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.

A FRAMEWORK FOR A COMPUTATIONAL TOXICOLOGY RESEARCH PROGRAM IN ORD

EPA Science Inventory

"A Framework for a Computational Toxicology Research Program in ORD" was drafted by a Technical Writing Team having representatives from all of ORD's Laboratories and Centers. The document describes a framework for the development of an program within ORD to utilize approaches d...

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.

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.

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…

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)

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…

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 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.

[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 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.

Simulation Framework for Intelligent Transportation Systems

DOT National Transportation Integrated Search

1996-10-01

A simulation framework has been developed for a large-scale, comprehensive, scaleable simulation of an Intelligent Transportation System. The simulator is designed for running on parellel computers and distributed (networked) computer systems, but ca...

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…

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

EPA Science Inventory

Abstract

The EPA sponsored a workshop held September 29-30, 2003 at the EPA in RTP that was focused on a proposal entitled "A Framework for a Computational Toxicology Research Program in ORD" (www.epa.gov/computox). Computational toxicology is a new research ini...

Development of Parallel Computing Framework to Enhance Radiation Transport Code Capabilities for Rare Isotope Beam Facility Design

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

Kostin, Mikhail; Mokhov, Nikolai; Niita, Koji

A 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. It is intended to be used with older radiation transport codes implemented in Fortran77, Fortran 90 or C. 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 developed and tested in conjunction with the MARS15 code. It is possible to use it with other codes such as PHITS, FLUKA andmore » MCNP after certain adjustments. Besides the parallel computing functionality, the framework offers a checkpoint facility that allows restarting calculations with a saved checkpoint file. The checkpoint facility can be used in single process calculations as well as in the parallel regime. The framework 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 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.

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.

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.

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.

Computational structural mechanics methods research using an evolving framework

NASA Technical Reports Server (NTRS)

Knight, N. F., Jr.; Lotts, C. G.; Gillian, R. E.

1990-01-01

Advanced structural analysis and computational methods that exploit high-performance computers are being developed in a computational structural mechanics research activity sponsored by the NASA Langley Research Center. These new methods are developed in an evolving framework and applied to representative complex structural analysis problems from the aerospace industry. An overview of the methods development environment is presented, and methods research areas are described. Selected application studies are also summarized.

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

The following reports are presented on this project:A first year progress report on: Development of a Dynamically Configurable,Object-Oriented Framework for Distributed, Multi-modal Computational Aerospace Systems Simulation; A second year progress report on: Development of a Dynamically Configurable, Object-Oriented Framework for Distributed, Multi-modal Computational Aerospace Systems Simulation; An Extensible, Interchangeable and Sharable Database Model for Improving Multidisciplinary Aircraft Design; Interactive, Secure Web-enabled Aircraft Engine Simulation Using XML Databinding Integration; and Improving the Aircraft Design Process Using Web-based Modeling and Simulation.

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.

Computable visually observed phenotype ontological framework for plants

PubMed Central

2011-01-01

Background The ability to search for and precisely compare similar phenotypic appearances within and across species has vast potential in plant science and genetic research. The difficulty in doing so lies in the fact that many visual phenotypic data, especially visually observed phenotypes that often times cannot be directly measured quantitatively, are in the form of text annotations, and these descriptions are plagued by semantic ambiguity, heterogeneity, and low granularity. Though several bio-ontologies have been developed to standardize phenotypic (and genotypic) information and permit comparisons across species, these semantic issues persist and prevent precise analysis and retrieval of information. A framework suitable for the modeling and analysis of precise computable representations of such phenotypic appearances is needed. Results We have developed a new framework called the Computable Visually Observed Phenotype Ontological Framework for plants. This work provides a novel quantitative view of descriptions of plant phenotypes that leverages existing bio-ontologies and utilizes a computational approach to capture and represent domain knowledge in a machine-interpretable form. This is accomplished by means of a robust and accurate semantic mapping module that automatically maps high-level semantics to low-level measurements computed from phenotype imagery. The framework was applied to two different plant species with semantic rules mined and an ontology constructed. Rule quality was evaluated and showed high quality rules for most semantics. This framework also facilitates automatic annotation of phenotype images and can be adopted by different plant communities to aid in their research. Conclusions The Computable Visually Observed Phenotype Ontological Framework for plants has been developed for more efficient and accurate management of visually observed phenotypes, which play a significant role in plant genomics research. The uniqueness of this framework is its ability to bridge the knowledge of informaticians and plant science researchers by translating descriptions of visually observed phenotypes into standardized, machine-understandable representations, thus enabling the development of advanced information retrieval and phenotype annotation analysis tools for the plant science community. PMID:21702966

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 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…

Framework for computationally-predicted AOPs

EPA Science Inventory

Framework for computationally-predicted AOPs Given that there are a vast number of existing and new chemicals in the commercial pipeline, emphasis is placed on developing high throughput screening (HTS) methods for hazard prediction. Adverse Outcome Pathways (AOPs) represent a...

An Adaptive Sensor Mining Framework for Pervasive Computing Applications

NASA Astrophysics Data System (ADS)

Rashidi, Parisa; Cook, Diane J.

Analyzing sensor data in pervasive computing applications brings unique challenges to the KDD community. The challenge is heightened when the underlying data source is dynamic and the patterns change. We introduce a new adaptive mining framework that detects patterns in sensor data, and more importantly, adapts to the changes in the underlying model. In our framework, the frequent and periodic patterns of data are first discovered by the Frequent and Periodic Pattern Miner (FPPM) algorithm; and then any changes in the discovered patterns over the lifetime of the system are discovered by the Pattern Adaptation Miner (PAM) algorithm, in order to adapt to the changing environment. This framework also captures vital context information present in pervasive computing applications, such as the startup triggers and temporal information. In this paper, we present a description of our mining framework and validate the approach using data collected in the CASAS smart home testbed.

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.

ELM Meets Urban Big Data Analysis: Case Studies

PubMed Central

Chen, Huajun; Chen, Jiaoyan

2016-01-01

In the latest years, the rapid progress of urban computing has engendered big issues, which creates both opportunities and challenges. The heterogeneous and big volume of data and the big difference between physical and virtual worlds have resulted in lots of problems in quickly solving practical problems in urban computing. In this paper, we propose a general application framework of ELM for urban computing. We present several real case studies of the framework like smog-related health hazard prediction and optimal retain store placement. Experiments involving urban data in China show the efficiency, accuracy, and flexibility of our proposed framework. PMID:27656203

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.

Digital data acquisition for a CAD/CAM-fabricated titanium framework and zirconium oxide restorations for an implant-supported fixed complete dental prosthesis.

PubMed

Lin, Wei-Shao; Metz, Michael J; Pollini, Adrien; Ntounis, Athanasios; Morton, Dean

2014-12-01

This dental technique report describes a digital workflow with digital data acquisition at the implant level, computer-aided design and computer-aided manufacturing fabricated, tissue-colored, anodized titanium framework, individually luted zirconium oxide restorations, and autopolymerizing injection-molded acrylic resin to fabricate an implant-supported, metal-ceramic-resin fixed complete dental prosthesis in an edentulous mandible. The 1-step computer-aided design and computer-aided manufacturing fabrication of titanium framework and zirconium oxide restorations can provide a cost-effective alternative to the conventional metal-resin fixed complete dental prosthesis. Copyright © 2014 Editorial Council for the Journal of Prosthetic Dentistry. Published by Elsevier Inc. All rights reserved.

[Computer aided design and rapid manufacturing of removable partial denture frameworks].

PubMed

Han, Jing; Lü, Pei-jun; Wang, Yong

2010-08-01

To introduce a method of digital modeling and fabricating removable partial denture (RPD) frameworks using self-developed software for RPD design and rapid manufacturing system. The three-dimensional data of two partially dentate dental casts were obtained using a three-dimensional crossing section scanner. Self-developed software package for RPD design was used to decide the path of insertion and to design different components of RPD frameworks. The components included occlusal rest, clasp, lingual bar, polymeric retention framework and maxillary major connector. The design procedure for the components was as following: first, determine the outline of the component. Second, build the tissue surface of the component using the scanned data within the outline. Third, preset cross section was used to produce the polished surface. Finally, different RPD components were modeled respectively and connected by minor connectors to form an integrated RPD framework. The finished data were imported into a self-developed selective laser melting (SLM) machine and metal frameworks were fabricated directly. RPD frameworks for the two scanned dental casts were modeled with this self-developed program and metal RPD frameworks were successfully fabricated using SLM method. The finished metal frameworks fit well on the plaster models. The self-developed computer aided design and computer aided manufacture (CAD-CAM) system for RPD design and fabrication has completely independent intellectual property rights. It provides a new method of manufacturing metal RPD frameworks.

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.

JACOB: an enterprise framework for computational chemistry.

PubMed

Waller, Mark P; Dresselhaus, Thomas; Yang, Jack

2013-06-15

Here, we present just a collection of beans (JACOB): an integrated batch-based framework designed for the rapid development of computational chemistry applications. The framework expedites developer productivity by handling the generic infrastructure tier, and can be easily extended by user-specific scientific code. Paradigms from enterprise software engineering were rigorously applied to create a scalable, testable, secure, and robust framework. A centralized web application is used to configure and control the operation of the framework. The application-programming interface provides a set of generic tools for processing large-scale noninteractive jobs (e.g., systematic studies), or for coordinating systems integration (e.g., complex workflows). The code for the JACOB framework is open sourced and is available at: www.wallerlab.org/jacob. Copyright © 2013 Wiley Periodicals, Inc.

HCI∧2 framework: a software framework for multimodal human-computer interaction systems.

PubMed

Shen, Jie; Pantic, Maja

2013-12-01

This paper presents a novel software framework for the development and research in the area of multimodal human-computer interface (MHCI) systems. The proposed software framework, which is called the HCI∧2 Framework, is built upon publish/subscribe (P/S) architecture. It implements a shared-memory-based data transport protocol for message delivery and a TCP-based system management protocol. The latter ensures that the integrity of system structure is maintained at runtime. With the inclusion of bridging modules, the HCI∧2 Framework is interoperable with other software frameworks including Psyclone and ActiveMQ. In addition to the core communication middleware, we also present the integrated development environment (IDE) of the HCI∧2 Framework. It provides a complete graphical environment to support every step in a typical MHCI system development process, including module development, debugging, packaging, and management, as well as the whole system management and testing. The quantitative evaluation indicates that our framework outperforms other similar tools in terms of average message latency and maximum data throughput under a typical single PC scenario. To demonstrate HCI∧2 Framework's capabilities in integrating heterogeneous modules, we present several example modules working with a variety of hardware and software. We also present an example of a full system developed using the proposed HCI∧2 Framework, which is called the CamGame system and represents a computer game based on hand-held marker(s) and low-cost camera(s).

Cloud computing strategic framework (FY13 - FY15).

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

Arellano, Lawrence R.; Arroyo, Steven C.; Giese, Gerald J.

This document presents an architectural framework (plan) and roadmap for the implementation of a robust Cloud Computing capability at Sandia National Laboratories. It is intended to be a living document and serve as the basis for detailed implementation plans, project proposals and strategic investment requests.

The Unlock Project: a Python-based framework for practical brain-computer interface communication "app" development.

PubMed

Brumberg, Jonathan S; Lorenz, Sean D; Galbraith, Byron V; Guenther, Frank H

2012-01-01

In this paper we present a framework for reducing the development time needed for creating applications for use in non-invasive brain-computer interfaces (BCI). Our framework is primarily focused on facilitating rapid software "app" development akin to current efforts in consumer portable computing (e.g. smart phones and tablets). This is accomplished by handling intermodule communication without direct user or developer implementation, instead relying on a core subsystem for communication of standard, internal data formats. We also provide a library of hardware interfaces for common mobile EEG platforms for immediate use in BCI applications. A use-case example is described in which a user with amyotrophic lateral sclerosis participated in an electroencephalography-based BCI protocol developed using the proposed framework. We show that our software environment is capable of running in real-time with updates occurring 50-60 times per second with limited computational overhead (5 ms system lag) while providing accurate data acquisition and signal analysis.

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 Framework for Measuring Student Learning Gains and Engagement in an Introductory Computing Course: A Preliminary Report of Findings

ERIC Educational Resources Information Center

Lim, Billy; Hosack, Bryan; Vogt, Paul

2012-01-01

This paper describes a framework for measuring student learning gains and engagement in a Computer Science 1 (CS 1) / Information Systems 1 (IS 1) course. The framework is designed for a CS1/IS1 course as it has been traditionally taught over the years as well as when it is taught using a new pedagogical approach with Web services. It enables the…

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

Real-time tracking of visually attended objects in virtual environments and its application to LOD.

PubMed

Lee, Sungkil; Kim, Gerard Jounghyun; Choi, Seungmoon

2009-01-01

This paper presents a real-time framework for computationally tracking objects visually attended by the user while navigating in interactive virtual environments. In addition to the conventional bottom-up (stimulus-driven) saliency map, the proposed framework uses top-down (goal-directed) contexts inferred from the user's spatial and temporal behaviors, and identifies the most plausibly attended objects among candidates in the object saliency map. The computational framework was implemented using GPU, exhibiting high computational performance adequate for interactive virtual environments. A user experiment was also conducted to evaluate the prediction accuracy of the tracking framework by comparing objects regarded as visually attended by the framework to actual human gaze collected with an eye tracker. The results indicated that the accuracy was in the level well supported by the theory of human cognition for visually identifying single and multiple attentive targets, especially owing to the addition of top-down contextual information. Finally, we demonstrate how the visual attention tracking framework can be applied to managing the level of details in virtual environments, without any hardware for head or eye tracking.

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.

Towards a neuro-computational account of prism adaptation.

PubMed

Petitet, Pierre; O'Reilly, Jill X; O'Shea, Jacinta

2017-12-14

Prism adaptation has a long history as an experimental paradigm used to investigate the functional and neural processes that underlie sensorimotor control. In the neuropsychology literature, prism adaptation behaviour is typically explained by reference to a traditional cognitive psychology framework that distinguishes putative functions, such as 'strategic control' versus 'spatial realignment'. This theoretical framework lacks conceptual clarity, quantitative precision and explanatory power. Here, we advocate for an alternative computational framework that offers several advantages: 1) an algorithmic explanatory account of the computations and operations that drive behaviour; 2) expressed in quantitative mathematical terms; 3) embedded within a principled theoretical framework (Bayesian decision theory, state-space modelling); 4) that offers a means to generate and test quantitative behavioural predictions. This computational framework offers a route towards mechanistic neurocognitive explanations of prism adaptation behaviour. Thus it constitutes a conceptual advance compared to the traditional theoretical framework. In this paper, we illustrate how Bayesian decision theory and state-space models offer principled explanations for a range of behavioural phenomena in the field of prism adaptation (e.g. visual capture, magnitude of visual versus proprioceptive realignment, spontaneous recovery and dynamics of adaptation memory). We argue that this explanatory framework can advance understanding of the functional and neural mechanisms that implement prism adaptation behaviour, by enabling quantitative tests of hypotheses that go beyond merely descriptive mapping claims that 'brain area X is (somehow) involved in psychological process Y'. Copyright © 2017 The Authors. Published by Elsevier Ltd.. All rights reserved.

A Riemannian framework for orientation distribution function computing.

PubMed

Cheng, Jian; Ghosh, Aurobrata; Jiang, Tianzi; Deriche, Rachid

2009-01-01

Compared with Diffusion Tensor Imaging (DTI), High Angular Resolution Imaging (HARDI) can better explore the complex microstructure of white matter. Orientation Distribution Function (ODF) is used to describe the probability of the fiber direction. Fisher information metric has been constructed for probability density family in Information Geometry theory and it has been successfully applied for tensor computing in DTI. In this paper, we present a state of the art Riemannian framework for ODF computing based on Information Geometry and sparse representation of orthonormal bases. In this Riemannian framework, the exponential map, logarithmic map and geodesic have closed forms. And the weighted Frechet mean exists uniquely on this manifold. We also propose a novel scalar measurement, named Geometric Anisotropy (GA), which is the Riemannian geodesic distance between the ODF and the isotropic ODF. The Renyi entropy H1/2 of the ODF can be computed from the GA. Moreover, we present an Affine-Euclidean framework and a Log-Euclidean framework so that we can work in an Euclidean space. As an application, Lagrange interpolation on ODF field is proposed based on weighted Frechet mean. We validate our methods on synthetic and real data experiments. Compared with existing Riemannian frameworks on ODF, our framework is model-free. The estimation of the parameters, i.e. Riemannian coordinates, is robust and linear. Moreover it should be noted that our theoretical results can be used for any probability density function (PDF) under an orthonormal basis representation.

A Secure Framework for Location Verification in Pervasive Computing

NASA Astrophysics Data System (ADS)

Liu, Dawei; Lee, Moon-Chuen; Wu, Dan

The way people use computing devices has been changed in some way by the relatively new pervasive computing paradigm. For example, a person can use a mobile device to obtain its location information at anytime and anywhere. There are several security issues concerning whether this information is reliable in a pervasive environment. For example, a malicious user may disable the localization system by broadcasting a forged location, and it may impersonate other users by eavesdropping their locations. In this paper, we address the verification of location information in a secure manner. We first present the design challenges for location verification, and then propose a two-layer framework VerPer for secure location verification in a pervasive computing environment. Real world GPS-based wireless sensor network experiments confirm the effectiveness of the proposed framework.

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.

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.

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.

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

A Flexible Computational Framework Using R and Map-Reduce for Permutation Tests of Massive Genetic Analysis of Complex Traits.

PubMed

Mahjani, Behrang; Toor, Salman; Nettelblad, Carl; Holmgren, Sverker

2017-01-01

In quantitative trait locus (QTL) mapping significance of putative QTL is often determined using permutation testing. The computational needs to calculate the significance level are immense, 10 4 up to 10 8 or even more permutations can be needed. We have previously introduced the PruneDIRECT algorithm for multiple QTL scan with epistatic interactions. This algorithm has specific strengths for permutation testing. Here, we present a flexible, parallel computing framework for identifying multiple interacting QTL using the PruneDIRECT algorithm which uses the map-reduce model as implemented in Hadoop. The framework is implemented in R, a widely used software tool among geneticists. This enables users to rearrange algorithmic steps to adapt genetic models, search algorithms, and parallelization steps to their needs in a flexible way. Our work underlines the maturity of accessing distributed parallel computing for computationally demanding bioinformatics applications through building workflows within existing scientific environments. We investigate the PruneDIRECT algorithm, comparing its performance to exhaustive search and DIRECT algorithm using our framework on a public cloud resource. We find that PruneDIRECT is vastly superior for permutation testing, and perform 2 ×10 5 permutations for a 2D QTL problem in 15 hours, using 100 cloud processes. We show that our framework scales out almost linearly for a 3D QTL search.

A Columnar Storage Strategy with Spatiotemporal Index for Big Climate Data

NASA Astrophysics Data System (ADS)

Hu, F.; Bowen, M. K.; Li, Z.; Schnase, J. L.; Duffy, D.; Lee, T. J.; Yang, C. P.

2015-12-01

Large collections of observational, reanalysis, and climate model output data may grow to as large as a 100 PB in the coming years, so climate dataset is in the Big Data domain, and various distributed computing frameworks have been utilized to address the challenges by big climate data analysis. However, due to the binary data format (NetCDF, HDF) with high spatial and temporal dimensions, the computing frameworks in Apache Hadoop ecosystem are not originally suited for big climate data. In order to make the computing frameworks in Hadoop ecosystem directly support big climate data, we propose a columnar storage format with spatiotemporal index to store climate data, which will support any project in the Apache Hadoop ecosystem (e.g. MapReduce, Spark, Hive, Impala). With this approach, the climate data will be transferred into binary Parquet data format, a columnar storage format, and spatial and temporal index will be built and attached into the end of Parquet files to enable real-time data query. Then such climate data in Parquet data format could be available to any computing frameworks in Hadoop ecosystem. The proposed approach is evaluated using the NASA Modern-Era Retrospective Analysis for Research and Applications (MERRA) climate reanalysis dataset. Experimental results show that this approach could efficiently overcome the gap between the big climate data and the distributed computing frameworks, and the spatiotemporal index could significantly accelerate data querying and processing.

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.

Human errors and violations in computer and information security: the viewpoint of network administrators and security specialists.

PubMed

Kraemer, Sara; Carayon, Pascale

2007-03-01

This paper describes human errors and violations of end users and network administration in computer and information security. This information is summarized in a conceptual framework for examining the human and organizational factors contributing to computer and information security. This framework includes human error taxonomies to describe the work conditions that contribute adversely to computer and information security, i.e. to security vulnerabilities and breaches. The issue of human error and violation in computer and information security was explored through a series of 16 interviews with network administrators and security specialists. The interviews were audio taped, transcribed, and analyzed by coding specific themes in a node structure. The result is an expanded framework that classifies types of human error and identifies specific human and organizational factors that contribute to computer and information security. Network administrators tended to view errors created by end users as more intentional than unintentional, while errors created by network administrators as more unintentional than intentional. Organizational factors, such as communication, security culture, policy, and organizational structure, were the most frequently cited factors associated with computer and information security.

Framework to model neutral particle flux in convex high aspect ratio structures using one-dimensional radiosity

NASA Astrophysics Data System (ADS)

Manstetten, Paul; Filipovic, Lado; Hössinger, Andreas; Weinbub, Josef; Selberherr, Siegfried

2017-02-01

We present a computationally efficient framework to compute the neutral flux in high aspect ratio structures during three-dimensional plasma etching simulations. The framework is based on a one-dimensional radiosity approach and is applicable to simulations of convex rotationally symmetric holes and convex symmetric trenches with a constant cross-section. The framework is intended to replace the full three-dimensional simulation step required to calculate the neutral flux during plasma etching simulations. Especially for high aspect ratio structures, the computational effort, required to perform the full three-dimensional simulation of the neutral flux at the desired spatial resolution, conflicts with practical simulation time constraints. Our results are in agreement with those obtained by three-dimensional Monte Carlo based ray tracing simulations for various aspect ratios and convex geometries. With this framework we present a comprehensive analysis of the influence of the geometrical properties of high aspect ratio structures as well as of the particle sticking probability on the neutral particle flux.

OpenCluster: A Flexible Distributed Computing Framework for Astronomical Data Processing

NASA Astrophysics Data System (ADS)

Wei, Shoulin; Wang, Feng; Deng, Hui; Liu, Cuiyin; Dai, Wei; Liang, Bo; Mei, Ying; Shi, Congming; Liu, Yingbo; Wu, Jingping

2017-02-01

The volume of data generated by modern astronomical telescopes is extremely large and rapidly growing. However, current high-performance data processing architectures/frameworks are not well suited for astronomers because of their limitations and programming difficulties. In this paper, we therefore present OpenCluster, an open-source distributed computing framework to support rapidly developing high-performance processing pipelines of astronomical big data. We first detail the OpenCluster design principles and implementations and present the APIs facilitated by the framework. We then demonstrate a case in which OpenCluster is used to resolve complex data processing problems for developing a pipeline for the Mingantu Ultrawide Spectral Radioheliograph. Finally, we present our OpenCluster performance evaluation. Overall, OpenCluster provides not only high fault tolerance and simple programming interfaces, but also a flexible means of scaling up the number of interacting entities. OpenCluster thereby provides an easily integrated distributed computing framework for quickly developing a high-performance data processing system of astronomical telescopes and for significantly reducing software development expenses.

MOOSE: A parallel computational framework for coupled systems of nonlinear equations.

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

Derek Gaston; Chris Newman; Glen Hansen

Systems of coupled, nonlinear partial differential equations (PDEs) often arise in simulation of nuclear processes. MOOSE: Multiphysics Object Oriented Simulation Environment, a parallel computational framework targeted at the solution of such systems, is presented. As opposed to traditional data-flow oriented computational frameworks, MOOSE is instead founded on the mathematical principle of Jacobian-free Newton-Krylov (JFNK) solution methods. Utilizing the mathematical structure present in JFNK, physics expressions are modularized into `Kernels,'' allowing for rapid production of new simulation tools. In addition, systems are solved implicitly and fully coupled, employing physics based preconditioning, which provides great flexibility even with large variance in timemore » scales. A summary of the mathematics, an overview of the structure of MOOSE, and several representative solutions from applications built on the framework are presented.« less

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.

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...

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.

Combinatorial-topological framework for the analysis of global dynamics.

PubMed

Bush, Justin; Gameiro, Marcio; Harker, Shaun; Kokubu, Hiroshi; Mischaikow, Konstantin; Obayashi, Ippei; Pilarczyk, Paweł

2012-12-01

We discuss an algorithmic framework based on efficient graph algorithms and algebraic-topological computational tools. The framework is aimed at automatic computation of a database of global dynamics of a given m-parameter semidynamical system with discrete time on a bounded subset of the n-dimensional phase space. We introduce the mathematical background, which is based upon Conley's topological approach to dynamics, describe the algorithms for the analysis of the dynamics using rectangular grids both in phase space and parameter space, and show two sample applications.

Combinatorial-topological framework for the analysis of global dynamics

NASA Astrophysics Data System (ADS)

Bush, Justin; Gameiro, Marcio; Harker, Shaun; Kokubu, Hiroshi; Mischaikow, Konstantin; Obayashi, Ippei; Pilarczyk, Paweł

2012-12-01

We discuss an algorithmic framework based on efficient graph algorithms and algebraic-topological computational tools. The framework is aimed at automatic computation of a database of global dynamics of a given m-parameter semidynamical system with discrete time on a bounded subset of the n-dimensional phase space. We introduce the mathematical background, which is based upon Conley's topological approach to dynamics, describe the algorithms for the analysis of the dynamics using rectangular grids both in phase space and parameter space, and show two sample applications.

BlueSky Cloud Framework: An E-Learning Framework Embracing Cloud Computing

NASA Astrophysics Data System (ADS)

Dong, Bo; Zheng, Qinghua; Qiao, Mu; Shu, Jian; Yang, Jie

Currently, E-Learning has grown into a widely accepted way of learning. With the huge growth of users, services, education contents and resources, E-Learning systems are facing challenges of optimizing resource allocations, dealing with dynamic concurrency demands, handling rapid storage growth requirements and cost controlling. In this paper, an E-Learning framework based on cloud computing is presented, namely BlueSky cloud framework. Particularly, the architecture and core components of BlueSky cloud framework are introduced. In BlueSky cloud framework, physical machines are virtualized, and allocated on demand for E-Learning systems. Moreover, BlueSky cloud framework combines with traditional middleware functions (such as load balancing and data caching) to serve for E-Learning systems as a general architecture. It delivers reliable, scalable and cost-efficient services to E-Learning systems, and E-Learning organizations can establish systems through these services in a simple way. BlueSky cloud framework solves the challenges faced by E-Learning, and improves the performance, availability and scalability of E-Learning systems.

Activities with Parents on the Computer: An Ecological Framework

ERIC Educational Resources Information Center

Paiva, João C.; Morais, Carla; Moreira, Luciano

2017-01-01

This paper proposes an ecological framework "Activities with Parents on the Computer" (APC) to bridge home and school contexts by involving parents and students in digital media based assignments. An exploratory case-study was conducted based on ten parent-child dyads that engaged in an APC at home. Attitudes were assessed through a…

Computational Thermodynamics and Kinetics-Based ICME Framework for High-Temperature Shape Memory Alloys

NASA Astrophysics Data System (ADS)

Arróyave, Raymundo; Talapatra, Anjana; Johnson, Luke; Singh, Navdeep; Ma, Ji; Karaman, Ibrahim

2015-11-01

Over the last decade, considerable interest in the development of High-Temperature Shape Memory Alloys (HTSMAs) for solid-state actuation has increased dramatically as key applications in the aerospace and automotive industry demand actuation temperatures well above those of conventional SMAs. Most of the research to date has focused on establishing the (forward) connections between chemistry, processing, (micro)structure, properties, and performance. Much less work has been dedicated to the development of frameworks capable of addressing the inverse problem of establishing necessary chemistry and processing schedules to achieve specific performance goals. Integrated Computational Materials Engineering (ICME) has emerged as a powerful framework to address this problem, although it has yet to be applied to the development of HTSMAs. In this paper, the contributions of computational thermodynamics and kinetics to ICME of HTSMAs are described. Some representative examples of the use of computational thermodynamics and kinetics to understand the phase stability and microstructural evolution in HTSMAs are discussed. Some very recent efforts at combining both to assist in the design of HTSMAs and limitations to the full implementation of ICME frameworks for HTSMA development are presented.

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.

Eighteen-Month Outcomes of Titanium Frameworks Using Computer-Aided Design and Computer-Aided Manufacturing Method.

