraft analysis tools. These tools typically use table look-up aerodynamics, simplified inflow models and perform aeroelastic analysis using Computational Structural Dynamics (CSD). Due to the simplified aerodynamics, most design studies are performed varying structural related design variables like sectional mass and stiffness. The optimization of shape related variables in forward flight using these tools is complicated and results are viewed with skepticism because rotor blade loads are not accurately predicted. The most accurate methods of rotor simulation utilize Computational Fluid Dynamics (CFD) but have historically been considered too computationally intensive to be used in computer based optimization, where numerous simulations are required. An approach is needed where high fidelity CFD rotor analysis can be utilized in a shape variable optimization problem with multiple objectives. Any approach should be capable of working in forward flight in addition to hover. An alternative is proposed and founded on the idea that efficient hybrid CFD methods of rotor analysis are ready to be used in preliminary design. In addition, the proposed approach recognizes the usefulness of lower fidelity physics based analysis and surrogate modeling. Together, they are used with high fidelity analysis in an intelligent process of surrogate model building of parameters in the high fidelity domain. Closing the loop between high and low fidelity analysis is a key aspect of the proposed approach. This is done by using information from higher fidelity analysis to improve predictions made with lower fidelity models. This thesis documents the development of automated low and high fidelity physics based rotor simulation frameworks. The low fidelity framework uses a comprehensive code with simplified aerodynamics. The high fidelity model uses a parallel processor capable CFD/CSD methodology. Both low and high fidelity frameworks include an aeroacoustic simulation for prediction of noise. A synergistic process is developed that uses both the low and high fidelity frameworks together to build approximate models of important high fidelity metrics as functions of certain design variables. To test the process, a 4-bladed hingeless rotor model is used as a baseline. The design variables investigated include tip geometry and spanwise twist distribution. Approximation models are built for metrics related to rotor efficiency and vibration using the results from 60+ high fidelity (CFD/CSD) experiments and 400+ low fidelity experiments. Optimization using the approximation models found the Pareto Frontier anchor points, or the design having maximum rotor efficiency and the design having minimum vibration. Various Pareto generation methods are used to find designs on the frontier between these two anchor designs. When tested in the high fidelity framework, the Pareto anchor designs are shown to be very good designs when compared with other designs from the high fidelity database. This provides evidence that the process proposed has merit. Ultimately, this process can be utilized by industry rotor designers with their existing tools to bring high fidelity analysis into the preliminary design stage of rotors. In conclusion, the methods developed and documented in this thesis have made several novel contributions. First, an automated high fidelity CFD based forward flight simulation framework has been built for use in preliminary design optimization. The framework was built around an integrated, parallel processor capable CFD/CSD/AA process. Second, a novel method of building approximate models of high fidelity parameters has been developed. The method uses a combination of low and high fidelity results and combines Design of Experiments, statistical effects analysis, and aspects of approximation model management. And third, the determination of rotor blade shape variables through optimization using CFD based analysis in forward flight has been performed. This was done using the high fidelity CFD/CSD/AA framework and method mentioned above. While the low and high fidelity predictions methods used in the work still have inaccuracies that can affect the absolute levels of the results, a framework has been successfully developed and demonstrated that allows for an efficient process to improve rotor blade designs in terms of a selected choice of objective function(s). Using engineering judgment, this methodology could be applied today to investigate opportunities to improve existing designs. With improvements in the low and high fidelity prediction components that will certainly occur, this framework could become a powerful tool for future rotorcraft design work. (Abstract shortened by UMI.)

Development and application of unified algorithms for problems in computational science

NASA Technical Reports Server (NTRS)

Shankar, Vijaya; Chakravarthy, Sukumar

1987-01-01

A framework is presented for developing computationally unified numerical algorithms for solving nonlinear equations that arise in modeling various problems in mathematical physics. The concept of computational unification is an attempt to encompass efficient solution procedures for computing various nonlinear phenomena that may occur in a given problem. For example, in Computational Fluid Dynamics (CFD), a unified algorithm will be one that allows for solutions to subsonic (elliptic), transonic (mixed elliptic-hyperbolic), and supersonic (hyperbolic) flows for both steady and unsteady problems. The objectives are: development of superior unified algorithms emphasizing accuracy and efficiency aspects; development of codes based on selected algorithms leading to validation; application of mature codes to realistic problems; and extension/application of CFD-based algorithms to problems in other areas of mathematical physics. The ultimate objective is to achieve integration of multidisciplinary technologies to enhance synergism in the design process through computational simulation. Specific unified algorithms for a hierarchy of gas dynamics equations and their applications to two other areas: electromagnetic scattering, and laser-materials interaction accounting for melting.

Development and Evaluation of an Integrated Hydrological Modeling Framework for Monitoring and Understanding Floods and Droughts

NASA Astrophysics Data System (ADS)

Yang, Z. L.; Wu, W. Y.; Lin, P.; Maidment, D. R.

2017-12-01

Extreme water events such as catastrophic floods and severe droughts have increased in recent decades. Mitigating the risk to lives, food security, infrastructure, energy supplies, as well as numerous other industries posed by these extreme events requires informed decision-making and planning based on sound science. We are developing a global water modeling capability by building models that will provide total operational water predictions (evapotranspiration, soil moisture, groundwater, channel flow, inundation, snow) at unprecedented spatial resolutions and updated frequencies. Toward this goal, this talk presents an integrated global hydrological modeling framework that takes advantage of gridded meteorological forcing, land surface modeling, channeled flow modeling, ground observations, and satellite remote sensing. Launched in August 2016, the National Water Model successfully incorporates weather forecasts to predict river flows for more than 2.7 million rivers across the continental United States, which transfers a "synoptic weather map" to a "synoptic river flow map" operationally. In this study, we apply a similar framework to a high-resolution global river network database, which is developed from a hierarchical Dominant River Tracing (DRT) algorithm, and runoff output from the Global Land Data Assimilation System (GLDAS) to a vector-based river routing model (The Routing Application for Parallel Computation of Discharge, RAPID) to produce river flows from 2001 to 2016 using Message Passing Interface (MPI) on Texas Advanced Computer Center's Stampede system. In this simulation, global river discharges for more than 177,000 rivers are computed every 30 minutes. The modeling framework's performance is evaluated with various observations including river flows at more than 400 gauge stations globally. Overall, the model exhibits a reasonably good performance in simulating the averaged patterns of terrestrial water storage, evapotranspiration and runoff. The system is appropriate for monitoring and studying floods and droughts. Directions for future research will be outlined and discussed.

["What I don't Appreciate in Real Life": Online Role Playing Game Addiction of an Adolescent--Case Study].

PubMed

Gerlach, Marie; Traxl, Bernd

2015-01-01

The present article aims to provide an insight into the life story of a computer-game addicted adolescent. Here, the relationship between the symptom game addiction, the family as a reference framework, the game's characteristics, as well as the subjective emotional state of the adolescent are of particular interest. An emphasis is also laid on the psychodynamically approached question of the impact of infantile and current relationship experiences (both within a family environment as well as with peers) on personal development. Last, still within a psychodynamic framework, we hope to provide a better understanding of the role of online computer-game addiction in the process of experiences potentially dominated by conflicts.

Towards a sustainable framework for computer based health information systems (CHIS) for least developed countries (LDCs).

PubMed

Gordon, Abekah Nkrumah; Hinson, Robert Ebo

2007-01-01

The purpose of this paper is to argue for a theoretical framework by which development of computer based health information systems (CHIS) can be made sustainable. Health Management and promotion thrive on well-articulated CHIS. There are high levels of risk associated with the development of CHIS in the context of least developed countries (LDC), thereby making them unsustainable. This paper is based largely on literature survey on health promotion and information systems. The main factors accounting for the sustainability problem in less developed countries include poor infrastructure, inappropriate donor policies and strategies, poor infrastructure and inadequate human resource capacity. To counter these challenges and to ensure that CHIS deployment in LDCs is sustainable, it is proposed that the activities involved in the implementation of these systems be incorporated into organizational routines. This will ensure and secure the needed resources as well as the relevant support from all stakeholders of the system; on a continuous basis. This paper sets out to look at the issue of CHIS sustainability in LDCs, theoretically explains the factors that account for the sustainability problem and develops a conceptual model based on theoretical literature and existing empirical findings.

Validation Methods for Fault-Tolerant avionics and control systems, working group meeting 1

NASA Technical Reports Server (NTRS)

1979-01-01

The proceedings of the first working group meeting on validation methods for fault tolerant computer design are presented. The state of the art in fault tolerant computer validation was examined in order to provide a framework for future discussions concerning research issues for the validation of fault tolerant avionics and flight control systems. The development of positions concerning critical aspects of the validation process are given.

The diffusive finite state projection algorithm for efficient simulation of the stochastic reaction-diffusion master equation.

PubMed

Drawert, Brian; Lawson, Michael J; Petzold, Linda; Khammash, Mustafa

2010-02-21

We have developed a computational framework for accurate and efficient simulation of stochastic spatially inhomogeneous biochemical systems. The new computational method employs a fractional step hybrid strategy. A novel formulation of the finite state projection (FSP) method, called the diffusive FSP method, is introduced for the efficient and accurate simulation of diffusive transport. Reactions are handled by the stochastic simulation algorithm.

1:1 Computing Programs: An Analysis of the Stages of Concerns of 1:1 Integration, Professional Development Training and Level of Classroom Use by Illinois High School Teachers

ERIC Educational Resources Information Center

Detering, Brad

2017-01-01

This research study, grounded in the theoretical framework of education change, used the Concerns-Based Adoption Model of change to examine the concerns of Illinois high school teachers and administrators regarding the implementation of 1:1 computing programs. A quantitative study of educators investigated the stages of concern and the mathematics…

Development of Multidisciplinary, Multifidelity Analysis, Integration, and Optimization of Aerospace Vehicles

DTIC Science & Technology

2010-02-27

investigated in more detail. The intermediate level of fidelity, though more expensive, is then used to refine the analysis , add geometric detail, and...design stage is used to further refine the analysis , narrowing the design to a handful of options. Figure 1. Integrated Hierarchical Framework. In...computational structural and computational fluid modeling. For the structural analysis tool we used McIntosh Structural Dynamics’ finite element code CNEVAL

Generative models for clinical applications in computational psychiatry.

PubMed

Frässle, Stefan; Yao, Yu; Schöbi, Dario; Aponte, Eduardo A; Heinzle, Jakob; Stephan, Klaas E

2018-05-01

Despite the success of modern neuroimaging techniques in furthering our understanding of cognitive and pathophysiological processes, translation of these advances into clinically relevant tools has been virtually absent until now. Neuromodeling represents a powerful framework for overcoming this translational deadlock, and the development of computational models to solve clinical problems has become a major scientific goal over the last decade, as reflected by the emergence of clinically oriented neuromodeling fields like Computational Psychiatry, Computational Neurology, and Computational Psychosomatics. Generative models of brain physiology and connectivity in the human brain play a key role in this endeavor, striving for computational assays that can be applied to neuroimaging data from individual patients for differential diagnosis and treatment prediction. In this review, we focus on dynamic causal modeling (DCM) and its use for Computational Psychiatry. DCM is a widely used generative modeling framework for functional magnetic resonance imaging (fMRI) and magneto-/electroencephalography (M/EEG) data. This article reviews the basic concepts of DCM, revisits examples where it has proven valuable for addressing clinically relevant questions, and critically discusses methodological challenges and recent methodological advances. We conclude this review with a more general discussion of the promises and pitfalls of generative models in Computational Psychiatry and highlight the path that lies ahead of us. This article is categorized under: Neuroscience > Computation Neuroscience > Clinical Neuroscience. © 2018 Wiley Periodicals, Inc.

Evolution of the ATLAS distributed computing system during the LHC long shutdown

NASA Astrophysics Data System (ADS)

Campana, S.; Atlas Collaboration

2014-06-01

The ATLAS Distributed Computing project (ADC) was established in 2007 to develop and operate a framework, following the ATLAS computing model, to enable data storage, processing and bookkeeping on top of the Worldwide LHC Computing Grid (WLCG) distributed infrastructure. ADC development has always been driven by operations and this contributed to its success. The system has fulfilled the demanding requirements of ATLAS, daily consolidating worldwide up to 1 PB of data and running more than 1.5 million payloads distributed globally, supporting almost one thousand concurrent distributed analysis users. Comprehensive automation and monitoring minimized the operational manpower required. The flexibility of the system to adjust to operational needs has been important to the success of the ATLAS physics program. The LHC shutdown in 2013-2015 affords an opportunity to improve the system in light of operational experience and scale it to cope with the demanding requirements of 2015 and beyond, most notably a much higher trigger rate and event pileup. We will describe the evolution of the ADC software foreseen during this period. This includes consolidating the existing Production and Distributed Analysis framework (PanDA) and ATLAS Grid Information System (AGIS), together with the development and commissioning of next generation systems for distributed data management (DDM/Rucio) and production (Prodsys-2). We will explain how new technologies such as Cloud Computing and NoSQL databases, which ATLAS investigated as R&D projects in past years, will be integrated in production. Finally, we will describe more fundamental developments such as breaking job-to-data locality by exploiting storage federations and caches, and event level (rather than file or dataset level) workload engines.

Patch forest: a hybrid framework of random forest and patch-based segmentation

NASA Astrophysics Data System (ADS)

Xie, Zhongliu; Gillies, Duncan

2016-03-01

The development of an accurate, robust and fast segmentation algorithm has long been a research focus in medical computer vision. State-of-the-art practices often involve non-rigidly registering a target image with a set of training atlases for label propagation over the target space to perform segmentation, a.k.a. multi-atlas label propagation (MALP). In recent years, the patch-based segmentation (PBS) framework has gained wide attention due to its advantage of relaxing the strict voxel-to-voxel correspondence to a series of pair-wise patch comparisons for contextual pattern matching. Despite a high accuracy reported in many scenarios, computational efficiency has consistently been a major obstacle for both approaches. Inspired by recent work on random forest, in this paper we propose a patch forest approach, which by equipping the conventional PBS with a fast patch search engine, is able to boost segmentation speed significantly while retaining an equal level of accuracy. In addition, a fast forest training mechanism is also proposed, with the use of a dynamic grid framework to efficiently approximate data compactness computation and a 3D integral image technique for fast box feature retrieval.

Probabilistic graphs as a conceptual and computational tool in hydrology and water management

NASA Astrophysics Data System (ADS)

Schoups, Gerrit

2014-05-01

Originally developed in the fields of machine learning and artificial intelligence, probabilistic graphs constitute a general framework for modeling complex systems in the presence of uncertainty. The framework consists of three components: 1. Representation of the model as a graph (or network), with nodes depicting random variables in the model (e.g. parameters, states, etc), which are joined together by factors. Factors are local probabilistic or deterministic relations between subsets of variables, which, when multiplied together, yield the joint distribution over all variables. 2. Consistent use of probability theory for quantifying uncertainty, relying on basic rules of probability for assimilating data into the model and expressing unknown variables as a function of observations (via the posterior distribution). 3. Efficient, distributed approximation of the posterior distribution using general-purpose algorithms that exploit model structure encoded in the graph. These attributes make probabilistic graphs potentially useful as a conceptual and computational tool in hydrology and water management (and beyond). Conceptually, they can provide a common framework for existing and new probabilistic modeling approaches (e.g. by drawing inspiration from other fields of application), while computationally they can make probabilistic inference feasible in larger hydrological models. The presentation explores, via examples, some of these benefits.

Reconstructing constructivism: Causal models, Bayesian learning mechanisms and the theory theory

PubMed Central

Gopnik, Alison; Wellman, Henry M.

2012-01-01

We propose a new version of the “theory theory” grounded in the computational framework of probabilistic causal models and Bayesian learning. Probabilistic models allow a constructivist but rigorous and detailed approach to cognitive development. They also explain the learning of both more specific causal hypotheses and more abstract framework theories. We outline the new theoretical ideas, explain the computational framework in an intuitive and non-technical way, and review an extensive but relatively recent body of empirical results that supports these ideas. These include new studies of the mechanisms of learning. Children infer causal structure from statistical information, through their own actions on the world and through observations of the actions of others. Studies demonstrate these learning mechanisms in children from 16 months to 4 years old and include research on causal statistical learning, informal experimentation through play, and imitation and informal pedagogy. They also include studies of the variability and progressive character of intuitive theory change, particularly theory of mind. These studies investigate both the physical and psychological and social domains. We conclude with suggestions for further collaborative projects between developmental and computational cognitive scientists. PMID:22582739

Fully Associative, Nonisothermal, Potential-Based Unified Viscoplastic Model for Titanium-Based Matrices

NASA Technical Reports Server (NTRS)

2005-01-01

A number of titanium matrix composite (TMC) systems are currently being investigated for high-temperature air frame and propulsion system applications. As a result, numerous computational methodologies for predicting both deformation and life for this class of materials are under development. An integral part of these methodologies is an accurate and computationally efficient constitutive model for the metallic matrix constituent. Furthermore, because these systems are designed to operate at elevated temperatures, the required constitutive models must account for both time-dependent and time-independent deformations. To accomplish this, the NASA Lewis Research Center is employing a recently developed, complete, potential-based framework. This framework, which utilizes internal state variables, was put forth for the derivation of reversible and irreversible constitutive equations. The framework, and consequently the resulting constitutive model, is termed complete because the existence of the total (integrated) form of the Gibbs complementary free energy and complementary dissipation potentials are assumed a priori. The specific forms selected here for both the Gibbs and complementary dissipation potentials result in a fully associative, multiaxial, nonisothermal, unified viscoplastic model with nonlinear kinematic hardening. This model constitutes one of many models in the Generalized Viscoplasticity with Potential Structure (GVIPS) class of inelastic constitutive equations.

All-optical reservoir computer based on saturation of absorption.

PubMed

Dejonckheere, Antoine; Duport, François; Smerieri, Anteo; Fang, Li; Oudar, Jean-Louis; Haelterman, Marc; Massar, Serge

2014-05-05

Reservoir computing is a new bio-inspired computation paradigm. It exploits a dynamical system driven by a time-dependent input to carry out computation. For efficient information processing, only a few parameters of the reservoir needs to be tuned, which makes it a promising framework for hardware implementation. Recently, electronic, opto-electronic and all-optical experimental reservoir computers were reported. In those implementations, the nonlinear response of the reservoir is provided by active devices such as optoelectronic modulators or optical amplifiers. By contrast, we propose here the first reservoir computer based on a fully passive nonlinearity, namely the saturable absorption of a semiconductor mirror. Our experimental setup constitutes an important step towards the development of ultrafast low-consumption analog computers.

Visual programming for next-generation sequencing data analytics.

PubMed

Milicchio, Franco; Rose, Rebecca; Bian, Jiang; Min, Jae; Prosperi, Mattia

2016-01-01

High-throughput or next-generation sequencing (NGS) technologies have become an established and affordable experimental framework in biological and medical sciences for all basic and translational research. Processing and analyzing NGS data is challenging. NGS data are big, heterogeneous, sparse, and error prone. Although a plethora of tools for NGS data analysis has emerged in the past decade, (i) software development is still lagging behind data generation capabilities, and (ii) there is a 'cultural' gap between the end user and the developer. Generic software template libraries specifically developed for NGS can help in dealing with the former problem, whilst coupling template libraries with visual programming may help with the latter. Here we scrutinize the state-of-the-art low-level software libraries implemented specifically for NGS and graphical tools for NGS analytics. An ideal developing environment for NGS should be modular (with a native library interface), scalable in computational methods (i.e. serial, multithread, distributed), transparent (platform-independent), interoperable (with external software interface), and usable (via an intuitive graphical user interface). These characteristics should facilitate both the run of standardized NGS pipelines and the development of new workflows based on technological advancements or users' needs. We discuss in detail the potential of a computational framework blending generic template programming and visual programming that addresses all of the current limitations. In the long term, a proper, well-developed (although not necessarily unique) software framework will bridge the current gap between data generation and hypothesis testing. This will eventually facilitate the development of novel diagnostic tools embedded in routine healthcare.

Early postnatal myelin content estimate of white matter via T1w/T2w ratio

NASA Astrophysics Data System (ADS)

Lee, Kevin; Cherel, Marie; Budin, Francois; Gilmore, John; Zaldarriaga Consing, Kirsten; Rasmussen, Jerod; Wadhwa, Pathik D.; Entringer, Sonja; Glasser, Matthew F.; Van Essen, David C.; Buss, Claudia; Styner, Martin

2015-03-01

To develop and evaluate a novel processing framework for the relative quantification of myelin content in cerebral white matter (WM) regions from brain MRI data via a computed ratio of T1 to T2 weighted intensity values. We employed high resolution (1mm3 isotropic) T1 and T2 weighted MRI from 46 (28 male, 18 female) neonate subjects (typically developing controls) scanned on a Siemens Tim Trio 3T at UC Irvine. We developed a novel, yet relatively straightforward image processing framework for WM myelin content estimation based on earlier work by Glasser, et al. We first co-register the structural MRI data to correct for motion. Then, background areas are masked out via a joint T1w and T2 foreground mask computed. Raw T1w/T2w-ratios images are computed next. For purpose of calibration across subjects, we first coarsely segment the fat-rich facial regions via an atlas co-registration. Linear intensity rescaling based on median T1w/T2w-ratio values in those facial regions yields calibrated T1w/T2wratio images. Mean values in lobar regions are evaluated using standard statistical analysis to investigate their interaction with age at scan. Several lobes have strongly positive significant interactions of age at scan with the computed T1w/T2w-ratio. Most regions do not show sex effects. A few regions show no measurable effects of change in myelin content change within the first few weeks of postnatal development, such as cingulate and CC areas, which we attribute to sample size and measurement variability. We developed and evaluated a novel way to estimate white matter myelin content for use in studies of brain white matter development.

Visualization and Interaction in Research, Teaching, and Scientific Communication

NASA Astrophysics Data System (ADS)

Ammon, C. J.

2017-12-01

Modern computing provides many tools for exploring observations, numerical calculations, and theoretical relationships. The number of options is, in fact, almost overwhelming. But the choices provide those with modest programming skills opportunities to create unique views of scientific information and to develop deeper insights into their data, their computations, and the underlying theoretical data-model relationships. I present simple examples of using animation and human-computer interaction to explore scientific data and scientific-analysis approaches. I illustrate how valuable a little programming ability can free scientists from the constraints of existing tools and can facilitate the development of deeper appreciation data and models. I present examples from a suite of programming languages ranging from C to JavaScript including the Wolfram Language. JavaScript is valuable for sharing tools and insight (hopefully) with others because it is integrated into one of the most powerful communication tools in human history, the web browser. Although too much of that power is often spent on distracting advertisements, the underlying computation and graphics engines are efficient, flexible, and almost universally available in desktop and mobile computing platforms. Many are working to fulfill the browser's potential to become the most effective tool for interactive study. Open-source frameworks for visualizing everything from algorithms to data are available, but advance rapidly. One strategy for dealing with swiftly changing tools is to adopt common, open data formats that are easily adapted (often by framework or tool developers). I illustrate the use of animation and interaction in research and teaching with examples from earthquake seismology.

A framework for optimization and quantification of uncertainty and sensitivity for developing carbon capture systems

DOE PAGES

Eslick, John C.; Ng, Brenda; Gao, Qianwen; ...

2014-12-31

Under the auspices of the U.S. Department of Energy’s Carbon Capture Simulation Initiative (CCSI), a Framework for Optimization and Quantification of Uncertainty and Sensitivity (FOQUS) has been developed. This tool enables carbon capture systems to be rapidly synthesized and rigorously optimized, in an environment that accounts for and propagates uncertainties in parameters and models. FOQUS currently enables (1) the development of surrogate algebraic models utilizing the ALAMO algorithm, which can be used for superstructure optimization to identify optimal process configurations, (2) simulation-based optimization utilizing derivative free optimization (DFO) algorithms with detailed black-box process models, and (3) rigorous uncertainty quantification throughmore » PSUADE. FOQUS utilizes another CCSI technology, the Turbine Science Gateway, to manage the thousands of simulated runs necessary for optimization and UQ. Thus, this computational framework has been demonstrated for the design and analysis of a solid sorbent based carbon capture system.« less

Mississippi Curriculum Framework for Computer Information Systems Technology. Computer Information Systems Technology (Program CIP: 52.1201--Management Information Systems & Business Data). Computer Programming (Program CIP: 52.1201). Network Support (Program CIP: 52.1290--Computer Network Support Technology). Postsecondary Programs.

ERIC Educational Resources Information Center

Mississippi Research and Curriculum Unit for Vocational and Technical Education, State College.

This document, which is intended for use by community and junior colleges throughout Mississippi, contains curriculum frameworks for two programs in the state's postsecondary-level computer information systems technology cluster: computer programming and network support. Presented in the introduction are program descriptions and suggested course…

MCdevelop - a universal framework for Stochastic Simulations

NASA Astrophysics Data System (ADS)

Slawinska, M.; Jadach, S.

2011-03-01

We present MCdevelop, a universal computer framework for developing and exploiting the wide class of Stochastic Simulations (SS) software. This powerful universal SS software development tool has been derived from a series of scientific projects for precision calculations in high energy physics (HEP), which feature a wide range of functionality in the SS software needed for advanced precision Quantum Field Theory calculations for the past LEP experiments and for the ongoing LHC experiments at CERN, Geneva. MCdevelop is a "spin-off" product of HEP to be exploited in other areas, while it will still serve to develop new SS software for HEP experiments. Typically SS involve independent generation of large sets of random "events", often requiring considerable CPU power. Since SS jobs usually do not share memory it makes them easy to parallelize. The efficient development, testing and running in parallel SS software requires a convenient framework to develop software source code, deploy and monitor batch jobs, merge and analyse results from multiple parallel jobs, even before the production runs are terminated. Throughout the years of development of stochastic simulations for HEP, a sophisticated framework featuring all the above mentioned functionality has been implemented. MCdevelop represents its latest version, written mostly in C++ (GNU compiler gcc). It uses Autotools to build binaries (optionally managed within the KDevelop 3.5.3 Integrated Development Environment (IDE)). It uses the open-source ROOT package for histogramming, graphics and the mechanism of persistency for the C++ objects. MCdevelop helps to run multiple parallel jobs on any computer cluster with NQS-type batch system. Program summaryProgram title:MCdevelop Catalogue identifier: AEHW_v1_0 Program summary URL:http://cpc.cs.qub.ac.uk/summaries/AEHW_v1_0.html Program obtainable from: CPC Program Library, Queen's University, Belfast, N. Ireland Licensing provisions: Standard CPC licence, http://cpc.cs.qub.ac.uk/licence/licence.html No. of lines in distributed program, including test data, etc.: 48 136 No. of bytes in distributed program, including test data, etc.: 355 698 Distribution format: tar.gz Programming language: ANSI C++ Computer: Any computer system or cluster with C++ compiler and UNIX-like operating system. Operating system: Most UNIX systems, Linux. The application programs were thoroughly tested under Ubuntu 7.04, 8.04 and CERN Scientific Linux 5. Has the code been vectorised or parallelised?: Tools (scripts) for optional parallelisation on a PC farm are included. RAM: 500 bytes Classification: 11.3 External routines: ROOT package version 5.0 or higher ( http://root.cern.ch/drupal/). Nature of problem: Developing any type of stochastic simulation program for high energy physics and other areas. Solution method: Object Oriented programming in C++ with added persistency mechanism, batch scripts for running on PC farms and Autotools.

Accelerating Adverse Outcome Pathway (AOP) development via computationally predicted AOP networks

EPA Science Inventory

The Adverse Outcome Pathway (AOP) framework is increasingly being adopted as a tool for organizing and summarizing the mechanistic information connecting molecular perturbations by environmental stressors with adverse outcomes relevant for ecological and human health outcomes. Ho...

Fundamentals and Recent Developments in Approximate Bayesian Computation

PubMed Central

Lintusaari, Jarno; Gutmann, Michael U.; Dutta, Ritabrata; Kaski, Samuel; Corander, Jukka

2017-01-01

Abstract Bayesian inference plays an important role in phylogenetics, evolutionary biology, and in many other branches of science. It provides a principled framework for dealing with uncertainty and quantifying how it changes in the light of new evidence. For many complex models and inference problems, however, only approximate quantitative answers are obtainable. Approximate Bayesian computation (ABC) refers to a family of algorithms for approximate inference that makes a minimal set of assumptions by only requiring that sampling from a model is possible. We explain here the fundamentals of ABC, review the classical algorithms, and highlight recent developments. [ABC; approximate Bayesian computation; Bayesian inference; likelihood-free inference; phylogenetics; simulator-based models; stochastic simulation models; tree-based models.] PMID:28175922

Environments for online maritime simulators with cloud computing capabilities

NASA Astrophysics Data System (ADS)

Raicu, Gabriel; Raicu, Alexandra

2016-12-01

This paper presents the cloud computing environments, network principles and methods for graphical development in realistic naval simulation, naval robotics and virtual interactions. The aim of this approach is to achieve a good simulation quality in large networked environments using open source solutions designed for educational purposes. Realistic rendering of maritime environments requires near real-time frameworks with enhanced computing capabilities during distance interactions. E-Navigation concepts coupled with the last achievements in virtual and augmented reality will enhance the overall experience leading to new developments and innovations. We have to deal with a multiprocessing situation using advanced technologies and distributed applications using remote ship scenario and automation of ship operations.

Designing Computer Learning Environments for Engineering and Computer Science: The Scaffolded Knowledge Integration Framework.

ERIC Educational Resources Information Center

Linn, Marcia C.

1995-01-01

Describes a framework called scaffolded knowledge integration and illustrates how it guided the design of two successful course enhancements in the field of computer science and engineering: the LISP Knowledge Integration Environment and the spatial reasoning environment. (101 references) (Author/MKR)

A Framework for Enterprise Operating Systems Based on Zachman Framework

NASA Astrophysics Data System (ADS)

Ostadzadeh, S. Shervin; Rahmani, Amir Masoud

Nowadays, the Operating System (OS) isn't only the software that runs your computer. In the typical information-driven organization, the operating system is part of a much larger platform for applications and data that extends across the LAN, WAN and Internet. An OS cannot be an island unto itself; it must work with the rest of the enterprise. Enterprise wide applications require an Enterprise Operating System (EOS). Enterprise operating systems used in an enterprise have brought about an inevitable tendency to lunge towards organizing their information activities in a comprehensive way. In this respect, Enterprise Architecture (EA) has proven to be the leading option for development and maintenance of enterprise operating systems. EA clearly provides a thorough outline of the whole information system comprising an enterprise. To establish such an outline, a logical framework needs to be laid upon the entire information system. Zachman Framework (ZF) has been widely accepted as a standard scheme for identifying and organizing descriptive representations that have prominent roles in enterprise-wide system development. In this paper, we propose a framework based on ZF for enterprise operating systems. The presented framework helps developers to design and justify completely integrated business, IT systems, and operating systems which results in improved project success rate.

A geostatistical extreme-value framework for fast simulation of natural hazard events

PubMed Central

Stephenson, David B.

2016-01-01

We develop a statistical framework for simulating natural hazard events that combines extreme value theory and geostatistics. Robust generalized additive model forms represent generalized Pareto marginal distribution parameters while a Student’s t-process captures spatial dependence and gives a continuous-space framework for natural hazard event simulations. Efficiency of the simulation method allows many years of data (typically over 10 000) to be obtained at relatively little computational cost. This makes the model viable for forming the hazard module of a catastrophe model. We illustrate the framework by simulating maximum wind gusts for European windstorms, which are found to have realistic marginal and spatial properties, and validate well against wind gust measurements. PMID:27279768

Predictive framework for shape-selective separations in three-dimensional zeolites and metal-organic frameworks.

PubMed

First, Eric L; Gounaris, Chrysanthos E; Floudas, Christodoulos A

2013-05-07

With the growing number of zeolites and metal-organic frameworks (MOFs) available, computational methods are needed to screen databases of structures to identify those most suitable for applications of interest. We have developed novel methods based on mathematical optimization to predict the shape selectivity of zeolites and MOFs in three dimensions by considering the energy costs of transport through possible pathways. Our approach is applied to databases of over 1800 microporous materials including zeolites, MOFs, zeolitic imidazolate frameworks, and hypothetical MOFs. New materials are identified for applications in gas separations (CO2/N2, CO2/CH4, and CO2/H2), air separation (O2/N2), and chemicals (propane/propylene, ethane/ethylene, styrene/ethylbenzene, and xylenes).

PARTONS: PARtonic Tomography Of Nucleon Software. A computing framework for the phenomenology of Generalized Parton Distributions

NASA Astrophysics Data System (ADS)

Berthou, B.; Binosi, D.; Chouika, N.; Colaneri, L.; Guidal, M.; Mezrag, C.; Moutarde, H.; Rodríguez-Quintero, J.; Sabatié, F.; Sznajder, P.; Wagner, J.

2018-06-01

We describe the architecture and functionalities of a C++ software framework, coined PARTONS, dedicated to the phenomenology of Generalized Parton Distributions. These distributions describe the three-dimensional structure of hadrons in terms of quarks and gluons, and can be accessed in deeply exclusive lepto- or photo-production of mesons or photons. PARTONS provides a necessary bridge between models of Generalized Parton Distributions and experimental data collected in various exclusive production channels. We outline the specification of the PARTONS framework in terms of practical needs, physical content and numerical capacity. This framework will be useful for physicists - theorists or experimentalists - not only to develop new models, but also to interpret existing measurements and even design new experiments.

Uses of the Drupal CMS Collaborative Framework in the Woods Hole Scientific Community (Invited)

NASA Astrophysics Data System (ADS)

Maffei, A. R.; Chandler, C. L.; Work, T. T.; Shorthouse, D.; Furfey, J.; Miller, H.

2010-12-01

Organizations that comprise the Woods Hole scientific community (Woods Hole Oceanographic Institution, Marine Biological Laboratory, USGS Woods Hole Coastal and Marine Science Center, Woods Hole Research Center, NOAA NMFS Northeast Fisheries Science Center, SEA Education Association) have a long history of collaborative activity regarding computing, computer network and information technologies that support common, inter-disciplinary science needs. Over the past several years there has been growing interest in the use of the Drupal Content Management System (CMS) playing a variety of roles in support of research projects resident at several of these organizations. Many of these projects are part of science programs that are national and international in scope. Here we survey the current uses of Drupal within the Woods Hole scientific community and examine reasons it has been adopted. The promise of emerging semantic features in the Drupal framework is examined and projections of how pre-existing Drupal-based websites might benefit are made. Closer examination of Drupal software design exposes it as more than simply a content management system. The flexibility of its architecture; the power of its taxonomy module; the care taken in nurturing the open-source developer community that surrounds it (including organized and often well-attended code sprints); the ability to bind emerging software technologies as Drupal modules; the careful selection process used in adopting core functionality; multi-site hosting and cross-site deployment of updates and a recent trend towards development of use-case inspired Drupal distributions casts Drupal as a general-purpose application deployment framework. Recent work in the semantic arena casts Drupal as an emerging RDF framework as well. Examples of roles played by Drupal-based websites within the Woods Hole scientific community that will be discussed include: science data metadata database, organization main website, biological taxonomy development, bibliographic database, physical media data archive inventory manager, disaster-response website development framework, science project task management, science conference planning, and spreadsheet-to-database converter.

Faster than Real-Time Dynamic Simulation for Large-Size Power System with Detailed Dynamic Models using High-Performance Computing Platform

DOE Office of Scientific and Technical Information (OSTI.GOV)

Huang, Renke; Jin, Shuangshuang; Chen, Yousu

This paper presents a faster-than-real-time dynamic simulation software package that is designed for large-size power system dynamic simulation. It was developed on the GridPACKTM high-performance computing (HPC) framework. The key features of the developed software package include (1) faster-than-real-time dynamic simulation for a WECC system (17,000 buses) with different types of detailed generator, controller, and relay dynamic models, (2) a decoupled parallel dynamic simulation algorithm with optimized computation architecture to better leverage HPC resources and technologies, (3) options for HPC-based linear and iterative solvers, (4) hidden HPC details, such as data communication and distribution, to enable development centered on mathematicalmore » models and algorithms rather than on computational details for power system researchers, and (5) easy integration of new dynamic models and related algorithms into the software package.« less

Computational Foundations of Natural Intelligence

PubMed Central

van Gerven, Marcel

2017-01-01

New developments in AI and neuroscience are revitalizing the quest to understanding natural intelligence, offering insight about how to equip machines with human-like capabilities. This paper reviews some of the computational principles relevant for understanding natural intelligence and, ultimately, achieving strong AI. After reviewing basic principles, a variety of computational modeling approaches is discussed. Subsequently, I concentrate on the use of artificial neural networks as a framework for modeling cognitive processes. This paper ends by outlining some of the challenges that remain to fulfill the promise of machines that show human-like intelligence. PMID:29375355

Commentary on: "Toward Computer-Based Support of Metacognitive Skills: A Computational Framework to Coach Self Explanation"

ERIC Educational Resources Information Center

Conati, Cristina

2016-01-01

This paper is a commentary on "Toward Computer-Based Support of Meta-Cognitive Skills: a Computational Framework to Coach Self-Explanation", by Cristina Conati and Kurt Vanlehn, published in the "IJAED" in 2000 (Conati and VanLehn 2010). This work was one of the first examples of Intelligent Learning Environments (ILE) that…

ICADx: interpretable computer aided diagnosis of breast masses

NASA Astrophysics Data System (ADS)

Kim, Seong Tae; Lee, Hakmin; Kim, Hak Gu; Ro, Yong Man

2018-02-01

In this study, a novel computer aided diagnosis (CADx) framework is devised to investigate interpretability for classifying breast masses. Recently, a deep learning technology has been successfully applied to medical image analysis including CADx. Existing deep learning based CADx approaches, however, have a limitation in explaining the diagnostic decision. In real clinical practice, clinical decisions could be made with reasonable explanation. So current deep learning approaches in CADx are limited in real world deployment. In this paper, we investigate interpretability in CADx with the proposed interpretable CADx (ICADx) framework. The proposed framework is devised with a generative adversarial network, which consists of interpretable diagnosis network and synthetic lesion generative network to learn the relationship between malignancy and a standardized description (BI-RADS). The lesion generative network and the interpretable diagnosis network compete in an adversarial learning so that the two networks are improved. The effectiveness of the proposed method was validated on public mammogram database. Experimental results showed that the proposed ICADx framework could provide the interpretability of mass as well as mass classification. It was mainly attributed to the fact that the proposed method was effectively trained to find the relationship between malignancy and interpretations via the adversarial learning. These results imply that the proposed ICADx framework could be a promising approach to develop the CADx system.