PubMed

Turkyilmaz, Ilser; Asar, Neset Volkan

2017-06-01

The aim of the report is to introduce a new software and a new scanner with a noncontact laser probe and to present outcomes of computer-aided design and computer-aided manufacturing titanium frameworks using this new software and scanner with a laser probe. Seven patients received 40 implants placed using a 1-stage protocol. After all implants were planned using an implant planning software (NobelClinician), either 5 or 6 implants were placed in each edentulous arch. Each edentulous arch was treated with a fixed dental prosthesis using implant-supported complete-arch milled-titanium framework using the software (NobelProcera) and the scanner. All patients were followed up for 18 ± 3 months. Implant survival, prosthesis survival, framework fit, marginal bone levels, and maintenance requirements were evaluated. One implant was lost during the follow-up period, giving the implant survival rate of 97.5%; 0.4 ± 0.2 mm marginal bone loss was noted for all implants after 18 ± 3 months. None of the prostheses needed a replacement, indicating the prosthesis success rate of 100%. The results of this clinical study suggest that titanium frameworks fabricated using the software and scanner presented in this study fit accurately and may be a viable option to restore edentulous arches.

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.

Computing Diffeomorphic Paths for Large Motion Interpolation.

PubMed

Seo, Dohyung; Jeffrey, Ho; Vemuri, Baba C

2013-06-01

In this paper, we introduce a novel framework for computing a path of diffeomorphisms between a pair of input diffeomorphisms. Direct computation of a geodesic path on the space of diffeomorphisms Diff (Ω) is difficult, and it can be attributed mainly to the infinite dimensionality of Diff (Ω). Our proposed framework, to some degree, bypasses this difficulty using the quotient map of Diff (Ω) to the quotient space Diff ( M )/ Diff ( M ) μ obtained by quotienting out the subgroup of volume-preserving diffeomorphisms Diff ( M ) μ . This quotient space was recently identified as the unit sphere in a Hilbert space in mathematics literature, a space with well-known geometric properties. Our framework leverages this recent result by computing the diffeomorphic path in two stages. First, we project the given diffeomorphism pair onto this sphere and then compute the geodesic path between these projected points. Second, we lift the geodesic on the sphere back to the space of diffeomerphisms, by solving a quadratic programming problem with bilinear constraints using the augmented Lagrangian technique with penalty terms. In this way, we can estimate the path of diffeomorphisms, first, staying in the space of diffeomorphisms, and second, preserving shapes/volumes in the deformed images along the path as much as possible. We have applied our framework to interpolate intermediate frames of frame-sub-sampled video sequences. In the reported experiments, our approach compares favorably with the popular Large Deformation Diffeomorphic Metric Mapping framework (LDDMM).

Computational models of neuromodulation.

PubMed

Fellous, J M; Linster, C

1998-05-15

Computational modeling of neural substrates provides an excellent theoretical framework for the understanding of the computational roles of neuromodulation. In this review, we illustrate, with a large number of modeling studies, the specific computations performed by neuromodulation in the context of various neural models of invertebrate and vertebrate preparations. We base our characterization of neuromodulations on their computational and functional roles rather than on anatomical or chemical criteria. We review the main framework in which neuromodulation has been studied theoretically (central pattern generation and oscillations, sensory processing, memory and information integration). Finally, we present a detailed mathematical overview of how neuromodulation has been implemented at the single cell and network levels in modeling studies. Overall, neuromodulation is found to increase and control computational complexity.

The BioIntelligence Framework: a new computational platform for biomedical knowledge computing.

PubMed

Farley, Toni; Kiefer, Jeff; Lee, Preston; Von Hoff, Daniel; Trent, Jeffrey M; Colbourn, Charles; Mousses, Spyro

2013-01-01

Breakthroughs in molecular profiling technologies are enabling a new data-intensive approach to biomedical research, with the potential to revolutionize how we study, manage, and treat complex diseases. The next great challenge for clinical applications of these innovations will be to create scalable computational solutions for intelligently linking complex biomedical patient data to clinically actionable knowledge. Traditional database management systems (DBMS) are not well suited to representing complex syntactic and semantic relationships in unstructured biomedical information, introducing barriers to realizing such solutions. We propose a scalable computational framework for addressing this need, which leverages a hypergraph-based data model and query language that may be better suited for representing complex multi-lateral, multi-scalar, and multi-dimensional relationships. We also discuss how this framework can be used to create rapid learning knowledge base systems to intelligently capture and relate complex patient data to biomedical knowledge in order to automate the recovery of clinically actionable information.

Framework for cognitive analysis of dynamic perfusion computed tomography with visualization of large volumetric data

NASA Astrophysics Data System (ADS)

Hachaj, Tomasz; Ogiela, Marek R.

2012-10-01

The proposed framework for cognitive analysis of perfusion computed tomography images is a fusion of image processing, pattern recognition, and image analysis procedures. The output data of the algorithm consists of: regions of perfusion abnormalities, anatomy atlas description of brain tissues, measures of perfusion parameters, and prognosis for infracted tissues. That information is superimposed onto volumetric computed tomography data and displayed to radiologists. Our rendering algorithm enables rendering large volumes on off-the-shelf hardware. This portability of rendering solution is very important because our framework can be run without using expensive dedicated hardware. The other important factors are theoretically unlimited size of rendered volume and possibility of trading of image quality for rendering speed. Such rendered, high quality visualizations may be further used for intelligent brain perfusion abnormality identification, and computer aided-diagnosis of selected types of pathologies.

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.

Press Play for Learning: A Framework to Guide Serious Computer Game Use in the Classroom

ERIC Educational Resources Information Center

Southgate, Erica; Budd, Janene; Smith, Shamus

2017-01-01

Computer gaming is a global phenomenon and there has been rapid growth in "serious" games for learning. An emergent body of evidence demonstrates how serious games can be used in primary and secondary school classrooms. Despite the popularity of serious games and their pedagogical potential, there are few specialised frameworks to guide…

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

Energy and Power Aware Computing Through Management of Computational Entropy

DTIC Science & Technology

2008-01-01

18 2.4.1 ACIP living framework forum task...This research focused on two sub- tasks: (1) Assessing the need and planning for a potential “Living Framework Forum ” (LFF) software architecture...probabilistic switching with plausible device realizations to save energy in our patent application [35]. In [35], we showed an introverted switch in

A Framework for the Design of Computer-Assisted Simulation Training for Complex Police Situations

ERIC Educational Resources Information Center

Söderström, Tor; Åström, Jan; Anderson, Greg; Bowles, Ron

2014-01-01

Purpose: The purpose of this paper is to report progress concerning the design of a computer-assisted simulation training (CAST) platform for developing decision-making skills in police students. The overarching aim is to outline a theoretical framework for the design of CAST to facilitate police students' development of search techniques in…

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,…

The Concept of Energy in Psychological Theory. Cognitive Science Program, Technical Report No. 86-2.

ERIC Educational Resources Information Center

Posner, Michael I.; Rothbart, Mary Klevjord

This paper describes a basic framework for integration of computational and energetic concepts in psychological theory. The framework is adapted from a general effort to understand the neural systems underlying cognition. The element of the cognitive system that provides the best basis for attempting to relate energetic and computational ideas is…

Computer Mediated Communication in the Universal Design for Learning Framework for Preparation of Special Education Teachers

ERIC Educational Resources Information Center

Basham, James D.; Lowrey, K. Alisa; deNoyelles, Aimee

2010-01-01

This study investigated the Universal Design for Learning (UDL) framework as a basis for a bi-university computer mediated communication (CMC) collaborative project. Participants in the research included 78 students from two special education programs enrolled in teacher education courses. The focus of the investigation was on exploring the…

The Effects of Routing and Scoring within a Computer Adaptive Multi-Stage Framework

ERIC Educational Resources Information Center

Dallas, Andrew

2014-01-01

This dissertation examined the overall effects of routing and scoring within a computer adaptive multi-stage framework (ca-MST). Testing in a ca-MST environment has become extremely popular in the testing industry. Testing companies enjoy its efficiency benefits as compared to traditionally linear testing and its quality-control features over…

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.

A locally p-adaptive approach for Large Eddy Simulation of compressible flows in a DG framework

NASA Astrophysics Data System (ADS)

Tugnoli, Matteo; Abbà, Antonella; Bonaventura, Luca; Restelli, Marco

2017-11-01

We investigate the possibility of reducing the computational burden of LES models by employing local polynomial degree adaptivity in the framework of a high-order DG method. A novel degree adaptation technique especially featured to be effective for LES applications is proposed and its effectiveness is compared to that of other criteria already employed in the literature. The resulting locally adaptive approach allows to achieve significant reductions in computational cost of representative LES computations.

A graph-based computational framework for simulation and optimisation of coupled infrastructure networks

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

Jalving, Jordan; Abhyankar, Shrirang; Kim, Kibaek

Here, we present a computational framework that facilitates the construction, instantiation, and analysis of large-scale optimization and simulation applications of coupled energy networks. The framework integrates the optimization modeling package PLASMO and the simulation package DMNetwork (built around PETSc). These tools use a common graphbased abstraction that enables us to achieve compatibility between data structures and to build applications that use network models of different physical fidelity. We also describe how to embed these tools within complex computational workflows using SWIFT, which is a tool that facilitates parallel execution of multiple simulation runs and management of input and output data.more » We discuss how to use these capabilities to target coupled natural gas and electricity systems.« less

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.

A graph-based computational framework for simulation and optimisation of coupled infrastructure networks

DOE PAGES

Jalving, Jordan; Abhyankar, Shrirang; Kim, Kibaek; ...

2017-04-24

Here, we present a computational framework that facilitates the construction, instantiation, and analysis of large-scale optimization and simulation applications of coupled energy networks. The framework integrates the optimization modeling package PLASMO and the simulation package DMNetwork (built around PETSc). These tools use a common graphbased abstraction that enables us to achieve compatibility between data structures and to build applications that use network models of different physical fidelity. We also describe how to embed these tools within complex computational workflows using SWIFT, which is a tool that facilitates parallel execution of multiple simulation runs and management of input and output data.more » We discuss how to use these capabilities to target coupled natural gas and electricity systems.« less

Amelie: A Recombinant Computing Framework for Ambient Awareness

NASA Astrophysics Data System (ADS)

Metaxas, Georgios; Markopoulos, Panos; Aarts, Emile

This paper presents Amelie, a service oriented framework that supports the implementation of awareness systems. Amelie adopts the tenets of Recombinant computing to address an important non-functional requirement for Ambient Intelligence software, namely the heterogeneous combination of services and components. Amelie is founded upon FN-AAR an abstract model of Awareness Systems which enables the immediate expression and implementation of socially salient requirements, such as symmetry and social translucence. We discuss the framework and show how system behaviours can be specified using the Awareness Mark-up Language AML.

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.

FORESEE: Fully Outsourced secuRe gEnome Study basEd on homomorphic Encryption

PubMed Central

2015-01-01

Background The increasing availability of genome data motivates massive research studies in personalized treatment and precision medicine. Public cloud services provide a flexible way to mitigate the storage and computation burden in conducting genome-wide association studies (GWAS). However, data privacy has been widely concerned when sharing the sensitive information in a cloud environment. Methods We presented a novel framework (FORESEE: Fully Outsourced secuRe gEnome Study basEd on homomorphic Encryption) to fully outsource GWAS (i.e., chi-square statistic computation) using homomorphic encryption. The proposed framework enables secure divisions over encrypted data. We introduced two division protocols (i.e., secure errorless division and secure approximation division) with a trade-off between complexity and accuracy in computing chi-square statistics. Results The proposed framework was evaluated for the task of chi-square statistic computation with two case-control datasets from the 2015 iDASH genome privacy protection challenge. Experimental results show that the performance of FORESEE can be significantly improved through algorithmic optimization and parallel computation. Remarkably, the secure approximation division provides significant performance gain, but without missing any significance SNPs in the chi-square association test using the aforementioned datasets. Conclusions Unlike many existing HME based studies, in which final results need to be computed by the data owner due to the lack of the secure division operation, the proposed FORESEE framework support complete outsourcing to the cloud and output the final encrypted chi-square statistics. PMID:26733391

FORESEE: Fully Outsourced secuRe gEnome Study basEd on homomorphic Encryption.

PubMed

Zhang, Yuchen; Dai, Wenrui; Jiang, Xiaoqian; Xiong, Hongkai; Wang, Shuang

2015-01-01

The increasing availability of genome data motivates massive research studies in personalized treatment and precision medicine. Public cloud services provide a flexible way to mitigate the storage and computation burden in conducting genome-wide association studies (GWAS). However, data privacy has been widely concerned when sharing the sensitive information in a cloud environment. We presented a novel framework (FORESEE: Fully Outsourced secuRe gEnome Study basEd on homomorphic Encryption) to fully outsource GWAS (i.e., chi-square statistic computation) using homomorphic encryption. The proposed framework enables secure divisions over encrypted data. We introduced two division protocols (i.e., secure errorless division and secure approximation division) with a trade-off between complexity and accuracy in computing chi-square statistics. The proposed framework was evaluated for the task of chi-square statistic computation with two case-control datasets from the 2015 iDASH genome privacy protection challenge. Experimental results show that the performance of FORESEE can be significantly improved through algorithmic optimization and parallel computation. Remarkably, the secure approximation division provides significant performance gain, but without missing any significance SNPs in the chi-square association test using the aforementioned datasets. Unlike many existing HME based studies, in which final results need to be computed by the data owner due to the lack of the secure division operation, the proposed FORESEE framework support complete outsourcing to the cloud and output the final encrypted chi-square statistics.

Autonomic Management of Application Workflows on Hybrid Computing Infrastructure

DOE PAGES

Kim, Hyunjoo; el-Khamra, Yaakoub; Rodero, Ivan; ...

2011-01-01

In this paper, we present a programming and runtime framework that enables the autonomic management of complex application workflows on hybrid computing infrastructures. The framework is designed to address system and application heterogeneity and dynamics to ensure that application objectives and constraints are satisfied. The need for such autonomic system and application management is becoming critical as computing infrastructures become increasingly heterogeneous, integrating different classes of resources from high-end HPC systems to commodity clusters and clouds. For example, the framework presented in this paper can be used to provision the appropriate mix of resources based on application requirements and constraints.more » The framework also monitors the system/application state and adapts the application and/or resources to respond to changing requirements or environment. To demonstrate the operation of the framework and to evaluate its ability, we employ a workflow used to characterize an oil reservoir executing on a hybrid infrastructure composed of TeraGrid nodes and Amazon EC2 instances of various types. Specifically, we show how different applications objectives such as acceleration, conservation and resilience can be effectively achieved while satisfying deadline and budget constraints, using an appropriate mix of dynamically provisioned resources. Our evaluations also demonstrate that public clouds can be used to complement and reinforce the scheduling and usage of traditional high performance computing infrastructure.« less

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.

Decoding the "CoDe": A Framework for Conceptualizing and Designing Help Options in Computer-Based Second Language Listening

ERIC Educational Resources Information Center

Cardenas-Claros, Monica Stella; Gruba, Paul A.

2013-01-01

This paper proposes a theoretical framework for the conceptualization and design of help options in computer-based second language (L2) listening. Based on four empirical studies, it aims at clarifying both conceptualization and design (CoDe) components. The elements of conceptualization consist of a novel four-part classification of help options:…

Rewards and Penalties: A Gamification Approach for Increasing Attendance and Engagement in an Undergraduate Computing Module

ERIC Educational Resources Information Center

Caton, Hope; Greenhill, Darrel

2014-01-01

This paper describes how a gamified rewards and penalties framework was used to increase attendance and engagement in a level six undergraduate computing module teaching game production. The framework was applied to the same module over two consecutive years: a control year and a trial year. In both years the tutor, assignments and assessment…

Investigating the Potential of Computer Environments for the Teaching and Learning of Functions: A Double Analysis from Two Research Traditions

ERIC Educational Resources Information Center

Lagrange, Jean-Baptiste; Psycharis, Giorgos

2014-01-01

The general goal of this paper is to explore the potential of computer environments for the teaching and learning of functions. To address this, different theoretical frameworks and corresponding research traditions are available. In this study, we aim to network different frameworks by following a "double analysis" method to analyse two…

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...

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.

A new framework for comprehensive, robust, and efficient global sensitivity analysis: 1. Theory

NASA Astrophysics Data System (ADS)

Razavi, Saman; Gupta, Hoshin V.

2016-01-01

Computer simulation models are continually growing in complexity with increasingly more factors to be identified. Sensitivity Analysis (SA) provides an essential means for understanding the role and importance of these factors in producing model responses. However, conventional approaches to SA suffer from (1) an ambiguous characterization of sensitivity, and (2) poor computational efficiency, particularly as the problem dimension grows. Here, we present a new and general sensitivity analysis framework (called VARS), based on an analogy to "variogram analysis," that provides an intuitive and comprehensive characterization of sensitivity across the full spectrum of scales in the factor space. We prove, theoretically, that Morris (derivative-based) and Sobol (variance-based) methods and their extensions are special cases of VARS, and that their SA indices can be computed as by-products of the VARS framework. Synthetic functions that resemble actual model response surfaces are used to illustrate the concepts, and show VARS to be as much as two orders of magnitude more computationally efficient than the state-of-the-art Sobol approach. In a companion paper, we propose a practical implementation strategy, and demonstrate the effectiveness, efficiency, and reliability (robustness) of the VARS framework on real-data case studies.

Computation of elementary modes: a unifying framework and the new binary approach

PubMed Central

Gagneur, Julien; Klamt, Steffen

2004-01-01

Background Metabolic pathway analysis has been recognized as a central approach to the structural analysis of metabolic networks. The concept of elementary (flux) modes provides a rigorous formalism to describe and assess pathways and has proven to be valuable for many applications. However, computing elementary modes is a hard computational task. In recent years we assisted in a multiplication of algorithms dedicated to it. We require a summarizing point of view and a continued improvement of the current methods. Results We show that computing the set of elementary modes is equivalent to computing the set of extreme rays of a convex cone. This standard mathematical representation provides a unified framework that encompasses the most prominent algorithmic methods that compute elementary modes and allows a clear comparison between them. Taking lessons from this benchmark, we here introduce a new method, the binary approach, which computes the elementary modes as binary patterns of participating reactions from which the respective stoichiometric coefficients can be computed in a post-processing step. We implemented the binary approach in FluxAnalyzer 5.1, a software that is free for academics. The binary approach decreases the memory demand up to 96% without loss of speed giving the most efficient method available for computing elementary modes to date. Conclusions The equivalence between elementary modes and extreme ray computations offers opportunities for employing tools from polyhedral computation for metabolic pathway analysis. The new binary approach introduced herein was derived from this general theoretical framework and facilitates the computation of elementary modes in considerably larger networks. PMID:15527509

Computational model of lightness perception in high dynamic range imaging

NASA Astrophysics Data System (ADS)

Krawczyk, Grzegorz; Myszkowski, Karol; Seidel, Hans-Peter

2006-02-01

An anchoring theory of lightness perception by Gilchrist et al. [1999] explains many characteristics of human visual system such as lightness constancy and its spectacular failures which are important in the perception of images. The principal concept of this theory is the perception of complex scenes in terms of groups of consistent areas (frameworks). Such areas, following the gestalt theorists, are defined by the regions of common illumination. The key aspect of the image perception is the estimation of lightness within each framework through the anchoring to the luminance perceived as white, followed by the computation of the global lightness. In this paper we provide a computational model for automatic decomposition of HDR images into frameworks. We derive a tone mapping operator which predicts lightness perception of the real world scenes and aims at its accurate reproduction on low dynamic range displays. Furthermore, such a decomposition into frameworks opens new grounds for local image analysis in view of human perception.

A Computational Framework for Bioimaging Simulation.

PubMed

Watabe, Masaki; Arjunan, Satya N V; Fukushima, Seiya; Iwamoto, Kazunari; Kozuka, Jun; Matsuoka, Satomi; Shindo, Yuki; Ueda, Masahiro; Takahashi, Koichi

2015-01-01

Using bioimaging technology, biologists have attempted to identify and document analytical interpretations that underlie biological phenomena in biological cells. Theoretical biology aims at distilling those interpretations into knowledge in the mathematical form of biochemical reaction networks and understanding how higher level functions emerge from the combined action of biomolecules. However, there still remain formidable challenges in bridging the gap between bioimaging and mathematical modeling. Generally, measurements using fluorescence microscopy systems are influenced by systematic effects that arise from stochastic nature of biological cells, the imaging apparatus, and optical physics. Such systematic effects are always present in all bioimaging systems and hinder quantitative comparison between the cell model and bioimages. Computational tools for such a comparison are still unavailable. Thus, in this work, we present a computational framework for handling the parameters of the cell models and the optical physics governing bioimaging systems. Simulation using this framework can generate digital images of cell simulation results after accounting for the systematic effects. We then demonstrate that such a framework enables comparison at the level of photon-counting units.

An Unified Multiscale Framework for Planar, Surface, and Curve Skeletonization.

PubMed

Jalba, Andrei C; Sobiecki, Andre; Telea, Alexandru C

2016-01-01

Computing skeletons of 2D shapes, and medial surface and curve skeletons of 3D shapes, is a challenging task. In particular, there is no unified framework that detects all types of skeletons using a single model, and also produces a multiscale representation which allows to progressively simplify, or regularize, all skeleton types. In this paper, we present such a framework. We model skeleton detection and regularization by a conservative mass transport process from a shape's boundary to its surface skeleton, next to its curve skeleton, and finally to the shape center. The resulting density field can be thresholded to obtain a multiscale representation of progressively simplified surface, or curve, skeletons. We detail a numerical implementation of our framework which is demonstrably stable and has high computational efficiency. We demonstrate our framework on several complex 2D and 3D shapes.

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.

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.

Benchmarking high performance computing architectures with CMS’ skeleton framework

NASA Astrophysics Data System (ADS)

Sexton-Kennedy, E.; Gartung, P.; Jones, C. D.

2017-10-01

In 2012 CMS evaluated which underlying concurrency technology would be the best to use for its multi-threaded framework. The available technologies were evaluated on the high throughput computing systems dominating the resources in use at that time. A skeleton framework benchmarking suite that emulates the tasks performed within a CMSSW application was used to select Intel’s Thread Building Block library, based on the measured overheads in both memory and CPU on the different technologies benchmarked. In 2016 CMS will get access to high performance computing resources that use new many core architectures; machines such as Cori Phase 1&2, Theta, Mira. Because of this we have revived the 2012 benchmark to test it’s performance and conclusions on these new architectures. This talk will discuss the results of this exercise.

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.

When does a physical system compute?

PubMed

Horsman, Clare; Stepney, Susan; Wagner, Rob C; Kendon, Viv

2014-09-08

Computing is a high-level process of a physical system. Recent interest in non-standard computing systems, including quantum and biological computers, has brought this physical basis of computing to the forefront. There has been, however, no consensus on how to tell if a given physical system is acting as a computer or not; leading to confusion over novel computational devices, and even claims that every physical event is a computation. In this paper, we introduce a formal framework that can be used to determine whether a physical system is performing a computation. We demonstrate how the abstract computational level interacts with the physical device level, in comparison with the use of mathematical models in experimental science. This powerful formulation allows a precise description of experiments, technology, computation and simulation, giving our central conclusion: physical computing is the use of a physical system to predict the outcome of an abstract evolution . We give conditions for computing, illustrated using a range of non-standard computing scenarios. The framework also covers broader computing contexts, where there is no obvious human computer user. We introduce the notion of a 'computational entity', and its critical role in defining when computing is taking place in physical systems.

When does a physical system compute?

PubMed Central

Horsman, Clare; Stepney, Susan; Wagner, Rob C.; Kendon, Viv

2014-01-01

Computing is a high-level process of a physical system. Recent interest in non-standard computing systems, including quantum and biological computers, has brought this physical basis of computing to the forefront. There has been, however, no consensus on how to tell if a given physical system is acting as a computer or not; leading to confusion over novel computational devices, and even claims that every physical event is a computation. In this paper, we introduce a formal framework that can be used to determine whether a physical system is performing a computation. We demonstrate how the abstract computational level interacts with the physical device level, in comparison with the use of mathematical models in experimental science. This powerful formulation allows a precise description of experiments, technology, computation and simulation, giving our central conclusion: physical computing is the use of a physical system to predict the outcome of an abstract evolution. We give conditions for computing, illustrated using a range of non-standard computing scenarios. The framework also covers broader computing contexts, where there is no obvious human computer user. We introduce the notion of a ‘computational entity’, and its critical role in defining when computing is taking place in physical systems. PMID:25197245

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 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

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.

Introduction into the Virtual Olympic Games Framework for online communities.

PubMed

Stoilescu, Dorian

2009-06-01

This paper presents the design of the Virtual Olympic Games Framework (VOGF), a computer application designated for athletics, health care, general well-being, nutrition and fitness, which offers multiple benefits for its participants. A special interest in starting the design of the framework was in exploring how people can connect and participate together using existing computer technologies (i.e. gaming consoles, exercise equipment with computer interfaces, devices of measuring health, speed, force and distance and Web 2.0 applications). A stationary bike set-up offering information to users about their individual health and athletic performances has been considered as a starting model. While this model is in the design stage, some preliminary findings are encouraging, suggesting the potential for various fields: sports, medicine, theories of learning, technologies and cybercultural studies. First, this framework would allow participants to perform a variety of sports and improve their health. Second, this would involve creating an online environment able to store health information and sport performances correlated with accessing multi-media data and research about performing sports. Third, participants could share experiences with other athletes, coaches and researchers. Fourth, this framework also provides support for the research community in their future investigations.

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…

Proposal for a Security Management in Cloud Computing for Health Care

PubMed Central

Dzombeta, Srdan; Brandis, Knud

2014-01-01

Cloud computing is actually one of the most popular themes of information systems research. Considering the nature of the processed information especially health care organizations need to assess and treat specific risks according to cloud computing in their information security management system. Therefore, in this paper we propose a framework that includes the most important security processes regarding cloud computing in the health care sector. Starting with a framework of general information security management processes derived from standards of the ISO 27000 family the most important information security processes for health care organizations using cloud computing will be identified considering the main risks regarding cloud computing and the type of information processed. The identified processes will help a health care organization using cloud computing to focus on the most important ISMS processes and establish and operate them at an appropriate level of maturity considering limited resources. PMID:24701137

Proposal for a security management in cloud computing for health care.

PubMed

Haufe, Knut; Dzombeta, Srdan; Brandis, Knud

2014-01-01

Cloud computing is actually one of the most popular themes of information systems research. Considering the nature of the processed information especially health care organizations need to assess and treat specific risks according to cloud computing in their information security management system. Therefore, in this paper we propose a framework that includes the most important security processes regarding cloud computing in the health care sector. Starting with a framework of general information security management processes derived from standards of the ISO 27000 family the most important information security processes for health care organizations using cloud computing will be identified considering the main risks regarding cloud computing and the type of information processed. The identified processes will help a health care organization using cloud computing to focus on the most important ISMS processes and establish and operate them at an appropriate level of maturity considering limited resources.

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.

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…

Applications of the MapReduce programming framework to clinical big data analysis: current landscape and future trends

PubMed Central

2014-01-01

The emergence of massive datasets in a clinical setting presents both challenges and opportunities in data storage and analysis. This so called “big data” challenges traditional analytic tools and will increasingly require novel solutions adapted from other fields. Advances in information and communication technology present the most viable solutions to big data analysis in terms of efficiency and scalability. It is vital those big data solutions are multithreaded and that data access approaches be precisely tailored to large volumes of semi-structured/unstructured data. The MapReduce programming framework uses two tasks common in functional programming: Map and Reduce. MapReduce is a new parallel processing framework and Hadoop is its open-source implementation on a single computing node or on clusters. Compared with existing parallel processing paradigms (e.g. grid computing and graphical processing unit (GPU)), MapReduce and Hadoop have two advantages: 1) fault-tolerant storage resulting in reliable data processing by replicating the computing tasks, and cloning the data chunks on different computing nodes across the computing cluster; 2) high-throughput data processing via a batch processing framework and the Hadoop distributed file system (HDFS). Data are stored in the HDFS and made available to the slave nodes for computation. In this paper, we review the existing applications of the MapReduce programming framework and its implementation platform Hadoop in clinical big data and related medical health informatics fields. The usage of MapReduce and Hadoop on a distributed system represents a significant advance in clinical big data processing and utilization, and opens up new opportunities in the emerging era of big data analytics. The objective of this paper is to summarize the state-of-the-art efforts in clinical big data analytics and highlight what might be needed to enhance the outcomes of clinical big data analytics tools. This paper is concluded by summarizing the potential usage of the MapReduce programming framework and Hadoop platform to process huge volumes of clinical data in medical health informatics related fields. PMID:25383096

Applications of the MapReduce programming framework to clinical big data analysis: current landscape and future trends.

PubMed

Mohammed, Emad A; Far, Behrouz H; Naugler, Christopher

2014-01-01

The emergence of massive datasets in a clinical setting presents both challenges and opportunities in data storage and analysis. This so called "big data" challenges traditional analytic tools and will increasingly require novel solutions adapted from other fields. Advances in information and communication technology present the most viable solutions to big data analysis in terms of efficiency and scalability. It is vital those big data solutions are multithreaded and that data access approaches be precisely tailored to large volumes of semi-structured/unstructured data. THE MAPREDUCE PROGRAMMING FRAMEWORK USES TWO TASKS COMMON IN FUNCTIONAL PROGRAMMING: Map and Reduce. MapReduce is a new parallel processing framework and Hadoop is its open-source implementation on a single computing node or on clusters. Compared with existing parallel processing paradigms (e.g. grid computing and graphical processing unit (GPU)), MapReduce and Hadoop have two advantages: 1) fault-tolerant storage resulting in reliable data processing by replicating the computing tasks, and cloning the data chunks on different computing nodes across the computing cluster; 2) high-throughput data processing via a batch processing framework and the Hadoop distributed file system (HDFS). Data are stored in the HDFS and made available to the slave nodes for computation. In this paper, we review the existing applications of the MapReduce programming framework and its implementation platform Hadoop in clinical big data and related medical health informatics fields. The usage of MapReduce and Hadoop on a distributed system represents a significant advance in clinical big data processing and utilization, and opens up new opportunities in the emerging era of big data analytics. The objective of this paper is to summarize the state-of-the-art efforts in clinical big data analytics and highlight what might be needed to enhance the outcomes of clinical big data analytics tools. This paper is concluded by summarizing the potential usage of the MapReduce programming framework and Hadoop platform to process huge volumes of clinical data in medical health informatics related fields.

Bayesian Parameter Inference and Model Selection by Population Annealing in Systems Biology

PubMed Central

Murakami, Yohei

2014-01-01

Parameter inference and model selection are very important for mathematical modeling in systems biology. Bayesian statistics can be used to conduct both parameter inference and model selection. Especially, the framework named approximate Bayesian computation is often used for parameter inference and model selection in systems biology. However, Monte Carlo methods needs to be used to compute Bayesian posterior distributions. In addition, the posterior distributions of parameters are sometimes almost uniform or very similar to their prior distributions. In such cases, it is difficult to choose one specific value of parameter with high credibility as the representative value of the distribution. To overcome the problems, we introduced one of the population Monte Carlo algorithms, population annealing. Although population annealing is usually used in statistical mechanics, we showed that population annealing can be used to compute Bayesian posterior distributions in the approximate Bayesian computation framework. To deal with un-identifiability of the representative values of parameters, we proposed to run the simulations with the parameter ensemble sampled from the posterior distribution, named “posterior parameter ensemble”. We showed that population annealing is an efficient and convenient algorithm to generate posterior parameter ensemble. We also showed that the simulations with the posterior parameter ensemble can, not only reproduce the data used for parameter inference, but also capture and predict the data which was not used for parameter inference. Lastly, we introduced the marginal likelihood in the approximate Bayesian computation framework for Bayesian model selection. We showed that population annealing enables us to compute the marginal likelihood in the approximate Bayesian computation framework and conduct model selection depending on the Bayes factor. PMID:25089832

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.

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

The BioIntelligence Framework: a new computational platform for biomedical knowledge computing

PubMed Central

Farley, Toni; Kiefer, Jeff; Lee, Preston; Von Hoff, Daniel; Trent, Jeffrey M; Colbourn, Charles

2013-01-01

Breakthroughs in molecular profiling technologies are enabling a new data-intensive approach to biomedical research, with the potential to revolutionize how we study, manage, and treat complex diseases. The next great challenge for clinical applications of these innovations will be to create scalable computational solutions for intelligently linking complex biomedical patient data to clinically actionable knowledge. Traditional database management systems (DBMS) are not well suited to representing complex syntactic and semantic relationships in unstructured biomedical information, introducing barriers to realizing such solutions. We propose a scalable computational framework for addressing this need, which leverages a hypergraph-based data model and query language that may be better suited for representing complex multi-lateral, multi-scalar, and multi-dimensional relationships. We also discuss how this framework can be used to create rapid learning knowledge base systems to intelligently capture and relate complex patient data to biomedical knowledge in order to automate the recovery of clinically actionable information. PMID:22859646

Exploiting on-node heterogeneity for in-situ analytics of climate simulations via a functional partitioning framework

NASA Astrophysics Data System (ADS)

Sapra, Karan; Gupta, Saurabh; Atchley, Scott; Anantharaj, Valentine; Miller, Ross; Vazhkudai, Sudharshan

2016-04-01

Efficient resource utilization is critical for improved end-to-end computing and workflow of scientific applications. Heterogeneous node architectures, such as the GPU-enabled Titan supercomputer at the Oak Ridge Leadership Computing Facility (OLCF), present us with further challenges. In many HPC applications on Titan, the accelerators are the primary compute engines while the CPUs orchestrate the offloading of work onto the accelerators, and moving the output back to the main memory. On the other hand, applications that do not exploit GPUs, the CPU usage is dominant while the GPUs idle. We utilized Heterogenous Functional Partitioning (HFP) runtime framework that can optimize usage of resources on a compute node to expedite an application's end-to-end workflow. This approach is different from existing techniques for in-situ analyses in that it provides a framework for on-the-fly analysis on-node by dynamically exploiting under-utilized resources therein. We have implemented in the Community Earth System Model (CESM) a new concurrent diagnostic processing capability enabled by the HFP framework. Various single variate statistics, such as means and distributions, are computed in-situ by launching HFP tasks on the GPU via the node local HFP daemon. Since our current configuration of CESM does not use GPU resources heavily, we can move these tasks to GPU using the HFP framework. Each rank running the atmospheric model in CESM pushes the variables of of interest via HFP function calls to the HFP daemon. This node local daemon is responsible for receiving the data from main program and launching the designated analytics tasks on the GPU. We have implemented these analytics tasks in C and use OpenACC directives to enable GPU acceleration. This methodology is also advantageous while executing GPU-enabled configurations of CESM when the CPUs will be idle during portions of the runtime. In our implementation results, we demonstrate that it is more efficient to use HFP framework to offload the tasks to GPUs instead of doing it in the main application. We observe increased resource utilization and overall productivity in this approach by using HFP framework for end-to-end workflow.

Resonant transition-based quantum computation

NASA Astrophysics Data System (ADS)

Chiang, Chen-Fu; Hsieh, Chang-Yu

2017-05-01

In this article we assess a novel quantum computation paradigm based on the resonant transition (RT) phenomenon commonly associated with atomic and molecular systems. We thoroughly analyze the intimate connections between the RT-based quantum computation and the well-established adiabatic quantum computation (AQC). Both quantum computing frameworks encode solutions to computational problems in the spectral properties of a Hamiltonian and rely on the quantum dynamics to obtain the desired output state. We discuss how one can adapt any adiabatic quantum algorithm to a corresponding RT version and the two approaches are limited by different aspects of Hamiltonians' spectra. The RT approach provides a compelling alternative to the AQC under various circumstances. To better illustrate the usefulness of the novel framework, we analyze the time complexity of an algorithm for 3-SAT problems and discuss straightforward methods to fine tune its efficiency.

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.

A Framework to Design the Computational Load Distribution of Wireless Sensor Networks in Power Consumption Constrained Environments

PubMed Central

Sánchez-Álvarez, David; Rodríguez-Pérez, Francisco-Javier

2018-01-01

In this paper, we present a work based on the computational load distribution among the homogeneous nodes and the Hub/Sink of Wireless Sensor Networks (WSNs). The main contribution of the paper is an early decision support framework helping WSN designers to take decisions about computational load distribution for those WSNs where power consumption is a key issue (when we refer to “framework” in this work, we are considering it as a support tool to make decisions where the executive judgment can be included along with the set of mathematical tools of the WSN designer; this work shows the need to include the load distribution as an integral component of the WSN system for making early decisions regarding energy consumption). The framework takes advantage of the idea that balancing sensors nodes and Hub/Sink computational load can lead to improved energy consumption for the whole or at least the battery-powered nodes of the WSN. The approach is not trivial and it takes into account related issues such as the required data distribution, nodes, and Hub/Sink connectivity and availability due to their connectivity features and duty-cycle. For a practical demonstration, the proposed framework is applied to an agriculture case study, a sector very relevant in our region. In this kind of rural context, distances, low costs due to vegetable selling prices and the lack of continuous power supplies may lead to viable or inviable sensing solutions for the farmers. The proposed framework systematize and facilitates WSN designers the required complex calculations taking into account the most relevant variables regarding power consumption, avoiding full/partial/prototype implementations, and measurements of different computational load distribution potential solutions for a specific WSN. PMID:29570645

Computers and Play.

ERIC Educational Resources Information Center

Colker, Larry

Viewing computers in various forms as developmentally appropriate objects for children, this discussion provides a framework for integrating conceptions of computers and conceptions of play. Several instances are cited from the literature in which explicit analogies have been made between computers and playthings or play environments.…

RSTensorFlow: GPU Enabled TensorFlow for Deep Learning on Commodity Android Devices

PubMed Central

Alzantot, Moustafa; Wang, Yingnan; Ren, Zhengshuang; Srivastava, Mani B.

2018-01-01

Mobile devices have become an essential part of our daily lives. By virtue of both their increasing computing power and the recent progress made in AI, mobile devices evolved to act as intelligent assistants in many tasks rather than a mere way of making phone calls. However, popular and commonly used tools and frameworks for machine intelligence are still lacking the ability to make proper use of the available heterogeneous computing resources on mobile devices. In this paper, we study the benefits of utilizing the heterogeneous (CPU and GPU) computing resources available on commodity android devices while running deep learning models. We leveraged the heterogeneous computing framework RenderScript to accelerate the execution of deep learning models on commodity Android devices. Our system is implemented as an extension to the popular open-source framework TensorFlow. By integrating our acceleration framework tightly into TensorFlow, machine learning engineers can now easily make benefit of the heterogeneous computing resources on mobile devices without the need of any extra tools. We evaluate our system on different android phones models to study the trade-offs of running different neural network operations on the GPU. We also compare the performance of running different models architectures such as convolutional and recurrent neural networks on CPU only vs using heterogeneous computing resources. Our result shows that although GPUs on the phones are capable of offering substantial performance gain in matrix multiplication on mobile devices. Therefore, models that involve multiplication of large matrices can run much faster (approx. 3 times faster in our experiments) due to GPU support. PMID:29629431

RSTensorFlow: GPU Enabled TensorFlow for Deep Learning on Commodity Android Devices.

PubMed

Alzantot, Moustafa; Wang, Yingnan; Ren, Zhengshuang; Srivastava, Mani B

2017-06-01

Mobile devices have become an essential part of our daily lives. By virtue of both their increasing computing power and the recent progress made in AI, mobile devices evolved to act as intelligent assistants in many tasks rather than a mere way of making phone calls. However, popular and commonly used tools and frameworks for machine intelligence are still lacking the ability to make proper use of the available heterogeneous computing resources on mobile devices. In this paper, we study the benefits of utilizing the heterogeneous (CPU and GPU) computing resources available on commodity android devices while running deep learning models. We leveraged the heterogeneous computing framework RenderScript to accelerate the execution of deep learning models on commodity Android devices. Our system is implemented as an extension to the popular open-source framework TensorFlow. By integrating our acceleration framework tightly into TensorFlow, machine learning engineers can now easily make benefit of the heterogeneous computing resources on mobile devices without the need of any extra tools. We evaluate our system on different android phones models to study the trade-offs of running different neural network operations on the GPU. We also compare the performance of running different models architectures such as convolutional and recurrent neural networks on CPU only vs using heterogeneous computing resources. Our result shows that although GPUs on the phones are capable of offering substantial performance gain in matrix multiplication on mobile devices. Therefore, models that involve multiplication of large matrices can run much faster (approx. 3 times faster in our experiments) due to GPU support.

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.

Benchmarking high performance computing architectures with CMS’ skeleton framework

DOE PAGES

Sexton-Kennedy, E.; Gartung, P.; Jones, C. D.

2017-11-23

Here, in 2012 CMS evaluated which underlying concurrency technology would be the best to use for its multi-threaded framework. The available technologies were evaluated on the high throughput computing systems dominating the resources in use at that time. A skeleton framework benchmarking suite that emulates the tasks performed within a CMSSW application was used to select Intel’s Thread Building Block library, based on the measured overheads in both memory and CPU on the different technologies benchmarked. In 2016 CMS will get access to high performance computing resources that use new many core architectures; machines such as Cori Phase 1&2, Theta,more » Mira. Because of this we have revived the 2012 benchmark to test it’s performance and conclusions on these new architectures. This talk will discuss the results of this exercise.« less

Benchmarking high performance computing architectures with CMS’ skeleton framework

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

Sexton-Kennedy, E.; Gartung, P.; Jones, C. D.

Here, in 2012 CMS evaluated which underlying concurrency technology would be the best to use for its multi-threaded framework. The available technologies were evaluated on the high throughput computing systems dominating the resources in use at that time. A skeleton framework benchmarking suite that emulates the tasks performed within a CMSSW application was used to select Intel’s Thread Building Block library, based on the measured overheads in both memory and CPU on the different technologies benchmarked. In 2016 CMS will get access to high performance computing resources that use new many core architectures; machines such as Cori Phase 1&2, Theta,more » Mira. Because of this we have revived the 2012 benchmark to test it’s performance and conclusions on these new architectures. This talk will discuss the results of this exercise.« less

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.

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.

First-Principles Framework to Compute Sum-Frequency Generation Vibrational Spectra of Semiconductors and Insulators.

PubMed

Wan, Quan; Galli, Giulia

2015-12-11

We present a first-principles framework to compute sum-frequency generation (SFG) vibrational spectra of semiconductors and insulators. The method is based on density functional theory and the use of maximally localized Wannier functions to compute the response to electric fields, and it includes the effect of electric field gradients at surfaces. In addition, it includes quadrupole contributions to SFG spectra, thus enabling the verification of the dipole approximation, whose validity determines the surface specificity of SFG spectroscopy. We compute the SFG spectra of ice I_{h} basal surfaces and identify which spectra components are affected by bulk contributions. Our results are in good agreement with experiments at low temperature.

Toward a computational framework for cognitive biology: Unifying approaches from cognitive neuroscience and comparative cognition

NASA Astrophysics Data System (ADS)

Fitch, W. Tecumseh

2014-09-01

Progress in understanding cognition requires a quantitative, theoretical framework, grounded in the other natural sciences and able to bridge between implementational, algorithmic and computational levels of explanation. I review recent results in neuroscience and cognitive biology that, when combined, provide key components of such an improved conceptual framework for contemporary cognitive science. Starting at the neuronal level, I first discuss the contemporary realization that single neurons are powerful tree-shaped computers, which implies a reorientation of computational models of learning and plasticity to a lower, cellular, level. I then turn to predictive systems theory (predictive coding and prediction-based learning) which provides a powerful formal framework for understanding brain function at a more global level. Although most formal models concerning predictive coding are framed in associationist terms, I argue that modern data necessitate a reinterpretation of such models in cognitive terms: as model-based predictive systems. Finally, I review the role of the theory of computation and formal language theory in the recent explosion of comparative biological research attempting to isolate and explore how different species differ in their cognitive capacities. Experiments to date strongly suggest that there is an important difference between humans and most other species, best characterized cognitively as a propensity by our species to infer tree structures from sequential data. Computationally, this capacity entails generative capacities above the regular (finite-state) level; implementationally, it requires some neural equivalent of a push-down stack. I dub this unusual human propensity "dendrophilia", and make a number of concrete suggestions about how such a system may be implemented in the human brain, about how and why it evolved, and what this implies for models of language acquisition. I conclude that, although much remains to be done, a neurally-grounded framework for theoretical cognitive science is within reach that can move beyond polarized debates and provide a more adequate theoretical future for cognitive biology.

Toward a computational framework for cognitive biology: unifying approaches from cognitive neuroscience and comparative cognition.

PubMed

Fitch, W Tecumseh

2014-09-01

Progress in understanding cognition requires a quantitative, theoretical framework, grounded in the other natural sciences and able to bridge between implementational, algorithmic and computational levels of explanation. I review recent results in neuroscience and cognitive biology that, when combined, provide key components of such an improved conceptual framework for contemporary cognitive science. Starting at the neuronal level, I first discuss the contemporary realization that single neurons are powerful tree-shaped computers, which implies a reorientation of computational models of learning and plasticity to a lower, cellular, level. I then turn to predictive systems theory (predictive coding and prediction-based learning) which provides a powerful formal framework for understanding brain function at a more global level. Although most formal models concerning predictive coding are framed in associationist terms, I argue that modern data necessitate a reinterpretation of such models in cognitive terms: as model-based predictive systems. Finally, I review the role of the theory of computation and formal language theory in the recent explosion of comparative biological research attempting to isolate and explore how different species differ in their cognitive capacities. Experiments to date strongly suggest that there is an important difference between humans and most other species, best characterized cognitively as a propensity by our species to infer tree structures from sequential data. Computationally, this capacity entails generative capacities above the regular (finite-state) level; implementationally, it requires some neural equivalent of a push-down stack. I dub this unusual human propensity "dendrophilia", and make a number of concrete suggestions about how such a system may be implemented in the human brain, about how and why it evolved, and what this implies for models of language acquisition. I conclude that, although much remains to be done, a neurally-grounded framework for theoretical cognitive science is within reach that can move beyond polarized debates and provide a more adequate theoretical future for cognitive biology. Copyright © 2014. Published by Elsevier B.V.

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.

A Computational Framework for Quantitative Evaluation of Movement during Rehabilitation

NASA Astrophysics Data System (ADS)

Chen, Yinpeng; Duff, Margaret; Lehrer, Nicole; Sundaram, Hari; He, Jiping; Wolf, Steven L.; Rikakis, Thanassis

2011-06-01

This paper presents a novel generalized computational framework for quantitative kinematic evaluation of movement in a rehabilitation clinic setting. The framework integrates clinical knowledge and computational data-driven analysis together in a systematic manner. The framework provides three key benefits to rehabilitation: (a) the resulting continuous normalized measure allows the clinician to monitor movement quality on a fine scale and easily compare impairments across participants, (b) the framework reveals the effect of individual movement components on the composite movement performance helping the clinician decide the training foci, and (c) the evaluation runs in real-time, which allows the clinician to constantly track a patient's progress and make appropriate adaptations to the therapy protocol. The creation of such an evaluation is difficult because of the sparse amount of recorded clinical observations, the high dimensionality of movement and high variations in subject's performance. We address these issues by modeling the evaluation function as linear combination of multiple normalized kinematic attributes y = Σwiφi(xi) and estimating the attribute normalization function φi(ṡ) by integrating distributions of idealized movement and deviated movement. The weights wi are derived from a therapist's pair-wise comparison using a modified RankSVM algorithm. We have applied this framework to evaluate upper limb movement for stroke survivors with excellent results—the evaluation results are highly correlated to the therapist's observations.

A Distributed Computing Framework for Real-Time Detection of Stress and of Its Propagation in a Team.

PubMed

Pandey, Parul; Lee, Eun Kyung; Pompili, Dario

2016-11-01

Stress is one of the key factor that impacts the quality of our daily life: From the productivity and efficiency in the production processes to the ability of (civilian and military) individuals in making rational decisions. Also, stress can propagate from one individual to other working in a close proximity or toward a common goal, e.g., in a military operation or workforce. Real-time assessment of the stress of individuals alone is, however, not sufficient, as understanding its source and direction in which it propagates in a group of people is equally-if not more-important. A continuous near real-time in situ personal stress monitoring system to quantify level of stress of individuals and its direction of propagation in a team is envisioned. However, stress monitoring of an individual via his/her mobile device may not always be possible for extended periods of time due to limited battery capacity of these devices. To overcome this challenge a novel distributed mobile computing framework is proposed to organize the resources in the vicinity and form a mobile device cloud that enables offloading of computation tasks in stress detection algorithm from resource constrained devices (low residual battery, limited CPU cycles) to resource rich devices. Our framework also supports computing parallelization and workflows, defining how the data and tasks divided/assigned among the entities of the framework are designed. The direction of propagation and magnitude of influence of stress in a group of individuals are studied by applying real-time, in situ analysis of Granger Causality. Tangible benefits (in terms of energy expenditure and execution time) of the proposed framework in comparison to a centralized framework are presented via thorough simulations and real experiments.

Coalescent: an open-source and scalable framework for exact calculations in coalescent theory

PubMed Central

2012-01-01

Background Currently, there is no open-source, cross-platform and scalable framework for coalescent analysis in population genetics. There is no scalable GUI based user application either. Such a framework and application would not only drive the creation of more complex and realistic models but also make them truly accessible. Results As a first attempt, we built a framework and user application for the domain of exact calculations in coalescent analysis. The framework provides an API with the concepts of model, data, statistic, phylogeny, gene tree and recursion. Infinite-alleles and infinite-sites models are considered. It defines pluggable computations such as counting and listing all the ancestral configurations and genealogies and computing the exact probability of data. It can visualize a gene tree, trace and visualize the internals of the recursion algorithm for further improvement and attach dynamically a number of output processors. The user application defines jobs in a plug-in like manner so that they can be activated, deactivated, installed or uninstalled on demand. Multiple jobs can be run and their inputs edited. Job inputs are persisted across restarts and running jobs can be cancelled where applicable. Conclusions Coalescent theory plays an increasingly important role in analysing molecular population genetic data. Models involved are mathematically difficult and computationally challenging. An open-source, scalable framework that lets users immediately take advantage of the progress made by others will enable exploration of yet more difficult and realistic models. As models become more complex and mathematically less tractable, the need for an integrated computational approach is obvious. Object oriented designs, though has upfront costs, are practical now and can provide such an integrated approach. PMID:23033878

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.

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.

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.

Sputnik: ad hoc distributed computation.

PubMed

Völkel, Gunnar; Lausser, Ludwig; Schmid, Florian; Kraus, Johann M; Kestler, Hans A

2015-04-15

In bioinformatic applications, computationally demanding algorithms are often parallelized to speed up computation. Nevertheless, setting up computational environments for distributed computation is often tedious. Aim of this project were the lightweight ad hoc set up and fault-tolerant computation requiring only a Java runtime, no administrator rights, while utilizing all CPU cores most effectively. The Sputnik framework provides ad hoc distributed computation on the Java Virtual Machine which uses all supplied CPU cores fully. It provides a graphical user interface for deployment setup and a web user interface displaying the current status of current computation jobs. Neither a permanent setup nor administrator privileges are required. We demonstrate the utility of our approach on feature selection of microarray data. The Sputnik framework is available on Github http://github.com/sysbio-bioinf/sputnik under the Eclipse Public License. hkestler@fli-leibniz.de or hans.kestler@uni-ulm.de Supplementary data are available at Bioinformatics online. © The Author 2014. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Global computing for bioinformatics.

PubMed

Loewe, Laurence

2002-12-01

Global computing, the collaboration of idle PCs via the Internet in a SETI@home style, emerges as a new way of massive parallel multiprocessing with potentially enormous CPU power. Its relations to the broader, fast-moving field of Grid computing are discussed without attempting a review of the latter. This review (i) includes a short table of milestones in global computing history, (ii) lists opportunities global computing offers for bioinformatics, (iii) describes the structure of problems well suited for such an approach, (iv) analyses the anatomy of successful projects and (v) points to existing software frameworks. Finally, an evaluation of the various costs shows that global computing indeed has merit, if the problem to be solved is already coded appropriately and a suitable global computing framework can be found. Then, either significant amounts of computing power can be recruited from the general public, or--if employed in an enterprise-wide Intranet for security reasons--idle desktop PCs can substitute for an expensive dedicated cluster.

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.

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.

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.

VIRTUAL LIVER: AN IN SILICO FRAMEWORK FOR ANALYZING CHEMICAL-INDUCED HEPATOTOXICITY

EPA Science Inventory

The US EPA Virtual Liver (v-LiverTM) is an in silico framework for the dose-dependent perturbation of normal hepatic functions by chemicals using in vitro data. The framework consists of a computable knowledge-base (KB) to infer putative pathways in hepatotoxicity and a cellular...

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.

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.

A Computational Framework for Bioimaging Simulation

PubMed Central

Watabe, Masaki; Arjunan, Satya N. V.; Fukushima, Seiya; Iwamoto, Kazunari; Kozuka, Jun; Matsuoka, Satomi; Shindo, Yuki; Ueda, Masahiro; Takahashi, Koichi

2015-01-01

Using bioimaging technology, biologists have attempted to identify and document analytical interpretations that underlie biological phenomena in biological cells. Theoretical biology aims at distilling those interpretations into knowledge in the mathematical form of biochemical reaction networks and understanding how higher level functions emerge from the combined action of biomolecules. However, there still remain formidable challenges in bridging the gap between bioimaging and mathematical modeling. Generally, measurements using fluorescence microscopy systems are influenced by systematic effects that arise from stochastic nature of biological cells, the imaging apparatus, and optical physics. Such systematic effects are always present in all bioimaging systems and hinder quantitative comparison between the cell model and bioimages. Computational tools for such a comparison are still unavailable. Thus, in this work, we present a computational framework for handling the parameters of the cell models and the optical physics governing bioimaging systems. Simulation using this framework can generate digital images of cell simulation results after accounting for the systematic effects. We then demonstrate that such a framework enables comparison at the level of photon-counting units. PMID:26147508

Privacy-preserving GWAS analysis on federated genomic datasets.

PubMed

Constable, Scott D; Tang, Yuzhe; Wang, Shuang; Jiang, Xiaoqian; Chapin, Steve

2015-01-01

The biomedical community benefits from the increasing availability of genomic data to support meaningful scientific research, e.g., Genome-Wide Association Studies (GWAS). However, high quality GWAS usually requires a large amount of samples, which can grow beyond the capability of a single institution. Federated genomic data analysis holds the promise of enabling cross-institution collaboration for effective GWAS, but it raises concerns about patient privacy and medical information confidentiality (as data are being exchanged across institutional boundaries), which becomes an inhibiting factor for the practical use. We present a privacy-preserving GWAS framework on federated genomic datasets. Our method is to layer the GWAS computations on top of secure multi-party computation (MPC) systems. This approach allows two parties in a distributed system to mutually perform secure GWAS computations, but without exposing their private data outside. We demonstrate our technique by implementing a framework for minor allele frequency counting and χ2 statistics calculation, one of typical computations used in GWAS. For efficient prototyping, we use a state-of-the-art MPC framework, i.e., Portable Circuit Format (PCF) 1. Our experimental results show promise in realizing both efficient and secure cross-institution GWAS computations.

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.

Gender Differences in Teacher Computer Acceptance

ERIC Educational Resources Information Center

Yuen, Allan H. K.; Ma, Will W. K.

2002-01-01

Teachers' computer acceptance is an important factor to the successful use of computers in education. This article explores the gender differences in teacher computer acceptance. The Technology Acceptance Model (TAM) was used as the framework to determine if such differences are present. Survey questionnaires were administered to 186 preservice…

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.

Cable median barrier maintenance manual.

DOT National Transportation Integrated Search

2008-08-01

This implementation guide describes the conceptual framework, data requirements, and computational procedures for determining the safety and mobility impacts of work zones in Texas. Researchers designed the framework and procedures to assist district...

QCDLoop: A comprehensive framework for one-loop scalar integrals

NASA Astrophysics Data System (ADS)

Carrazza, Stefano; Ellis, R. Keith; Zanderighi, Giulia

2016-12-01

We present a new release of the QCDLoop library based on a modern object-oriented framework. We discuss the available new features such as the extension to the complex masses, the possibility to perform computations in double and quadruple precision simultaneously, and useful caching mechanisms to improve the computational speed. We benchmark the performance of the new library, and provide practical examples of phenomenological implementations by interfacing this new library to Monte Carlo programs.

Bayesian inference and decision theory - A framework for decision making in natural resource management

USGS Publications Warehouse

Dorazio, R.M.; Johnson, F.A.

2003-01-01

Bayesian inference and decision theory may be used in the solution of relatively complex problems of natural resource management, owing to recent advances in statistical theory and computing. In particular, Markov chain Monte Carlo algorithms provide a computational framework for fitting models of adequate complexity and for evaluating the expected consequences of alternative management actions. We illustrate these features using an example based on management of waterfowl habitat.

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.

PRESAGE: PRivacy-preserving gEnetic testing via SoftwAre Guard Extension.

PubMed

Chen, Feng; Wang, Chenghong; Dai, Wenrui; Jiang, Xiaoqian; Mohammed, Noman; Al Aziz, Md Momin; Sadat, Md Nazmus; Sahinalp, Cenk; Lauter, Kristin; Wang, Shuang

2017-07-26

Advances in DNA sequencing technologies have prompted a wide range of genomic applications to improve healthcare and facilitate biomedical research. However, privacy and security concerns have emerged as a challenge for utilizing cloud computing to handle sensitive genomic data. We present one of the first implementations of Software Guard Extension (SGX) based securely outsourced genetic testing framework, which leverages multiple cryptographic protocols and minimal perfect hash scheme to enable efficient and secure data storage and computation outsourcing. We compared the performance of the proposed PRESAGE framework with the state-of-the-art homomorphic encryption scheme, as well as the plaintext implementation. The experimental results demonstrated significant performance over the homomorphic encryption methods and a small computational overhead in comparison to plaintext implementation. The proposed PRESAGE provides an alternative solution for secure and efficient genomic data outsourcing in an untrusted cloud by using a hybrid framework that combines secure hardware and multiple crypto protocols.