Planning in context: A situated view of children's management of science projects

NASA Astrophysics Data System (ADS)

Marshall, Susan Katharine

This study investigated children's collaborative planning of a complex, long-term software design project. Using sociocultural methods, it examined over time the development of design teams' planning negotiations and tools to document the coconstruction of cultural frameworks to organize teams' shared understanding of what and how to plan. Results indicated that student teams developed frameworks to address a set of common planning functions that included design planning, project metaplanning (things such as division of labor or sharing of computer resources) and team collaboration management planning. There were also some between-team variations in planning frameworks, within a bandwidth of options. Teams engaged in opportunistic planning, which reflected shifts in strategies in response to new circumstances over time. Team members with past design project experience ("oldtimers") demonstrated the transfer of their planning framework to the current design task, and they supported the developing participation of "newcomers." Teams constructed physical tools (e.g. planning boards) that acted as visual representations of teams' planning frameworks, and inscriptions of team thinking. The assigned functions of the tools also shifted over time with changing project circumstances. The discussion reexamines current approaches to the study of planning and discusses their educational implications.

Knowledge-transfer learning for prediction of matrix metalloprotease substrate-cleavage sites.

PubMed

Wang, Yanan; Song, Jiangning; Marquez-Lago, Tatiana T; Leier, André; Li, Chen; Lithgow, Trevor; Webb, Geoffrey I; Shen, Hong-Bin

2017-07-18

Matrix Metalloproteases (MMPs) are an important family of proteases that play crucial roles in key cellular and disease processes. Therefore, MMPs constitute important targets for drug design, development and delivery. Advanced proteomic technologies have identified type-specific target substrates; however, the complete repertoire of MMP substrates remains uncharacterized. Indeed, computational prediction of substrate-cleavage sites associated with MMPs is a challenging problem. This holds especially true when considering MMPs with few experimentally verified cleavage sites, such as for MMP-2, -3, -7, and -8. To fill this gap, we propose a new knowledge-transfer computational framework which effectively utilizes the hidden shared knowledge from some MMP types to enhance predictions of other, distinct target substrate-cleavage sites. Our computational framework uses support vector machines combined with transfer machine learning and feature selection. To demonstrate the value of the model, we extracted a variety of substrate sequence-derived features and compared the performance of our method using both 5-fold cross-validation and independent tests. The results show that our transfer-learning-based method provides a robust performance, which is at least comparable to traditional feature-selection methods for prediction of MMP-2, -3, -7, -8, -9 and -12 substrate-cleavage sites on independent tests. The results also demonstrate that our proposed computational framework provides a useful alternative for the characterization of sequence-level determinants of MMP-substrate specificity.

Towards a Theory-Based Design Framework for an Effective E-Learning Computer Programming Course

ERIC Educational Resources Information Center

McGowan, Ian S.

2016-01-01

Built on Dabbagh (2005), this paper presents a four component theory-based design framework for an e-learning session in introductory computer programming. The framework, driven by a body of exemplars component, emphasizes the transformative interaction between the knowledge building community (KBC) pedagogical model, a mixed instructional…

A Framework for the Evaluation of CASE Tool Learnability in Educational Environments

ERIC Educational Resources Information Center

Senapathi, Mali

2005-01-01

The aim of the research is to derive a framework for the evaluation of Computer Aided Software Engineering (CASE) tool learnability in educational environments. Drawing from the literature of Human Computer Interaction and educational research, a framework for evaluating CASE tool learnability in educational environments is derived. The two main…

Comparative Evaluation of a Four-Implant-Supported Polyetherketoneketone Framework Prosthesis: A Three-Dimensional Finite Element Analysis Based on Cone Beam Computed Tomography and Computer-Aided Design.

PubMed

Lee, Ki-Sun; Shin, Sang-Wan; Lee, Sang-Pyo; Kim, Jong-Eun; Kim, Jee-Hwan; Lee, Jeong-Yol

The purpose of this pilot study was to evaluate and compare polyetherketoneketone (PEKK) with different framework materials for implant-supported prostheses by means of a three-dimensional finite element analysis (3D-FEA) based on cone beam computed tomography (CBCT) and computer-aided design (CAD) data. A geometric model that consisted of four maxillary implants supporting a prosthesis framework was constructed from CBCT and CAD data of a treated patient. Three different materials (zirconia, titanium, and PEKK) were selected, and their material properties were simulated using FEA software in the generated geometric model. In the PEKK framework (ie, low elastic modulus) group, the stress transferred to the implant and simulated adjacent tissue was reduced when compressive stress was dominant, but increased when tensile stress was dominant. This study suggests that the shock-absorbing effects of a resilient implant-supported framework are limited in some areas and that rigid framework material shows a favorable stress distribution and safety of overall components of the prosthesis.

A novel approach for estimating ingested dose associated with paracetamol overdose

PubMed Central

Zurlinden, Todd J.; Heard, Kennon

2015-01-01

Aim In cases of paracetamol (acetaminophen, APAP) overdose, an accurate estimate of tissue‐specific paracetamol pharmacokinetics (PK) and ingested dose can offer health care providers important information for the individualized treatment and follow‐up of affected patients. Here a novel methodology is presented to make such estimates using a standard serum paracetamol measurement and a computational framework. Methods The core component of the computational framework was a physiologically‐based pharmacokinetic (PBPK) model developed and evaluated using an extensive set of human PK data. Bayesian inference was used for parameter and dose estimation, allowing the incorporation of inter‐study variability, and facilitating the calculation of uncertainty in model outputs. Results Simulations of paracetamol time course concentrations in the blood were in close agreement with experimental data under a wide range of dosing conditions. Also, predictions of administered dose showed good agreement with a large collection of clinical and emergency setting PK data over a broad dose range. In addition to dose estimation, the platform was applied for the determination of optimal blood sampling times for dose reconstruction and quantitation of the potential role of paracetamol conjugate measurement on dose estimation. Conclusions Current therapies for paracetamol overdose rely on a generic methodology involving the use of a clinical nomogram. By using the computational framework developed in this study, serum sample data, and the individual patient's anthropometric and physiological information, personalized serum and liver pharmacokinetic profiles and dose estimate could be generated to help inform an individualized overdose treatment and follow‐up plan. PMID:26441245

A novel approach for estimating ingested dose associated with paracetamol overdose.

PubMed

Zurlinden, Todd J; Heard, Kennon; Reisfeld, Brad

2016-04-01

In cases of paracetamol (acetaminophen, APAP) overdose, an accurate estimate of tissue-specific paracetamol pharmacokinetics (PK) and ingested dose can offer health care providers important information for the individualized treatment and follow-up of affected patients. Here a novel methodology is presented to make such estimates using a standard serum paracetamol measurement and a computational framework. The core component of the computational framework was a physiologically-based pharmacokinetic (PBPK) model developed and evaluated using an extensive set of human PK data. Bayesian inference was used for parameter and dose estimation, allowing the incorporation of inter-study variability, and facilitating the calculation of uncertainty in model outputs. Simulations of paracetamol time course concentrations in the blood were in close agreement with experimental data under a wide range of dosing conditions. Also, predictions of administered dose showed good agreement with a large collection of clinical and emergency setting PK data over a broad dose range. In addition to dose estimation, the platform was applied for the determination of optimal blood sampling times for dose reconstruction and quantitation of the potential role of paracetamol conjugate measurement on dose estimation. Current therapies for paracetamol overdose rely on a generic methodology involving the use of a clinical nomogram. By using the computational framework developed in this study, serum sample data, and the individual patient's anthropometric and physiological information, personalized serum and liver pharmacokinetic profiles and dose estimate could be generated to help inform an individualized overdose treatment and follow-up plan. © 2015 The British Pharmacological Society.

Implementing Scientific Simulation Codes Highly Tailored for Vector Architectures Using Custom Configurable Computing Machines

NASA Technical Reports Server (NTRS)

Rutishauser, David

2006-01-01

The motivation for this work comes from an observation that amidst the push for Massively Parallel (MP) solutions to high-end computing problems such as numerical physical simulations, large amounts of legacy code exist that are highly optimized for vector supercomputers. Because re-hosting legacy code often requires a complete re-write of the original code, which can be a very long and expensive effort, this work examines the potential to exploit reconfigurable computing machines in place of a vector supercomputer to implement an essentially unmodified legacy source code. Custom and reconfigurable computing resources could be used to emulate an original application's target platform to the extent required to achieve high performance. To arrive at an architecture that delivers the desired performance subject to limited resources involves solving a multi-variable optimization problem with constraints. Prior research in the area of reconfigurable computing has demonstrated that designing an optimum hardware implementation of a given application under hardware resource constraints is an NP-complete problem. The premise of the approach is that the general issue of applying reconfigurable computing resources to the implementation of an application, maximizing the performance of the computation subject to physical resource constraints, can be made a tractable problem by assuming a computational paradigm, such as vector processing. This research contributes a formulation of the problem and a methodology to design a reconfigurable vector processing implementation of a given application that satisfies a performance metric. A generic, parametric, architectural framework for vector processing implemented in reconfigurable logic is developed as a target for a scheduling/mapping algorithm that maps an input computation to a given instance of the architecture. This algorithm is integrated with an optimization framework to arrive at a specification of the architecture parameters that attempts to minimize execution time, while staying within resource constraints. The flexibility of using a custom reconfigurable implementation is exploited in a unique manner to leverage the lessons learned in vector supercomputer development. The vector processing framework is tailored to the application, with variable parameters that are fixed in traditional vector processing. Benchmark data that demonstrates the functionality and utility of the approach is presented. The benchmark data includes an identified bottleneck in a real case study example vector code, the NASA Langley Terminal Area Simulation System (TASS) application.

Fracture behavior of metal-ceramic fixed dental prostheses with frameworks from cast or a newly developed sintered cobalt-chromium alloy.

PubMed

Krug, Klaus-Peter; Knauber, Andreas W; Nothdurft, Frank P

2015-03-01

The aim of this study was to investigate the fracture behavior of metal-ceramic bridges with frameworks from cobalt-chromium-molybdenum (CoCrMo), which are manufactured using conventional casting or a new computer-aided design/computer-aided manufacturing (CAD/CAM) milling and sintering technique. A total of 32 metal-ceramic fixed dental prostheses (FDPs), which are based on a nonprecious metal framework, was produced using a conventional casting process (n = 16) or a new CAD/CAM milling and sintering process (n = 16). Eight unveneered frameworks were manufactured using each of the techniques. After thermal and mechanical aging of half of the restorations, all samples were subjected to a static loading test in a universal testing machine, in which acoustic emission monitoring was performed. Three different critical forces were revealed: the fracture force (F max), the force at the first reduction in force (F decr1), and the force at the critical acoustic event (F acoust1). With the exception of the veneered restorations with cast or sintered metal frameworks without artificial aging, which presented a statistically significant but slightly different F max, no statistically significant differences between cast and CAD/CAM sintered and milled FDPs were detected. Thermal and mechanical loading did not significantly affect the resulting forces. Cast and CAD/CAM milled and sintered metal-ceramic bridges were determined to be comparable with respect to the fracture behavior. FDPs based on CAD/CAM milled and sintered frameworks may be an applicable and less technique-sensitive alternative to frameworks that are based on conventionally cast frameworks.

Designing a parallel evolutionary algorithm for inferring gene networks on the cloud computing environment.

PubMed

Lee, Wei-Po; Hsiao, Yu-Ting; Hwang, Wei-Che

2014-01-16

To improve the tedious task of reconstructing gene networks through testing experimentally the possible interactions between genes, it becomes a trend to adopt the automated reverse engineering procedure instead. Some evolutionary algorithms have been suggested for deriving network parameters. However, to infer large networks by the evolutionary algorithm, it is necessary to address two important issues: premature convergence and high computational cost. To tackle the former problem and to enhance the performance of traditional evolutionary algorithms, it is advisable to use parallel model evolutionary algorithms. To overcome the latter and to speed up the computation, it is advocated to adopt the mechanism of cloud computing as a promising solution: most popular is the method of MapReduce programming model, a fault-tolerant framework to implement parallel algorithms for inferring large gene networks. This work presents a practical framework to infer large gene networks, by developing and parallelizing a hybrid GA-PSO optimization method. Our parallel method is extended to work with the Hadoop MapReduce programming model and is executed in different cloud computing environments. To evaluate the proposed approach, we use a well-known open-source software GeneNetWeaver to create several yeast S. cerevisiae sub-networks and use them to produce gene profiles. Experiments have been conducted and the results have been analyzed. They show that our parallel approach can be successfully used to infer networks with desired behaviors and the computation time can be largely reduced. Parallel population-based algorithms can effectively determine network parameters and they perform better than the widely-used sequential algorithms in gene network inference. These parallel algorithms can be distributed to the cloud computing environment to speed up the computation. By coupling the parallel model population-based optimization method and the parallel computational framework, high quality solutions can be obtained within relatively short time. This integrated approach is a promising way for inferring large networks.

Designing a parallel evolutionary algorithm for inferring gene networks on the cloud computing environment

PubMed Central

2014-01-01

Background To improve the tedious task of reconstructing gene networks through testing experimentally the possible interactions between genes, it becomes a trend to adopt the automated reverse engineering procedure instead. Some evolutionary algorithms have been suggested for deriving network parameters. However, to infer large networks by the evolutionary algorithm, it is necessary to address two important issues: premature convergence and high computational cost. To tackle the former problem and to enhance the performance of traditional evolutionary algorithms, it is advisable to use parallel model evolutionary algorithms. To overcome the latter and to speed up the computation, it is advocated to adopt the mechanism of cloud computing as a promising solution: most popular is the method of MapReduce programming model, a fault-tolerant framework to implement parallel algorithms for inferring large gene networks. Results This work presents a practical framework to infer large gene networks, by developing and parallelizing a hybrid GA-PSO optimization method. Our parallel method is extended to work with the Hadoop MapReduce programming model and is executed in different cloud computing environments. To evaluate the proposed approach, we use a well-known open-source software GeneNetWeaver to create several yeast S. cerevisiae sub-networks and use them to produce gene profiles. Experiments have been conducted and the results have been analyzed. They show that our parallel approach can be successfully used to infer networks with desired behaviors and the computation time can be largely reduced. Conclusions Parallel population-based algorithms can effectively determine network parameters and they perform better than the widely-used sequential algorithms in gene network inference. These parallel algorithms can be distributed to the cloud computing environment to speed up the computation. By coupling the parallel model population-based optimization method and the parallel computational framework, high quality solutions can be obtained within relatively short time. This integrated approach is a promising way for inferring large networks. PMID:24428926

Numerical investigation of interactions between marine atmospheric boundary layer and offshore wind farm

NASA Astrophysics Data System (ADS)

Lyu, Pin; Chen, Wenli; Li, Hui; Shen, Lian

2017-11-01

In recent studies, Yang, Meneveau & Shen (Physics of Fluids, 2014; Renewable Energy, 2014) developed a hybrid numerical framework for simulation of offshore wind farm. The framework consists of simulation of nonlinear surface waves using a high-order spectral method, large-eddy simulation of wind turbulence on a wave-surface-fitted curvilinear grid, and an actuator disk model for wind turbines. In the present study, several more precise wind turbine models, including the actuator line model, actuator disk model with rotation, and nacelle model, are introduced into the computation. Besides offshore wind turbines on fixed piles, the new computational framework has the capability to investigate the interaction among wind, waves, and floating wind turbines. In this study, onshore, offshore fixed pile, and offshore floating wind farms are compared in terms of flow field statistics and wind turbine power extraction rate. The authors gratefully acknowledge financial support from China Scholarship Council (No. 201606120186) and the Institute on the Environment of University of Minnesota.

Java Tool Framework for Automation of Hardware Commissioning and Maintenance Procedures

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ho, J C; Fisher, J M; Gordon, J B

2007-10-02

The National Ignition Facility (NIF) is a 192-beam laser system designed to study high energy density physics. Each beam line contains a variety of line replaceable units (LRUs) that contain optics, stepping motors, sensors and other devices to control and diagnose the laser. During commissioning and subsequent maintenance of the laser, LRUs undergo a qualification process using the Integrated Computer Control System (ICCS) to verify and calibrate the equipment. The commissioning processes are both repetitive and tedious when we use remote manual computer controls, making them ideal candidates for software automation. Maintenance and Commissioning Tool (MCT) software was developed tomore » improve the efficiency of the qualification process. The tools are implemented in Java, leveraging ICCS services and CORBA to communicate with the control devices. The framework provides easy-to-use mechanisms for handling configuration data, task execution, task progress reporting, and generation of commissioning test reports. The tool framework design and application examples will be discussed.« less

On the Use of CAD and Cartesian Methods for Aerodynamic Optimization

NASA Technical Reports Server (NTRS)

Nemec, M.; Aftosmis, M. J.; Pulliam, T. H.

2004-01-01

The objective for this paper is to present the development of an optimization capability for Curt3D, a Cartesian inviscid-flow analysis package. We present the construction of a new optimization framework and we focus on the following issues: 1) Component-based geometry parameterization approach using parametric-CAD models and CAPRI. A novel geometry server is introduced that addresses the issue of parallel efficiency while only sparingly consuming CAD resources; 2) The use of genetic and gradient-based algorithms for three-dimensional aerodynamic design problems. The influence of noise on the optimization methods is studied. Our goal is to create a responsive and automated framework that efficiently identifies design modifications that result in substantial performance improvements. In addition, we examine the architectural issues associated with the deployment of a CAD-based approach in a heterogeneous parallel computing environment that contains both CAD workstations and dedicated compute engines. We demonstrate the effectiveness of the framework for a design problem that features topology changes and complex geometry.

An IoT-Based Computational Framework for Healthcare Monitoring in Mobile Environments.

PubMed

Mora, Higinio; Gil, David; Terol, Rafael Muñoz; Azorín, Jorge; Szymanski, Julian

2017-10-10

The new Internet of Things paradigm allows for small devices with sensing, processing and communication capabilities to be designed, which enable the development of sensors, embedded devices and other 'things' ready to understand the environment. In this paper, a distributed framework based on the internet of things paradigm is proposed for monitoring human biomedical signals in activities involving physical exertion. The main advantages and novelties of the proposed system is the flexibility in computing the health application by using resources from available devices inside the body area network of the user. This proposed framework can be applied to other mobile environments, especially those where intensive data acquisition and high processing needs take place. Finally, we present a case study in order to validate our proposal that consists in monitoring footballers' heart rates during a football match. The real-time data acquired by these devices presents a clear social objective of being able to predict not only situations of sudden death but also possible injuries.

A new line-of-sight approach to the non-linear Cosmic Microwave Background

DOE Office of Scientific and Technical Information (OSTI.GOV)

Fidler, Christian; Koyama, Kazuya; Pettinari, Guido W., E-mail: christian.fidler@port.ac.uk, E-mail: kazuya.koyama@port.ac.uk, E-mail: guido.pettinari@gmail.com

2015-04-01

We develop the transport operator formalism, a new line-of-sight integration framework to calculate the anisotropies of the Cosmic Microwave Background (CMB) at the linear and non-linear level. This formalism utilises a transformation operator that removes all inhomogeneous propagation effects acting on the photon distribution function, thus achieving a split between perturbative collisional effects at recombination and non-perturbative line-of-sight effects at later times. The former can be computed in the framework of standard cosmological perturbation theory with a second-order Boltzmann code such as SONG, while the latter can be treated within a separate perturbative scheme allowing the use of non-linear Newtonianmore » potentials. We thus provide a consistent framework to compute all physical effects contained in the Boltzmann equation and to combine the standard remapping approach with Boltzmann codes at any order in perturbation theory, without assuming that all sources are localised at recombination.« less

An IoT-Based Computational Framework for Healthcare Monitoring in Mobile Environments

PubMed Central

Szymanski, Julian

2017-01-01

The new Internet of Things paradigm allows for small devices with sensing, processing and communication capabilities to be designed, which enable the development of sensors, embedded devices and other ‘things’ ready to understand the environment. In this paper, a distributed framework based on the internet of things paradigm is proposed for monitoring human biomedical signals in activities involving physical exertion. The main advantages and novelties of the proposed system is the flexibility in computing the health application by using resources from available devices inside the body area network of the user. This proposed framework can be applied to other mobile environments, especially those where intensive data acquisition and high processing needs take place. Finally, we present a case study in order to validate our proposal that consists in monitoring footballers’ heart rates during a football match. The real-time data acquired by these devices presents a clear social objective of being able to predict not only situations of sudden death but also possible injuries. PMID:28994743

NHDPlusHR: A national geospatial framework for surface-water information

USGS Publications Warehouse

Viger, Roland; Rea, Alan H.; Simley, Jeffrey D.; Hanson, Karen M.

2016-01-01

The U.S. Geological Survey is developing a new geospatial hydrographic framework for the United States, called the National Hydrography Dataset Plus High Resolution (NHDPlusHR), that integrates a diversity of the best-available information, robustly supports ongoing dataset improvements, enables hydrographic generalization to derive alternate representations of the network while maintaining feature identity, and supports modern scientific computing and Internet accessibility needs. This framework is based on the High Resolution National Hydrography Dataset, the Watershed Boundaries Dataset, and elevation from the 3-D Elevation Program, and will provide an authoritative, high precision, and attribute-rich geospatial framework for surface-water information for the United States. Using this common geospatial framework will provide a consistent basis for indexing water information in the United States, eliminate redundancy, and harmonize access to, and exchange of water information.

DEVELOPMENT OF A CHEMICAL PROCESS MODELING ENVIRONMENT BASED ON CAPE-OPEN INTERFACE STANDARDS AND THE MICROSOFT .NET FRAMEWORK

EPA Science Inventory

Chemical process simulation has long been used as a design tool in the development of chemical plants, and has long been considered a means to evaluate different design options. With the advent of large scale computer networks and interface models for program components, it is po...

Applications of General Systems Theory to the Development of an Adjustable Tutorial Software Machine.

ERIC Educational Resources Information Center

Vos, Hans J.

1994-01-01

Describes the construction of a model of computer-assisted instruction using a qualitative block diagram based on general systems theory (GST) as a framework. Subject matter representation is discussed, and appendices include system variables and system equations of the GST model, as well as an example of developing flexible courseware. (Contains…

Improvement of DHRA-DMDC Physical Access Software DBIDS Using Cloud Computing Technology: A Case Study

DTIC Science & Technology

2012-06-01

technology originally developed on the Java platform. The Hibernate framework supports rapid development of a data access layer without requiring a...31 viii 2. Hibernate ................................................................................ 31 3. Database Design...protect from security threats; o Easy aggregate management operations via file tags; 2. Hibernate We recommend using Hibernate technology for object

Modeling potential movements of the emerald ash borer: the model framework

Treesearch

Louis R. Iverson; Anantha Prasad; Jonathan Bossenbroek; Davis Sydnor; Mark W. Schwartz

2010-01-01

The emerald ash borer (EAB, Agrilus planipennis Fairmaire) is threatening to decimate native ashes (Fraxinus spp.) across North America and, so far, has devastated ash populations across sections of Michigan, Ohio, Indiana, and Ontario. We are attempting to develop a computer model that will predict EAB future movement by adapting a model developed...

A Hybrid Optimization Framework with POD-based Order Reduction and Design-Space Evolution Scheme

NASA Astrophysics Data System (ADS)

Ghoman, Satyajit S.

The main objective of this research is to develop an innovative multi-fidelity multi-disciplinary design, analysis and optimization suite that integrates certain solution generation codes and newly developed innovative tools to improve the overall optimization process. The research performed herein is divided into two parts: (1) the development of an MDAO framework by integration of variable fidelity physics-based computational codes, and (2) enhancements to such a framework by incorporating innovative features extending its robustness. The first part of this dissertation describes the development of a conceptual Multi-Fidelity Multi-Strategy and Multi-Disciplinary Design Optimization Environment (M3 DOE), in context of aircraft wing optimization. M 3 DOE provides the user a capability to optimize configurations with a choice of (i) the level of fidelity desired, (ii) the use of a single-step or multi-step optimization strategy, and (iii) combination of a series of structural and aerodynamic analyses. The modularity of M3 DOE allows it to be a part of other inclusive optimization frameworks. The M 3 DOE is demonstrated within the context of shape and sizing optimization of the wing of a Generic Business Jet aircraft. Two different optimization objectives, viz. dry weight minimization, and cruise range maximization are studied by conducting one low-fidelity and two high-fidelity optimization runs to demonstrate the application scope of M3 DOE. The second part of this dissertation describes the development of an innovative hybrid optimization framework that extends the robustness of M 3 DOE by employing a proper orthogonal decomposition-based design-space order reduction scheme combined with the evolutionary algorithm technique. The POD method of extracting dominant modes from an ensemble of candidate configurations is used for the design-space order reduction. The snapshot of candidate population is updated iteratively using evolutionary algorithm technique of fitness-driven retention. This strategy capitalizes on the advantages of evolutionary algorithm as well as POD-based reduced order modeling, while overcoming the shortcomings inherent with these techniques. When linked with M3 DOE, this strategy offers a computationally efficient methodology for problems with high level of complexity and a challenging design-space. This newly developed framework is demonstrated for its robustness on a nonconventional supersonic tailless air vehicle wing shape optimization problem.

Novel schemes for measurement-based quantum computation.

PubMed

Gross, D; Eisert, J

2007-06-01

We establish a framework which allows one to construct novel schemes for measurement-based quantum computation. The technique develops tools from many-body physics-based on finitely correlated or projected entangled pair states-to go beyond the cluster-state based one-way computer. We identify resource states radically different from the cluster state, in that they exhibit nonvanishing correlations, can be prepared using nonmaximally entangling gates, or have very different local entanglement properties. In the computational models, randomness is compensated in a different manner. It is shown that there exist resource states which are locally arbitrarily close to a pure state. We comment on the possibility of tailoring computational models to specific physical systems.

A Security Architecture Based on Trust Management for Pervasive Computing Systems

DTIC Science & Technology

2005-01-01

SmartSpace framework, we extended the C2 [16] ar- chitecture, which in turn is based on the Centaurus [10] model. In Centaurus a Client can access...the services provided by the nearest Centaurus Service Manager (SM) via some short-range communi- cation. The SM acts as an active proxy by executing...The In the Centaurus project [10], the main design goal is the development of a framework for building portals to services using various types of

Software Issues in High-Performance Computing and a Framework for the Development of HPC Applications

DTIC Science & Technology

1995-01-01

possible to determine communication points. For this version, a C program spawning Posix threads and using semaphores to synchronize would have to...performance such as the time required for network communication and synchronization as well as issues of asynchrony and memory hierarchy. For example...enhances reusability. Process (or task) parallel computations can also be succinctly expressed with a small set of process creation and synchronization

Using Computer Simulations for Promoting Model-based Reasoning. Epistemological and Educational Dimensions

NASA Astrophysics Data System (ADS)

Develaki, Maria

2017-11-01

Scientific reasoning is particularly pertinent to science education since it is closely related to the content and methodologies of science and contributes to scientific literacy. Much of the research in science education investigates the appropriate framework and teaching methods and tools needed to promote students' ability to reason and evaluate in a scientific way. This paper aims (a) to contribute to an extended understanding of the nature and pedagogical importance of model-based reasoning and (b) to exemplify how using computer simulations can support students' model-based reasoning. We provide first a background for both scientific reasoning and computer simulations, based on the relevant philosophical views and the related educational discussion. This background suggests that the model-based framework provides an epistemologically valid and pedagogically appropriate basis for teaching scientific reasoning and for helping students develop sounder reasoning and decision-taking abilities and explains how using computer simulations can foster these abilities. We then provide some examples illustrating the use of computer simulations to support model-based reasoning and evaluation activities in the classroom. The examples reflect the procedure and criteria for evaluating models in science and demonstrate the educational advantages of their application in classroom reasoning activities.

MODELS-3/CMAQ APPLICATIONS WHICH ILLUSTRATE CAPABILITY AND FUNCTIONALITY

EPA Science Inventory

The Models-3/CMAQ developed by the U.S. Environmental Protections Agency (USEPA) is a third generation multiscale, multi-pollutant air quality modeling system within a high-level, object-oriented computer framework (Models-3). It has been available to the scientific community ...

Development of a Computational Framework for Big Data-Driven Prediction of Long-Term Bridge Performance and Traffic Flow

DOT National Transportation Integrated Search

2018-04-01

Consistent efforts with dense sensor deployment and data gathering processes for bridge big data have accumulated profound information regarding bridge performance, associated environments, and traffic flows. However, direct applications of bridge bi...

Quantum plug n’ play: modular computation in the quantum regime

NASA Astrophysics Data System (ADS)

Thompson, Jayne; Modi, Kavan; Vedral, Vlatko; Gu, Mile

2018-01-01

Classical computation is modular. It exploits plug n’ play architectures which allow us to use pre-fabricated circuits without knowing their construction. This bestows advantages such as allowing parts of the computational process to be outsourced, and permitting individual circuit components to be exchanged and upgraded. Here, we introduce a formal framework to describe modularity in the quantum regime. We demonstrate a ‘no-go’ theorem, stipulating that it is not always possible to make use of quantum circuits without knowing their construction. This has significant consequences for quantum algorithms, forcing the circuit implementation of certain quantum algorithms to be rebuilt almost entirely from scratch after incremental changes in the problem—such as changing the number being factored in Shor’s algorithm. We develop a workaround capable of restoring modularity, and apply it to design a modular version of Shor’s algorithm that exhibits increased versatility and reduced complexity. In doing so we pave the way to a realistic framework whereby ‘quantum chips’ and remote servers can be invoked (or assembled) to implement various parts of a more complex quantum computation.

[Computer aided design for fixed partial denture framework based on reverse engineering technology].

PubMed

Sun, Yu-chun; Lü, Pei-jun; Wang, Yong

2006-03-01

To explore a computer aided design (CAD) route for the framework of domestic fixed partial denture (FPD) and confirm the suitable method of 3-D CAD. The working area of a dentition model was scanned with a 3-D mechanical scanner. Using the reverse engineering (RE) software, margin and border curves were extracted and several reference curves were created to ensure the dimension and location of pontic framework that was taken from the standard database. The shoulder parts of the retainers were created after axial surfaces constructed. The connecting areas, axial line and curving surface of the framework connector were finally created. The framework of a three-unit FPD was designed with RE technology, which showed smooth surfaces and continuous contours. The design route is practical. The result of this study is significant in theory and practice, which will provide a reference for establishing the computer aided design/computer aided manufacture (CAD/CAM) system of domestic FPD.

A Probabilistic Framework for the Validation and Certification of Computer Simulations

NASA Technical Reports Server (NTRS)

Ghanem, Roger; Knio, Omar

2000-01-01

The paper presents a methodology for quantifying, propagating, and managing the uncertainty in the data required to initialize computer simulations of complex phenomena. The purpose of the methodology is to permit the quantitative assessment of a certification level to be associated with the predictions from the simulations, as well as the design of a data acquisition strategy to achieve a target level of certification. The value of a methodology that can address the above issues is obvious, specially in light of the trend in the availability of computational resources, as well as the trend in sensor technology. These two trends make it possible to probe physical phenomena both with physical sensors, as well as with complex models, at previously inconceivable levels. With these new abilities arises the need to develop the knowledge to integrate the information from sensors and computer simulations. This is achieved in the present work by tracing both activities back to a level of abstraction that highlights their commonalities, thus allowing them to be manipulated in a mathematically consistent fashion. In particular, the mathematical theory underlying computer simulations has long been associated with partial differential equations and functional analysis concepts such as Hilbert spares and orthogonal projections. By relying on a probabilistic framework for the modeling of data, a Hilbert space framework emerges that permits the modeling of coefficients in the governing equations as random variables, or equivalently, as elements in a Hilbert space. This permits the development of an approximation theory for probabilistic problems that parallels that of deterministic approximation theory. According to this formalism, the solution of the problem is identified by its projection on a basis in the Hilbert space of random variables, as opposed to more traditional techniques where the solution is approximated by its first or second-order statistics. The present representation, in addition to capturing significantly more information than the traditional approach, facilitates the linkage between different interacting stochastic systems as is typically observed in real-life situations.

The QuakeSim Project: Numerical Simulations for Active Tectonic Processes

NASA Technical Reports Server (NTRS)

Donnellan, Andrea; Parker, Jay; Lyzenga, Greg; Granat, Robert; Fox, Geoffrey; Pierce, Marlon; Rundle, John; McLeod, Dennis; Grant, Lisa; Tullis, Terry

2004-01-01

In order to develop a solid earth science framework for understanding and studying of active tectonic and earthquake processes, this task develops simulation and analysis tools to study the physics of earthquakes using state-of-the art modeling, data manipulation, and pattern recognition technologies. We develop clearly defined accessible data formats and code protocols as inputs to the simulations. these are adapted to high-performance computers because the solid earth system is extremely complex and nonlinear resulting in computationally intensive problems with millions of unknowns. With these tools it will be possible to construct the more complex models and simulations necessary to develop hazard assessment systems critical for reducing future losses from major earthquakes.

Universal blind quantum computation for hybrid system

NASA Astrophysics Data System (ADS)

Huang, He-Liang; Bao, Wan-Su; Li, Tan; Li, Feng-Guang; Fu, Xiang-Qun; Zhang, Shuo; Zhang, Hai-Long; Wang, Xiang

2017-08-01

As progress on the development of building quantum computer continues to advance, first-generation practical quantum computers will be available for ordinary users in the cloud style similar to IBM's Quantum Experience nowadays. Clients can remotely access the quantum servers using some simple devices. In such a situation, it is of prime importance to keep the security of the client's information. Blind quantum computation protocols enable a client with limited quantum technology to delegate her quantum computation to a quantum server without leaking any privacy. To date, blind quantum computation has been considered only for an individual quantum system. However, practical universal quantum computer is likely to be a hybrid system. Here, we take the first step to construct a framework of blind quantum computation for the hybrid system, which provides a more feasible way for scalable blind quantum computation.

A neotropical Miocene pollen database employing image-based search and semantic modeling.

PubMed

Han, Jing Ginger; Cao, Hongfei; Barb, Adrian; Punyasena, Surangi W; Jaramillo, Carlos; Shyu, Chi-Ren

2014-08-01

Digital microscopic pollen images are being generated with increasing speed and volume, producing opportunities to develop new computational methods that increase the consistency and efficiency of pollen analysis and provide the palynological community a computational framework for information sharing and knowledge transfer. • Mathematical methods were used to assign trait semantics (abstract morphological representations) of the images of neotropical Miocene pollen and spores. Advanced database-indexing structures were built to compare and retrieve similar images based on their visual content. A Web-based system was developed to provide novel tools for automatic trait semantic annotation and image retrieval by trait semantics and visual content. • Mathematical models that map visual features to trait semantics can be used to annotate images with morphology semantics and to search image databases with improved reliability and productivity. Images can also be searched by visual content, providing users with customized emphases on traits such as color, shape, and texture. • Content- and semantic-based image searches provide a powerful computational platform for pollen and spore identification. The infrastructure outlined provides a framework for building a community-wide palynological resource, streamlining the process of manual identification, analysis, and species discovery.

Mass detection in digital breast tomosynthesis data using convolutional neural networks and multiple instance learning.

PubMed

Yousefi, Mina; Krzyżak, Adam; Suen, Ching Y

2018-05-01

Digital breast tomosynthesis (DBT) was developed in the field of breast cancer screening as a new tomographic technique to minimize the limitations of conventional digital mammography breast screening methods. A computer-aided detection (CAD) framework for mass detection in DBT has been developed and is described in this paper. The proposed framework operates on a set of two-dimensional (2D) slices. With plane-to-plane analysis on corresponding 2D slices from each DBT, it automatically learns complex patterns of 2D slices through a deep convolutional neural network (DCNN). It then applies multiple instance learning (MIL) with a randomized trees approach to classify DBT images based on extracted information from 2D slices. This CAD framework was developed and evaluated using 5040 2D image slices derived from 87 DBT volumes. The empirical results demonstrate that this proposed CAD framework achieves much better performance than CAD systems that use hand-crafted features and deep cardinality-restricted Bolzmann machines to detect masses in DBTs. Copyright © 2018 Elsevier Ltd. All rights reserved.