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.

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...

Dual-scan technique for the customization of zirconia computer-aided design/computer-aided manufacturing frameworks.

PubMed

Andreiuolo, Rafael Ferrone; Sabrosa, Carlos Eduardo; Dias, Katia Regina H Cervantes

2013-09-01

The use of bi-layered all-ceramic crowns has continuously grown since the introduction of computer-aided design/computer-aided manufacturing (CAD/CAM) zirconia cores. Unfortunately, despite the outstanding mechanical properties of zirconia, problems related to porcelain cracking or chipping remain. One of the reasons for this is that ceramic copings are usually milled to uniform thicknesses of 0.3-0.6 mm around the whole tooth preparation. This may not provide uniform thickness or appropriate support for the veneering porcelain. To prevent these problems, the dual-scan technique demonstrates an alternative that allows the restorative team to customize zirconia CAD/CAM frameworks with adequate porcelain thickness and support in a simple manner.

Cloud-based crowd sensing: a framework for location-based crowd analyzer and advisor

NASA Astrophysics Data System (ADS)

Aishwarya, K. C.; Nambi, A.; Hudson, S.; Nadesh, R. K.

2017-11-01

Cloud computing is an emerging field of computer science to integrate and explore large and powerful computing systems and storages for personal and also for enterprise requirements. Mobile Cloud Computing is the inheritance of this concept towards mobile hand-held devices. Crowdsensing, or to be precise, Mobile Crowdsensing is the process of sharing resources from an available group of mobile handheld devices that support sharing of different resources such as data, memory and bandwidth to perform a single task for collective reasons. In this paper, we propose a framework to use Crowdsensing and perform a crowd analyzer and advisor whether the user can go to the place or not. This is an ongoing research and is a new concept to which the direction of cloud computing has shifted and is viable for more expansion in the near future.

NASA Exhibits

NASA Technical Reports Server (NTRS)

Deardorff, Glenn; Djomehri, M. Jahed; Freeman, Ken; Gambrel, Dave; Green, Bryan; Henze, Chris; Hinke, Thomas; Hood, Robert; Kiris, Cetin; Moran, Patrick;

Scaling an urban emergency evacuation framework : challenges and practices.

DOT National Transportation Integrated Search

2014-01-01

Critical infrastructure disruption, caused by severe weather events, natural disasters, terrorist : attacks, etc., has significant impacts on urban transportation systems. We built a computational : framework to simulate urban transportation systems ...

Symbolic Computation Using Cellular Automata-Based Hyperdimensional Computing.

PubMed

Yilmaz, Ozgur

2015-12-01

This letter introduces a novel framework of reservoir computing that is capable of both connectionist machine intelligence and symbolic computation. A cellular automaton is used as the reservoir of dynamical systems. Input is randomly projected onto the initial conditions of automaton cells, and nonlinear computation is performed on the input via application of a rule in the automaton for a period of time. The evolution of the automaton creates a space-time volume of the automaton state space, and it is used as the reservoir. The proposed framework is shown to be capable of long-term memory, and it requires orders of magnitude less computation compared to echo state networks. As the focus of the letter, we suggest that binary reservoir feature vectors can be combined using Boolean operations as in hyperdimensional computing, paving a direct way for concept building and symbolic processing. To demonstrate the capability of the proposed system, we make analogies directly on image data by asking, What is the automobile of air?

The Computer in the School: Tutor, Tool, Tutee.

ERIC Educational Resources Information Center

Taylor, Robert, Ed.

Nineteen essays by five pioneers in the field of computers in education are presented in this volume. The essays provide a foundation for understanding the basic issues involved in using computers in schools, the teacher's role in helping the student make full use of computing, and the general limitations of computer use. A framework is presented…

A numerical framework for bubble transport in a subcooled fluid flow

NASA Astrophysics Data System (ADS)

Jareteg, Klas; Sasic, Srdjan; Vinai, Paolo; Demazière, Christophe

2017-09-01

In this paper we present a framework for the simulation of dispersed bubbly two-phase flows, with the specific aim of describing vapor-liquid systems with condensation. We formulate and implement a framework that consists of a population balance equation (PBE) for the bubble size distribution and an Eulerian-Eulerian two-fluid solver. The PBE is discretized using the Direct Quadrature Method of Moments (DQMOM) in which we include the condensation of the bubbles as an internal phase space convection. We investigate the robustness of the DQMOM formulation and the numerical issues arising from the rapid shrinkage of the vapor bubbles. In contrast to a PBE method based on the multiple-size-group (MUSIG) method, the DQMOM formulation allows us to compute a distribution with dynamic bubble sizes. Such a property is advantageous to capture the wide range of bubble sizes associated with the condensation process. Furthermore, we compare the computational performance of the DQMOM-based framework with the MUSIG method. The results demonstrate that DQMOM is able to retrieve the bubble size distribution with a good numerical precision in only a small fraction of the computational time required by MUSIG. For the two-fluid solver, we examine the implementation of the mass, momentum and enthalpy conservation equations in relation to the coupling to the PBE. In particular, we propose a formulation of the pressure and liquid continuity equations, that was shown to correctly preserve mass when computing the vapor fraction with DQMOM. In addition, the conservation of enthalpy was also proven. Therefore a consistent overall framework that couples the PBE and two-fluid solvers is achieved.

Computing with scale-invariant neural representations

NASA Astrophysics Data System (ADS)

Howard, Marc; Shankar, Karthik

The Weber-Fechner law is perhaps the oldest quantitative relationship in psychology. Consider the problem of the brain representing a function f (x) . Different neurons have receptive fields that support different parts of the range, such that the ith neuron has a receptive field at xi. Weber-Fechner scaling refers to the finding that the width of the receptive field scales with xi as does the difference between the centers of adjacent receptive fields. Weber-Fechner scaling is exponentially resource-conserving. Neurophysiological evidence suggests that neural representations obey Weber-Fechner scaling in the visual system and perhaps other systems as well. We describe an optimality constraint that is solved by Weber-Fechner scaling, providing an information-theoretic rationale for this principle of neural coding. Weber-Fechner scaling can be generated within a mathematical framework using the Laplace transform. Within this framework, simple computations such as translation, correlation and cross-correlation can be accomplished. This framework can in principle be extended to provide a general computational language for brain-inspired cognitive computation on scale-invariant representations. Supported by NSF PHY 1444389 and the BU Initiative for the Physics and Mathematics of Neural Systems,.

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

Solis, John Hector

In this paper, we present a modular framework for constructing a secure and efficient program obfuscation scheme. Our approach, inspired by the obfuscation with respect to oracle machines model of [4], retains an interactive online protocol with an oracle, but relaxes the original computational and storage restrictions. We argue this is reasonable given the computational resources of modern personal devices. Furthermore, we relax the information-theoretic security requirement for computational security to utilize established cryptographic primitives. With this additional flexibility we are free to explore different cryptographic buildingblocks. Our approach combines authenticated encryption with private information retrieval to construct a securemore » program obfuscation framework. We give a formal specification of our framework, based on desired functionality and security properties, and provide an example instantiation. In particular, we implement AES in Galois/Counter Mode for authenticated encryption and the Gentry-Ramzan [13]constant communication-rate private information retrieval scheme. We present our implementation results and show that non-trivial sized programs can be realized, but scalability is quickly limited by computational overhead. Finally, we include a discussion on security considerations when instantiating specific modules.« less

Intelligent Control of a Sensor-Actuator System via Kernelized Least-Squares Policy Iteration

PubMed Central

Liu, Bo; Chen, Sanfeng; Li, Shuai; Liang, Yongsheng

2012-01-01

In this paper a new framework, called Compressive Kernelized Reinforcement Learning (CKRL), for computing near-optimal policies in sequential decision making with uncertainty is proposed via incorporating the non-adaptive data-independent Random Projections and nonparametric Kernelized Least-squares Policy Iteration (KLSPI). Random Projections are a fast, non-adaptive dimensionality reduction framework in which high-dimensionality data is projected onto a random lower-dimension subspace via spherically random rotation and coordination sampling. KLSPI introduce kernel trick into the LSPI framework for Reinforcement Learning, often achieving faster convergence and providing automatic feature selection via various kernel sparsification approaches. In this approach, policies are computed in a low-dimensional subspace generated by projecting the high-dimensional features onto a set of random basis. We first show how Random Projections constitute an efficient sparsification technique and how our method often converges faster than regular LSPI, while at lower computational costs. Theoretical foundation underlying this approach is a fast approximation of Singular Value Decomposition (SVD). Finally, simulation results are exhibited on benchmark MDP domains, which confirm gains both in computation time and in performance in large feature spaces. PMID:22736969

A comprehensive risk assessment framework for offsite transportation of inflammable hazardous waste.

PubMed

Das, Arup; Gupta, A K; Mazumder, T N

2012-08-15

A framework for risk assessment due to offsite transportation of hazardous wastes is designed based on the type of event that can be triggered from an accident of a hazardous waste carrier. The objective of this study is to design a framework for computing the risk to population associated with offsite transportation of inflammable and volatile wastes. The framework is based on traditional definition of risk and is designed for conditions where accident databases are not available. The probability based variable in risk assessment framework is substituted by a composite accident index proposed in this study. The framework computes the impacts due to a volatile cloud explosion based on TNO Multi-energy model. The methodology also estimates the vulnerable population in terms of disability adjusted life years (DALY) which takes into consideration the demographic profile of the population and the degree of injury on mortality and morbidity sustained. The methodology is illustrated using a case study of a pharmaceutical industry in the Kolkata metropolitan area. Copyright © 2012 Elsevier B.V. All rights reserved.

MOOSE: A PARALLEL COMPUTATIONAL FRAMEWORK FOR COUPLED SYSTEMS OF NONLINEAR EQUATIONS.

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

G. Hansen; C. Newman; D. Gaston

Systems of coupled, nonlinear partial di?erential equations often arise in sim- ulation of nuclear processes. MOOSE: Multiphysics Ob ject Oriented Simulation Environment, a parallel computational framework targeted at solving these systems is presented. As opposed to traditional data / ?ow oriented com- putational frameworks, MOOSE is instead founded on mathematics based on Jacobian-free Newton Krylov (JFNK). Utilizing the mathematical structure present in JFNK, physics are modularized into “Kernels” allowing for rapid production of new simulation tools. In addition, systems are solved fully cou- pled and fully implicit employing physics based preconditioning allowing for a large amount of ?exibility even withmore » large variance in time scales. Background on the mathematics, an inspection of the structure of MOOSE and several rep- resentative solutions from applications built on the framework are presented.« less

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.

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

Space-Time Processing for Tactical Mobile Ad Hoc Networks

DTIC Science & Technology

2008-08-01

vision for multiple concurrent communication settings, i.e., a many-to-many framework where multi-packet transmissions (MPTs) and multi-packet...modelling framework of capacity-delay tradeoffs We have introduced the first unified modeling framework for the computation of fundamental limits o We...dalities in wireless n twor i-packet modelling framework to account for the use of m lti-packet reception (MPR) f ad hoc networks with MPT under

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.

Representations, approximations, and limitations within a computational framework for cognitive science. Comment on “Toward a computational framework for cognitive biology: Unifying approaches from cognitive neuroscience and comparative cognition” by W. Tecumseh Fitch

NASA Astrophysics Data System (ADS)

Perfors, Amy

2014-09-01

There is much to approve of in this provocative and interesting paper. I strongly agree in many parts, especially the point that dichotomies like nature/nurture are actively detrimental to the field. I also appreciate the idea that cognitive scientists should take the "biological wetware" of the cell (rather than the network) more seriously.

Dynamic optimization of chemical processes using ant colony framework.

PubMed

Rajesh, J; Gupta, K; Kusumakar, H S; Jayaraman, V K; Kulkarni, B D

2001-11-01

Ant colony framework is illustrated by considering dynamic optimization of six important bench marking examples. This new computational tool is simple to implement and can tackle problems with state as well as terminal constraints in a straightforward fashion. It requires fewer grid points to reach the global optimum at relatively very low computational effort. The examples with varying degree of complexities, analyzed here, illustrate its potential for solving a large class of process optimization problems in chemical engineering.

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.

ProjectQ Software Framework

NASA Astrophysics Data System (ADS)

Steiger, Damian S.; Haener, Thomas; Troyer, Matthias

Quantum computers promise to transform our notions of computation by offering a completely new paradigm. A high level quantum programming language and optimizing compilers are essential components to achieve scalable quantum computation. In order to address this, we introduce the ProjectQ software framework - an open source effort to support both theorists and experimentalists by providing intuitive tools to implement and run quantum algorithms. Here, we present our ProjectQ quantum compiler, which compiles a quantum algorithm from our high-level Python-embedded language down to low-level quantum gates available on the target system. We demonstrate how this compiler can be used to control actual hardware and to run high-performance simulations.

A Framework for Load Balancing of Tensor Contraction Expressions via Dynamic Task Partitioning

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

Lai, Pai-Wei; Stock, Kevin; Rajbhandari, Samyam

In this paper, we introduce the Dynamic Load-balanced Tensor Contractions (DLTC), a domain-specific library for efficient task parallel execution of tensor contraction expressions, a class of computation encountered in quantum chemistry and physics. Our framework decomposes each contraction into smaller unit of tasks, represented by an abstraction referred to as iterators. We exploit an extra level of parallelism by having tasks across independent contractions executed concurrently through a dynamic load balancing run- time. We demonstrate the improved performance, scalability, and flexibility for the computation of tensor contraction expressions on parallel computers using examples from coupled cluster methods.

A Cyber-ITS Framework for Massive Traffic Data Analysis Using Cyber Infrastructure

PubMed Central

Fontaine, Michael D.

2013-01-01

Traffic data is commonly collected from widely deployed sensors in urban areas. This brings up a new research topic, data-driven intelligent transportation systems (ITSs), which means to integrate heterogeneous traffic data from different kinds of sensors and apply it for ITS applications. This research, taking into consideration the significant increase in the amount of traffic data and the complexity of data analysis, focuses mainly on the challenge of solving data-intensive and computation-intensive problems. As a solution to the problems, this paper proposes a Cyber-ITS framework to perform data analysis on Cyber Infrastructure (CI), by nature parallel-computing hardware and software systems, in the context of ITS. The techniques of the framework include data representation, domain decomposition, resource allocation, and parallel processing. All these techniques are based on data-driven and application-oriented models and are organized as a component-and-workflow-based model in order to achieve technical interoperability and data reusability. A case study of the Cyber-ITS framework is presented later based on a traffic state estimation application that uses the fusion of massive Sydney Coordinated Adaptive Traffic System (SCATS) data and GPS data. The results prove that the Cyber-ITS-based implementation can achieve a high accuracy rate of traffic state estimation and provide a significant computational speedup for the data fusion by parallel computing. PMID:23766690

A Cyber-ITS framework for massive traffic data analysis using cyber infrastructure.

PubMed

Xia, Yingjie; Hu, Jia; Fontaine, Michael D

2013-01-01

Traffic data is commonly collected from widely deployed sensors in urban areas. This brings up a new research topic, data-driven intelligent transportation systems (ITSs), which means to integrate heterogeneous traffic data from different kinds of sensors and apply it for ITS applications. This research, taking into consideration the significant increase in the amount of traffic data and the complexity of data analysis, focuses mainly on the challenge of solving data-intensive and computation-intensive problems. As a solution to the problems, this paper proposes a Cyber-ITS framework to perform data analysis on Cyber Infrastructure (CI), by nature parallel-computing hardware and software systems, in the context of ITS. The techniques of the framework include data representation, domain decomposition, resource allocation, and parallel processing. All these techniques are based on data-driven and application-oriented models and are organized as a component-and-workflow-based model in order to achieve technical interoperability and data reusability. A case study of the Cyber-ITS framework is presented later based on a traffic state estimation application that uses the fusion of massive Sydney Coordinated Adaptive Traffic System (SCATS) data and GPS data. The results prove that the Cyber-ITS-based implementation can achieve a high accuracy rate of traffic state estimation and provide a significant computational speedup for the data fusion by parallel computing.

Self-evaluation of decision-making: A general Bayesian framework for metacognitive computation.

PubMed

Fleming, Stephen M; Daw, Nathaniel D

2017-01-01

People are often aware of their mistakes, and report levels of confidence in their choices that correlate with objective performance. These metacognitive assessments of decision quality are important for the guidance of behavior, particularly when external feedback is absent or sporadic. However, a computational framework that accounts for both confidence and error detection is lacking. In addition, accounts of dissociations between performance and metacognition have often relied on ad hoc assumptions, precluding a unified account of intact and impaired self-evaluation. Here we present a general Bayesian framework in which self-evaluation is cast as a "second-order" inference on a coupled but distinct decision system, computationally equivalent to inferring the performance of another actor. Second-order computation may ensue whenever there is a separation between internal states supporting decisions and confidence estimates over space and/or time. We contrast second-order computation against simpler first-order models in which the same internal state supports both decisions and confidence estimates. Through simulations we show that second-order computation provides a unified account of different types of self-evaluation often considered in separate literatures, such as confidence and error detection, and generates novel predictions about the contribution of one's own actions to metacognitive judgments. In addition, the model provides insight into why subjects' metacognition may sometimes be better or worse than task performance. We suggest that second-order computation may underpin self-evaluative judgments across a range of domains. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

Self-Evaluation of Decision-Making: A General Bayesian Framework for Metacognitive Computation

PubMed Central

2017-01-01

People are often aware of their mistakes, and report levels of confidence in their choices that correlate with objective performance. These metacognitive assessments of decision quality are important for the guidance of behavior, particularly when external feedback is absent or sporadic. However, a computational framework that accounts for both confidence and error detection is lacking. In addition, accounts of dissociations between performance and metacognition have often relied on ad hoc assumptions, precluding a unified account of intact and impaired self-evaluation. Here we present a general Bayesian framework in which self-evaluation is cast as a “second-order” inference on a coupled but distinct decision system, computationally equivalent to inferring the performance of another actor. Second-order computation may ensue whenever there is a separation between internal states supporting decisions and confidence estimates over space and/or time. We contrast second-order computation against simpler first-order models in which the same internal state supports both decisions and confidence estimates. Through simulations we show that second-order computation provides a unified account of different types of self-evaluation often considered in separate literatures, such as confidence and error detection, and generates novel predictions about the contribution of one’s own actions to metacognitive judgments. In addition, the model provides insight into why subjects’ metacognition may sometimes be better or worse than task performance. We suggest that second-order computation may underpin self-evaluative judgments across a range of domains. PMID:28004960

An enhanced mobile-healthcare emergency system based on extended chaotic maps.

PubMed

Lee, Cheng-Chi; Hsu, Che-Wei; Lai, Yan-Ming; Vasilakos, Athanasios

2013-10-01

Mobile Healthcare (m-Healthcare) systems, namely smartphone applications of pervasive computing that utilize wireless body sensor networks (BSNs), have recently been proposed to provide smartphone users with health monitoring services and received great attentions. An m-Healthcare system with flaws, however, may leak out the smartphone user's personal information and cause security, privacy preservation, or user anonymity problems. In 2012, Lu et al. proposed a secure and privacy-preserving opportunistic computing (SPOC) framework for mobile-Healthcare emergency. The brilliant SPOC framework can opportunistically gather resources on the smartphone such as computing power and energy to process the computing-intensive personal health information (PHI) in case of an m-Healthcare emergency with minimal privacy disclosure. To balance between the hazard of PHI privacy disclosure and the necessity of PHI processing and transmission in m-Healthcare emergency, in their SPOC framework, Lu et al. introduced an efficient user-centric privacy access control system which they built on the basis of an attribute-based access control mechanism and a new privacy-preserving scalar product computation (PPSPC) technique. However, we found out that Lu et al.'s protocol still has some secure flaws such as user anonymity and mutual authentication. To fix those problems and further enhance the computation efficiency of Lu et al.'s protocol, in this article, the authors will present an improved mobile-Healthcare emergency system based on extended chaotic maps. The new system is capable of not only providing flawless user anonymity and mutual authentication but also reducing the computation cost.

Computational Properties of the Hippocampus Increase the Efficiency of Goal-Directed Foraging through Hierarchical Reinforcement Learning

PubMed Central

Chalmers, Eric; Luczak, Artur; Gruber, Aaron J.

2016-01-01

The mammalian brain is thought to use a version of Model-based Reinforcement Learning (MBRL) to guide “goal-directed” behavior, wherein animals consider goals and make plans to acquire desired outcomes. However, conventional MBRL algorithms do not fully explain animals' ability to rapidly adapt to environmental changes, or learn multiple complex tasks. They also require extensive computation, suggesting that goal-directed behavior is cognitively expensive. We propose here that key features of processing in the hippocampus support a flexible MBRL mechanism for spatial navigation that is computationally efficient and can adapt quickly to change. We investigate this idea by implementing a computational MBRL framework that incorporates features inspired by computational properties of the hippocampus: a hierarchical representation of space, “forward sweeps” through future spatial trajectories, and context-driven remapping of place cells. We find that a hierarchical abstraction of space greatly reduces the computational load (mental effort) required for adaptation to changing environmental conditions, and allows efficient scaling to large problems. It also allows abstract knowledge gained at high levels to guide adaptation to new obstacles. Moreover, a context-driven remapping mechanism allows learning and memory of multiple tasks. Simulating dorsal or ventral hippocampal lesions in our computational framework qualitatively reproduces behavioral deficits observed in rodents with analogous lesions. The framework may thus embody key features of how the brain organizes model-based RL to efficiently solve navigation and other difficult tasks. PMID:28018203

A Semantic Grid Oriented to E-Tourism

NASA Astrophysics Data System (ADS)

Zhang, Xiao Ming

With increasing complexity of tourism business models and tasks, there is a clear need of the next generation e-Tourism infrastructure to support flexible automation, integration, computation, storage, and collaboration. Currently several enabling technologies such as semantic Web, Web service, agent and grid computing have been applied in the different e-Tourism applications, however there is no a unified framework to be able to integrate all of them. So this paper presents a promising e-Tourism framework based on emerging semantic grid, in which a number of key design issues are discussed including architecture, ontologies structure, semantic reconciliation, service and resource discovery, role based authorization and intelligent agent. The paper finally provides the implementation of the framework.

Applicability Analysis of Validation Evidence for Biomedical Computational Models

DOE PAGES

Pathmanathan, Pras; Gray, Richard A.; Romero, Vicente J.; ...

2017-09-07

Computational modeling has the potential to revolutionize medicine the way it transformed engineering. However, despite decades of work, there has only been limited progress to successfully translate modeling research to patient care. One major difficulty which often occurs with biomedical computational models is an inability to perform validation in a setting that closely resembles how the model will be used. For example, for a biomedical model that makes in vivo clinically relevant predictions, direct validation of predictions may be impossible for ethical, technological, or financial reasons. Unavoidable limitations inherent to the validation process lead to challenges in evaluating the credibilitymore » of biomedical model predictions. Therefore, when evaluating biomedical models, it is critical to rigorously assess applicability, that is, the relevance of the computational model, and its validation evidence to the proposed context of use (COU). However, there are no well-established methods for assessing applicability. In this paper, we present a novel framework for performing applicability analysis and demonstrate its use with a medical device computational model. The framework provides a systematic, step-by-step method for breaking down the broad question of applicability into a series of focused questions, which may be addressed using supporting evidence and subject matter expertise. The framework can be used for model justification, model assessment, and validation planning. While motivated by biomedical models, it is relevant to a broad range of disciplines and underlying physics. Finally, the proposed applicability framework could help overcome some of the barriers inherent to validation of, and aid clinical implementation of, biomedical models.« less

Applicability Analysis of Validation Evidence for Biomedical Computational Models

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

Pathmanathan, Pras; Gray, Richard A.; Romero, Vicente J.

Computational modeling has the potential to revolutionize medicine the way it transformed engineering. However, despite decades of work, there has only been limited progress to successfully translate modeling research to patient care. One major difficulty which often occurs with biomedical computational models is an inability to perform validation in a setting that closely resembles how the model will be used. For example, for a biomedical model that makes in vivo clinically relevant predictions, direct validation of predictions may be impossible for ethical, technological, or financial reasons. Unavoidable limitations inherent to the validation process lead to challenges in evaluating the credibilitymore » of biomedical model predictions. Therefore, when evaluating biomedical models, it is critical to rigorously assess applicability, that is, the relevance of the computational model, and its validation evidence to the proposed context of use (COU). However, there are no well-established methods for assessing applicability. In this paper, we present a novel framework for performing applicability analysis and demonstrate its use with a medical device computational model. The framework provides a systematic, step-by-step method for breaking down the broad question of applicability into a series of focused questions, which may be addressed using supporting evidence and subject matter expertise. The framework can be used for model justification, model assessment, and validation planning. While motivated by biomedical models, it is relevant to a broad range of disciplines and underlying physics. Finally, the proposed applicability framework could help overcome some of the barriers inherent to validation of, and aid clinical implementation of, biomedical models.« less

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%.

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.

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...

Implementation guide for monitoring work zone safety and mobility impacts

DOT National Transportation Integrated Search

2009-01-01

This implementation guide describes the conceptual framework, data requirements, and computational procedures for determining the safety and mobility impacts of work zones in Texas. Researchers designed the framework and procedures to assist district...

Predictive Models and Computational Embryology

EPA Science Inventory

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

Designing Educational Games for Computer Programming: A Holistic Framework

ERIC Educational Resources Information Center

Malliarakis, Christos; Satratzemi, Maya; Xinogalos, Stelios

2014-01-01

Computer science is continuously evolving during the past decades. This has also brought forth new knowledge that should be incorporated and new learning strategies must be adopted for the successful teaching of all sub-domains. For example, computer programming is a vital knowledge area within computer science with constantly changing curriculum…

Capturing and analyzing wheelchair maneuvering patterns with mobile cloud computing.

PubMed

Fu, Jicheng; Hao, Wei; White, Travis; Yan, Yuqing; Jones, Maria; Jan, Yih-Kuen

2013-01-01

Power wheelchairs have been widely used to provide independent mobility to people with disabilities. Despite great advancements in power wheelchair technology, research shows that wheelchair related accidents occur frequently. To ensure safe maneuverability, capturing wheelchair maneuvering patterns is fundamental to enable other research, such as safe robotic assistance for wheelchair users. In this study, we propose to record, store, and analyze wheelchair maneuvering data by means of mobile cloud computing. Specifically, the accelerometer and gyroscope sensors in smart phones are used to record wheelchair maneuvering data in real-time. Then, the recorded data are periodically transmitted to the cloud for storage and analysis. The analyzed results are then made available to various types of users, such as mobile phone users, traditional desktop users, etc. The combination of mobile computing and cloud computing leverages the advantages of both techniques and extends the smart phone's capabilities of computing and data storage via the Internet. We performed a case study to implement the mobile cloud computing framework using Android smart phones and Google App Engine, a popular cloud computing platform. Experimental results demonstrated the feasibility of the proposed mobile cloud computing framework.

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

EPA Science Inventory

Fine-scale Computational Fluid Dynamics (CFD) simulation of pollutant concentrations within roadway and building microenvironments is feasible using high performance computing. Unlike currently used regulatory air quality models, fine-scale CFD simulations are able to account rig...

Polyphony: A Workflow Orchestration Framework for Cloud Computing

NASA Technical Reports Server (NTRS)

Shams, Khawaja S.; Powell, Mark W.; Crockett, Tom M.; Norris, Jeffrey S.; Rossi, Ryan; Soderstrom, Tom

2010-01-01

Cloud Computing has delivered unprecedented compute capacity to NASA missions at affordable rates. Missions like the Mars Exploration Rovers (MER) and Mars Science Lab (MSL) are enjoying the elasticity that enables them to leverage hundreds, if not thousands, or machines for short durations without making any hardware procurements. In this paper, we describe Polyphony, a resilient, scalable, and modular framework that efficiently leverages a large set of computing resources to perform parallel computations. Polyphony can employ resources on the cloud, excess capacity on local machines, as well as spare resources on the supercomputing center, and it enables these resources to work in concert to accomplish a common goal. Polyphony is resilient to node failures, even if they occur in the middle of a transaction. We will conclude with an evaluation of a production-ready application built on top of Polyphony to perform image-processing operations of images from around the solar system, including Mars, Saturn, and Titan.

Reinventing patient-centered computing for the twenty-first century.

PubMed

Goldberg, H S; Morales, A; Gottlieb, L; Meador, L; Safran, C

2001-01-01

Despite evidence over the past decade that patients like and will use patient-centered computing systems in managing their health, patients have remained forgotten stakeholders in advances in clinical computing systems. We present a framework for patient empowerment and the technical realization of that framework in an architecture called CareLink. In an evaluation of the initial deployment of CareLink in the support of neonatal intensive care, we have demonstrated a reduction in the length of stay for very-low birthweight infants, and an improvement in family satisfaction with care delivery. With the ubiquitous adoption of the Internet into the general culture, patient-centered computing provides the opportunity to mend broken health care relationships and reconnect patients to the care delivery process. CareLink itself provides functionality to support both clinical care and research, and provides a living laboratory for the further study of patient-centered computing.