Contemporary cybernetics and its facets of cognitive informatics and computational intelligence.

PubMed

Wang, Yingxu; Kinsner, Witold; Zhang, Du

2009-08-01

This paper explores the architecture, theoretical foundations, and paradigms of contemporary cybernetics from perspectives of cognitive informatics (CI) and computational intelligence. The modern domain and the hierarchical behavioral model of cybernetics are elaborated at the imperative, autonomic, and cognitive layers. The CI facet of cybernetics is presented, which explains how the brain may be mimicked in cybernetics via CI and neural informatics. The computational intelligence facet is described with a generic intelligence model of cybernetics. The compatibility between natural and cybernetic intelligence is analyzed. A coherent framework of contemporary cybernetics is presented toward the development of transdisciplinary theories and applications in cybernetics, CI, and computational intelligence.

Least squares QR-based decomposition provides an efficient way of computing optimal regularization parameter in photoacoustic tomography.

PubMed

Shaw, Calvin B; Prakash, Jaya; Pramanik, Manojit; Yalavarthy, Phaneendra K

2013-08-01

A computationally efficient approach that computes the optimal regularization parameter for the Tikhonov-minimization scheme is developed for photoacoustic imaging. This approach is based on the least squares-QR decomposition which is a well-known dimensionality reduction technique for a large system of equations. It is shown that the proposed framework is effective in terms of quantitative and qualitative reconstructions of initial pressure distribution enabled via finding an optimal regularization parameter. The computational efficiency and performance of the proposed method are shown using a test case of numerical blood vessel phantom, where the initial pressure is exactly known for quantitative comparison.

Neural Networks for Computer Vision: A Framework for Specifications of a General Purpose Vision System

NASA Astrophysics Data System (ADS)

Skrzypek, Josef; Mesrobian, Edmond; Gungner, David J.

1989-03-01

The development of autonomous land vehicles (ALV) capable of operating in an unconstrained environment has proven to be a formidable research effort. The unpredictability of events in such an environment calls for the design of a robust perceptual system, an impossible task requiring the programming of a system bases on the expectation of future, unconstrained events. Hence, the need for a "general purpose" machine vision system that is capable of perceiving and understanding images in an unconstrained environment in real-time. The research undertaken at the UCLA Machine Perception Laboratory addresses this need by focusing on two specific issues: 1) the long term goals for machine vision research as a joint effort between the neurosciences and computer science; and 2) a framework for evaluating progress in machine vision. In the past, vision research has been carried out independently within different fields including neurosciences, psychology, computer science, and electrical engineering. Our interdisciplinary approach to vision research is based on the rigorous combination of computational neuroscience, as derived from neurophysiology and neuropsychology, with computer science and electrical engineering. The primary motivation behind our approach is that the human visual system is the only existing example of a "general purpose" vision system and using a neurally based computing substrate, it can complete all necessary visual tasks in real-time.

Development of an integrated economic and ecological framework for ecosystem-based fisheries management in New England

NASA Astrophysics Data System (ADS)

Jin, D.; Hoagland, P.; Dalton, T. M.; Thunberg, E. M.

2012-09-01

We present an integrated economic-ecological framework designed to help assess the implementation of ecosystem-based fisheries management (EBFM) in New England. We develop the framework by linking a computable general equilibrium (CGE) model of a coastal economy to an end-to-end (E2E) model of a marine food web for Georges Bank. We focus on the New England region using coastal county economic data for a restricted set of industry sectors and marine ecological data for three top level trophic feeding guilds: planktivores, benthivores, and piscivores. We undertake numerical simulations to model the welfare effects of changes in alternative combinations of yields from feeding guilds and alternative manifestations of biological productivity. We estimate the economic and distributional effects of these alternative simulations across a range of consumer income levels. This framework could be used to extend existing methodologies for assessing the impacts on human communities of groundfish stock rebuilding strategies, such as those expected through the implementation of the sector management program in the US northeast fishery. We discuss other possible applications of and modifications and limitations to the framework.

Physically Based Modeling and Simulation with Dynamic Spherical Volumetric Simplex Splines

PubMed Central

Tan, Yunhao; Hua, Jing; Qin, Hong

2009-01-01

In this paper, we present a novel computational modeling and simulation framework based on dynamic spherical volumetric simplex splines. The framework can handle the modeling and simulation of genus-zero objects with real physical properties. In this framework, we first develop an accurate and efficient algorithm to reconstruct the high-fidelity digital model of a real-world object with spherical volumetric simplex splines which can represent with accuracy geometric, material, and other properties of the object simultaneously. With the tight coupling of Lagrangian mechanics, the dynamic volumetric simplex splines representing the object can accurately simulate its physical behavior because it can unify the geometric and material properties in the simulation. The visualization can be directly computed from the object’s geometric or physical representation based on the dynamic spherical volumetric simplex splines during simulation without interpolation or resampling. We have applied the framework for biomechanic simulation of brain deformations, such as brain shifting during the surgery and brain injury under blunt impact. We have compared our simulation results with the ground truth obtained through intra-operative magnetic resonance imaging and the real biomechanic experiments. The evaluations demonstrate the excellent performance of our new technique. PMID:20161636

A proposal for a computer-based framework of support for public health in the management of biological incidents: the Czech Republic experience.

PubMed

Bures, Vladimír; Otcenásková, Tereza; Cech, Pavel; Antos, Karel

2012-11-01

Biological incidents jeopardising public health require decision-making that consists of one dominant feature: complexity. Therefore, public health decision-makers necessitate appropriate support. Based on the analogy with business intelligence (BI) principles, the contextual analysis of the environment and available data resources, and conceptual modelling within systems and knowledge engineering, this paper proposes a general framework for computer-based decision support in the case of a biological incident. At the outset, the analysis of potential inputs to the framework is conducted and several resources such as demographic information, strategic documents, environmental characteristics, agent descriptors and surveillance systems are considered. Consequently, three prototypes were developed, tested and evaluated by a group of experts. Their selection was based on the overall framework scheme. Subsequently, an ontology prototype linked with an inference engine, multi-agent-based model focusing on the simulation of an environment, and expert-system prototypes were created. All prototypes proved to be utilisable support tools for decision-making in the field of public health. Nevertheless, the research revealed further issues and challenges that might be investigated by both public health focused researchers and practitioners.

Integrated framework for developing search and discrimination metrics

NASA Astrophysics Data System (ADS)

Copeland, Anthony C.; Trivedi, Mohan M.

1997-06-01

This paper presents an experimental framework for evaluating target signature metrics as models of human visual search and discrimination. This framework is based on a prototype eye tracking testbed, the Integrated Testbed for Eye Movement Studies (ITEMS). ITEMS determines an observer's visual fixation point while he studies a displayed image scene, by processing video of the observer's eye. The utility of this framework is illustrated with an experiment using gray-scale images of outdoor scenes that contain randomly placed targets. Each target is a square region of a specific size containing pixel values from another image of an outdoor scene. The real-world analogy of this experiment is that of a military observer looking upon the sensed image of a static scene to find camouflaged enemy targets that are reported to be in the area. ITEMS provides the data necessary to compute various statistics for each target to describe how easily the observers located it, including the likelihood the target was fixated or identified and the time required to do so. The computed values of several target signature metrics are compared to these statistics, and a second-order metric based on a model of image texture was found to be the most highly correlated.

A Web GIS Enabled Comprehensive Hydrologic Information System for Indian Water Resources Systems

NASA Astrophysics Data System (ADS)

Goyal, A.; Tyagi, H.; Gosain, A. K.; Khosa, R.

2017-12-01

Hydrological systems across the globe are getting increasingly water stressed with each passing season due to climate variability & snowballing water demand. Hence, to safeguard food, livelihood & economic security, it becomes imperative to employ scientific studies for holistic management of indispensable resource like water. However, hydrological study of any scale & purpose is heavily reliant on various spatio-temporal datasets which are not only difficult to discover/access but are also tough to use & manage. Besides, owing to diversity of water sector agencies & dearth of standard operating procedures, seamless information exchange is challenging for collaborators. Extensive research is being done worldwide to address these issues but regrettably not much has been done in developing countries like India. Therefore, the current study endeavours to develop a Hydrological Information System framework in a Web-GIS environment for empowering Indian water resources systems. The study attempts to harmonize the standards for metadata, terminology, symbology, versioning & archiving for effective generation, processing, dissemination & mining of data required for hydrological studies. Furthermore, modelers with humble computing resources at their disposal, can consume this standardized data in high performance simulation modelling using cloud computing within the developed Web-GIS framework. They can also integrate the inputs-outputs of different numerical models available on the platform and integrate their results for comprehensive analysis of the chosen hydrological system. Thus, the developed portal is an all-in-one framework that can facilitate decision makers, industry professionals & researchers in efficient water management.

A Scatter-Based Prototype Framework and Multi-Class Extension of Support Vector Machines

PubMed Central

Jenssen, Robert; Kloft, Marius; Zien, Alexander; Sonnenburg, Sören; Müller, Klaus-Robert

2012-01-01

We provide a novel interpretation of the dual of support vector machines (SVMs) in terms of scatter with respect to class prototypes and their mean. As a key contribution, we extend this framework to multiple classes, providing a new joint Scatter SVM algorithm, at the level of its binary counterpart in the number of optimization variables. This enables us to implement computationally efficient solvers based on sequential minimal and chunking optimization. As a further contribution, the primal problem formulation is developed in terms of regularized risk minimization and the hinge loss, revealing the score function to be used in the actual classification of test patterns. We investigate Scatter SVM properties related to generalization ability, computational efficiency, sparsity and sensitivity maps, and report promising results. PMID:23118845

Computers and Cultural Diversity. Restructuring for School Success. SUNY Series, Computers in Education.

ERIC Educational Resources Information Center

DeVillar, Robert A.; Faltis, Christian J.

This book offers an alternative conceptual framework for effectively incorporating computer use within the heterogeneous classroom. The framework integrates Vygotskian social-learning theory with Allport's contact theory and the principles of cooperative learning. In Part 1 an essential element is identified for each of these areas. These are, in…

The Center for Computational Biology: resources, achievements, and challenges

PubMed Central

Dinov, Ivo D; Thompson, Paul M; Woods, Roger P; Van Horn, John D; Shattuck, David W; Parker, D Stott

2011-01-01

The Center for Computational Biology (CCB) is a multidisciplinary program where biomedical scientists, engineers, and clinicians work jointly to combine modern mathematical and computational techniques, to perform phenotypic and genotypic studies of biological structure, function, and physiology in health and disease. CCB has developed a computational framework built around the Manifold Atlas, an integrated biomedical computing environment that enables statistical inference on biological manifolds. These manifolds model biological structures, features, shapes, and flows, and support sophisticated morphometric and statistical analyses. The Manifold Atlas includes tools, workflows, and services for multimodal population-based modeling and analysis of biological manifolds. The broad spectrum of biomedical topics explored by CCB investigators include the study of normal and pathological brain development, maturation and aging, discovery of associations between neuroimaging and genetic biomarkers, and the modeling, analysis, and visualization of biological shape, form, and size. CCB supports a wide range of short-term and long-term collaborations with outside investigators, which drive the center's computational developments and focus the validation and dissemination of CCB resources to new areas and scientific domains. PMID:22081221

The Center for Computational Biology: resources, achievements, and challenges.

PubMed

Toga, Arthur W; Dinov, Ivo D; Thompson, Paul M; Woods, Roger P; Van Horn, John D; Shattuck, David W; Parker, D Stott

2012-01-01

The Center for Computational Biology (CCB) is a multidisciplinary program where biomedical scientists, engineers, and clinicians work jointly to combine modern mathematical and computational techniques, to perform phenotypic and genotypic studies of biological structure, function, and physiology in health and disease. CCB has developed a computational framework built around the Manifold Atlas, an integrated biomedical computing environment that enables statistical inference on biological manifolds. These manifolds model biological structures, features, shapes, and flows, and support sophisticated morphometric and statistical analyses. The Manifold Atlas includes tools, workflows, and services for multimodal population-based modeling and analysis of biological manifolds. The broad spectrum of biomedical topics explored by CCB investigators include the study of normal and pathological brain development, maturation and aging, discovery of associations between neuroimaging and genetic biomarkers, and the modeling, analysis, and visualization of biological shape, form, and size. CCB supports a wide range of short-term and long-term collaborations with outside investigators, which drive the center's computational developments and focus the validation and dissemination of CCB resources to new areas and scientific domains.

A high-level 3D visualization API for Java and ImageJ.

PubMed

Schmid, Benjamin; Schindelin, Johannes; Cardona, Albert; Longair, Mark; Heisenberg, Martin

2010-05-21

Current imaging methods such as Magnetic Resonance Imaging (MRI), Confocal microscopy, Electron Microscopy (EM) or Selective Plane Illumination Microscopy (SPIM) yield three-dimensional (3D) data sets in need of appropriate computational methods for their analysis. The reconstruction, segmentation and registration are best approached from the 3D representation of the data set. Here we present a platform-independent framework based on Java and Java 3D for accelerated rendering of biological images. Our framework is seamlessly integrated into ImageJ, a free image processing package with a vast collection of community-developed biological image analysis tools. Our framework enriches the ImageJ software libraries with methods that greatly reduce the complexity of developing image analysis tools in an interactive 3D visualization environment. In particular, we provide high-level access to volume rendering, volume editing, surface extraction, and image annotation. The ability to rely on a library that removes the low-level details enables concentrating software development efforts on the algorithm implementation parts. Our framework enables biomedical image software development to be built with 3D visualization capabilities with very little effort. We offer the source code and convenient binary packages along with extensive documentation at http://3dviewer.neurofly.de.

al3c: high-performance software for parameter inference using Approximate Bayesian Computation.

PubMed

Stram, Alexander H; Marjoram, Paul; Chen, Gary K

2015-11-01

The development of Approximate Bayesian Computation (ABC) algorithms for parameter inference which are both computationally efficient and scalable in parallel computing environments is an important area of research. Monte Carlo rejection sampling, a fundamental component of ABC algorithms, is trivial to distribute over multiple processors but is inherently inefficient. While development of algorithms such as ABC Sequential Monte Carlo (ABC-SMC) help address the inherent inefficiencies of rejection sampling, such approaches are not as easily scaled on multiple processors. As a result, current Bayesian inference software offerings that use ABC-SMC lack the ability to scale in parallel computing environments. We present al3c, a C++ framework for implementing ABC-SMC in parallel. By requiring only that users define essential functions such as the simulation model and prior distribution function, al3c abstracts the user from both the complexities of parallel programming and the details of the ABC-SMC algorithm. By using the al3c framework, the user is able to scale the ABC-SMC algorithm in parallel computing environments for his or her specific application, with minimal programming overhead. al3c is offered as a static binary for Linux and OS-X computing environments. The user completes an XML configuration file and C++ plug-in template for the specific application, which are used by al3c to obtain the desired results. Users can download the static binaries, source code, reference documentation and examples (including those in this article) by visiting https://github.com/ahstram/al3c. astram@usc.edu Supplementary data are available at Bioinformatics online. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

A computational framework to detect normal and tuberculosis infected lung from H and E-stained whole slide images

NASA Astrophysics Data System (ADS)

Niazi, M. Khalid Khan; Beamer, Gillian; Gurcan, Metin N.

2017-03-01

Accurate detection and quantification of normal lung tissue in the context of Mycobacterium tuberculosis infection is of interest from a biological perspective. The automatic detection and quantification of normal lung will allow the biologists to focus more intensely on regions of interest within normal and infected tissues. We present a computational framework to extract individual tissue sections from whole slide images having multiple tissue sections. It automatically detects the background, red blood cells and handwritten digits to bring efficiency as well as accuracy in quantification of tissue sections. For efficiency, we model our framework with logical and morphological operations as they can be performed in linear time. We further divide these individual tissue sections into normal and infected areas using deep neural network. The computational framework was trained on 60 whole slide images. The proposed computational framework resulted in an overall accuracy of 99.2% when extracting individual tissue sections from 120 whole slide images in the test dataset. The framework resulted in a relatively higher accuracy (99.7%) while classifying individual lung sections into normal and infected areas. Our preliminary findings suggest that the proposed framework has good agreement with biologists on how define normal and infected lung areas.

Development of a CAD Model Simplification Framework for Finite Element Analysis

DTIC Science & Technology

2012-01-01

A. Senthil Kumar , and KH Lee. Automatic solid decomposition and reduction for non-manifold geometric model generation. Computer-Aided Design, 36(13...CAD/CAM: concepts, techniques, and applications. Wiley-interscience, 1995. [38] Avneesh Sud, Mark Foskey, and Dinesh Manocha. Homotopy-preserving

A framework for developing and integrating effective routing strategies within the emergency management decision-support system : [research brief].

DOT National Transportation Integrated Search

2012-05-01

The terrorist attacks on September 11th, as well as other coordinated attacks on transit centers in Madrid and London, have underscored the importance of evacuation planning to : transportation professionals. With computer technology advancement, urb...

Adverse Outcome Pathways: A Conceptual Framework to Support Ecotoxicology Research and Risk Assessment

EPA Science Inventory

Ecological risk assessors face increasing demands to assess more chemicals, with greater speed and accuracy, and to do so using fewer resources and experimental animals. New approaches in biological and computational sciences are being developed to generate mechanistic informatio...

Enhancing Manufacturing Process Education via Computer Simulation and Visualization

ERIC Educational Resources Information Center

Manohar, Priyadarshan A.; Acharya, Sushil; Wu, Peter

2014-01-01

Industrially significant metal manufacturing processes such as melting, casting, rolling, forging, machining, and forming are multi-stage, complex processes that are labor, time, and capital intensive. Academic research develops mathematical modeling of these processes that provide a theoretical framework for understanding the process variables…

AN INTEGRATED COMPUTATIONAL FRAMEWORK FOR THE INTERPRETATION OF ORGANOPHOSPHORUS PESTICIDE BIOMARKERS

EPA Science Inventory

We anticipate that the software tool developed, and targeted data acquired, will be useful in the interpretation of biomarkers indicative of exposure to OP insecticide mixtures, including the effects of population and dose variability and uncertainty. Therefore, we expect tha...

Event-based simulation of networks with pulse delayed coupling

NASA Astrophysics Data System (ADS)

Klinshov, Vladimir; Nekorkin, Vladimir

2017-10-01

Pulse-mediated interactions are common in networks of different nature. Here we develop a general framework for simulation of networks with pulse delayed coupling. We introduce the discrete map governing the dynamics of such networks and describe the computation algorithm for its numerical simulation.

Riemann tensor of motion vision revisited.

PubMed

Brill, M

2001-07-02

This note shows that the Riemann-space interpretation of motion vision developed by Barth and Watson is neither necessary for their results, nor sufficient to handle an intrinsic coordinate problem. Recasting the Barth-Watson framework as a classical velocity-solver (as in computer vision) solves these problems.

RABIX: AN OPEN-SOURCE WORKFLOW EXECUTOR SUPPORTING RECOMPUTABILITY AND INTEROPERABILITY OF WORKFLOW DESCRIPTIONS

PubMed Central

Ivkovic, Sinisa; Simonovic, Janko; Tijanic, Nebojsa; Davis-Dusenbery, Brandi; Kural, Deniz

2016-01-01

As biomedical data has become increasingly easy to generate in large quantities, the methods used to analyze it have proliferated rapidly. Reproducible and reusable methods are required to learn from large volumes of data reliably. To address this issue, numerous groups have developed workflow specifications or execution engines, which provide a framework with which to perform a sequence of analyses. One such specification is the Common Workflow Language, an emerging standard which provides a robust and flexible framework for describing data analysis tools and workflows. In addition, reproducibility can be furthered by executors or workflow engines which interpret the specification and enable additional features, such as error logging, file organization, optimizations1 to computation and job scheduling, and allow for easy computing on large volumes of data. To this end, we have developed the Rabix Executor a , an open-source workflow engine for the purposes of improving reproducibility through reusability and interoperability of workflow descriptions. PMID:27896971

RABIX: AN OPEN-SOURCE WORKFLOW EXECUTOR SUPPORTING RECOMPUTABILITY AND INTEROPERABILITY OF WORKFLOW DESCRIPTIONS.

PubMed

Kaushik, Gaurav; Ivkovic, Sinisa; Simonovic, Janko; Tijanic, Nebojsa; Davis-Dusenbery, Brandi; Kural, Deniz

2017-01-01

As biomedical data has become increasingly easy to generate in large quantities, the methods used to analyze it have proliferated rapidly. Reproducible and reusable methods are required to learn from large volumes of data reliably. To address this issue, numerous groups have developed workflow specifications or execution engines, which provide a framework with which to perform a sequence of analyses. One such specification is the Common Workflow Language, an emerging standard which provides a robust and flexible framework for describing data analysis tools and workflows. In addition, reproducibility can be furthered by executors or workflow engines which interpret the specification and enable additional features, such as error logging, file organization, optim1izations to computation and job scheduling, and allow for easy computing on large volumes of data. To this end, we have developed the Rabix Executor, an open-source workflow engine for the purposes of improving reproducibility through reusability and interoperability of workflow descriptions.

Computational modeling of electrically-driven deposition of ionized polydisperse particulate powder mixtures in advanced manufacturing processes

NASA Astrophysics Data System (ADS)

Zohdi, T. I.

2017-07-01

A key part of emerging advanced additive manufacturing methods is the deposition of specialized particulate mixtures of materials on substrates. For example, in many cases these materials are polydisperse powder mixtures whereby one set of particles is chosen with the objective to electrically, thermally or mechanically functionalize the overall mixture material and another set of finer-scale particles serves as an interstitial filler/binder. Often, achieving controllable, precise, deposition is difficult or impossible using mechanical means alone. It is for this reason that electromagnetically-driven methods are being pursued in industry, whereby the particles are ionized and an electromagnetic field is used to guide them into place. The goal of this work is to develop a model and simulation framework to investigate the behavior of a deposition as a function of an applied electric field. The approach develops a modular discrete-element type method for the simulation of the particle dynamics, which provides researchers with a framework to construct computational tools for this growing industry.

Software Architecture for a Virtual Environment for Nano Scale Assembly (VENSA).

PubMed

Lee, Yong-Gu; Lyons, Kevin W; Feng, Shaw C

2004-01-01

A Virtual Environment (VE) uses multiple computer-generated media to let a user experience situations that are temporally and spatially prohibiting. The information flow between the user and the VE is bidirectional and the user can influence the environment. The software development of a VE requires orchestrating multiple peripherals and computers in a synchronized way in real time. Although a multitude of useful software components for VEs exists, many of these are packaged within a complex framework and can not be used separately. In this paper, an architecture is presented which is designed to let multiple frameworks work together while being shielded from the application program. This architecture, which is called the Virtual Environment for Nano Scale Assembly (VENSA), has been constructed for interfacing with an optical tweezers instrument for nanotechnology development. However, this approach can be generalized for most virtual environments. Through the use of VENSA, the programmer can rely on existing solutions and concentrate more on the application software design.

Rapid and Accurate Machine Learning Recognition of High Performing Metal Organic Frameworks for CO2 Capture.

PubMed

Fernandez, Michael; Boyd, Peter G; Daff, Thomas D; Aghaji, Mohammad Zein; Woo, Tom K

2014-09-04

In this work, we have developed quantitative structure-property relationship (QSPR) models using advanced machine learning algorithms that can rapidly and accurately recognize high-performing metal organic framework (MOF) materials for CO2 capture. More specifically, QSPR classifiers have been developed that can, in a fraction of a section, identify candidate MOFs with enhanced CO2 adsorption capacity (>1 mmol/g at 0.15 bar and >4 mmol/g at 1 bar). The models were tested on a large set of 292 050 MOFs that were not part of the training set. The QSPR classifier could recover 945 of the top 1000 MOFs in the test set while flagging only 10% of the whole library for compute intensive screening. Thus, using the machine learning classifiers as part of a high-throughput screening protocol would result in an order of magnitude reduction in compute time and allow intractably large structure libraries and search spaces to be screened.

Software Architecture for a Virtual Environment for Nano Scale Assembly (VENSA)

PubMed Central

Lee, Yong-Gu; Lyons, Kevin W.; Feng, Shaw C.

2004-01-01

A Virtual Environment (VE) uses multiple computer-generated media to let a user experience situations that are temporally and spatially prohibiting. The information flow between the user and the VE is bidirectional and the user can influence the environment. The software development of a VE requires orchestrating multiple peripherals and computers in a synchronized way in real time. Although a multitude of useful software components for VEs exists, many of these are packaged within a complex framework and can not be used separately. In this paper, an architecture is presented which is designed to let multiple frameworks work together while being shielded from the application program. This architecture, which is called the Virtual Environment for Nano Scale Assembly (VENSA), has been constructed for interfacing with an optical tweezers instrument for nanotechnology development. However, this approach can be generalized for most virtual environments. Through the use of VENSA, the programmer can rely on existing solutions and concentrate more on the application software design. PMID:27366610

A model for the development of university curricula in nanoelectronics

NASA Astrophysics Data System (ADS)

Bruun, E.; Nielsen, I.

2010-12-01

Nanotechnology is having an increasing impact on university curricula in electrical engineering and in physics. Major influencers affecting developments in university programmes related to nanoelectronics are discussed and a model for university programme development is described. The model takes into account that nanotechnology affects not only physics but also electrical engineering and computer engineering because of the advent of new nanoelectronics devices. The model suggests that curriculum development tends to follow one of three major tracks: physics; electrical engineering; computer engineering. Examples of European curricula following this framework are identified and described. These examples may serve as sources of inspiration for future developments and the model presented may provide guidelines for a systematic selection of topics in the university programmes.

Towards large-scale data analysis: challenges in the design of portable systems and use of Cloud computing.

PubMed

Diaz, Javier; Arrizabalaga, Saioa; Bustamante, Paul; Mesa, Iker; Añorga, Javier; Goya, Jon

2013-01-01

Portable systems and global communications open a broad spectrum for new health applications. In the framework of electrophysiological applications, several challenges are faced when developing portable systems embedded in Cloud computing services. In order to facilitate new developers in this area based on our experience, five areas of interest are presented in this paper where strategies can be applied for improving the performance of portable systems: transducer and conditioning, processing, wireless communications, battery and power management. Likewise, for Cloud services, scalability, portability, privacy and security guidelines have been highlighted.

Meaning of Interior Tomography

PubMed Central

Wang, Ge; Yu, Hengyong

2013-01-01

The classic imaging geometry for computed tomography is for collection of un-truncated projections and reconstruction of a global image, with the Fourier transform as the theoretical foundation that is intrinsically non-local. Recently, interior tomography research has led to theoretically exact relationships between localities in the projection and image spaces and practically promising reconstruction algorithms. Initially, interior tomography was developed for x-ray computed tomography. Then, it has been elevated as a general imaging principle. Finally, a novel framework known as “omni-tomography” is being developed for grand fusion of multiple imaging modalities, allowing tomographic synchrony of diversified features. PMID:23912256

A New Computational Framework for Atmospheric and Surface Remote Sensing

NASA Technical Reports Server (NTRS)

Timucin, Dogan A.

2004-01-01

A Bayesian data-analysis framework is described for atmospheric and surface retrievals from remotely-sensed hyper-spectral data. Some computational techniques are high- lighted for improved accuracy in the forward physics model.

Corra: Computational framework and tools for LC-MS discovery and targeted mass spectrometry-based proteomics

PubMed Central

Brusniak, Mi-Youn; Bodenmiller, Bernd; Campbell, David; Cooke, Kelly; Eddes, James; Garbutt, Andrew; Lau, Hollis; Letarte, Simon; Mueller, Lukas N; Sharma, Vagisha; Vitek, Olga; Zhang, Ning; Aebersold, Ruedi; Watts, Julian D

2008-01-01

Background Quantitative proteomics holds great promise for identifying proteins that are differentially abundant between populations representing different physiological or disease states. A range of computational tools is now available for both isotopically labeled and label-free liquid chromatography mass spectrometry (LC-MS) based quantitative proteomics. However, they are generally not comparable to each other in terms of functionality, user interfaces, information input/output, and do not readily facilitate appropriate statistical data analysis. These limitations, along with the array of choices, present a daunting prospect for biologists, and other researchers not trained in bioinformatics, who wish to use LC-MS-based quantitative proteomics. Results We have developed Corra, a computational framework and tools for discovery-based LC-MS proteomics. Corra extends and adapts existing algorithms used for LC-MS-based proteomics, and statistical algorithms, originally developed for microarray data analyses, appropriate for LC-MS data analysis. Corra also adapts software engineering technologies (e.g. Google Web Toolkit, distributed processing) so that computationally intense data processing and statistical analyses can run on a remote server, while the user controls and manages the process from their own computer via a simple web interface. Corra also allows the user to output significantly differentially abundant LC-MS-detected peptide features in a form compatible with subsequent sequence identification via tandem mass spectrometry (MS/MS). We present two case studies to illustrate the application of Corra to commonly performed LC-MS-based biological workflows: a pilot biomarker discovery study of glycoproteins isolated from human plasma samples relevant to type 2 diabetes, and a study in yeast to identify in vivo targets of the protein kinase Ark1 via phosphopeptide profiling. Conclusion The Corra computational framework leverages computational innovation to enable biologists or other researchers to process, analyze and visualize LC-MS data with what would otherwise be a complex and not user-friendly suite of tools. Corra enables appropriate statistical analyses, with controlled false-discovery rates, ultimately to inform subsequent targeted identification of differentially abundant peptides by MS/MS. For the user not trained in bioinformatics, Corra represents a complete, customizable, free and open source computational platform enabling LC-MS-based proteomic workflows, and as such, addresses an unmet need in the LC-MS proteomics field. PMID:19087345

Software Engineering Support of the Third Round of Scientific Grand Challenge Investigations: An Earth Modeling System Software Framework Strawman Design that Integrates Cactus and UCLA/UCB Distributed Data Broker

NASA Technical Reports Server (NTRS)

Talbot, Bryan; Zhou, Shu-Jia; Higgins, Glenn

2002-01-01

One of the most significant challenges in large-scale climate modeling, as well as in high-performance computing in other scientific fields, is that of effectively integrating many software models from multiple contributors. A software framework facilitates the integration task. both in the development and runtime stages of the simulation. Effective software frameworks reduce the programming burden for the investigators, freeing them to focus more on the science and less on the parallel communication implementation, while maintaining high performance across numerous supercomputer and workstation architectures. This document proposes a strawman framework design for the climate community based on the integration of Cactus, from the relativistic physics community, and UCLA/UCB Distributed Data Broker (DDB) from the climate community. This design is the result of an extensive survey of climate models and frameworks in the climate community as well as frameworks from many other scientific communities. The design addresses fundamental development and runtime needs using Cactus, a framework with interfaces for FORTRAN and C-based languages, and high-performance model communication needs using DDB. This document also specifically explores object-oriented design issues in the context of climate modeling as well as climate modeling issues in terms of object-oriented design.

Performance Analysis of Cloud Computing Architectures Using Discrete Event Simulation

NASA Technical Reports Server (NTRS)

Stocker, John C.; Golomb, Andrew M.

2011-01-01

Cloud computing offers the economic benefit of on-demand resource allocation to meet changing enterprise computing needs. However, the flexibility of cloud computing is disadvantaged when compared to traditional hosting in providing predictable application and service performance. Cloud computing relies on resource scheduling in a virtualized network-centric server environment, which makes static performance analysis infeasible. We developed a discrete event simulation model to evaluate the overall effectiveness of organizations in executing their workflow in traditional and cloud computing architectures. The two part model framework characterizes both the demand using a probability distribution for each type of service request as well as enterprise computing resource constraints. Our simulations provide quantitative analysis to design and provision computing architectures that maximize overall mission effectiveness. We share our analysis of key resource constraints in cloud computing architectures and findings on the appropriateness of cloud computing in various applications.

Cross-domain Collaborative Research and People Interoperability: Beyond Knowledge Representation Frameworks

NASA Astrophysics Data System (ADS)

Fox, P. A.; Diviacco, P.; Busato, A.

2016-12-01

Geo-scientific research collaboration commonly faces of complex systems where multiple skills and competences are needed at the same time. Efficacy of such collaboration among researchers then becomes of paramount importance. Multidisciplinary studies draw from domains that are far from each other. Researchers also need to understand: how to extract what data they need and eventually produce something that can be used by others. The management of information and knowledge in this perspective is non-trivial. Interoperability is frequently sought in computer-to-computer environements, so-as to overcome mismatches in vocabulary, data formats, coordinate reference system and so on. Successful researcher collaboration also relies on interoperability of the people! Smaller, synchronous and face-to-face settings for researchers are knownn to enhance people interoperability. However changing settings; either geographically; temporally; or with increasing the team size, diversity, and expertise requires people-computer-people-computer (...) interoperability. To date, knowledge representation framework have been proposed but not proven as necessary and sufficient to achieve multi-way interoperability. In this contribution, we address epistemology and sociology of science advocating for a fluid perspective where science is mostly a social construct, conditioned by cognitive issues; especially cognitive bias. Bias cannot be obliterated. On the contrary it must be carefully taken into consideration. Information-centric interfaces built from different perspectives and ways of thinking by actors with different point of views, approaches and aims, are proposed as a means for enhancing people interoperability in computer-based settings. The contribution will provide details on the approach of augmenting and interfacing to knowledge representation frameworks to the cognitive-conceptual frameworks for people that are needed to meet and exceed collaborative research goals in the 21st century. A web based collaborative portal has been developed that integrates both approaches and will be presented. Reports will be given on initial tests that have encouraging results.

Kodiak: An Implementation Framework for Branch and Bound Algorithms

NASA Technical Reports Server (NTRS)

Smith, Andrew P.; Munoz, Cesar A.; Narkawicz, Anthony J.; Markevicius, Mantas

2015-01-01

Recursive branch and bound algorithms are often used to refine and isolate solutions to several classes of global optimization problems. A rigorous computation framework for the solution of systems of equations and inequalities involving nonlinear real arithmetic over hyper-rectangular variable and parameter domains is presented. It is derived from a generic branch and bound algorithm that has been formally verified, and utilizes self-validating enclosure methods, namely interval arithmetic and, for polynomials and rational functions, Bernstein expansion. Since bounds computed by these enclosure methods are sound, this approach may be used reliably in software verification tools. Advantage is taken of the partial derivatives of the constraint functions involved in the system, firstly to reduce the branching factor by the use of bisection heuristics and secondly to permit the computation of bifurcation sets for systems of ordinary differential equations. The associated software development, Kodiak, is presented, along with examples of three different branch and bound problem types it implements.

A Methodology for Evaluating the Hygroscopic Behavior of Wood in Adaptive Building Skins using Motion Grammar

NASA Astrophysics Data System (ADS)

El-Dabaa, Rana; Abdelmohsen, Sherif

2018-05-01

The challenge in designing kinetic architecture lies in the lack of applying computational design and human computer interaction to successfully design intelligent and interactive interfaces. The use of ‘programmable materials’ as specifically fabricated composite materials that afford motion upon stimulation is promising for low-cost low-tech systems for kinetic facades in buildings. Despite efforts to develop working prototypes, there has been no clear methodological framework for understanding and controlling the behavior of programmable materials or for using them for such purposes. This paper introduces a methodology for evaluating the motion acquired from programmed material – resulting from the hygroscopic behavior of wood – through ‘motion grammar’. Motion grammar typically allows for the explanation of desired motion control in a computationally tractable method. The paper analyzed and evaluated motion parameters related to the hygroscopic properties and behavior of wood, and introduce a framework for tracking and controlling wood as a programmable material for kinetic architecture.

Improvements in the Scalability of the NASA Goddard Multiscale Modeling Framework for Hurricane Climate Studies

NASA Technical Reports Server (NTRS)

Shen, Bo-Wen; Tao, Wei-Kuo; Chern, Jiun-Dar

2007-01-01

Improving our understanding of hurricane inter-annual variability and the impact of climate change (e.g., doubling CO2 and/or global warming) on hurricanes brings both scientific and computational challenges to researchers. As hurricane dynamics involves multiscale interactions among synoptic-scale flows, mesoscale vortices, and small-scale cloud motions, an ideal numerical model suitable for hurricane studies should demonstrate its capabilities in simulating these interactions. The newly-developed multiscale modeling framework (MMF, Tao et al., 2007) and the substantial computing power by the NASA Columbia supercomputer show promise in pursuing the related studies, as the MMF inherits the advantages of two NASA state-of-the-art modeling components: the GEOS4/fvGCM and 2D GCEs. This article focuses on the computational issues and proposes a revised methodology to improve the MMF's performance and scalability. It is shown that this prototype implementation enables 12-fold performance improvements with 364 CPUs, thereby making it more feasible to study hurricane climate.