GPU based framework for geospatial analyses

NASA Astrophysics Data System (ADS)

Cosmin Sandric, Ionut; Ionita, Cristian; Dardala, Marian; Furtuna, Titus

2017-04-01

Parallel processing on multiple CPU cores is already used at large scale in geocomputing, but parallel processing on graphics cards is just at the beginning. Being able to use an simple laptop with a dedicated graphics card for advanced and very fast geocomputation is an advantage that each scientist wants to have. The necessity to have high speed computation in geosciences has increased in the last 10 years, mostly due to the increase in the available datasets. These datasets are becoming more and more detailed and hence they require more space to store and more time to process. Distributed computation on multicore CPU's and GPU's plays an important role by processing one by one small parts from these big datasets. These way of computations allows to speed up the process, because instead of using just one process for each dataset, the user can use all the cores from a CPU or up to hundreds of cores from GPU The framework provide to the end user a standalone tools for morphometry analyses at multiscale level. An important part of the framework is dedicated to uncertainty propagation in geospatial analyses. The uncertainty may come from the data collection or may be induced by the model or may have an infinite sources. These uncertainties plays important roles when a spatial delineation of the phenomena is modelled. Uncertainty propagation is implemented inside the GPU framework using Monte Carlo simulations. The GPU framework with the standalone tools proved to be a reliable tool for modelling complex natural phenomena The framework is based on NVidia Cuda technology and is written in C++ programming language. The code source will be available on github at https://github.com/sandricionut/GeoRsGPU Acknowledgement: GPU framework for geospatial analysis, Young Researchers Grant (ICUB-University of Bucharest) 2016, director Ionut Sandric

Rainbow: A Framework for Analysing Computer-Mediated Pedagogical Debates

ERIC Educational Resources Information Center

Baker, Michael; Andriessen, Jerry; Lund, Kristine; van Amelsvoort, Marie; Quignard, Matthieu

2007-01-01

In this paper we present a framework for analysing when and how students engage in a specific form of interactive knowledge elaboration in CSCL environments: broadening and deepening understanding of a space of debate. The framework is termed "Rainbow," as it comprises seven principal analytical categories, to each of which a colour is assigned,…

Mathematical Frameworks for Diagnostics, Prognostics and Condition Based Maintenance Problems

DTIC Science & Technology

2008-08-15

REPORT Mathematical Frameworks for Diagnostics, Prognostics and Condition Based Maintenance Problems (W911NF-05-1-0426) 14. ABSTRACT 16. SECURITY ...other documentation. 12. DISTRIBUTION AVAILIBILITY STATEMENT Approved for Public Release; Distribution Unlimited 9. SPONSORING/MONITORING AGENCY NAME...parallel and distributed computing environment were researched. In support of the Condition Based Maintenance (CBM) philosophy, a theoretical framework

Advances in the spatially distributed ages-w model: parallel computation, java connection framework (JCF) integration, and streamflow/nitrogen dynamics assessment

USDA-ARS?s Scientific Manuscript database

AgroEcoSystem-Watershed (AgES-W) is a modular, Java-based spatially distributed model which implements hydrologic and water quality (H/WQ) simulation components under the Java Connection Framework (JCF) and the Object Modeling System (OMS) environmental modeling framework. AgES-W is implicitly scala...

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.

Computer Assistance in Information Work. Part I: Conceptual Framework for Improving the Computer/User Interface in Information Work. Part II: Catalog of Acceleration, Augmentation, and Delegation Functions in Information Work.

ERIC Educational Resources Information Center

Paisley, William; Butler, Matilda

This study of the computer/user interface investigated the role of the computer in performing information tasks that users now perform without computer assistance. Users' perceptual/cognitive processes are to be accelerated or augmented by the computer; a long term goal is to delegate information tasks entirely to the computer. Cybernetic and…

Eye-movements and Voice as Interface Modalities to Computer Systems

NASA Astrophysics Data System (ADS)

Farid, Mohsen M.; Murtagh, Fionn D.

2003-03-01

We investigate the visual and vocal modalities of interaction with computer systems. We focus our attention on the integration of visual and vocal interface as possible replacement and/or additional modalities to enhance human-computer interaction. We present a new framework for employing eye gaze as a modality of interface. While voice commands, as means of interaction with computers, have been around for a number of years, integration of both the vocal interface and the visual interface, in terms of detecting user's eye movements through an eye-tracking device, is novel and promises to open the horizons for new applications where a hand-mouse interface provides little or no apparent support to the task to be accomplished. We present an array of applications to illustrate the new framework and eye-voice integration.

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

A compressive sensing based secure watermark detection and privacy preserving storage framework.

PubMed

Qia Wang; Wenjun Zeng; Jun Tian

2014-03-01

Privacy is a critical issue when the data owners outsource data storage or processing to a third party computing service, such as the cloud. In this paper, we identify a cloud computing application scenario that requires simultaneously performing secure watermark detection and privacy preserving multimedia data storage. We then propose a compressive sensing (CS)-based framework using secure multiparty computation (MPC) protocols to address such a requirement. In our framework, the multimedia data and secret watermark pattern are presented to the cloud for secure watermark detection in a CS domain to protect the privacy. During CS transformation, the privacy of the CS matrix and the watermark pattern is protected by the MPC protocols under the semi-honest security model. We derive the expected watermark detection performance in the CS domain, given the target image, watermark pattern, and the size of the CS matrix (but without the CS matrix itself). The correctness of the derived performance has been validated by our experiments. Our theoretical analysis and experimental results show that secure watermark detection in the CS domain is feasible. Our framework can also be extended to other collaborative secure signal processing and data-mining applications in the cloud.

Tracking the Reorganization of Module Structure in Time-Varying Weighted Brain Functional Connectivity Networks.

PubMed

Schmidt, Christoph; Piper, Diana; Pester, Britta; Mierau, Andreas; Witte, Herbert

2018-05-01

Identification of module structure in brain functional networks is a promising way to obtain novel insights into neural information processing, as modules correspond to delineated brain regions in which interactions are strongly increased. Tracking of network modules in time-varying brain functional networks is not yet commonly considered in neuroscience despite its potential for gaining an understanding of the time evolution of functional interaction patterns and associated changing degrees of functional segregation and integration. We introduce a general computational framework for extracting consensus partitions from defined time windows in sequences of weighted directed edge-complete networks and show how the temporal reorganization of the module structure can be tracked and visualized. Part of the framework is a new approach for computing edge weight thresholds for individual networks based on multiobjective optimization of module structure quality criteria as well as an approach for matching modules across time steps. By testing our framework using synthetic network sequences and applying it to brain functional networks computed from electroencephalographic recordings of healthy subjects that were exposed to a major balance perturbation, we demonstrate the framework's potential for gaining meaningful insights into dynamic brain function in the form of evolving network modules. The precise chronology of the neural processing inferred with our framework and its interpretation helps to improve the currently incomplete understanding of the cortical contribution for the compensation of such balance perturbations.

Predictive Models and Computational Toxicology (II IBAMTOX)

EPA Science Inventory

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

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…

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.

Titanium removable denture based on a one-metal rehabilitation concept.

PubMed

Ohkubo, Chikahiro; Sato, Yohei; Nishiyama, Yuichiro; Suzuki, Yasunori

2017-09-26

The use of a single metal for all restorations would be necessary because it protects against metal corrosion caused by the contact of different metals. For this "one-metal rehabilitation" concept, non-alloyed commercially pure (CP) titanium should be used for all restorations. Titanium frameworks have been cast and used for the long term without catastrophic failure, whereas they have been fabricated recently using computer-aided design/computer-aided manufacturing (CAD/CAM). However, the milling process for the frameworks of removable partial dentures (RPDs) is not easy because they have very complicated shapes and consist of many components. Currently, the fabrication of RPD frameworks has been challenged by one-process molding using repeated laser sintering and high-speed milling. Laser welding has also been used typically for repairing and rebuilding titanium frameworks. Although laboratory and clinical problems still remain, the one-metal rehabilitation concept using CP titanium as a bioinert metal can be recommended for all restorations.

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.

An application framework of three-dimensional reconstruction and measurement for endodontic research.

PubMed

Gao, Yuan; Peters, Ove A; Wu, Hongkun; Zhou, Xuedong

2009-02-01

The purpose of this study was to customize an application framework by using the MeVisLab image processing and visualization platform for three-dimensional reconstruction and assessment of tooth and root canal morphology. One maxillary first molar was scanned before and after preparation with ProTaper by using micro-computed tomography. With a customized application framework based on MeVisLab, internal and external anatomy was reconstructed. Furthermore, the dimensions of root canal and radicular dentin were quantified, and effects of canal preparation were assessed. Finally, a virtual preparation with risk analysis was performed to simulate the removal of a broken instrument. This application framework provided an economical platform and met current requirements of endodontic research. The broad-based use of high-quality free software and the resulting exchange of experience might help to improve the quality of endodontic research with micro-computed tomography.

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.

Decomposing dendrophilia. Comment on “Toward a computational framework for cognitive biology: Unifying approaches from cognitive neuroscience and comparative cognition” by W. Tecumseh Fitch

NASA Astrophysics Data System (ADS)

Honing, Henkjan; Zuidema, Willem

2014-09-01

The future of cognitive science will be about bridging neuroscience and behavioral studies, with essential roles played by comparative biology, formal modeling, and the theory of computation. Nowhere will this integration be more strongly needed than in understanding the biological basis of language and music. We thus strongly sympathize with the general framework that Fitch [1] proposes, and welcome the remarkably broad and readable review he presents to support it.

Software Framework for Peer Data-Management Services

NASA Technical Reports Server (NTRS)

Hughes, John; Hardman, Sean; Crichton, Daniel; Hyon, Jason; Kelly, Sean; Tran, Thuy

2007-01-01

Object Oriented Data Technology (OODT) is a software framework for creating a Web-based system for exchange of scientific data that are stored in diverse formats on computers at different sites under the management of scientific peers. OODT software consists of a set of cooperating, distributed peer components that provide distributed peer-to-peer (P2P) services that enable one peer to search and retrieve data managed by another peer. In effect, computers running OODT software at different locations become parts of an integrated data-management system.

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.

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

Exploring methodological frameworks for a mental task-based near-infrared spectroscopy brain-computer interface.

PubMed

Weyand, Sabine; Takehara-Nishiuchi, Kaori; Chau, Tom

2015-10-30

Near-infrared spectroscopy (NIRS) brain-computer interfaces (BCIs) enable users to interact with their environment using only cognitive activities. This paper presents the results of a comparison of four methodological frameworks used to select a pair of tasks to control a binary NIRS-BCI; specifically, three novel personalized task paradigms and the state-of-the-art prescribed task framework were explored. Three types of personalized task selection approaches were compared, including: user-selected mental tasks using weighted slope scores (WS-scores), user-selected mental tasks using pair-wise accuracy rankings (PWAR), and researcher-selected mental tasks using PWAR. These paradigms, along with the state-of-the-art prescribed mental task framework, where mental tasks are selected based on the most commonly used tasks in literature, were tested by ten able-bodied participants who took part in five NIRS-BCI sessions. The frameworks were compared in terms of their accuracy, perceived ease-of-use, computational time, user preference, and length of training. Most notably, researcher-selected personalized tasks resulted in significantly higher accuracies, while user-selected personalized tasks resulted in significantly higher perceived ease-of-use. It was also concluded that PWAR minimized the amount of data that needed to be collected; while, WS-scores maximized user satisfaction and minimized computational time. In comparison to the state-of-the-art prescribed mental tasks, our findings show that overall, personalized tasks appear to be superior to prescribed tasks with respect to accuracy and perceived ease-of-use. The deployment of personalized rather than prescribed mental tasks ought to be considered and further investigated in future NIRS-BCI studies. Copyright © 2015 Elsevier B.V. All rights reserved.

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.

Microcephaly: computational and organotypic modeling of a ...

EPA Pesticide Factsheets

lecture discusses computational and organotypic models of microcephaly in an AOP Framework and ToxCast assays. Lecture slide presentation at UNC Chapel Hill for Advanced Toxicology course lecture on Computational Approaches to Developmental and Reproductive Toxicology with presentation on computational and organotypic modeling of a complex human birth defect microcephaly with is associated with the recent Zika virus outbreak.

Students' Mathematics Word Problem-Solving Achievement in a Computer-Based Story

ERIC Educational Resources Information Center

Gunbas, N.

2015-01-01

The purpose of this study was to investigate the effect of a computer-based story, which was designed in anchored instruction framework, on sixth-grade students' mathematics word problem-solving achievement. Problems were embedded in a story presented on a computer as computer story, and then compared with the paper-based version of the same story…

Affective Feedback from Computers and its Effect on Perceived Ability and Affect: A Test of the Computers as Social Actor Hypothesis

ERIC Educational Resources Information Center

Mishra, Punya

2006-01-01

We report an experimental study that examined two questions: (a) The effect of affective feedback from computers on participants' motivation and self-perception of ability; and (b) whether people respond similarly to computer feedback as they do to human feedback. This study, framed within the Computers As Social Actors (CASA) framework,…

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.

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.

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.

Application of Computer Technology to Educational Administration in the United States.

ERIC Educational Resources Information Center

Bozeman, William C.; And Others

1991-01-01

Description of evolution of computer applications in U.S. educational administration is followed by an overview of the structure and governance of public education and Visscher's developmental framework. Typical administrative computer applications in education are discussed, including student records, personnel management, budgeting, library…

New Information Dispersal Techniques for Trustworthy Computing

ERIC Educational Resources Information Center

Parakh, Abhishek

2011-01-01

Information dispersal algorithms (IDA) are used for distributed data storage because they simultaneously provide security, reliability and space efficiency, constituting a trustworthy computing framework for many critical applications, such as cloud computing, in the information society. In the most general sense, this is achieved by dividing data…

Reconstructing Population Exposures to Environmental Chemicals from Biomarkers: Challenges and Opportunities

EPA Science Inventory

A conceptual/computational framework for exposure reconstruction from biomarker data combined with auxiliary exposure-related data is presented, evaluated with example applications, and examined in the context of future needs and opportunities. This framework employs Physiologica...

A Formal Valuation Framework for Emotions and Their Control.

PubMed

Huys, Quentin J M; Renz, Daniel

2017-09-15

Computational psychiatry aims to apply mathematical and computational techniques to help improve psychiatric care. To achieve this, the phenomena under scrutiny should be within the scope of formal methods. As emotions play an important role across many psychiatric disorders, such computational methods must encompass emotions. Here, we consider formal valuation accounts of emotions. We focus on the fact that the flexibility of emotional responses and the nature of appraisals suggest the need for a model-based valuation framework for emotions. However, resource limitations make plain model-based valuation impossible and require metareasoning strategies to apportion cognitive resources adaptively. We argue that emotions may implement such metareasoning approximations by restricting the range of behaviors and states considered. We consider the processes that guide the deployment of the approximations, discerning between innate, model-free, heuristic, and model-based controllers. A formal valuation and metareasoning framework may thus provide a principled approach to examining emotions. Copyright © 2017 Society of Biological Psychiatry. Published by Elsevier Inc. All rights reserved.

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.

Image processing for navigation on a mobile embedded platform

NASA Astrophysics Data System (ADS)

Preuss, Thomas; Gentsch, Lars; Rambow, Mark

2006-02-01

Mobile computing devices such as PDAs or cellular phones may act as "Personal Multimedia Exchanges", but they are limited in their processing power as well as in their connectivity. Sensors as well as cellular phones and PDAs are able to gather multimedia data, e. g. images, but leak computing power to process that data on their own. Therefore, it is necessary, that these devices connect to devices with more performance, which provide e.g. image processing services. In this paper, a generic approach is presented that connects different kinds of clients with each other and allows them to interact with more powerful devices. This architecture, called BOSPORUS, represents a communication framework for dynamic peer-to-peer computing. Each peer offers and uses services in this network and communicates loosely coupled and asynchronously with the others. These features make BOSPORUS a service oriented network architecture (SONA). A mobile embedded system, which uses external services for image processing based on the BOSPORUS Framework is shown as an application of the BOSPORUS framework.

Multi-Dielectric Brownian Dynamics and Design-Space-Exploration Studies of Permeation in Ion Channels.

PubMed

Siksik, May; Krishnamurthy, Vikram

2017-09-01

This paper proposes a multi-dielectric Brownian dynamics simulation framework for design-space-exploration (DSE) studies of ion-channel permeation. The goal of such DSE studies is to estimate the channel modeling-parameters that minimize the mean-squared error between the simulated and expected "permeation characteristics." To address this computational challenge, we use a methodology based on statistical inference that utilizes the knowledge of channel structure to prune the design space. We demonstrate the proposed framework and DSE methodology using a case study based on the KcsA ion channel, in which the design space is successfully reduced from a 6-D space to a 2-D space. Our results show that the channel dielectric map computed using the framework matches with that computed directly using molecular dynamics with an error of 7%. Finally, the scalability and resolution of the model used are explored, and it is shown that the memory requirements needed for DSE remain constant as the number of parameters (degree of heterogeneity) increases.

SCALING AN URBAN EMERGENCY EVACUATION FRAMEWORK: CHALLENGES AND PRACTICES

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

Karthik, Rajasekar; Lu, Wei

2014-01-01

Critical infrastructure disruption, caused by severe weather events, natural disasters, terrorist attacks, etc., has significant impacts on urban transportation systems. We built a computational framework to simulate urban transportation systems under critical infrastructure disruption in order to aid real-time emergency evacuation. This framework will use large scale datasets to provide a scalable tool for emergency planning and management. Our framework, World-Wide Emergency Evacuation (WWEE), integrates population distribution and urban infrastructure networks to model travel demand in emergency situations at global level. Also, a computational model of agent-based traffic simulation is used to provide an optimal evacuation plan for traffic operationmore » purpose [1]. In addition, our framework provides a web-based high resolution visualization tool for emergency evacuation modelers and practitioners. We have successfully tested our framework with scenarios in both United States (Alexandria, VA) and Europe (Berlin, Germany) [2]. However, there are still some major drawbacks for scaling this framework to handle big data workloads in real time. On our back-end, lack of proper infrastructure limits us in ability to process large amounts of data, run the simulation efficiently and quickly, and provide fast retrieval and serving of data. On the front-end, the visualization performance of microscopic evacuation results is still not efficient enough due to high volume data communication between server and client. We are addressing these drawbacks by using cloud computing and next-generation web technologies, namely Node.js, NoSQL, WebGL, Open Layers 3 and HTML5 technologies. We will describe briefly about each one and how we are using and leveraging these technologies to provide an efficient tool for emergency management organizations. Our early experimentation demonstrates that using above technologies is a promising approach to build a scalable and high performance urban emergency evacuation framework that can improve traffic mobility and safety under critical infrastructure disruption in today s socially connected world.« less

Integration of drug dosing data with physiological data streams using a cloud computing paradigm.

PubMed

Bressan, Nadja; James, Andrew; McGregor, Carolyn

2013-01-01

Many drugs are used during the provision of intensive care for the preterm newborn infant. Recommendations for drug dosing in newborns depend upon data from population based pharmacokinetic research. There is a need to be able to modify drug dosing in response to the preterm infant's response to the standard dosing recommendations. The real-time integration of physiological data with drug dosing data would facilitate individualised drug dosing for these immature infants. This paper proposes the use of a novel computational framework that employs real-time, temporal data analysis for this task. Deployment of the framework within the cloud computing paradigm will enable widespread distribution of individualized drug dosing for newborn infants.

Modeling Criminal Activity in Urban Landscapes

NASA Astrophysics Data System (ADS)

Brantingham, Patricia; Glässer, Uwe; Jackson, Piper; Vajihollahi, Mona

Computational and mathematical methods arguably have an enormous potential for serving practical needs in crime analysis and prevention by offering novel tools for crime investigations and experimental platforms for evidence-based policy making. We present a comprehensive formal framework and tool support for mathematical and computational modeling of criminal behavior to facilitate systematic experimental studies of a wide range of criminal activities in urban environments. The focus is on spatial and temporal aspects of different forms of crime, including opportunistic and serial violent crimes. However, the proposed framework provides a basis to push beyond conventional empirical research and engage the use of computational thinking and social simulations in the analysis of terrorism and counter-terrorism.

Complex optimization for big computational and experimental neutron datasets

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

Bao, Feng; Oak Ridge National Lab.; Archibald, Richard

Here, we present a framework to use high performance computing to determine accurate solutions to the inverse optimization problem of big experimental data against computational models. We demonstrate how image processing, mathematical regularization, and hierarchical modeling can be used to solve complex optimization problems on big data. We also demonstrate how both model and data information can be used to further increase solution accuracy of optimization by providing confidence regions for the processing and regularization algorithms. Finally, we use the framework in conjunction with the software package SIMPHONIES to analyze results from neutron scattering experiments on silicon single crystals, andmore » refine first principles calculations to better describe the experimental data.« less

Why is a computational framework for motivational and metacognitive control needed?

NASA Astrophysics Data System (ADS)

Sun, Ron

2018-01-01

This paper discusses, in the context of computational modelling and simulation of cognition, the relevance of deeper structures in the control of behaviour. Such deeper structures include motivational control of behaviour, which provides underlying causes for actions, and also metacognitive control, which provides higher-order processes for monitoring and regulation. It is argued that such deeper structures are important and thus cannot be ignored in computational cognitive architectures. A general framework based on the Clarion cognitive architecture is outlined that emphasises the interaction amongst action selection, motivation, and metacognition. The upshot is that it is necessary to incorporate all essential processes; short of that, the understanding of cognition can only be incomplete.

Complex optimization for big computational and experimental neutron datasets

DOE PAGES

Bao, Feng; Oak Ridge National Lab.; Archibald, Richard; ...

2016-11-07

Here, we present a framework to use high performance computing to determine accurate solutions to the inverse optimization problem of big experimental data against computational models. We demonstrate how image processing, mathematical regularization, and hierarchical modeling can be used to solve complex optimization problems on big data. We also demonstrate how both model and data information can be used to further increase solution accuracy of optimization by providing confidence regions for the processing and regularization algorithms. Finally, we use the framework in conjunction with the software package SIMPHONIES to analyze results from neutron scattering experiments on silicon single crystals, andmore » refine first principles calculations to better describe the experimental data.« less

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…

Building a Semantic Framework for eScience

NASA Astrophysics Data System (ADS)

Movva, S.; Ramachandran, R.; Maskey, M.; Li, X.

2009-12-01

The e-Science vision focuses on the use of advanced computing technologies to support scientists. Recent research efforts in this area have focused primarily on “enabling” use of infrastructure resources for both data and computational access especially in Geosciences. One of the existing gaps in the existing e-Science efforts has been the failure to incorporate stable semantic technologies within the design process itself. In this presentation, we describe our effort in designing a framework for e-Science built using Service Oriented Architecture. Our framework provides users capabilities to create science workflows and mine distributed data. Our e-Science framework is being designed around a mass market tool to promote reusability across many projects. Semantics is an integral part of this framework and our design goal is to leverage the latest stable semantic technologies. The use of these stable semantic technologies will provide the users of our framework the useful features such as: allow search engines to find their content with RDFa tags; create RDF triple data store for their content; create RDF end points to share with others; and semantically mash their content with other online content available as RDF end point.

Support for User Interfaces for Distributed Systems

NASA Technical Reports Server (NTRS)

Eychaner, Glenn; Niessner, Albert

2005-01-01

An extensible Java(TradeMark) software framework supports the construction and operation of graphical user interfaces (GUIs) for distributed computing systems typified by ground control systems that send commands to, and receive telemetric data from, spacecraft. Heretofore, such GUIs have been custom built for each new system at considerable expense. In contrast, the present framework affords generic capabilities that can be shared by different distributed systems. Dynamic class loading, reflection, and other run-time capabilities of the Java language and JavaBeans component architecture enable the creation of a GUI for each new distributed computing system with a minimum of custom effort. By use of this framework, GUI components in control panels and menus can send commands to a particular distributed system with a minimum of system-specific code. The framework receives, decodes, processes, and displays telemetry data; custom telemetry data handling can be added for a particular system. The framework supports saving and later restoration of users configurations of control panels and telemetry displays with a minimum of effort in writing system-specific code. GUIs constructed within this framework can be deployed in any operating system with a Java run-time environment, without recompilation or code changes.

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.

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

A proposed framework on hybrid feature selection techniques for handling high dimensional educational data

NASA Astrophysics Data System (ADS)

Shahiri, Amirah Mohamed; Husain, Wahidah; Rashid, Nur'Aini Abd

2017-10-01

Huge amounts of data in educational datasets may cause the problem in producing quality data. Recently, data mining approach are increasingly used by educational data mining researchers for analyzing the data patterns. However, many research studies have concentrated on selecting suitable learning algorithms instead of performing feature selection process. As a result, these data has problem with computational complexity and spend longer computational time for classification. The main objective of this research is to provide an overview of feature selection techniques that have been used to analyze the most significant features. Then, this research will propose a framework to improve the quality of students' dataset. The proposed framework uses filter and wrapper based technique to support prediction process in future study.

Efficient Server-Aided Secure Two-Party Function Evaluation with Applications to Genomic Computation

DTIC Science & Technology

2016-07-14

of the important properties of secure computation . In particular, it is known that full fairness cannot be achieved in the case of two-party com...Jakobsen, J. Nielsen, and C. Orlandi. A framework for outsourcing of secure computation . In ACM Workshop on Cloud Computing Security (CCSW), pages...Function Evaluation with Applications to Genomic Computation Abstract: Computation based on genomic data is becoming increasingly popular today, be it

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.

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.

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.

Discovering Tradeoffs, Vulnerabilities, and Dependencies within Water Resources Systems

NASA Astrophysics Data System (ADS)

Reed, P. M.

2015-12-01

There is a growing recognition and interest in using emerging computational tools for discovering the tradeoffs that emerge across complex combinations infrastructure options, adaptive operations, and sign posts. As a field concerned with "deep uncertainties", it is logically consistent to include a more direct acknowledgement that our choices for dealing with computationally demanding simulations, advanced search algorithms, and sensitivity analysis tools are themselves subject to failures that could adversely bias our understanding of how systems' vulnerabilities change with proposed actions. Balancing simplicity versus complexity in our computational frameworks is nontrivial given that we are often exploring high impact irreversible decisions. It is not always clear that accepted models even encompass important failure modes. Moreover as they become more complex and computationally demanding the benefits and consequences of simplifications are often untested. This presentation discusses our efforts to address these challenges through our "many-objective robust decision making" (MORDM) framework for the design and management water resources systems. The MORDM framework has four core components: (1) elicited problem conception and formulation, (2) parallel many-objective search, (3) interactive visual analytics, and (4) negotiated selection of robust alternatives. Problem conception and formulation is the process of abstracting a practical design problem into a mathematical representation. We build on the emerging work in visual analytics to exploit interactive visualization of both the design space and the objective space in multiple heterogeneous linked views that permit exploration and discovery. Many-objective search produces tradeoff solutions from potentially competing problem formulations that can each consider up to ten conflicting objectives based on current computational search capabilities. Negotiated design selection uses interactive visualization, reformulation, and optimization to discover desirable designs for implementation. Multi-city urban water supply portfolio planning will be used to illustrate the MORDM framework.

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.

Decision Making and Reward in Frontal Cortex

PubMed Central

Kennerley, Steven W.; Walton, Mark E.

2011-01-01

Patients with damage to the prefrontal cortex (PFC)—especially the ventral and medial parts of PFC—often show a marked inability to make choices that meet their needs and goals. These decision-making impairments often reflect both a deficit in learning concerning the consequences of a choice, as well as deficits in the ability to adapt future choices based on experienced value of the current choice. Thus, areas of PFC must support some value computations that are necessary for optimal choice. However, recent frameworks of decision making have highlighted that optimal and adaptive decision making does not simply rest on a single computation, but a number of different value computations may be necessary. Using this framework as a guide, we summarize evidence from both lesion studies and single-neuron physiology for the representation of different value computations across PFC areas. PMID:21534649

Cloud Computing for Teaching Practice: A New Design?

ERIC Educational Resources Information Center

Saadatdoost, Robab; Sim, Alex Tze Hiang; Jafarkarimi, Hosein; Hee, Jee Mei; Saadatdoost, Leila

2014-01-01

Recently researchers have shown an increased interest in cloud computing technology. It is becoming increasingly difficult to ignore cloud computing technology in education context. However rapid changes in information technology are having a serious effect on teaching framework designs. So far, however, there has been little discussion about…

A Framework for Understanding Physics Students' Computational Modeling Practices

ERIC Educational Resources Information Center

Lunk, Brandon Robert

2012-01-01

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…

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…

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...

Herding Elephants: Coping with the Technological Revolution in our Schools.

ERIC Educational Resources Information Center

Tunison, Scott

2002-01-01

Considers the extent to which schools need to address computer technology, and discusses which strategies can be employed to maximize the benefits and minimize the difficulties in integrating computer technology into the current educational framework. Advocates incorporation of computer technology into educational practices. (Contains 17…

Assessment of Examinations in Computer Science Doctoral Education

ERIC Educational Resources Information Center

Straub, Jeremy

2014-01-01

This article surveys the examination requirements for attaining degree candidate (candidacy) status in computer science doctoral programs at all of the computer science doctoral granting institutions in the United States. It presents a framework for program examination requirement categorization, and categorizes these programs by the type or types…

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…

Technology Acceptance Predictors among Student Teachers and Experienced Classroom Teachers

ERIC Educational Resources Information Center

Smarkola, Claudia

2007-01-01

This study investigated 160 student teachers' and 158 experienced teachers' self-reported computer usage and their future intentions to use computer applications for school assignments. The Technology Acceptance Model (TAM) was used as the framework to determine computer usage and intentions. Statistically significant results showed that after…

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…

An Integrated Framework for Improved Computer Science Education: Strategies, Implementations, and Results

ERIC Educational Resources Information Center

Soh, Leen-Kiat; Samal, Ashok; Nugent, Gwen

2007-01-01

This paper describes the Reinventing Computer Science Curriculum Project at the University of Nebraska-Lincoln. Motivated by rapid and significant changes in the information technology and computing areas, high diversity in student aptitudes, and high dropout rates, the project designed and implemented an integrated instructional/research…

Technology Teaching or Mediated Learning, Part I: Are Computers Skinnerian or Vygotskian?

ERIC Educational Resources Information Center

Coufal, Kathy L.

2002-01-01

This article highlights the theoretical framework that dominated speech-language pathology prior to the widespread introduction of microcomputers and poses questions regarding the application of computers in assessment and intervention for children with language-learning impairments. It discusses implications of computer use in the context of…

The Acceptance of Computer Technology by Teachers in Early Childhood Education

ERIC Educational Resources Information Center

Jeong, Hye In; Kim, Yeolib

2017-01-01

This study investigated kindergarten teachers' decision-making process regarding the acceptance of computer technology. We incorporated the Technology Acceptance Model framework, in addition to computer self-efficacy, subjective norm, and personal innovativeness in education technology as external variables. The data were obtained from 160…

Master of Puppets: An Animation-by-Demonstration Computer Puppetry Authoring Framework

NASA Astrophysics Data System (ADS)

Cui, Yaoyuan; Mousas, Christos

2018-03-01

This paper presents Master of Puppets (MOP), an animation-by-demonstration framework that allows users to control the motion of virtual characters (puppets) in real time. In the first step, the user is asked to perform the necessary actions that correspond to the character's motions. The user's actions are recorded, and a hidden Markov model is used to learn the temporal profile of the actions. During the runtime of the framework, the user controls the motions of the virtual character based on the specified activities. The advantage of the MOP framework is that it recognizes and follows the progress of the user's actions in real time. Based on the forward algorithm, the method predicts the evolution of the user's actions, which corresponds to the evolution of the character's motion. This method treats characters as puppets that can perform only one motion at a time. This means that combinations of motion segments (motion synthesis), as well as the interpolation of individual motion sequences, are not provided as functionalities. By implementing the framework and presenting several computer puppetry scenarios, its efficiency and flexibility in animating virtual characters is demonstrated.

The Integrated Plasma Simulator: A Flexible Python Framework for Coupled Multiphysics Simulation

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

Foley, Samantha S; Elwasif, Wael R; Bernholdt, David E

2011-11-01

High-fidelity coupled multiphysics simulations are an increasingly important aspect of computational science. In many domains, however, there has been very limited experience with simulations of this sort, therefore research in coupled multiphysics often requires computational frameworks with significant flexibility to respond to the changing directions of the physics and mathematics. This paper presents the Integrated Plasma Simulator (IPS), a framework designed for loosely coupled simulations of fusion plasmas. The IPS provides users with a simple component architecture into which a wide range of existing plasma physics codes can be inserted as components. Simulations can take advantage of multiple levels ofmore » parallelism supported in the IPS, and can be controlled by a high-level ``driver'' component, or by other coordination mechanisms, such as an asynchronous event service. We describe the requirements and design of the framework, and how they were implemented in the Python language. We also illustrate the flexibility of the framework by providing examples of different types of simulations that utilize various features of the IPS.« less

A computational framework for prime implicants identification in noncoherent dynamic systems.

PubMed

Di Maio, Francesco; Baronchelli, Samuele; Zio, Enrico

2015-01-01

Dynamic reliability methods aim at complementing the capability of traditional static approaches (e.g., event trees [ETs] and fault trees [FTs]) by accounting for the system dynamic behavior and its interactions with the system state transition process. For this, the system dynamics is here described by a time-dependent model that includes the dependencies with the stochastic transition events. In this article, we present a novel computational framework for dynamic reliability analysis whose objectives are i) accounting for discrete stochastic transition events and ii) identifying the prime implicants (PIs) of the dynamic system. The framework entails adopting a multiple-valued logic (MVL) to consider stochastic transitions at discretized times. Then, PIs are originally identified by a differential evolution (DE) algorithm that looks for the optimal MVL solution of a covering problem formulated for MVL accident scenarios. For testing the feasibility of the framework, a dynamic noncoherent system composed of five components that can fail at discretized times has been analyzed, showing the applicability of the framework to practical cases. © 2014 Society for Risk Analysis.

A programming environment for distributed complex computing. An overview of the Framework for Interdisciplinary Design Optimization (FIDO) project. NASA Langley TOPS exhibit H120b

NASA Technical Reports Server (NTRS)

Townsend, James C.; Weston, Robert P.; Eidson, Thomas M.

1993-01-01

The Framework for Interdisciplinary Design Optimization (FIDO) is a general programming environment for automating the distribution of complex computing tasks over a networked system of heterogeneous computers. For example, instead of manually passing a complex design problem between its diverse specialty disciplines, the FIDO system provides for automatic interactions between the discipline tasks and facilitates their communications. The FIDO system networks all the computers involved into a distributed heterogeneous computing system, so they have access to centralized data and can work on their parts of the total computation simultaneously in parallel whenever possible. Thus, each computational task can be done by the most appropriate computer. Results can be viewed as they are produced and variables changed manually for steering the process. The software is modular in order to ease migration to new problems: different codes can be substituted for each of the current code modules with little or no effect on the others. The potential for commercial use of FIDO rests in the capability it provides for automatically coordinating diverse computations on a networked system of workstations and computers. For example, FIDO could provide the coordination required for the design of vehicles or electronics or for modeling complex systems.

Has computational creativity successfully made it "Beyond the Fence" in musical theatre?

NASA Astrophysics Data System (ADS)

Jordanous, Anna

2017-10-01

A significant test for software is to task it with replicating human performance, as done recently with creative software and the commercial project Beyond the Fence (undertaken for a television documentary Computer Says Show). The remit of this project was to use computer software as much as possible to produce "the world's first computer-generated musical". Several creative systems were used to generate this musical, which was performed in London's West End in 2016. This paper considers the challenge of evaluating this project. Current computational creativity evaluation methods are ill-suited to evaluating projects that involve creative input from multiple systems and people. Following recent inspiration within computational creativity research from interaction design, here the DECIDE evaluation framework is applied to evaluate the Beyond the Fence project. Evaluation finds that the project was reasonably successful at achieving the task of using computational generation to produce a credible musical. Lessons have been learned for future computational creativity projects though, particularly for affording creative software more agency and enabling software to interact with other creative partners. Upon reflection, the DECIDE framework emerges as a useful evaluation "checklist" (if not a tangible operational methodology) for evaluating multiple creative systems participating in a creative task.

Cyberinfrastructure and Scientific Collaboration: Application of a Virtual Team Performance Framework with Potential Relevance to Education. WCER Working Paper No. 2010-12

ERIC Educational Resources Information Center

Kraemer, Sara; Thorn, Christopher A.

2010-01-01

The purpose of this exploratory study was to identify and describe some of the dimensions of scientific collaborations using high throughput computing (HTC) through the lens of a virtual team performance framework. A secondary purpose was to assess the viability of using a virtual team performance framework to study scientific collaborations using…

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

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.

The neural and computational bases of semantic cognition.

PubMed

Ralph, Matthew A Lambon; Jefferies, Elizabeth; Patterson, Karalyn; Rogers, Timothy T

2017-01-01

Semantic cognition refers to our ability to use, manipulate and generalize knowledge that is acquired over the lifespan to support innumerable verbal and non-verbal behaviours. This Review summarizes key findings and issues arising from a decade of research into the neurocognitive and neurocomputational underpinnings of this ability, leading to a new framework that we term controlled semantic cognition (CSC). CSC offers solutions to long-standing queries in philosophy and cognitive science, and yields a convergent framework for understanding the neural and computational bases of healthy semantic cognition and its dysfunction in brain disorders.

LAVA Simulations for the AIAA Sonic Boom Prediction Workshop

NASA Technical Reports Server (NTRS)

Housman, Jeffrey A.; Sozer, Emre; Moini-Yekta , Shayan; Kiris, Cetin C.

2014-01-01

Computational simulations using the Launch Ascent and Vehicle Aerodynamics (LAVA) framework are presented for the First AIAA Sonic Boom Prediction Workshop test cases. The framework is utilized with both structured overset and unstructured meshing approaches. The three workshop test cases include an axisymmetric body, a Delta Wing-Body model, and a complete low-boom supersonic transport concept. Solution sensitivity to mesh type and sizing, and several numerical convective flux discretization choices are presented and discussed. Favorable comparison between the computational simulations and experimental data of nearand mid-field pressure signatures were obtained.

Embedded Systems and TensorFlow Frameworks as Assistive Technology Solutions.

PubMed

Mulfari, Davide; Palla, Alessandro; Fanucci, Luca

2017-01-01

In the field of deep learning, this paper presents the design of a wearable computer vision system for visually impaired users. The Assistive Technology solution exploits a powerful single board computer and smart glasses with a camera in order to allow its user to explore the objects within his surrounding environment, while it employs Google TensorFlow machine learning framework in order to real time classify the acquired stills. Therefore the proposed aid can increase the awareness of the explored environment and it interacts with its user by means of audio messages.

A Real-time Strategy Agent Framework and Strategy Classifier for Computer Generated Forces

DTIC Science & Technology

2012-06-01

via our strategy definition schema, plays the game according to the defined strategy. 4 ) Generate a quality RTS data set. 5) Create an accurate and...General Approach . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4 1.6 Thesis Overview...Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 27 4 Agent Framework

Informatics approaches in the Biological Characterization of Adverse Outcome Pathways

EPA Science Inventory

Adverse Outcome Pathways (AOPs) are a conceptual framework to characterize toxicity pathways by a series of mechanistic steps from a molecular initiating event to population outcomes. This framework helps to direct risk assessment research, for example by aiding in computational ...

A framework for multi-stakeholder decision-making and conflict resolution

EPA Science Inventory

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) minimiz...

A Micro-Level Data-Calibrated Agent-Based Model: The Synergy between Microsimulation and Agent-Based Modeling.

PubMed

Singh, Karandeep; Ahn, Chang-Won; Paik, Euihyun; Bae, Jang Won; Lee, Chun-Hee

2018-01-01

Artificial life (ALife) examines systems related to natural life, its processes, and its evolution, using simulations with computer models, robotics, and biochemistry. In this article, we focus on the computer modeling, or "soft," aspects of ALife and prepare a framework for scientists and modelers to be able to support such experiments. The framework is designed and built to be a parallel as well as distributed agent-based modeling environment, and does not require end users to have expertise in parallel or distributed computing. Furthermore, we use this framework to implement a hybrid model using microsimulation and agent-based modeling techniques to generate an artificial society. We leverage this artificial society to simulate and analyze population dynamics using Korean population census data. The agents in this model derive their decisional behaviors from real data (microsimulation feature) and interact among themselves (agent-based modeling feature) to proceed in the simulation. The behaviors, interactions, and social scenarios of the agents are varied to perform an analysis of population dynamics. We also estimate the future cost of pension policies based on the future population structure of the artificial society. The proposed framework and model demonstrates how ALife techniques can be used by researchers in relation to social issues and policies.

Sideloading - Ingestion of Large Point Clouds Into the Apache Spark Big Data Engine

NASA Astrophysics Data System (ADS)

Boehm, J.; Liu, K.; Alis, C.

2016-06-01

In the geospatial domain we have now reached the point where data volumes we handle have clearly grown beyond the capacity of most desktop computers. This is particularly true in the area of point cloud processing. It is therefore naturally lucrative to explore established big data frameworks for big geospatial data. The very first hurdle is the import of geospatial data into big data frameworks, commonly referred to as data ingestion. Geospatial data is typically encoded in specialised binary file formats, which are not naturally supported by the existing big data frameworks. Instead such file formats are supported by software libraries that are restricted to single CPU execution. We present an approach that allows the use of existing point cloud file format libraries on the Apache Spark big data framework. We demonstrate the ingestion of large volumes of point cloud data into a compute cluster. The approach uses a map function to distribute the data ingestion across the nodes of a cluster. We test the capabilities of the proposed method to load billions of points into a commodity hardware compute cluster and we discuss the implications on scalability and performance. The performance is benchmarked against an existing native Apache Spark data import implementation.

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.

Fit of cobalt–chromium implant frameworks before and after ceramic veneering in comparison with CNC‐milled titanium frameworks

PubMed Central

Svanborg, Per; Eliasson, Alf

2015-01-01

Abstract Computer‐aided design/computer‐aided manufacturing fabrication of implant‐supported frameworks is a standard procedure, and the use of ceramic‐veneered cobalt–chromium alloys is increasing. However, no data are available concerning the precision of fit of these frameworks and the impact on the fit of the veneering procedure. The aim of this study was to evaluate the fit of computer numeric‐controlled‐milled cobalt–chromium and titanium implant frameworks for edentulous maxillas, provided with six implants. An additional aim was to evaluate the effect of ceramic veneering on the fit of the cobalt–chromium frameworks. Ten stone casts simulating an edentulous maxilla provided with six dental implants and abutments were produced. One computer numeric‐controlled‐milled cobalt–chromium framework and one titanium framework were fabricated for each stone cast. Each stone cast and corresponding titanium and cobalt–chromium framework was measured with a coordinate measuring machine in the three‐dimensional (X axis, Y axis, and Z axis) directions. Both milled titanium and cobalt–chromium frameworks presented a good fit in the vertical plane (Z axis), 5.3 µm for titanium frameworks and 4.6 µm for the cobalt–chromium frameworks. The titanium frameworks showed a statistically significant smaller mean degree of misfit in the horizontal plane, X (5.0 µm) and Y (2.8 µm) axes as compared with the cobalt–chromium frameworks presenting a mean deviation of 13.5 µm in X axis and 6.3 µm in Y axis (P < 0.001). After ceramic veneering of the cobalt–chromium frameworks, the horizontal distortion significantly decreased from 13.5 to 9.7 µm in X axis (P = 0.007) and from 6.3 to 4.4 µm in Y axis (P = 0.017). The fit of both titanium and cobalt–chromium frameworks was very good. There were small but significant differences in fit between the titanium and cobalt–chromium frameworks, but the difference is of no clinical significance. The ceramic veneering resulted in a minor but significant improvement of the fit for the cobalt–chromium frameworks. PMID:29744140

Semantics-based distributed I/O with the ParaMEDIC framework.

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

Balaji, P.; Feng, W.; Lin, H.

2008-01-01

Many large-scale applications simultaneously rely on multiple resources for efficient execution. For example, such applications may require both large compute and storage resources; however, very few supercomputing centers can provide large quantities of both. Thus, data generated at the compute site oftentimes has to be moved to a remote storage site for either storage or visualization and analysis. Clearly, this is not an efficient model, especially when the two sites are distributed over a wide-area network. Thus, we present a framework called 'ParaMEDIC: Parallel Metadata Environment for Distributed I/O and Computing' which uses application-specific semantic information to convert the generatedmore » data to orders-of-magnitude smaller metadata at the compute site, transfer the metadata to the storage site, and re-process the metadata at the storage site to regenerate the output. Specifically, ParaMEDIC trades a small amount of additional computation (in the form of data post-processing) for a potentially significant reduction in data that needs to be transferred in distributed environments.« less

Distributed parallel computing in stochastic modeling of groundwater systems.

PubMed

Dong, Yanhui; Li, Guomin; Xu, Haizhen

2013-03-01

Stochastic modeling is a rapidly evolving, popular approach to the study of the uncertainty and heterogeneity of groundwater systems. However, the use of Monte Carlo-type simulations to solve practical groundwater problems often encounters computational bottlenecks that hinder the acquisition of meaningful results. To improve the computational efficiency, a system that combines stochastic model generation with MODFLOW-related programs and distributed parallel processing is investigated. The distributed computing framework, called the Java Parallel Processing Framework, is integrated into the system to allow the batch processing of stochastic models in distributed and parallel systems. As an example, the system is applied to the stochastic delineation of well capture zones in the Pinggu Basin in Beijing. Through the use of 50 processing threads on a cluster with 10 multicore nodes, the execution times of 500 realizations are reduced to 3% compared with those of a serial execution. Through this application, the system demonstrates its potential in solving difficult computational problems in practical stochastic modeling. © 2012, The Author(s). Groundwater © 2012, National Ground Water Association.

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

pyNS: an open-source framework for 0D haemodynamic modelling.

PubMed

Manini, Simone; Antiga, Luca; Botti, Lorenzo; Remuzzi, Andrea

2015-06-01

A number of computational approaches have been proposed for the simulation of haemodynamics and vascular wall dynamics in complex vascular networks. Among them, 0D pulse wave propagation methods allow to efficiently model flow and pressure distributions and wall displacements throughout vascular networks at low computational costs. Although several techniques are documented in literature, the availability of open-source computational tools is still limited. We here present python Network Solver, a modular solver framework for 0D problems released under a BSD license as part of the archToolkit ( http://archtk.github.com ). As an application, we describe patient-specific models of the systemic circulation and detailed upper extremity for use in the prediction of maturation after surgical creation of vascular access for haemodialysis.

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.

An algorithmic framework for multiobjective optimization.

PubMed

Ganesan, T; Elamvazuthi, I; Shaari, Ku Zilati Ku; Vasant, P

2013-01-01

Multiobjective (MO) optimization is an emerging field which is increasingly being encountered in many fields globally. Various metaheuristic techniques such as differential evolution (DE), genetic algorithm (GA), gravitational search algorithm (GSA), and particle swarm optimization (PSO) have been used in conjunction with scalarization techniques such as weighted sum approach and the normal-boundary intersection (NBI) method to solve MO problems. Nevertheless, many challenges still arise especially when dealing with problems with multiple objectives (especially in cases more than two). In addition, problems with extensive computational overhead emerge when dealing with hybrid algorithms. This paper discusses these issues by proposing an alternative framework that utilizes algorithmic concepts related to the problem structure for generating efficient and effective algorithms. This paper proposes a framework to generate new high-performance algorithms with minimal computational overhead for MO optimization.

An Algorithmic Framework for Multiobjective Optimization

PubMed Central

Ganesan, T.; Elamvazuthi, I.; Shaari, Ku Zilati Ku; Vasant, P.

2013-01-01

Multiobjective (MO) optimization is an emerging field which is increasingly being encountered in many fields globally. Various metaheuristic techniques such as differential evolution (DE), genetic algorithm (GA), gravitational search algorithm (GSA), and particle swarm optimization (PSO) have been used in conjunction with scalarization techniques such as weighted sum approach and the normal-boundary intersection (NBI) method to solve MO problems. Nevertheless, many challenges still arise especially when dealing with problems with multiple objectives (especially in cases more than two). In addition, problems with extensive computational overhead emerge when dealing with hybrid algorithms. This paper discusses these issues by proposing an alternative framework that utilizes algorithmic concepts related to the problem structure for generating efficient and effective algorithms. This paper proposes a framework to generate new high-performance algorithms with minimal computational overhead for MO optimization. PMID:24470795

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.

A framework for optimizing micro-CT in dual-modality micro-CT/XFCT small-animal imaging system

NASA Astrophysics Data System (ADS)

Vedantham, Srinivasan; Shrestha, Suman; Karellas, Andrew; Cho, Sang Hyun

2017-09-01

Dual-modality Computed Tomography (CT)/X-ray Fluorescence Computed Tomography (XFCT) can be a valuable tool for imaging and quantifying the organ and tissue distribution of small concentrations of high atomic number materials in small-animal system. In this work, the framework for optimizing the micro-CT imaging system component of the dual-modality system is described, either when the micro-CT images are concurrently acquired with XFCT and using the x-ray spectral conditions for XFCT, or when the micro-CT images are acquired sequentially and independently of XFCT. This framework utilizes the cascaded systems analysis for task-specific determination of the detectability index using numerical observer models at a given radiation dose, where the radiation dose is determined using Monte Carlo simulations.

A unified framework for heat and mass transport at the atomic scale

NASA Astrophysics Data System (ADS)

Ponga, Mauricio; Sun, Dingyi

2018-04-01

We present a unified framework to simulate heat and mass transport in systems of particles. The proposed framework is based on kinematic mean field theory and uses a phenomenological master equation to compute effective transport rates between particles without the need to evaluate operators. We exploit this advantage and apply the model to simulate transport phenomena at the nanoscale. We demonstrate that, when calibrated to experimentally-measured transport coefficients, the model can accurately predict transient and steady state temperature and concentration profiles even in scenarios where the length of the device is comparable to the mean free path of the carriers. Through several example applications, we demonstrate the validity of our model for all classes of materials, including ones that, until now, would have been outside the domain of computational feasibility.

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

Holonomic quantum computation in the presence of decoherence.

PubMed

Fuentes-Guridi, I; Girelli, F; Livine, E

2005-01-21

We present a scheme to study non-Abelian adiabatic holonomies for open Markovian systems. As an application of our framework, we analyze the robustness of holonomic quantum computation against decoherence. We pinpoint the sources of error that must be corrected to achieve a geometric implementation of quantum computation completely resilient to Markovian decoherence.

A Semantic Based Policy Management Framework for Cloud Computing Environments

ERIC Educational Resources Information Center

Takabi, Hassan

2013-01-01

Cloud computing paradigm has gained tremendous momentum and generated intensive interest. Although security issues are delaying its fast adoption, cloud computing is an unstoppable force and we need to provide security mechanisms to ensure its secure adoption. In this dissertation, we mainly focus on issues related to policy management and access…

An Application of a Computer Instructional Management Package.

ERIC Educational Resources Information Center

Sullivan, David W.

Following the presentation of a conceptual framework for computer-based education (CBE), this paper examines the use of one aspect of CBE, computer-managed instruction (CMI), in a Major Appliance Serving Program. The paper begins with definitions and a graphic illustration of CBE and its components and uses, i.e., CMI, tutorial or…

An Exploratory Study of the Implementation of Computer Technology in an American Islamic Private School

ERIC Educational Resources Information Center

Saleem, Mohammed M.

2009-01-01

This exploratory study of the implementation of computer technology in an American Islamic private school leveraged the case study methodology and ethnographic methods informed by symbolic interactionism and the framework of the Muslim Diaspora. The study focused on describing the implementation of computer technology and identifying the…

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…

Business/Marketing Education. Business Analysis/Business Computer Applications.

ERIC Educational Resources Information Center

New York State Education Dept., Albany. Div. of Occupational Education Programs.

This document contains 12 modules: 4 on business analysis and 8 on business computer applications. The business analysis modules are as follows: (1) the framework of business; (2) universal activities of business; (3) selected business subsystems; and (4) your place in business. Computer applications modules are on the following topics: (1)…

Relevancy in Problem Solving: A Computational Framework

ERIC Educational Resources Information Center

Kwisthout, Johan

2012-01-01

When computer scientists discuss the computational complexity of, for example, finding the shortest path from building A to building B in some town or city, their starting point typically is a formal description of the problem at hand, e.g., a graph with weights on every edge where buildings correspond to vertices, routes between buildings to…

None but Ourselves Can Free Our Minds: Critical Computational Literacy as a Pedagogy of Resistance

ERIC Educational Resources Information Center

Lee, Clifford H.; Soep, Elisabeth

2016-01-01

Critical computational literacy (CCL) is a new pedagogical and conceptual framework that combines the strengths of critical literacy and computational thinking. Through CCL, young people conceptualize, create, and disseminate digital projects that break silences, expose important truths, and challenge unjust systems, all the while building skills…

Computer Game Theories for Designing Motivating Educational Software: A Survey Study

ERIC Educational Resources Information Center

Ang, Chee Siang; Rao, G. S. V. Radha Krishna

2008-01-01

The purpose of this study is to evaluate computer game theories for educational software. We propose a framework for designing engaging educational games based on contemporary game studies which includes ludology and narratology. Ludology focuses on the study of computer games as play and game activities, while narratology revolves around the…

Women and Computer Based Technologies: A Feminist Perspective.

ERIC Educational Resources Information Center

Morritt, Hope

The use of computer based technologies by professional women in education is examined through a feminist standpoint theory in this paper. The theory is grounded in eight claims which form the basis of the conceptual framework for the study. The experiences of nine women participants with computer based technologies were categorized using three…

Algorithmic Mechanism Design of Evolutionary Computation.

PubMed

Pei, Yan

2015-01-01

We consider algorithmic design, enhancement, and improvement of evolutionary computation as a mechanism design problem. All individuals or several groups of individuals can be considered as self-interested agents. The individuals in evolutionary computation can manipulate parameter settings and operations by satisfying their own preferences, which are defined by an evolutionary computation algorithm designer, rather than by following a fixed algorithm rule. Evolutionary computation algorithm designers or self-adaptive methods should construct proper rules and mechanisms for all agents (individuals) to conduct their evolution behaviour correctly in order to definitely achieve the desired and preset objective(s). As a case study, we propose a formal framework on parameter setting, strategy selection, and algorithmic design of evolutionary computation by considering the Nash strategy equilibrium of a mechanism design in the search process. The evaluation results present the efficiency of the framework. This primary principle can be implemented in any evolutionary computation algorithm that needs to consider strategy selection issues in its optimization process. The final objective of our work is to solve evolutionary computation design as an algorithmic mechanism design problem and establish its fundamental aspect by taking this perspective. This paper is the first step towards achieving this objective by implementing a strategy equilibrium solution (such as Nash equilibrium) in evolutionary computation algorithm.

Algorithmic Mechanism Design of Evolutionary Computation

PubMed Central

2015-01-01

We consider algorithmic design, enhancement, and improvement of evolutionary computation as a mechanism design problem. All individuals or several groups of individuals can be considered as self-interested agents. The individuals in evolutionary computation can manipulate parameter settings and operations by satisfying their own preferences, which are defined by an evolutionary computation algorithm designer, rather than by following a fixed algorithm rule. Evolutionary computation algorithm designers or self-adaptive methods should construct proper rules and mechanisms for all agents (individuals) to conduct their evolution behaviour correctly in order to definitely achieve the desired and preset objective(s). As a case study, we propose a formal framework on parameter setting, strategy selection, and algorithmic design of evolutionary computation by considering the Nash strategy equilibrium of a mechanism design in the search process. The evaluation results present the efficiency of the framework. This primary principle can be implemented in any evolutionary computation algorithm that needs to consider strategy selection issues in its optimization process. The final objective of our work is to solve evolutionary computation design as an algorithmic mechanism design problem and establish its fundamental aspect by taking this perspective. This paper is the first step towards achieving this objective by implementing a strategy equilibrium solution (such as Nash equilibrium) in evolutionary computation algorithm. PMID:26257777

Verifiable fault tolerance in measurement-based quantum computation

NASA Astrophysics Data System (ADS)

Fujii, Keisuke; Hayashi, Masahito

2017-09-01

Quantum systems, in general, cannot be simulated efficiently by a classical computer, and hence are useful for solving certain mathematical problems and simulating quantum many-body systems. This also implies, unfortunately, that verification of the output of the quantum systems is not so trivial, since predicting the output is exponentially hard. As another problem, the quantum system is very delicate for noise and thus needs an error correction. Here, we propose a framework for verification of the output of fault-tolerant quantum computation in a measurement-based model. In contrast to existing analyses on fault tolerance, we do not assume any noise model on the resource state, but an arbitrary resource state is tested by using only single-qubit measurements to verify whether or not the output of measurement-based quantum computation on it is correct. Verifiability is equipped by a constant time repetition of the original measurement-based quantum computation in appropriate measurement bases. Since full characterization of quantum noise is exponentially hard for large-scale quantum computing systems, our framework provides an efficient way to practically verify the experimental quantum error correction.

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.