Hydra: a scalable proteomic search engine which utilizes the Hadoop distributed computing framework

PubMed Central

2012-01-01

Background For shotgun mass spectrometry based proteomics the most computationally expensive step is in matching the spectra against an increasingly large database of sequences and their post-translational modifications with known masses. Each mass spectrometer can generate data at an astonishingly high rate, and the scope of what is searched for is continually increasing. Therefore solutions for improving our ability to perform these searches are needed. Results We present a sequence database search engine that is specifically designed to run efficiently on the Hadoop MapReduce distributed computing framework. The search engine implements the K-score algorithm, generating comparable output for the same input files as the original implementation. The scalability of the system is shown, and the architecture required for the development of such distributed processing is discussed. Conclusion The software is scalable in its ability to handle a large peptide database, numerous modifications and large numbers of spectra. Performance scales with the number of processors in the cluster, allowing throughput to expand with the available resources. PMID:23216909

Nemo: an evolutionary and population genetics programming framework.

PubMed

Guillaume, Frédéric; Rougemont, Jacques

2006-10-15

Nemo is an individual-based, genetically explicit and stochastic population computer program for the simulation of population genetics and life-history trait evolution in a metapopulation context. It comes as both a C++ programming framework and an executable program file. Its object-oriented programming design gives it the flexibility and extensibility needed to implement a large variety of forward-time evolutionary models. It provides developers with abstract models allowing them to implement their own life-history traits and life-cycle events. Nemo offers a large panel of population models, from the Island model to lattice models with demographic or environmental stochasticity and a variety of already implemented traits (deleterious mutations, neutral markers and more), life-cycle events (mating, dispersal, aging, selection, etc.) and output operators for saving data and statistics. It runs on all major computer platforms including parallel computing environments. The source code, binaries and documentation are available under the GNU General Public License at http://nemo2.sourceforge.net.

Hydra: a scalable proteomic search engine which utilizes the Hadoop distributed computing framework.

PubMed

Lewis, Steven; Csordas, Attila; Killcoyne, Sarah; Hermjakob, Henning; Hoopmann, Michael R; Moritz, Robert L; Deutsch, Eric W; Boyle, John

2012-12-05

For shotgun mass spectrometry based proteomics the most computationally expensive step is in matching the spectra against an increasingly large database of sequences and their post-translational modifications with known masses. Each mass spectrometer can generate data at an astonishingly high rate, and the scope of what is searched for is continually increasing. Therefore solutions for improving our ability to perform these searches are needed. We present a sequence database search engine that is specifically designed to run efficiently on the Hadoop MapReduce distributed computing framework. The search engine implements the K-score algorithm, generating comparable output for the same input files as the original implementation. The scalability of the system is shown, and the architecture required for the development of such distributed processing is discussed. The software is scalable in its ability to handle a large peptide database, numerous modifications and large numbers of spectra. Performance scales with the number of processors in the cluster, allowing throughput to expand with the available resources.

Orientation-modulated attention effect on visual evoked potential: Application for PIN system using brain-computer interface.

PubMed

Wilaiprasitporn, Theerawit; Yagi, Tohru

2015-01-01

This research demonstrates the orientation-modulated attention effect on visual evoked potential. We combined this finding with our previous findings about the motion-modulated attention effect and used the result to develop novel visual stimuli for a personal identification number (PIN) application based on a brain-computer interface (BCI) framework. An electroencephalography amplifier with a single electrode channel was sufficient for our application. A computationally inexpensive algorithm and small datasets were used in processing. Seven healthy volunteers participated in experiments to measure offline performance. Mean accuracy was 83.3% at 13.9 bits/min. Encouraged by these results, we plan to continue developing the BCI-based personal identification application toward real-time systems.

Applications of airborne ultrasound in human-computer interaction.

PubMed

Dahl, Tobias; Ealo, Joao L; Bang, Hans J; Holm, Sverre; Khuri-Yakub, Pierre

2014-09-01

Airborne ultrasound is a rapidly developing subfield within human-computer interaction (HCI). Touchless ultrasonic interfaces and pen tracking systems are part of recent trends in HCI and are gaining industry momentum. This paper aims to provide the background and overview necessary to understand the capabilities of ultrasound and its potential future in human-computer interaction. The latest developments on the ultrasound transducer side are presented, focusing on capacitive micro-machined ultrasonic transducers, or CMUTs. Their introduction is an important step toward providing real, low-cost multi-sensor array and beam-forming options. We also provide a unified mathematical framework for understanding and analyzing algorithms used for ultrasound detection and tracking for some of the most relevant applications. Copyright © 2014. Published by Elsevier B.V.

A multitasking finite state architecture for computer control of an electric powertrain

DOE Office of Scientific and Technical Information (OSTI.GOV)

Burba, J.C.

1984-01-01

Finite state techniques provide a common design language between the control engineer and the computer engineer for event driven computer control systems. They simplify communication and provide a highly maintainable control system understandable by both. This paper describes the development of a control system for an electric vehicle powertrain utilizing finite state concepts. The basics of finite state automata are provided as a framework to discuss a unique multitasking software architecture developed for this application. The architecture employs conventional time-sliced techniques with task scheduling controlled by a finite state machine representation of the control strategy of the powertrain. The complexitiesmore » of excitation variable sampling in this environment are also considered.« less

Measuring coherence of computer-assisted likelihood ratio methods.

PubMed

Haraksim, Rudolf; Ramos, Daniel; Meuwly, Didier; Berger, Charles E H

2015-04-01

Measuring the performance of forensic evaluation methods that compute likelihood ratios (LRs) is relevant for both the development and the validation of such methods. A framework of performance characteristics categorized as primary and secondary is introduced in this study to help achieve such development and validation. Ground-truth labelled fingerprint data is used to assess the performance of an example likelihood ratio method in terms of those performance characteristics. Discrimination, calibration, and especially the coherence of this LR method are assessed as a function of the quantity and quality of the trace fingerprint specimen. Assessment of the coherence revealed a weakness of the comparison algorithm in the computer-assisted likelihood ratio method used. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

The Climate Data Analytic Services (CDAS) Framework.

NASA Astrophysics Data System (ADS)

Maxwell, T. P.; Duffy, D.

2016-12-01

Faced with unprecedented growth in climate data volume and demand, NASA has developed the Climate Data Analytic Services (CDAS) framework. This framework enables scientists to execute data processing workflows combining common analysis operations in a high performance environment close to the massive data stores at NASA. The data is accessed in standard (NetCDF, HDF, etc.) formats in a POSIX file system and processed using vetted climate data analysis tools (ESMF, CDAT, NCO, etc.). A dynamic caching architecture enables interactive response times. CDAS utilizes Apache Spark for parallelization and a custom array framework for processing huge datasets within limited memory spaces. CDAS services are accessed via a WPS API being developed in collaboration with the ESGF Compute Working Team to support server-side analytics for ESGF. The API can be accessed using either direct web service calls, a python script, a unix-like shell client, or a javascript-based web application. Client packages in python, scala, or javascript contain everything needed to make CDAS requests. The CDAS architecture brings together the tools, data storage, and high-performance computing required for timely analysis of large-scale data sets, where the data resides, to ultimately produce societal benefits. It is is currently deployed at NASA in support of the Collaborative REAnalysis Technical Environment (CREATE) project, which centralizes numerous global reanalysis datasets onto a single advanced data analytics platform. This service permits decision makers to investigate climate changes around the globe, inspect model trends and variability, and compare multiple reanalysis datasets.

EpiK: A Knowledge Base for Epidemiological Modeling and Analytics of Infectious Diseases

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hasan, S. M. Shamimul; Fox, Edward A.; Bisset, Keith

Computational epidemiology seeks to develop computational methods to study the distribution and determinants of health-related states or events (including disease), and the application of this study to the control of diseases and other health problems. Recent advances in computing and data sciences have led to the development of innovative modeling environments to support this important goal. The datasets used to drive the dynamic models as well as the data produced by these models presents unique challenges owing to their size, heterogeneity and diversity. These datasets form the basis of effective and easy to use decision support and analytical environments. Asmore » a result, it is important to develop scalable data management systems to store, manage and integrate these datasets. In this paper, we develop EpiK—a knowledge base that facilitates the development of decision support and analytical environments to support epidemic science. An important goal is to develop a framework that links the input as well as output datasets to facilitate effective spatio-temporal and social reasoning that is critical in planning and intervention analysis before and during an epidemic. The data management framework links modeling workflow data and its metadata using a controlled vocabulary. The metadata captures information about storage, the mapping between the linked model and the physical layout, and relationships to support services. EpiK is designed to support agent-based modeling and analytics frameworks—aggregate models can be seen as special cases and are thus supported. We use semantic web technologies to create a representation of the datasets that encapsulates both the location and the schema heterogeneity. The choice of RDF as a representation language is motivated by the diversity and growth of the datasets that need to be integrated. A query bank is developed—the queries capture a broad range of questions that can be posed and answered during a typical case study pertaining to disease outbreaks. The queries are constructed using SPARQL Protocol and RDF Query Language (SPARQL) over the EpiK. EpiK can hide schema and location heterogeneity while efficiently supporting queries that span the computational epidemiology modeling pipeline: from model construction to simulation output. As a result, we show that the performance of benchmark queries varies significantly with respect to the choice of hardware underlying the database and resource description framework (RDF) engine.« less

EpiK: A Knowledge Base for Epidemiological Modeling and Analytics of Infectious Diseases

DOE PAGES

Hasan, S. M. Shamimul; Fox, Edward A.; Bisset, Keith; ...

2017-11-06

Computational epidemiology seeks to develop computational methods to study the distribution and determinants of health-related states or events (including disease), and the application of this study to the control of diseases and other health problems. Recent advances in computing and data sciences have led to the development of innovative modeling environments to support this important goal. The datasets used to drive the dynamic models as well as the data produced by these models presents unique challenges owing to their size, heterogeneity and diversity. These datasets form the basis of effective and easy to use decision support and analytical environments. Asmore » a result, it is important to develop scalable data management systems to store, manage and integrate these datasets. In this paper, we develop EpiK—a knowledge base that facilitates the development of decision support and analytical environments to support epidemic science. An important goal is to develop a framework that links the input as well as output datasets to facilitate effective spatio-temporal and social reasoning that is critical in planning and intervention analysis before and during an epidemic. The data management framework links modeling workflow data and its metadata using a controlled vocabulary. The metadata captures information about storage, the mapping between the linked model and the physical layout, and relationships to support services. EpiK is designed to support agent-based modeling and analytics frameworks—aggregate models can be seen as special cases and are thus supported. We use semantic web technologies to create a representation of the datasets that encapsulates both the location and the schema heterogeneity. The choice of RDF as a representation language is motivated by the diversity and growth of the datasets that need to be integrated. A query bank is developed—the queries capture a broad range of questions that can be posed and answered during a typical case study pertaining to disease outbreaks. The queries are constructed using SPARQL Protocol and RDF Query Language (SPARQL) over the EpiK. EpiK can hide schema and location heterogeneity while efficiently supporting queries that span the computational epidemiology modeling pipeline: from model construction to simulation output. As a result, we show that the performance of benchmark queries varies significantly with respect to the choice of hardware underlying the database and resource description framework (RDF) engine.« less

The “Common Solutions” Strategy of the Experiment Support group at CERN for the LHC Experiments

NASA Astrophysics Data System (ADS)

Girone, M.; Andreeva, J.; Barreiro Megino, F. H.; Campana, S.; Cinquilli, M.; Di Girolamo, A.; Dimou, M.; Giordano, D.; Karavakis, E.; Kenyon, M. J.; Kokozkiewicz, L.; Lanciotti, E.; Litmaath, M.; Magini, N.; Negri, G.; Roiser, S.; Saiz, P.; Saiz Santos, M. D.; Schovancova, J.; Sciabà, A.; Spiga, D.; Trentadue, R.; Tuckett, D.; Valassi, A.; Van der Ster, D. C.; Shiers, J. D.

2012-12-01

After two years of LHC data taking, processing and analysis and with numerous changes in computing technology, a number of aspects of the experiments’ computing, as well as WLCG deployment and operations, need to evolve. As part of the activities of the Experiment Support group in CERN's IT department, and reinforced by effort from the EGI-InSPIRE project, we present work aimed at common solutions across all LHC experiments. Such solutions allow us not only to optimize development manpower but also offer lower long-term maintenance and support costs. The main areas cover Distributed Data Management, Data Analysis, Monitoring and the LCG Persistency Framework. Specific tools have been developed including the HammerCloud framework, automated services for data placement, data cleaning and data integrity (such as the data popularity service for CMS, the common Victor cleaning agent for ATLAS and CMS and tools for catalogue/storage consistency), the Dashboard Monitoring framework (job monitoring, data management monitoring, File Transfer monitoring) and the Site Status Board. This talk focuses primarily on the strategic aspects of providing such common solutions and how this relates to the overall goals of long-term sustainability and the relationship to the various WLCG Technical Evolution Groups. The success of the service components has given us confidence in the process, and has developed the trust of the stakeholders. We are now attempting to expand the development of common solutions into the more critical workflows. The first is a feasibility study of common analysis workflow execution elements between ATLAS and CMS. We look forward to additional common development in the future.

Argonne simulation framework for intelligent transportation systems

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ewing, T.; Doss, E.; Hanebutte, U.

1996-04-01

A simulation framework has been developed which defines a high-level architecture for a large-scale, comprehensive, scalable simulation of an Intelligent Transportation System (ITS). The simulator is designed to run on parallel computers and distributed (networked) computer systems; however, a version for a stand alone workstation is also available. The ITS simulator includes an Expert Driver Model (EDM) of instrumented ``smart`` vehicles with in-vehicle navigation units. The EDM is capable of performing optimal route planning and communicating with Traffic Management Centers (TMC). A dynamic road map data base is sued for optimum route planning, where the data is updated periodically tomore » reflect any changes in road or weather conditions. The TMC has probe vehicle tracking capabilities (display position and attributes of instrumented vehicles), and can provide 2-way interaction with traffic to provide advisories and link times. Both the in-vehicle navigation module and the TMC feature detailed graphical user interfaces that includes human-factors studies to support safety and operational research. Realistic modeling of variations of the posted driving speed are based on human factor studies that take into consideration weather, road conditions, driver`s personality and behavior and vehicle type. The simulator has been developed on a distributed system of networked UNIX computers, but is designed to run on ANL`s IBM SP-X parallel computer system for large scale problems. A novel feature of the developed simulator is that vehicles will be represented by autonomous computer processes, each with a behavior model which performs independent route selection and reacts to external traffic events much like real vehicles. Vehicle processes interact with each other and with ITS components by exchanging messages. With this approach, one will be able to take advantage of emerging massively parallel processor (MPP) systems.« less

High Definition Information Systems. Report Prepared by the Subcommittee on Technology and Competitiveness Transmitted to the Committee on Science, Space, and Technology. House of Representatives, One Hundred Second Congress, Second Session.

ERIC Educational Resources Information Center

Congress of the U.S., Washington, DC. House Committee on Science, Space and Technology.

The integration of television into a digital framework makes possible the merger of television and computers. Development of a digital system will permit the consumer to receive television and computer images on the same screen at a quality approaching 35mm film. If fiber optic telecommunications lines are linked to the home and standards are…

Final Report: PAGE: Policy Analytics Generation Engine

DTIC Science & Technology

2016-08-12

develop a parallel framework for it. We also developed policies and methods by which a group of defensive resources (e.g. checkpoints) could be...Sarit Kraus. Learning to Reveal Information in Repeated Human -Computer Negotiation, Human -Agent Interaction Design and Models Workshop 2012. 04-JUN...Joseph Keshet, Sarit Kraus. Predicting Human Strategic Decisions Using Facial Expressions, International Joint Conference on Artificial

A Computational Framework to Optimize Subject-Specific Hemodialysis Blood Flow Rate to Prevent Intimal Hyperplasia

NASA Astrophysics Data System (ADS)

Mahmoudzadeh, Javid; Wlodarczyk, Marta; Cassel, Kevin

2017-11-01

Development of excessive intimal hyperplasia (IH) in the cephalic vein of renal failure patients who receive chronic hemodialysis treatment results in vascular access failure and multiple treatment complications. Specifically, cephalic arch stenosis (CAS) is known to exacerbate hypertensive blood pressure, thrombosis, and subsequent cardiovascular incidents that would necessitate costly interventional procedures with low success rates. It has been hypothesized that excessive blood flow rate post access maturation which strongly violates the venous homeostasis is the main hemodynamic factor that orchestrates the onset and development of CAS. In this article, a computational framework based on a strong coupling of computational fluid dynamics (CFD) and shape optimization is proposed that aims to identify the effective blood flow rate on a patient-specific basis that avoids the onset of CAS while providing the adequate blood flow rate required to facilitate hemodialysis. This effective flow rate can be achieved through implementation of Miller's surgical banding method after the maturation of the arteriovenous fistula and is rooted in the relaxation of wall stresses back to a homeostatic target value. The results are indicative that this optimized hemodialysis blood flow rate is, in fact, a subject-specific value that can be assessed post vascular access maturation and prior to the initiation of chronic hemodialysis treatment as a mitigative action against CAS-related access failure. This computational technology can be employed for individualized dialysis treatment.

FAST: framework for heterogeneous medical image computing and visualization.

PubMed

Smistad, Erik; Bozorgi, Mohammadmehdi; Lindseth, Frank

2015-11-01

Computer systems are becoming increasingly heterogeneous in the sense that they consist of different processors, such as multi-core CPUs and graphic processing units. As the amount of medical image data increases, it is crucial to exploit the computational power of these processors. However, this is currently difficult due to several factors, such as driver errors, processor differences, and the need for low-level memory handling. This paper presents a novel FrAmework for heterogeneouS medical image compuTing and visualization (FAST). The framework aims to make it easier to simultaneously process and visualize medical images efficiently on heterogeneous systems. FAST uses common image processing programming paradigms and hides the details of memory handling from the user, while enabling the use of all processors and cores on a system. The framework is open-source, cross-platform and available online. Code examples and performance measurements are presented to show the simplicity and efficiency of FAST. The results are compared to the insight toolkit (ITK) and the visualization toolkit (VTK) and show that the presented framework is faster with up to 20 times speedup on several common medical imaging algorithms. FAST enables efficient medical image computing and visualization on heterogeneous systems. Code examples and performance evaluations have demonstrated that the toolkit is both easy to use and performs better than existing frameworks, such as ITK and VTK.