Real-time solution of linear computational problems using databases of parametric reduced-order models with arbitrary underlying meshes

NASA Astrophysics Data System (ADS)

Amsallem, David; Tezaur, Radek; Farhat, Charbel

2016-12-01

A comprehensive approach for real-time computations using a database of parametric, linear, projection-based reduced-order models (ROMs) based on arbitrary underlying meshes is proposed. In the offline phase of this approach, the parameter space is sampled and linear ROMs defined by linear reduced operators are pre-computed at the sampled parameter points and stored. Then, these operators and associated ROMs are transformed into counterparts that satisfy a certain notion of consistency. In the online phase of this approach, a linear ROM is constructed in real-time at a queried but unsampled parameter point by interpolating the pre-computed linear reduced operators on matrix manifolds and therefore computing an interpolated linear ROM. The proposed overall model reduction framework is illustrated with two applications: a parametric inverse acoustic scattering problem associated with a mockup submarine, and a parametric flutter prediction problem associated with a wing-tank system. The second application is implemented on a mobile device, illustrating the capability of the proposed computational framework to operate in real-time.

A Strategic Approach to Network Defense: Framing the Cloud

DTIC Science & Technology

2011-03-10

accepted network defensive principles, to reduce risks associated with emerging virtualization capabilities and scalability of cloud computing . This expanded...defensive framework can assist enterprise networking and cloud computing architects to better design more secure systems.

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

Optimal directed searches for continuous gravitational waves

NASA Astrophysics Data System (ADS)

Ming, Jing; Krishnan, Badri; Papa, Maria Alessandra; Aulbert, Carsten; Fehrmann, Henning

2016-03-01

Wide parameter space searches for long-lived continuous gravitational wave signals are computationally limited. It is therefore critically important that the available computational resources are used rationally. In this paper we consider directed searches, i.e., targets for which the sky position is known accurately but the frequency and spin-down parameters are completely unknown. Given a list of such potential astrophysical targets, we therefore need to prioritize. On which target(s) should we spend scarce computing resources? What parameter space region in frequency and spin-down should we search through? Finally, what is the optimal search setup that we should use? In this paper we present a general framework that allows us to solve all three of these problems. This framework is based on maximizing the probability of making a detection subject to a constraint on the maximum available computational cost. We illustrate the method for a simplified problem.

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.

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.

Fit of screw-retained fixed implant frameworks fabricated by different methods: a systematic review.

PubMed

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

2011-01-01

The aim of this study was to review the published literature investigating the accuracy of fit of fixed implant frameworks fabricated using different materials and methods. A comprehensive electronic search was performed through PubMed (MEDLINE) using Boolean operators to combine key words. The search was limited to articles written in English and published through May 2010. In addition, a manual search through articles and reference lists retrieved from the electronic search and peer-reviewed journals was also conducted. A total of 248 articles were retrieved, and 26 met the specified inclusion criteria for the review. The selected articles assessed the fit of fixed implant frameworks fabricated by different techniques. The investigated fabrication approaches were one-piece casting, sectioning and reconnection, spark erosion with an electric discharge machine, computer-aided design/computer-assisted manufacturing (CAD/CAM), and framework bonding to prefabricated abutment cylinders. Cast noble metal frameworks have a predictable fit, and additional fit refinement treatment is not indicated in well-controlled conditions. Base metal castings do not provide a satisfactory level of fit unless additional refinement treatment is performed, such as sectioning and laser welding or spark erosion. Spark erosion, framework bonding to prefabricated abutment cylinders, and CAD/CAM have the potential to provide implant frameworks with an excellent fit; CAD/CAM is the most consistent and least technique-sensitive of these methods.

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 ...

The VIRTUAL EMBRYO. A Computational Framework for Developmental Toxicity

EPA Science Inventory

EPA’s ‘Virtual Embryo Project’ (v-Embryo™) is focused on the predictive toxicology of children’s health and developmental defects following prenatal exposure to environmental chemicals. The research is motivated by scientific principles in systems biology as a framework for the g...

Defining a Computational Framework for the Assessment of Taxonomic Applicability

EPA Science Inventory

The Adverse Outcome Pathway (AOP) framework describes the effects of environmental stressors across multiple scales of biological organization and function. This includes an evaluation of the potential for each key event to occur across a broad range of species in order to determ...

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.

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.

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

Distributed MRI reconstruction using Gadgetron-based cloud computing.

PubMed

Xue, Hui; Inati, Souheil; Sørensen, Thomas Sangild; Kellman, Peter; Hansen, Michael S

2015-03-01

To expand the open source Gadgetron reconstruction framework to support distributed computing and to demonstrate that a multinode version of the Gadgetron can be used to provide nonlinear reconstruction with clinically acceptable latency. The Gadgetron framework was extended with new software components that enable an arbitrary number of Gadgetron instances to collaborate on a reconstruction task. This cloud-enabled version of the Gadgetron was deployed on three different distributed computing platforms ranging from a heterogeneous collection of commodity computers to the commercial Amazon Elastic Compute Cloud. The Gadgetron cloud was used to provide nonlinear, compressed sensing reconstruction on a clinical scanner with low reconstruction latency (eg, cardiac and neuroimaging applications). The proposed setup was able to handle acquisition and 11 -SPIRiT reconstruction of nine high temporal resolution real-time, cardiac short axis cine acquisitions, covering the ventricles for functional evaluation, in under 1 min. A three-dimensional high-resolution brain acquisition with 1 mm(3) isotropic pixel size was acquired and reconstructed with nonlinear reconstruction in less than 5 min. A distributed computing enabled Gadgetron provides a scalable way to improve reconstruction performance using commodity cluster computing. Nonlinear, compressed sensing reconstruction can be deployed clinically with low image reconstruction latency. © 2014 Wiley Periodicals, Inc.

Computer-assisted framework for machine-learning-based delineation of GTV regions on datasets of planning CT and PET/CT images.

PubMed

Ikushima, Koujiro; Arimura, Hidetaka; Jin, Ze; Yabu-Uchi, Hidetake; Kuwazuru, Jumpei; Shioyama, Yoshiyuki; Sasaki, Tomonari; Honda, Hiroshi; Sasaki, Masayuki

2017-01-01

We have proposed a computer-assisted framework for machine-learning-based delineation of gross tumor volumes (GTVs) following an optimum contour selection (OCS) method. The key idea of the proposed framework was to feed image features around GTV contours (determined based on the knowledge of radiation oncologists) into a machine-learning classifier during the training step, after which the classifier produces the 'degree of GTV' for each voxel in the testing step. Initial GTV regions were extracted using a support vector machine (SVM) that learned the image features inside and outside each tumor region (determined by radiation oncologists). The leave-one-out-by-patient test was employed for training and testing the steps of the proposed framework. The final GTV regions were determined using the OCS method that can be used to select a global optimum object contour based on multiple active delineations with a LSM around the GTV. The efficacy of the proposed framework was evaluated in 14 lung cancer cases [solid: 6, ground-glass opacity (GGO): 4, mixed GGO: 4] using the 3D Dice similarity coefficient (DSC), which denotes the degree of region similarity between the GTVs contoured by radiation oncologists and those determined using the proposed framework. The proposed framework achieved an average DSC of 0.777 for 14 cases, whereas the OCS-based framework produced an average DSC of 0.507. The average DSCs for GGO and mixed GGO were 0.763 and 0.701, respectively, obtained by the proposed framework. The proposed framework can be employed as a tool to assist radiation oncologists in delineating various GTV regions. © The Author 2016. Published by Oxford University Press on behalf of The Japan Radiation Research Society and Japanese Society for Radiation Oncology.

Predicting visual semantic descriptive terms from radiological image data: preliminary results with liver lesions in CT.

PubMed

Depeursinge, Adrien; Kurtz, Camille; Beaulieu, Christopher; Napel, Sandy; Rubin, Daniel

2014-08-01

We describe a framework to model visual semantics of liver lesions in CT images in order to predict the visual semantic terms (VST) reported by radiologists in describing these lesions. Computational models of VST are learned from image data using linear combinations of high-order steerable Riesz wavelets and support vector machines (SVM). In a first step, these models are used to predict the presence of each semantic term that describes liver lesions. In a second step, the distances between all VST models are calculated to establish a nonhierarchical computationally-derived ontology of VST containing inter-term synonymy and complementarity. A preliminary evaluation of the proposed framework was carried out using 74 liver lesions annotated with a set of 18 VSTs from the RadLex ontology. A leave-one-patient-out cross-validation resulted in an average area under the ROC curve of 0.853 for predicting the presence of each VST. The proposed framework is expected to foster human-computer synergies for the interpretation of radiological images while using rotation-covariant computational models of VSTs to 1) quantify their local likelihood and 2) explicitly link them with pixel-based image content in the context of a given imaging domain.

Mobile-Cloud Assisted Video Summarization Framework for Efficient Management of Remote Sensing Data Generated by Wireless Capsule Sensors

PubMed Central

Mehmood, Irfan; Sajjad, Muhammad; Baik, Sung Wook

2014-01-01

Wireless capsule endoscopy (WCE) has great advantages over traditional endoscopy because it is portable and easy to use, especially in remote monitoring health-services. However, during the WCE process, the large amount of captured video data demands a significant deal of computation to analyze and retrieve informative video frames. In order to facilitate efficient WCE data collection and browsing task, we present a resource- and bandwidth-aware WCE video summarization framework that extracts the representative keyframes of the WCE video contents by removing redundant and non-informative frames. For redundancy elimination, we use Jeffrey-divergence between color histograms and inter-frame Boolean series-based correlation of color channels. To remove non-informative frames, multi-fractal texture features are extracted to assist the classification using an ensemble-based classifier. Owing to the limited WCE resources, it is impossible for the WCE system to perform computationally intensive video summarization tasks. To resolve computational challenges, mobile-cloud architecture is incorporated, which provides resizable computing capacities by adaptively offloading video summarization tasks between the client and the cloud server. The qualitative and quantitative results are encouraging and show that the proposed framework saves information transmission cost and bandwidth, as well as the valuable time of data analysts in browsing remote sensing data. PMID:25225874

Mobile-cloud assisted video summarization framework for efficient management of remote sensing data generated by wireless capsule sensors.

PubMed

Mehmood, Irfan; Sajjad, Muhammad; Baik, Sung Wook

2014-09-15

Wireless capsule endoscopy (WCE) has great advantages over traditional endoscopy because it is portable and easy to use, especially in remote monitoring health-services. However, during the WCE process, the large amount of captured video data demands a significant deal of computation to analyze and retrieve informative video frames. In order to facilitate efficient WCE data collection and browsing task, we present a resource- and bandwidth-aware WCE video summarization framework that extracts the representative keyframes of the WCE video contents by removing redundant and non-informative frames. For redundancy elimination, we use Jeffrey-divergence between color histograms and inter-frame Boolean series-based correlation of color channels. To remove non-informative frames, multi-fractal texture features are extracted to assist the classification using an ensemble-based classifier. Owing to the limited WCE resources, it is impossible for the WCE system to perform computationally intensive video summarization tasks. To resolve computational challenges, mobile-cloud architecture is incorporated, which provides resizable computing capacities by adaptively offloading video summarization tasks between the client and the cloud server. The qualitative and quantitative results are encouraging and show that the proposed framework saves information transmission cost and bandwidth, as well as the valuable time of data analysts in browsing remote sensing data.

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

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

Quantifying uncertainty and computational complexity for pore-scale simulations

NASA Astrophysics Data System (ADS)

Chen, C.; Yuan, Z.; Wang, P.; Yang, X.; Zhenyan, L.

2016-12-01

Pore-scale simulation is an essential tool to understand the complex physical process in many environmental problems, from multi-phase flow in the subsurface to fuel cells. However, in practice, factors such as sample heterogeneity, data sparsity and in general, our insufficient knowledge of the underlying process, render many simulation parameters and hence the prediction results uncertain. Meanwhile, most pore-scale simulations (in particular, direct numerical simulation) incur high computational cost due to finely-resolved spatio-temporal scales, which further limits our data/samples collection. To address those challenges, we propose a novel framework based on the general polynomial chaos (gPC) and build a surrogate model representing the essential features of the underlying system. To be specific, we apply the novel framework to analyze the uncertainties of the system behavior based on a series of pore-scale numerical experiments, such as flow and reactive transport in 2D heterogeneous porous media and 3D packed beds. Comparing with recent pore-scale uncertainty quantification studies using Monte Carlo techniques, our new framework requires fewer number of realizations and hence considerably reduce the overall computational cost, while maintaining the desired accuracy.

Fast image interpolation via random forests.

PubMed

Huang, Jun-Jie; Siu, Wan-Chi; Liu, Tian-Rui

2015-10-01

This paper proposes a two-stage framework for fast image interpolation via random forests (FIRF). The proposed FIRF method gives high accuracy, as well as requires low computation. The underlying idea of this proposed work is to apply random forests to classify the natural image patch space into numerous subspaces and learn a linear regression model for each subspace to map the low-resolution image patch to high-resolution image patch. The FIRF framework consists of two stages. Stage 1 of the framework removes most of the ringing and aliasing artifacts in the initial bicubic interpolated image, while Stage 2 further refines the Stage 1 interpolated image. By varying the number of decision trees in the random forests and the number of stages applied, the proposed FIRF method can realize computationally scalable image interpolation. Extensive experimental results show that the proposed FIRF(3, 2) method achieves more than 0.3 dB improvement in peak signal-to-noise ratio over the state-of-the-art nonlocal autoregressive modeling (NARM) method. Moreover, the proposed FIRF(1, 1) obtains similar or better results as NARM while only takes its 0.3% computational time.

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.

Action Understanding as Inverse Planning

ERIC Educational Resources Information Center

Baker, Chris L.; Saxe, Rebecca; Tenenbaum, Joshua B.

2009-01-01

Humans are adept at inferring the mental states underlying other agents' actions, such as goals, beliefs, desires, emotions and other thoughts. We propose a computational framework based on Bayesian inverse planning for modeling human action understanding. The framework represents an intuitive theory of intentional agents' behavior based on the…

Toward improved calibration of watershed models: multisite many objective measures of information

USDA-ARS?s Scientific Manuscript database

This paper presents a computational framework for incorporation of disparate information from observed hydrologic responses at multiple locations into the calibration of watershed models. The framework consists of four components: (i) an a-priori characterization of system behavior; (ii) a formal an...

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...

HexSim - A general purpose framework for spatially-explicit, individual-based modeling

EPA Science Inventory

HexSim is a framework for constructing spatially-explicit, individual-based computer models designed for simulating terrestrial wildlife population dynamics and interactions. HexSim is useful for a broad set of modeling applications. This talk will focus on a subset of those ap...

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…

Presence and Learning in a Community of Inquiry

ERIC Educational Resources Information Center

Maddrell, Jennifer A.; Morrison, Gary R.; Watson, Ginger S.

2017-01-01

The community of inquiry (CoI) framework suggests social presence, teaching presence, and cognitive presence are essential elements to foster successful educational experiences in computer-mediated distance learning environments. Although thousands of CoI-based articles have been published, those critical of the framework and related research…

Transnational Discourses of Knowledge and Learning in Professional Work: Examples from Computer Engineering

ERIC Educational Resources Information Center

Nerland, Monika

2010-01-01

Taking a Foucauldian framework as its point of departure, this paper discusses how transnational discourses of knowledge and learning operate in the profession of computer engineering and form a certain logic through which modes of being an engineer are regulated. Both the knowledge domain of computer engineering and its related labour market is…

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…

A Quantitative Risk Analysis Framework for Evaluating and Monitoring Operational Reliability of Cloud Computing

ERIC Educational Resources Information Center

Islam, Muhammad Faysal

2013-01-01

Cloud computing offers the advantage of on-demand, reliable and cost efficient computing solutions without the capital investment and management resources to build and maintain in-house data centers and network infrastructures. Scalability of cloud solutions enable consumers to upgrade or downsize their services as needed. In a cloud environment,…

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…

Teaching and Learning Methodologies Supported by ICT Applied in Computer Science

ERIC Educational Resources Information Center

Capacho, Jose

2016-01-01

The main objective of this paper is to show a set of new methodologies applied in the teaching of Computer Science using ICT. The methodologies are framed in the conceptual basis of the following sciences: Psychology, Education and Computer Science. The theoretical framework of the research is supported by Behavioral Theory, Gestalt Theory.…

Some Uses of a Computer in Teaching, Training, and Testing: Student/Learner Self-Assessment Responding.

ERIC Educational Resources Information Center

Hunt, Darwin P.

The use of systems theory as a conceptual framework is proposed as useful when considering computers as a machine component in teaching. Skinner's proposal that the label "computer" is inaccurate and counterproductive when used to refer to a machine being used for teaching is discussed. It is suggested that the alternative label…

Computer Science Education as a Cultural Encounter: A Socio-Cultural Framework for Articulating Teaching Difficulties

ERIC Educational Resources Information Center

Kolikant, Yifat Ben-David

2011-01-01

This study demonstrates the power of the cultural encounter metaphor in explaining learning and teaching difficulties, using as an example computer science education (CSE). CSE is envisioned as an encounter between veterans of two computer-oriented cultures, that of the teachers and that of the students. Forty questionnaires administered to CS…

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

dV/dt - Accelerating the Rate of Progress towards Extreme Scale Collaborative Science

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

Livny, Miron

This report introduces publications that report the results of a project that aimed to design a computational framework that enables computational experimentation at scale while supporting the model of “submit locally, compute globally”. The project focuses on estimating application resource needs, finding the appropriate computing resources, acquiring those resources,deploying the applications and data on the resources, managing applications and resources during run.

Spatiotemporal Dynamics and Reliable Computations in Recurrent Spiking Neural Networks

NASA Astrophysics Data System (ADS)

Pyle, Ryan; Rosenbaum, Robert

2017-01-01

Randomly connected networks of excitatory and inhibitory spiking neurons provide a parsimonious model of neural variability, but are notoriously unreliable for performing computations. We show that this difficulty is overcome by incorporating the well-documented dependence of connection probability on distance. Spatially extended spiking networks exhibit symmetry-breaking bifurcations and generate spatiotemporal patterns that can be trained to perform dynamical computations under a reservoir computing framework.

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.

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.

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.

KODAMA and VPC based Framework for Ubiquitous Systems and its Experiment

NASA Astrophysics Data System (ADS)

Takahashi, Kenichi; Amamiya, Satoshi; Iwao, Tadashige; Zhong, Guoqiang; Kainuma, Tatsuya; Amamiya, Makoto

Recently, agent technologies have attracted a lot of interest as an emerging programming paradigm. With such agent technologies, services are provided through collaboration among agents. At the same time, the spread of mobile technologies and communication infrastructures has made it possible to access the network anytime and from anywhere. Using agents and mobile technologies to realize ubiquitous computing systems, we propose a new framework based on KODAMA and VPC. KODAMA provides distributed management mechanisms by using the concept of community and communication infrastructure to deliver messages among agents without agents being aware of the physical network. VPC provides a method of defining peer-to-peer services based on agent communication with policy packages. By merging the characteristics of both KODAMA and VPC functions, we propose a new framework for ubiquitous computing environments. It provides distributed management functions according to the concept of agent communities, agent communications which are abstracted from the physical environment, and agent collaboration with policy packages. Using our new framework, we conducted a large-scale experiment in shopping malls in Nagoya, which sent advertisement e-mails to users' cellular phones according to user location and attributes. The empirical results showed that our new framework worked effectively for sales in shopping malls.

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.

An integrated framework for detecting suspicious behaviors in video surveillance

NASA Astrophysics Data System (ADS)

Zin, Thi Thi; Tin, Pyke; Hama, Hiromitsu; Toriu, Takashi

2014-03-01

In this paper, we propose an integrated framework for detecting suspicious behaviors in video surveillance systems which are established in public places such as railway stations, airports, shopping malls and etc. Especially, people loitering in suspicion, unattended objects left behind and exchanging suspicious objects between persons are common security concerns in airports and other transit scenarios. These involve understanding scene/event, analyzing human movements, recognizing controllable objects, and observing the effect of the human movement on those objects. In the proposed framework, multiple background modeling technique, high level motion feature extraction method and embedded Markov chain models are integrated for detecting suspicious behaviors in real time video surveillance systems. Specifically, the proposed framework employs probability based multiple backgrounds modeling technique to detect moving objects. Then the velocity and distance measures are computed as the high level motion features of the interests. By using an integration of the computed features and the first passage time probabilities of the embedded Markov chain, the suspicious behaviors in video surveillance are analyzed for detecting loitering persons, objects left behind and human interactions such as fighting. The proposed framework has been tested by using standard public datasets and our own video surveillance scenarios.

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.

An Argumentation Framework based on Paraconsistent Logic

NASA Astrophysics Data System (ADS)

Umeda, Yuichi; Takahashi, Takehisa; Sawamura, Hajime

Argumentation is the most representative of intelligent activities of humans. Therefore, it is natural to think that it could have many implications for artificial intelligence and computer science as well. Specifically, argumentation may be considered a most primitive capability for interaction among computational agents. In this paper we present an argumentation framework based on the four-valued paraconsistent logic. Tolerance and acceptance of inconsistency that this logic has as its logical feature allow for arguments on inconsistent knowledge bases with which we are often confronted. We introduce various concepts for argumentation, such as arguments, attack relations, argument justification, preferential criteria of arguments based on social norms, and so on, in a way proper to the four-valued paraconsistent logic. Then, we provide the fixpoint semantics and dialectical proof theory for our argumentation framework. We also give the proofs of the soundness and completeness.

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

Nonlinear and non-Gaussian Bayesian based handwriting beautification

NASA Astrophysics Data System (ADS)

Shi, Cao; Xiao, Jianguo; Xu, Canhui; Jia, Wenhua

2013-03-01

A framework is proposed in this paper to effectively and efficiently beautify handwriting by means of a novel nonlinear and non-Gaussian Bayesian algorithm. In the proposed framework, format and size of handwriting image are firstly normalized, and then typeface in computer system is applied to optimize vision effect of handwriting. The Bayesian statistics is exploited to characterize the handwriting beautification process as a Bayesian dynamic model. The model parameters to translate, rotate and scale typeface in computer system are controlled by state equation, and the matching optimization between handwriting and transformed typeface is employed by measurement equation. Finally, the new typeface, which is transformed from the original one and gains the best nonlinear and non-Gaussian optimization, is the beautification result of handwriting. Experimental results demonstrate the proposed framework provides a creative handwriting beautification methodology to improve visual acceptance.

Framework for Deploying a Virtualized Computing Environment for Collaborative and Secure Data Analytics

PubMed Central

Meyer, Adrian; Green, Laura; Faulk, Ciearro; Galla, Stephen; Meyer, Anne-Marie

2016-01-01

Introduction: Large amounts of health data generated by a wide range of health care applications across a variety of systems have the potential to offer valuable insight into populations and health care systems, but robust and secure computing and analytic systems are required to leverage this information. Framework: We discuss our experiences deploying a Secure Data Analysis Platform (SeDAP), and provide a framework to plan, build and deploy a virtual desktop infrastructure (VDI) to enable innovation, collaboration and operate within academic funding structures. It outlines 6 core components: Security, Ease of Access, Performance, Cost, Tools, and Training. Conclusion: A platform like SeDAP is not simply successful through technical excellence and performance. It’s adoption is dependent on a collaborative environment where researchers and users plan and evaluate the requirements of all aspects. PMID:27683665

A video coding scheme based on joint spatiotemporal and adaptive prediction.

PubMed

Jiang, Wenfei; Latecki, Longin Jan; Liu, Wenyu; Liang, Hui; Gorman, Ken

2009-05-01

We propose a video coding scheme that departs from traditional Motion Estimation/DCT frameworks and instead uses Karhunen-Loeve Transform (KLT)/Joint Spatiotemporal Prediction framework. In particular, a novel approach that performs joint spatial and temporal prediction simultaneously is introduced. It bypasses the complex H.26x interframe techniques and it is less computationally intensive. Because of the advantage of the effective joint prediction and the image-dependent color space transformation (KLT), the proposed approach is demonstrated experimentally to consistently lead to improved video quality, and in many cases to better compression rates and improved computational speed.

Automated interferometric synthetic aperture microscopy and computational adaptive optics for improved optical coherence tomography.

PubMed

Xu, Yang; Liu, Yuan-Zhi; Boppart, Stephen A; Carney, P Scott

2016-03-10

In this paper, we introduce an algorithm framework for the automation of interferometric synthetic aperture microscopy (ISAM). Under this framework, common processing steps such as dispersion correction, Fourier domain resampling, and computational adaptive optics aberration correction are carried out as metrics-assisted parameter search problems. We further present the results of this algorithm applied to phantom and biological tissue samples and compare with manually adjusted results. With the automated algorithm, near-optimal ISAM reconstruction can be achieved without manual adjustment. At the same time, the technical barrier for the nonexpert using ISAM imaging is also significantly lowered.

Computational Design of Functionalized Metal–Organic Framework Nodes for Catalysis

PubMed Central

2017-01-01

Recent progress in the synthesis and characterization of metal–organic frameworks (MOFs) has opened the door to an increasing number of possible catalytic applications. The great versatility of MOFs creates a large chemical space, whose thorough experimental examination becomes practically impossible. Therefore, computational modeling is a key tool to support, rationalize, and guide experimental efforts. In this outlook we survey the main methodologies employed to model MOFs for catalysis, and we review selected recent studies on the functionalization of their nodes. We pay special attention to catalytic applications involving natural gas conversion. PMID:29392172

A Human Factors Framework for Payload Display Design

NASA Technical Reports Server (NTRS)

Dunn, Mariea C.; Hutchinson, Sonya L.

1998-01-01

During missions to space, one charge of the astronaut crew is to conduct research experiments. These experiments, referred to as payloads, typically are controlled by computers. Crewmembers interact with payload computers by using visual interfaces or displays. To enhance the safety, productivity, and efficiency of crewmember interaction with payload displays, particular attention must be paid to the usability of these displays. Enhancing display usability requires adoption of a design process that incorporates human factors engineering principles at each stage. This paper presents a proposed framework for incorporating human factors engineering principles into the payload display design process.

System and methods of resource usage using an interoperable management framework

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

Heileman, Gregory L.; Jamkhedkar, Pramod A.; Lamb, Christopher C.

Generic rights expression language allowing interoperability across different computing environments including resource usage of different applications. A formal framework for usage management provides scaffolding upon which interoperable usage management systems can be built. Certain features of the framework are standardized, such as the operational semantics, including areas free of standards that necessitate choice and innovation to achieve a balance of flexibility and usability for interoperability in usage management systems.

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.

Computational Psychiatry of ADHD: Neural Gain Impairments across Marrian Levels of Analysis

PubMed Central

Hauser, Tobias U.; Fiore, Vincenzo G.; Moutoussis, Michael; Dolan, Raymond J.

2016-01-01

Attention-deficit hyperactivity disorder (ADHD), one of the most common psychiatric disorders, is characterised by unstable response patterns across multiple cognitive domains. However, the neural mechanisms that explain these characteristic features remain unclear. Using a computational multilevel approach, we propose that ADHD is caused by impaired gain modulation in systems that generate this phenotypic increased behavioural variability. Using Marr's three levels of analysis as a heuristic framework, we focus on this variable behaviour, detail how it can be explained algorithmically, and how it might be implemented at a neural level through catecholamine influences on corticostriatal loops. This computational, multilevel, approach to ADHD provides a framework for bridging gaps between descriptions of neuronal activity and behaviour, and provides testable predictions about impaired mechanisms. PMID:26787097

The Fight Against UCITA.

ERIC Educational Resources Information Center

Neal, James G.

2000-01-01

Discusses objections in the library community to the Uniform Computer Information Transactions Act (UCITA), a legal framework being considered by state governments regarding computer information, transactions, and software. Topics include copyright issues; user needs for access to information; license agreements; and costs that may prevent…

Integrated Language Skills CALL Course Design

ERIC Educational Resources Information Center

Watson, Kevin; Agawa, Grant

2013-01-01

The importance of a structured learning framework or interrelated frameworks is the cornerstone of a solid English as a foreign language (EFL) computer-assisted language learning (CALL) curriculum. While the benefits of CALL are widely promoted in the literature, there is often an endemic discord separating theory and practice. Oftentimes the…

Collaborative Rhetorical Structure: A Discourse Analysis Method for Analyzing Student Collaborative Inquiry via Computer Conferencing

ERIC Educational Resources Information Center

Kou, Xiaojing

2011-01-01

Various formats of online discussion have proven valuable for enhancing learning and collaboration in distance and blended learning contexts. However, despite their capacity to reveal essential processes in collaborative inquiry, current mainstream analytical frameworks, such as the cognitive presence framework (Garrison, Anderson, & Archer,…

Computer Technology, Large-Scale Social Integration, and the Local Community.

ERIC Educational Resources Information Center

Calhoun, Craig

1986-01-01

A conceptual framework is proposed for studying variations in kind and extent of social integration and relatedness, such as those new communication technology may foster. Emphasis is on the contrast between direct and indirect social relationships. The framework is illustrated by consideration of potential social impacts of widespread…

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…

Expansion and Validation of the PAPA Framework

ERIC Educational Resources Information Center

Woodward, Belle; Martin, Nancy; Imboden, Thomas

2011-01-01

In recent years, ethics has drawn increased interest from information technology and computer science practitioners as well as from academicians. This article investigates the issues outlined in the PAPA framework in today's environment and explores the possibility that new issues have emerged. Findings indicate that the ethicality of property…

Software Engineering Frameworks: Textbooks vs. Student Perceptions

ERIC Educational Resources Information Center

McMaster, Kirby; Hadfield, Steven; Wolthuis, Stuart; Sambasivam, Samuel

2012-01-01

This research examines the frameworks used by Computer Science and Information Systems students at the conclusion of their first semester of study of Software Engineering. A questionnaire listing 64 Software Engineering concepts was given to students upon completion of their first Software Engineering course. This survey was given to samples of…

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.