A K-6 Computational Thinking Curriculum Framework: Implications for Teacher Knowledge

ERIC Educational Resources Information Center

Angeli, Charoula; Voogt, Joke; Fluck, Andrew; Webb, Mary; Cox, Margaret; Malyn-Smith, Joyce; Zagami, Jason

2016-01-01

Adding computer science as a separate school subject to the core K-6 curriculum is a complex issue with educational challenges. The authors herein address two of these challenges: (1) the design of the curriculum based on a generic computational thinking framework, and (2) the knowledge teachers need to teach the curriculum. The first issue is…

BioQueue: a novel pipeline framework to accelerate bioinformatics analysis.

PubMed

Yao, Li; Wang, Heming; Song, Yuanyuan; Sui, Guangchao

2017-10-15

With the rapid development of Next-Generation Sequencing, a large amount of data is now available for bioinformatics research. Meanwhile, the presence of many pipeline frameworks makes it possible to analyse these data. However, these tools concentrate mainly on their syntax and design paradigms, and dispatch jobs based on users' experience about the resources needed by the execution of a certain step in a protocol. As a result, it is difficult for these tools to maximize the potential of computing resources, and avoid errors caused by overload, such as memory overflow. Here, we have developed BioQueue, a web-based framework that contains a checkpoint before each step to automatically estimate the system resources (CPU, memory and disk) needed by the step and then dispatch jobs accordingly. BioQueue possesses a shell command-like syntax instead of implementing a new script language, which means most biologists without computer programming background can access the efficient queue system with ease. BioQueue is freely available at https://github.com/liyao001/BioQueue. The extensive documentation can be found at http://bioqueue.readthedocs.io. li_yao@outlook.com or gcsui@nefu.edu.cn. Supplementary data are available at Bioinformatics online. © The Author (2017). Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com

Retrieving and Indexing Spatial Data in the Cloud Computing Environment

NASA Astrophysics Data System (ADS)

Wang, Yonggang; Wang, Sheng; Zhou, Daliang

In order to solve the drawbacks of spatial data storage in common Cloud Computing platform, we design and present a framework for retrieving, indexing, accessing and managing spatial data in the Cloud environment. An interoperable spatial data object model is provided based on the Simple Feature Coding Rules from the OGC such as Well Known Binary (WKB) and Well Known Text (WKT). And the classic spatial indexing algorithms like Quad-Tree and R-Tree are re-designed in the Cloud Computing environment. In the last we develop a prototype software based on Google App Engine to implement the proposed model.

A hierarchical spatial framework and database for the national river fish habitat condition assessment

USGS Publications Warehouse

Wang, L.; Infante, D.; Esselman, P.; Cooper, A.; Wu, D.; Taylor, W.; Beard, D.; Whelan, G.; Ostroff, A.

2011-01-01

Fisheries management programs, such as the National Fish Habitat Action Plan (NFHAP), urgently need a nationwide spatial framework and database for health assessment and policy development to protect and improve riverine systems. To meet this need, we developed a spatial framework and database using National Hydrography Dataset Plus (I-.100,000-scale); http://www.horizon-systems.com/nhdplus). This framework uses interconfluence river reaches and their local and network catchments as fundamental spatial river units and a series of ecological and political spatial descriptors as hierarchy structures to allow users to extract or analyze information at spatial scales that they define. This database consists of variables describing channel characteristics, network position/connectivity, climate, elevation, gradient, and size. It contains a series of catchment-natural and human-induced factors that are known to influence river characteristics. Our framework and database assembles all river reaches and their descriptors in one place for the first time for the conterminous United States. This framework and database provides users with the capability of adding data, conducting analyses, developing management scenarios and regulation, and tracking management progresses at a variety of spatial scales. This database provides the essential data needs for achieving the objectives of NFHAP and other management programs. The downloadable beta version database is available at http://ec2-184-73-40-15.compute-1.amazonaws.com/nfhap/main/.

Teaching Non-Recursive Binary Searching: Establishing a Conceptual Framework.

ERIC Educational Resources Information Center

Magel, E. Terry

1989-01-01

Discusses problems associated with teaching non-recursive binary searching in computer language classes, and describes a teacher-directed dialog based on dictionary use that helps students use their previous searching experiences to conceptualize the binary search process. Algorithmic development is discussed and appropriate classroom discussion…

Ensuring long-term utility of the AOP framework and knowledge for multiple stakeholders

EPA Science Inventory

1.Introduction There is a need to increase the development and implementation of predictive approaches to support chemical safety assessment. These predictive approaches feature generation of data from tools such as computational models, pathway-based in vitro assays, and short-t...

Virtual Control Systems Environment (VCSE)

ScienceCinema

Atkins, Will

2018-02-14

Will Atkins, a Sandia National Laboratories computer engineer discusses cybersecurity research work for process control systems. Will explains his work on the Virtual Control Systems Environment project to develop a modeling and simulation framework of the U.S. electric grid in order to study and mitigate possible cyberattacks on infrastructure.

Development of a Flexible Framework of Common Hypersonic Navier-Strokes Meshes for the Space Shuttle Orbiter

NASA Technical Reports Server (NTRS)

Alter, Stephen J.; Reuthler, James J.; McDaniel, Ryan D.

2003-01-01

A flexible framework for the development of block structured volume grids for hypersonic Navier-Stokes flow simulations was developed for analysis of the Shuttle Orbiter Columbia. The development of the flexible framework, resulted in an ability to quickly generate meshes to directly correlate solutions contributed by participating groups on a common surface mesh, providing confidence for the extension of the envelope of solutions and damage scenarios. The framework draws on the experience of NASA Langely and NASA Ames Research Centers in structured grid generation, and consists of a grid generation process that is implemented through a division of responsibilities. The nominal division of labor consisted of NASA Johnson Space Center coordinating the damage scenarios to be analyzed by the Aerothermodynamics Columbia Accident Investigation (CAI) team, Ames developing the surface grids that described the computational volume about the orbiter, and Langely improving grid quality of Ames generated data and constructing the final volume grids. Distributing the work among the participants in the Aerothermodynamic CIA team resulted in significantly less time required to construct complete meshes than possible by any individual participant. The approach demonstrated that the One-NASA grid generation team could sustain the demand for new meshes to explore new damage scenarios within a aggressive timeline.

CSP-TSM: Optimizing the performance of Riemannian tangent space mapping using common spatial pattern for MI-BCI.

PubMed

Kumar, Shiu; Mamun, Kabir; Sharma, Alok

2017-12-01

Classification of electroencephalography (EEG) signals for motor imagery based brain computer interface (MI-BCI) is an exigent task and common spatial pattern (CSP) has been extensively explored for this purpose. In this work, we focused on developing a new framework for classification of EEG signals for MI-BCI. We propose a single band CSP framework for MI-BCI that utilizes the concept of tangent space mapping (TSM) in the manifold of covariance matrices. The proposed method is named CSP-TSM. Spatial filtering is performed on the bandpass filtered MI EEG signal. Riemannian tangent space is utilized for extracting features from the spatial filtered signal. The TSM features are then fused with the CSP variance based features and feature selection is performed using Lasso. Linear discriminant analysis (LDA) is then applied to the selected features and finally classification is done using support vector machine (SVM) classifier. The proposed framework gives improved performance for MI EEG signal classification in comparison with several competing methods. Experiments conducted shows that the proposed framework reduces the overall classification error rate for MI-BCI by 3.16%, 5.10% and 1.70% (for BCI Competition III dataset IVa, BCI Competition IV Dataset I and BCI Competition IV Dataset IIb, respectively) compared to the conventional CSP method under the same experimental settings. The proposed CSP-TSM method produces promising results when compared with several competing methods in this paper. In addition, the computational complexity is less compared to that of TSM method. Our proposed CSP-TSM framework can be potentially used for developing improved MI-BCI systems. Copyright © 2017 Elsevier Ltd. All rights reserved.

Application of Adverse Outcome Pathways to U.S. EPA’s Endocrine Disruptor Screening Program

PubMed Central

Noyes, Pamela D.; Casey, Warren M.; Dix, David J.

2017-01-01

Background: The U.S. EPA’s Endocrine Disruptor Screening Program (EDSP) screens and tests environmental chemicals for potential effects in estrogen, androgen, and thyroid hormone pathways, and it is one of the only regulatory programs designed around chemical mode of action. Objectives: This review describes the EDSP’s use of adverse outcome pathway (AOP) and toxicity pathway frameworks to organize and integrate diverse biological data for evaluating the endocrine activity of chemicals. Using these frameworks helps to establish biologically plausible links between endocrine mechanisms and apical responses when those end points are not measured in the same assay. Results: Pathway frameworks can facilitate a weight of evidence determination of a chemical’s potential endocrine activity, identify data gaps, aid study design, direct assay development, and guide testing strategies. Pathway frameworks also can be used to evaluate the performance of computational approaches as alternatives for low-throughput and animal-based assays and predict downstream key events. In cases where computational methods can be validated based on performance, they may be considered as alternatives to specific assays or end points. Conclusions: A variety of biological systems affect apical end points used in regulatory risk assessments, and without mechanistic data, an endocrine mode of action cannot be determined. Because the EDSP was designed to consider mode of action, toxicity pathway and AOP concepts are a natural fit. Pathway frameworks have diverse applications to endocrine screening and testing. An estrogen pathway example is presented, and similar approaches are being used to evaluate alternative methods and develop predictive models for androgen and thyroid pathways. https://doi.org/10.1289/EHP1304 PMID:28934726

Framework of distributed coupled atmosphere-ocean-wave modeling system

NASA Astrophysics Data System (ADS)

Wen, Yuanqiao; Huang, Liwen; Deng, Jian; Zhang, Jinfeng; Wang, Sisi; Wang, Lijun

2006-05-01

In order to research the interactions between the atmosphere and ocean as well as their important role in the intensive weather systems of coastal areas, and to improve the forecasting ability of the hazardous weather processes of coastal areas, a coupled atmosphere-ocean-wave modeling system has been developed. The agent-based environment framework for linking models allows flexible and dynamic information exchange between models. For the purpose of flexibility, portability and scalability, the framework of the whole system takes a multi-layer architecture that includes a user interface layer, computational layer and service-enabling layer. The numerical experiment presented in this paper demonstrates the performance of the distributed coupled modeling system.

DEEP: a general computational framework for predicting enhancers

PubMed Central

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

2015-01-01

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/. PMID:25378307

Multiscale framework for predicting the coupling between deformation and fluid diffusion in porous rocks

DOE Office of Scientific and Technical Information (OSTI.GOV)

Andrade, José E; Rudnicki, John W

2012-12-14

In this project, a predictive multiscale framework will be developed to simulate the strong coupling between solid deformations and fluid diffusion in porous rocks. We intend to improve macroscale modeling by incorporating fundamental physical modeling at the microscale in a computationally efficient way. This is an essential step toward further developments in multiphysics modeling, linking hydraulic, thermal, chemical, and geomechanical processes. This research will focus on areas where severe deformations are observed, such as deformation bands, where classical phenomenology breaks down. Multiscale geometric complexities and key geomechanical and hydraulic attributes of deformation bands (e.g., grain sliding and crushing, and poremore » collapse, causing interstitial fluid expulsion under saturated conditions), can significantly affect the constitutive response of the skeleton and the intrinsic permeability. Discrete mechanics (DEM) and the lattice Boltzmann method (LBM) will be used to probe the microstructure---under the current state---to extract the evolution of macroscopic constitutive parameters and the permeability tensor. These evolving macroscopic constitutive parameters are then directly used in continuum scale predictions using the finite element method (FEM) accounting for the coupled solid deformation and fluid diffusion. A particularly valuable aspect of this research is the thorough quantitative verification and validation program at different scales. The multiscale homogenization framework will be validated using X-ray computed tomography and 3D digital image correlation in situ at the Advanced Photon Source in Argonne National Laboratories. Also, the hierarchical computations at the specimen level will be validated using the aforementioned techniques in samples of sandstone undergoing deformation bands.« less

Rapid indirect trajectory optimization on highly parallel computing architectures

NASA Astrophysics Data System (ADS)

Antony, Thomas

Trajectory optimization is a field which can benefit greatly from the advantages offered by parallel computing. The current state-of-the-art in trajectory optimization focuses on the use of direct optimization methods, such as the pseudo-spectral method. These methods are favored due to their ease of implementation and large convergence regions while indirect methods have largely been ignored in the literature in the past decade except for specific applications in astrodynamics. It has been shown that the shortcomings conventionally associated with indirect methods can be overcome by the use of a continuation method in which complex trajectory solutions are obtained by solving a sequence of progressively difficult optimization problems. High performance computing hardware is trending towards more parallel architectures as opposed to powerful single-core processors. Graphics Processing Units (GPU), which were originally developed for 3D graphics rendering have gained popularity in the past decade as high-performance, programmable parallel processors. The Compute Unified Device Architecture (CUDA) framework, a parallel computing architecture and programming model developed by NVIDIA, is one of the most widely used platforms in GPU computing. GPUs have been applied to a wide range of fields that require the solution of complex, computationally demanding problems. A GPU-accelerated indirect trajectory optimization methodology which uses the multiple shooting method and continuation is developed using the CUDA platform. The various algorithmic optimizations used to exploit the parallelism inherent in the indirect shooting method are described. The resulting rapid optimal control framework enables the construction of high quality optimal trajectories that satisfy problem-specific constraints and fully satisfy the necessary conditions of optimality. The benefits of the framework are highlighted by construction of maximum terminal velocity trajectories for a hypothetical long range weapon system. The techniques used to construct an initial guess from an analytic near-ballistic trajectory and the methods used to formulate the necessary conditions of optimality in a manner that is transparent to the designer are discussed. Various hypothetical mission scenarios that enforce different combinations of initial, terminal, interior point and path constraints demonstrate the rapid construction of complex trajectories without requiring any a-priori insight into the structure of the solutions. Trajectory problems of this kind were previously considered impractical to solve using indirect methods. The performance of the GPU-accelerated solver is found to be 2x--4x faster than MATLAB's bvp4c, even while running on GPU hardware that is five years behind the state-of-the-art.

Metrics for comparing neuronal tree shapes based on persistent homology.

PubMed

Li, Yanjie; Wang, Dingkang; Ascoli, Giorgio A; Mitra, Partha; Wang, Yusu

2017-01-01

As more and more neuroanatomical data are made available through efforts such as NeuroMorpho.Org and FlyCircuit.org, the need to develop computational tools to facilitate automatic knowledge discovery from such large datasets becomes more urgent. One fundamental question is how best to compare neuron structures, for instance to organize and classify large collection of neurons. We aim to develop a flexible yet powerful framework to support comparison and classification of large collection of neuron structures efficiently. Specifically we propose to use a topological persistence-based feature vectorization framework. Existing methods to vectorize a neuron (i.e, convert a neuron to a feature vector so as to support efficient comparison and/or searching) typically rely on statistics or summaries of morphometric information, such as the average or maximum local torque angle or partition asymmetry. These simple summaries have limited power in encoding global tree structures. Based on the concept of topological persistence recently developed in the field of computational topology, we vectorize each neuron structure into a simple yet informative summary. In particular, each type of information of interest can be represented as a descriptor function defined on the neuron tree, which is then mapped to a simple persistence-signature. Our framework can encode both local and global tree structure, as well as other information of interest (electrophysiological or dynamical measures), by considering multiple descriptor functions on the neuron. The resulting persistence-based signature is potentially more informative than simple statistical summaries (such as average/mean/max) of morphometric quantities-Indeed, we show that using a certain descriptor function will give a persistence-based signature containing strictly more information than the classical Sholl analysis. At the same time, our framework retains the efficiency associated with treating neurons as points in a simple Euclidean feature space, which would be important for constructing efficient searching or indexing structures over them. We present preliminary experimental results to demonstrate the effectiveness of our persistence-based neuronal feature vectorization framework.

Metrics for comparing neuronal tree shapes based on persistent homology

PubMed Central

Li, Yanjie; Wang, Dingkang; Ascoli, Giorgio A.; Mitra, Partha

2017-01-01

As more and more neuroanatomical data are made available through efforts such as NeuroMorpho.Org and FlyCircuit.org, the need to develop computational tools to facilitate automatic knowledge discovery from such large datasets becomes more urgent. One fundamental question is how best to compare neuron structures, for instance to organize and classify large collection of neurons. We aim to develop a flexible yet powerful framework to support comparison and classification of large collection of neuron structures efficiently. Specifically we propose to use a topological persistence-based feature vectorization framework. Existing methods to vectorize a neuron (i.e, convert a neuron to a feature vector so as to support efficient comparison and/or searching) typically rely on statistics or summaries of morphometric information, such as the average or maximum local torque angle or partition asymmetry. These simple summaries have limited power in encoding global tree structures. Based on the concept of topological persistence recently developed in the field of computational topology, we vectorize each neuron structure into a simple yet informative summary. In particular, each type of information of interest can be represented as a descriptor function defined on the neuron tree, which is then mapped to a simple persistence-signature. Our framework can encode both local and global tree structure, as well as other information of interest (electrophysiological or dynamical measures), by considering multiple descriptor functions on the neuron. The resulting persistence-based signature is potentially more informative than simple statistical summaries (such as average/mean/max) of morphometric quantities—Indeed, we show that using a certain descriptor function will give a persistence-based signature containing strictly more information than the classical Sholl analysis. At the same time, our framework retains the efficiency associated with treating neurons as points in a simple Euclidean feature space, which would be important for constructing efficient searching or indexing structures over them. We present preliminary experimental results to demonstrate the effectiveness of our persistence-based neuronal feature vectorization framework. PMID:28809960

a Web-Based Framework for Visualizing Industrial Spatiotemporal Distribution Using Standard Deviational Ellipse and Shifting Routes of Gravity Centers

NASA Astrophysics Data System (ADS)

Song, Y.; Gui, Z.; Wu, H.; Wei, Y.

2017-09-01

Analysing spatiotemporal distribution patterns and its dynamics of different industries can help us learn the macro-level developing trends of those industries, and in turn provides references for industrial spatial planning. However, the analysis process is challenging task which requires an easy-to-understand information presentation mechanism and a powerful computational technology to support the visual analytics of big data on the fly. Due to this reason, this research proposes a web-based framework to enable such a visual analytics requirement. The framework uses standard deviational ellipse (SDE) and shifting route of gravity centers to show the spatial distribution and yearly developing trends of different enterprise types according to their industry categories. The calculation of gravity centers and ellipses is paralleled using Apache Spark to accelerate the processing. In the experiments, we use the enterprise registration dataset in Mainland China from year 1960 to 2015 that contains fine-grain location information (i.e., coordinates of each individual enterprise) to demonstrate the feasibility of this framework. The experiment result shows that the developed visual analytics method is helpful to understand the multi-level patterns and developing trends of different industries in China. Moreover, the proposed framework can be used to analyse any nature and social spatiotemporal point process with large data volume, such as crime and disease.