SCIMITAR: Scalable Stream-Processing for Sensor Information Brokering

DTIC Science & Technology

2013-11-01

IaaS) cloud frameworks including Amazon Web Services and Eucalyptus . For load testing, we used The Grinder [9], a Java load testing framework that...internal Eucalyptus cluster which we could not scale as large as the Amazon environment due to a lack of computation resources. We recreated our

BRICK v0.2, a simple, accessible, and transparent model framework for climate and regional sea-level projections

NASA Astrophysics Data System (ADS)

Wong, Tony E.; Bakker, Alexander M. R.; Ruckert, Kelsey; Applegate, Patrick; Slangen, Aimée B. A.; Keller, Klaus

2017-07-01

Simple models can play pivotal roles in the quantification and framing of uncertainties surrounding climate change and sea-level rise. They are computationally efficient, transparent, and easy to reproduce. These qualities also make simple models useful for the characterization of risk. Simple model codes are increasingly distributed as open source, as well as actively shared and guided. Alas, computer codes used in the geosciences can often be hard to access, run, modify (e.g., with regards to assumptions and model components), and review. Here, we describe the simple model framework BRICK (Building blocks for Relevant Ice and Climate Knowledge) v0.2 and its underlying design principles. The paper adds detail to an earlier published model setup and discusses the inclusion of a land water storage component. The framework largely builds on existing models and allows for projections of global mean temperature as well as regional sea levels and coastal flood risk. BRICK is written in R and Fortran. BRICK gives special attention to the model values of transparency, accessibility, and flexibility in order to mitigate the above-mentioned issues while maintaining a high degree of computational efficiency. We demonstrate the flexibility of this framework through simple model intercomparison experiments. Furthermore, we demonstrate that BRICK is suitable for risk assessment applications by using a didactic example in local flood risk management.

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.

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.

Mechanical properties of cobalt-chromium 3-unit fixed dental prostheses fabricated by casting, milling, and additive manufacturing.

PubMed

Øilo, Marit; Nesse, Harald; Lundberg, Odd Johan; Gjerdet, Nils Roar

2018-04-25

New additive manufacturing techniques for nonprecious alloys have made the fabrication of metal-ceramic fixed partial dentures (FPDs) less expensive and less time-consuming. However, whether the mechanical properties produced by these techniques are comparable is unclear. The purpose of this in vitro study was to evaluate the mechanical properties of cobalt-chromium frameworks for FPDs fabricated by 3 different techniques. Thirty frameworks for 3-unit FPDs were fabricated by traditional casting, computer-aided design and computer-aided manufacturing (CAD-CAM) milling, and selective laser melting (SLM), with n=10 in each group. The frameworks were weighed, and distal and mesial connector areas measured. The frameworks were cemented and loaded centrally (0.5 mm/s) until deformation above 1 mm occurred. Stiffness was measured as the slope of the axis between 500 and 2000 N. Microhardness was measured on sectioned specimens by Vickers indentation. The microstructure was also analyzed by scanning electron microscopy. One-way ANOVA with Tukey post hoc analysis was used to compare the groups (α=.05). The framework design differed among the groups, making a comparison of strength impossible. The milled frameworks appeared bulky, while the cast and SLM frameworks were more slender. Statistically significant differences were found in microhardness, stiffness, wall thickness, weight, and connector size (P<.05), and a significant correlation was found between hardness and stiffness (-0.4, P<.005). Fabrication method affects the design, stiffness, microhardness, and microstructure of cobalt-chromium FPD frameworks. The SLM frameworks were stiffer and harder than the cast and milled specimens. Copyright © 2018 Editorial Council for the Journal of Prosthetic Dentistry. Published by Elsevier Inc. All rights reserved.

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.

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.

A UNIFIED FRAMEWORK FOR VARIANCE COMPONENT ESTIMATION WITH SUMMARY STATISTICS IN GENOME-WIDE ASSOCIATION STUDIES.

PubMed

Zhou, Xiang

2017-12-01

Linear mixed models (LMMs) are among the most commonly used tools for genetic association studies. However, the standard method for estimating variance components in LMMs-the restricted maximum likelihood estimation method (REML)-suffers from several important drawbacks: REML requires individual-level genotypes and phenotypes from all samples in the study, is computationally slow, and produces downward-biased estimates in case control studies. To remedy these drawbacks, we present an alternative framework for variance component estimation, which we refer to as MQS. MQS is based on the method of moments (MoM) and the minimal norm quadratic unbiased estimation (MINQUE) criterion, and brings two seemingly unrelated methods-the renowned Haseman-Elston (HE) regression and the recent LD score regression (LDSC)-into the same unified statistical framework. With this new framework, we provide an alternative but mathematically equivalent form of HE that allows for the use of summary statistics. We provide an exact estimation form of LDSC to yield unbiased and statistically more efficient estimates. A key feature of our method is its ability to pair marginal z -scores computed using all samples with SNP correlation information computed using a small random subset of individuals (or individuals from a proper reference panel), while capable of producing estimates that can be almost as accurate as if both quantities are computed using the full data. As a result, our method produces unbiased and statistically efficient estimates, and makes use of summary statistics, while it is computationally efficient for large data sets. Using simulations and applications to 37 phenotypes from 8 real data sets, we illustrate the benefits of our method for estimating and partitioning SNP heritability in population studies as well as for heritability estimation in family studies. Our method is implemented in the GEMMA software package, freely available at www.xzlab.org/software.html.

CSNS computing environment Based on OpenStack

NASA Astrophysics Data System (ADS)

Li, Yakang; Qi, Fazhi; Chen, Gang; Wang, Yanming; Hong, Jianshu

2017-10-01

Cloud computing can allow for more flexible configuration of IT resources and optimized hardware utilization, it also can provide computing service according to the real need. We are applying this computing mode to the China Spallation Neutron Source(CSNS) computing environment. So, firstly, CSNS experiment and its computing scenarios and requirements are introduced in this paper. Secondly, the design and practice of cloud computing platform based on OpenStack are mainly demonstrated from the aspects of cloud computing system framework, network, storage and so on. Thirdly, some improvments to openstack we made are discussed further. Finally, current status of CSNS cloud computing environment are summarized in the ending of this paper.

Framework for Computer Assisted Instruction Courseware: A Case Study.

ERIC Educational Resources Information Center

Betlach, Judith A.

1987-01-01

Systematically investigates, defines, and organizes variables related to production of internally designed and implemented computer assisted instruction (CAI) courseware: special needs of users; costs; identification and definition of realistic training needs; CAI definition and design methodology; hardware and software requirements; and general…

Computational Exposure Science: An Emerging Discipline to Support 21st-Century Risk Assessment

EPA Science Inventory

Background: Computational exposure science represents a frontier of environmental science that is emerging and quickly evolving.Objectives: In this commentary, we define this burgeoning discipline, describe a framework for implementation, and review some key ongoing research elem...

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...

Cooling the Collective Motion of Trapped Ions to Initialize a Quantum Register

DTIC Science & Technology

2016-09-13

computation [1] provides a gen- eral framework for fundamental investigations into sub- jects such as entanglement, quantum measurement, and quantum ...information theory. Since quantum computation relies on entanglement between qubits, any implementa- tion of a quantum computer must offer isolation from the...for realiz- ing a quantum computer , which is scalable to an arbitrary number of qubits. Their scheme is based on a collection of trapped atomic ions

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.

Privacy and Data Security under Cloud Computing Arrangements: The Legal Framework and Practical Do's and Don'ts

ERIC Educational Resources Information Center

Buckman, Joel; Gold, Stephanie

2012-01-01

This article outlines privacy and data security compliance issues facing postsecondary education institutions when they utilize cloud computing and concludes with a practical list of do's and dont's. Cloud computing does not change an institution's privacy and data security obligations. It does involve reliance on a third party, which requires an…

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…

NREL Kicks Off Next Phase of Advanced Computer-Aided Battery Engineering |

Science.gov Websites

lithium-ion (Li-ion) batteries, known as a multi-scale multi-domain (GH-MSMD) model framework, was News | NREL Kicks Off Next Phase of Advanced Computer-Aided Battery Engineering NREL Kicks Off Next Phase of Advanced Computer-Aided Battery Engineering March 16, 2016 NREL researcher looks across

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.

An Adaptive Priority Tuning System for Optimized Local CPU Scheduling using BOINC Clients

NASA Astrophysics Data System (ADS)

Mnaouer, Adel B.; Ragoonath, Colin

2010-11-01

Volunteer Computing (VC) is a Distributed Computing model which utilizes idle CPU cycles from computing resources donated by volunteers who are connected through the Internet to form a very large-scale, loosely coupled High Performance Computing environment. Distributed Volunteer Computing environments such as the BOINC framework is concerned mainly with the efficient scheduling of the available resources to the applications which require them. The BOINC framework thus contains a number of scheduling policies/algorithms both on the server-side and on the client which work together to maximize the available resources and to provide a degree of QoS in an environment which is highly volatile. This paper focuses on the BOINC client and introduces an adaptive priority tuning client side middleware application which improves the execution times of Work Units (WUs) while maintaining an acceptable Maximum Response Time (MRT) for the end user. We have conducted extensive experimentation of the proposed system and the results show clear speedup of BOINC applications using our optimized middleware as opposed to running using the original BOINC client.

Software designs of image processing tasks with incremental refinement of computation.

PubMed

Anastasia, Davide; Andreopoulos, Yiannis

2010-08-01

Software realizations of computationally-demanding image processing tasks (e.g., image transforms and convolution) do not currently provide graceful degradation when their clock-cycles budgets are reduced, e.g., when delay deadlines are imposed in a multitasking environment to meet throughput requirements. This is an important obstacle in the quest for full utilization of modern programmable platforms' capabilities since worst-case considerations must be in place for reasonable quality of results. In this paper, we propose (and make available online) platform-independent software designs performing bitplane-based computation combined with an incremental packing framework in order to realize block transforms, 2-D convolution and frame-by-frame block matching. The proposed framework realizes incremental computation: progressive processing of input-source increments improves the output quality monotonically. Comparisons with the equivalent nonincremental software realization of each algorithm reveal that, for the same precision of the result, the proposed approach can lead to comparable or faster execution, while it can be arbitrarily terminated and provide the result up to the computed precision. Application examples with region-of-interest based incremental computation, task scheduling per frame, and energy-distortion scalability verify that our proposal provides significant performance scalability with graceful degradation.

Computations of Combustion-Powered Actuation for Dynamic Stall Suppression

NASA Technical Reports Server (NTRS)

Jee, Solkeun; Bowles, Patrick O.; Matalanis, Claude G.; Min, Byung-Young; Wake, Brian E.; Crittenden, Tom; Glezer, Ari

2016-01-01

A computational framework for the simulation of dynamic stall suppression with combustion-powered actuation (COMPACT) is validated against wind tunnel experimental results on a VR-12 airfoil. COMPACT slots are located at 10% chord from the leading edge of the airfoil and directed tangentially along the suction-side surface. Helicopter rotor-relevant flow conditions are used in the study. A computationally efficient two-dimensional approach, based on unsteady Reynolds-averaged Navier-Stokes (RANS), is compared in detail against the baseline and the modified airfoil with COMPACT, using aerodynamic forces, pressure profiles, and flow-field data. The two-dimensional RANS approach predicts baseline static and dynamic stall very well. Most of the differences between the computational and experimental results are within two standard deviations of the experimental data. The current framework demonstrates an ability to predict COMPACT efficacy across the experimental dataset. Enhanced aerodynamic lift on the downstroke of the pitching cycle due to COMPACT is well predicted, and the cycleaveraged lift enhancement computed is within 3% of the test data. Differences with experimental data are discussed with a focus on three-dimensional features not included in the simulations and the limited computational model for COMPACT.

A visual study of computers on doctors' desks.

PubMed

Pearce, Christopher; Walker, Hannah; O'Shea, Carolyn

2008-01-01

General practice has rapidly computerised over the past ten years, thereby changing the nature of general practice rooms. Most general practice consulting rooms were designed and created in an era without computer hardware, establishing a pattern of work around maximising the doctor-patient relationship. General practitioners (GPs) and patients have had to integrate the computer into this environment. Twenty GPs allowed access to their rooms and consultations as part of a larger study. The results are based on an analysis of still shots of the consulting rooms. Analysis used dramaturgical methodology; thus the room is described as though it is the setting for a play. First, several desk areas were identified: a shared or patient area, a working area, a clinical area and an administrative area. Then, within that framework, we were able to identify two broad categories of setting, one inclusive of the patient and one exclusive. With the increasing significance of the computer in the three-way doctor-patient-computer relationship, an understanding of the social milieu in which the three players in the consultation interact (the staging) will inform further analysis of the interaction, and allow a framework for assessing the effects of different computer placements.

Precision Fit of Screw-Retained Implant-Supported Fixed Dental Prostheses Fabricated by CAD/CAM, Copy-Milling, and Conventional Methods.

PubMed

de França, Danilo Gonzaga; Morais, Maria Helena; das Neves, Flávio D; Carreiro, Adriana Fonte; Barbosa, Gustavo As

The aim of this study was to evaluate the effectiveness of fabrication methods (computer-aided design/computer-aided manufacture [CAD/CAM], copy-milling, and conventional casting) in the fit accuracy of three-unit, screw-retained fixed dental prostheses. Sixteen three-unit implant-supported screw-retained frameworks were fabricated to fit an in vitro model. Eight frameworks were fabricated using the CAD/CAM system, four in zirconia and four in cobalt-chromium. Four zirconia frameworks were fabricated using the copy-milled system, and four were cast in cobalt-chromium using conventional casting with premachined abutments. The vertical and horizontal misfit at the implant-framework interface was measured using scanning electron microscopy at ×250. The results for vertical misfit were analyzed using Kruskal-Wallis and Mann-Whitney tests. The horizontal misfits were categorized as underextended, equally extended, or overextended. Statistical analysis established differences between groups according to the chi-square test (α = .05). The mean vertical misfit was 5.9 ± 3.6 μm for CAD/CAM-fabricated zirconia, 1.2 ± 2.2 μm for CAD/CAM-fabricated cobalt-chromium frameworks, 7.6 ± 9.2 μm for copy-milling-fabricated zirconia frameworks, and 11.8 (9.8) μm for conventionally fabricated frameworks. The Mann-Whitney test revealed significant differences between all but the zirconia-fabricated frameworks. A significant association was observed between the horizontal misfits and the fabrication method. The percentage of horizontal misfits that were underextended and overextended was higher in milled zirconia (83.3%), CAD/CAM cobaltchromium (66.7%), cast cobalt-chromium (58.3%), and CAD/CAM zirconia (33.3%) frameworks. CAD/CAM-fabricated frameworks exhibit better vertical misfit and low variability compared with copy-milled and conventionally fabricated frameworks. The percentage of interfaces equally extended was higher when CAD/CAM and zirconia were used.

From computers to cultivation: reconceptualizing evolutionary psychology.

PubMed

Barrett, Louise; Pollet, Thomas V; Stulp, Gert

2014-01-01

Does evolutionary theorizing have a role in psychology? This is a more contentious issue than one might imagine, given that, as evolved creatures, the answer must surely be yes. The contested nature of evolutionary psychology lies not in our status as evolved beings, but in the extent to which evolutionary ideas add value to studies of human behavior, and the rigor with which these ideas are tested. This, in turn, is linked to the framework in which particular evolutionary ideas are situated. While the framing of the current research topic places the brain-as-computer metaphor in opposition to evolutionary psychology, the most prominent school of thought in this field (born out of cognitive psychology, and often known as the Santa Barbara school) is entirely wedded to the computational theory of mind as an explanatory framework. Its unique aspect is to argue that the mind consists of a large number of functionally specialized (i.e., domain-specific) computational mechanisms, or modules (the massive modularity hypothesis). Far from offering an alternative to, or an improvement on, the current perspective, we argue that evolutionary psychology is a mainstream computational theory, and that its arguments for domain-specificity often rest on shaky premises. We then go on to suggest that the various forms of e-cognition (i.e., embodied, embedded, enactive) represent a true alternative to standard computational approaches, with an emphasis on "cognitive integration" or the "extended mind hypothesis" in particular. We feel this offers the most promise for human psychology because it incorporates the social and historical processes that are crucial to human "mind-making" within an evolutionarily informed framework. In addition to linking to other research areas in psychology, this approach is more likely to form productive links to other disciplines within the social sciences, not least by encouraging a healthy pluralism in approach.

Product plots.

PubMed

Wickham, Hadley; Hofmann, Heike

2011-12-01

We propose a new framework for visualising tables of counts, proportions and probabilities. We call our framework product plots, alluding to the computation of area as a product of height and width, and the statistical concept of generating a joint distribution from the product of conditional and marginal distributions. The framework, with extensions, is sufficient to encompass over 20 visualisations previously described in fields of statistical graphics and infovis, including bar charts, mosaic plots, treemaps, equal area plots and fluctuation diagrams. © 2011 IEEE

Modeling Real-Time Coordination of Distributed Expertise and Event Response in NASA Mission Control Center Operations

NASA Astrophysics Data System (ADS)

Onken, Jeffrey

This dissertation introduces a multidisciplinary framework for the enabling of future research and analysis of alternatives for control centers for real-time operations of safety-critical systems. The multidisciplinary framework integrates functional and computational models that describe the dynamics in fundamental concepts of previously disparate engineering and psychology research disciplines, such as group performance and processes, supervisory control, situation awareness, events and delays, and expertise. The application in this dissertation is the real-time operations within the NASA Mission Control Center in Houston, TX. This dissertation operationalizes the framework into a model and simulation, which simulates the functional and computational models in the framework according to user-configured scenarios for a NASA human-spaceflight mission. The model and simulation generates data according to the effectiveness of the mission-control team in supporting the completion of mission objectives and detecting, isolating, and recovering from anomalies. Accompanying the multidisciplinary framework is a proof of concept, which demonstrates the feasibility of such a framework. The proof of concept demonstrates that variability occurs where expected based on the models. The proof of concept also demonstrates that the data generated from the model and simulation is useful for analyzing and comparing MCC configuration alternatives because an investigator can give a diverse set of scenarios to the simulation and the output compared in detail to inform decisions about the effect of MCC configurations on mission operations performance.

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…

HPC Software Stack Testing Framework

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

Garvey, Cormac

The HPC Software stack testing framework (hpcswtest) is used in the INL Scientific Computing Department to test the basic sanity and integrity of the HPC Software stack (Compilers, MPI, Numerical libraries and Applications) and to quickly discover hard failures, and as a by-product it will indirectly check the HPC infrastructure (network, PBS and licensing servers).

Integration of Voice, Data and Image as a Factor in Information Planning. AIR Forum 1981 Paper.

ERIC Educational Resources Information Center

Sheehan, Bernard S.; McMinn, William B.

Technological advances in computers and telecommunications that have significantly changed higher education are analyzed within a framework that associates technologies, applications, and aspects of institutions that are affected. Two further frameworks, one for information systems suggested by decision support systems study and one which is a map…

Researching the Community of Inquiry Framework: Review, Issues, and Future Directions

ERIC Educational Resources Information Center

Garrison, D. Randy; Arbaugh, J. B.

2007-01-01

Since its publication in "The Internet and Higher Education," Garrison, Anderson, and Archer's [Garrison, D. R., Anderson, T., & Archer, W. (2000). Critical inquiry in a text-based environment: Computer conferencing in higher education. "The Internet and Higher Education," 2(2-3), 87-105.] community of inquiry (CoI) framework has generated…

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…

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.

CLAss-Specific Subspace Kernel Representations and Adaptive Margin Slack Minimization for Large Scale Classification.

PubMed

Yu, Yinan; Diamantaras, Konstantinos I; McKelvey, Tomas; Kung, Sun-Yuan

2018-02-01

In kernel-based classification models, given limited computational power and storage capacity, operations over the full kernel matrix becomes prohibitive. In this paper, we propose a new supervised learning framework using kernel models for sequential data processing. The framework is based on two components that both aim at enhancing the classification capability with a subset selection scheme. The first part is a subspace projection technique in the reproducing kernel Hilbert space using a CLAss-specific Subspace Kernel representation for kernel approximation. In the second part, we propose a novel structural risk minimization algorithm called the adaptive margin slack minimization to iteratively improve the classification accuracy by an adaptive data selection. We motivate each part separately, and then integrate them into learning frameworks for large scale data. We propose two such frameworks: the memory efficient sequential processing for sequential data processing and the parallelized sequential processing for distributed computing with sequential data acquisition. We test our methods on several benchmark data sets and compared with the state-of-the-art techniques to verify the validity of the proposed techniques.

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.

ICCE/ICCAI 2000 Full & Short Papers (Others).

ERIC Educational Resources Information Center

2000

This document contains the following full and short papers from ICCE/ICCAI 2000 (International Conference on Computers in Education/International Conference on Computer-Assisted Instruction): (1) "A Code Restructuring Tool To Help Scaffold Novice Programmers" (Stuart Garner); (2) "An Assessment Framework for Information Technology Integrated…

Open Systems Interconnection.

ERIC Educational Resources Information Center

Denenberg, Ray

1985-01-01

Discusses the need for standards allowing computer-to-computer communication and gives examples of technical issues. The seven-layer framework of the Open Systems Interconnection (OSI) Reference Model is explained and illustrated. Sidebars feature public data networks and Recommendation X.25, OSI standards, OSI layer functions, and a glossary.…

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...

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.

Brains are not just neurons. Comment on “Toward a computational framework for cognitive biology: Unifying approaches from cognitive neuroscience and comparative cognition” by Fitch

NASA Astrophysics Data System (ADS)

Huber, Ludwig

2014-09-01

This comment addresses the first component of Fitch's framework: the computational power of single neurons [3]. Although I agree that traditional models of neural computation have vastly underestimated the computational power of single neurons, I am hesitant to follow him completely. The exclusive focus on neurons is likely to underestimate the importance of other cells in the brain. In the last years, two such cell types have received appropriate attention by neuroscientists: interneurons and glia. Interneurons are small, tightly packed cells involved in the control of information processing in learning and memory. Rather than transmitting externally (like motor or sensory neurons), these neurons process information within internal circuits of the brain (therefore also called 'relay neurons'). Some specialized interneuron subtypes temporally regulate the flow of information in a given cortical circuit during relevant behavioral events [4]. In the human brain approx. 100 billion interneurons control information processing and are implicated in disorders such as epilepsy and Parkinson's.

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

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.

Nature as a network of morphological infocomputational processes for cognitive agents

NASA Astrophysics Data System (ADS)

Dodig-Crnkovic, Gordana

2017-01-01

This paper presents a view of nature as a network of infocomputational agents organized in a dynamical hierarchy of levels. It provides a framework for unification of currently disparate understandings of natural, formal, technical, behavioral and social phenomena based on information as a structure, differences in one system that cause the differences in another system, and computation as its dynamics, i.e. physical process of morphological change in the informational structure. We address some of the frequent misunderstandings regarding the natural/morphological computational models and their relationships to physical systems, especially cognitive systems such as living beings. Natural morphological infocomputation as a conceptual framework necessitates generalization of models of computation beyond the traditional Turing machine model presenting symbol manipulation, and requires agent-based concurrent resource-sensitive models of computation in order to be able to cover the whole range of phenomena from physics to cognition. The central role of agency, particularly material vs. cognitive agency is highlighted.

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.

Inclusive prompt photon production in electron-nucleus scattering at small x

NASA Astrophysics Data System (ADS)

Roy, Kaushik; Venugopalan, Raju

2018-05-01

We compute the differential cross-section for inclusive prompt photon production in deeply inelastic scattering (DIS) of electrons on nuclei at small x in the framework of the Color Glass Condensate (CGC) effective theory. The leading order (LO) computation in this framework resums leading logarithms in x as well as power corrections to all orders in Q s, A 2 / Q 2, where Q s, A ( x) is the nuclear saturation scale. This LO result is proportional to universal dipole and quadrupole Wilson line correlators in the nucleus. In the soft photon limit, the Low-Burnett-Kroll theorem allows us to recover existing results on inclusive DIS dijet production. The k ⊥ and collinearly factorized expressions for prompt photon production in DIS are also recovered in a leading twist approximation to our result. In the latter case, our result corresponds to the dominant next-to-leading order (NLO) perturbative QCD contribution at small x. We next discuss the computation of the NLO corrections to inclusive prompt photon production in the CGC framework. In particular, we emphasize the advantages for higher order computations in inclusive photon production, and for fully inclusive DIS, arising from the simple momentum space structure of the dressed quark and gluon "shock wave" propagators in the "wrong" light cone gauge A - = 0 for a nucleus moving with P N + → ∞.

Reduced Design Load Basis for Ultimate Blade Loads Estimation in Multidisciplinary Design Optimization Frameworks

NASA Astrophysics Data System (ADS)

Pavese, Christian; Tibaldi, Carlo; Larsen, Torben J.; Kim, Taeseong; Thomsen, Kenneth

2016-09-01

The aim is to provide a fast and reliable approach to estimate ultimate blade loads for a multidisciplinary design optimization (MDO) framework. For blade design purposes, the standards require a large amount of computationally expensive simulations, which cannot be efficiently run each cost function evaluation of an MDO process. This work describes a method that allows integrating the calculation of the blade load envelopes inside an MDO loop. Ultimate blade load envelopes are calculated for a baseline design and a design obtained after an iteration of an MDO. These envelopes are computed for a full standard design load basis (DLB) and a deterministic reduced DLB. Ultimate loads extracted from the two DLBs with the two blade designs each are compared and analyzed. Although the reduced DLB supplies ultimate loads of different magnitude, the shape of the estimated envelopes are similar to the one computed using the full DLB. This observation is used to propose a scheme that is computationally cheap, and that can be integrated inside an MDO framework, providing a sufficiently reliable estimation of the blade ultimate loading. The latter aspect is of key importance when design variables implementing passive control methodologies are included in the formulation of the optimization problem. An MDO of a 10 MW wind turbine blade is presented as an applied case study to show the efficacy of the reduced DLB concept.

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.

A Framework for Modeling Competitive and Cooperative Computation in Retinal Processing

NASA Astrophysics Data System (ADS)

Moreno-Díaz, Roberto; de Blasio, Gabriel; Moreno-Díaz, Arminda

2008-07-01

The structure of the retina suggests that it should be treated (at least from the computational point of view), as a layered computer. Different retinal cells contribute to the coding of the signals down to ganglion cells. Also, because of the nature of the specialization of some ganglion cells, the structure suggests that all these specialization processes should take place at the inner plexiform layer and they should be of a local character, prior to a global integration and frequency-spike coding by the ganglion cells. The framework we propose consists of a layered computational structure, where outer layers provide essentially with band-pass space-time filtered signals which are progressively delayed, at least for their formal treatment. Specialization is supposed to take place at the inner plexiform layer by the action of spatio-temporal microkernels (acting very locally), and having a centerperiphery space-time structure. The resulting signals are then integrated by the ganglion cells through macrokernels structures. Practically all types of specialization found in different vertebrate retinas, as well as the quasilinear behavior in some higher vertebrates, can be modeled and simulated within this framework. Finally, possible feedback from central structures is considered. Though their relevance to retinal processing is not definitive, it is included here for the sake of completeness, since it is a formal requisite for recursiveness.

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

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

Compression-based integral curve data reuse framework for flow visualization

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

Hong, Fan; Bi, Chongke; Guo, Hanqi

Currently, by default, integral curves are repeatedly re-computed in different flow visualization applications, such as FTLE field computation, source-destination queries, etc., leading to unnecessary resource cost. We present a compression-based data reuse framework for integral curves, to greatly reduce their retrieval cost, especially in a resource-limited environment. In our design, a hierarchical and hybrid compression scheme is proposed to balance three objectives, including high compression ratio, controllable error, and low decompression cost. Specifically, we use and combine digitized curve sparse representation, floating-point data compression, and octree space partitioning to adaptively achieve the objectives. Results have shown that our data reusemore » framework could acquire tens of times acceleration in the resource-limited environment compared to on-the-fly particle tracing, and keep controllable information loss. Moreover, our method could provide fast integral curve retrieval for more complex data, such as unstructured mesh data.« less

DISCRN: A Distributed Storytelling Framework for Intelligence Analysis.

PubMed

Shukla, Manu; Dos Santos, Raimundo; Chen, Feng; Lu, Chang-Tien

2017-09-01

Storytelling connects entities (people, organizations) using their observed relationships to establish meaningful storylines. This can be extended to spatiotemporal storytelling that incorporates locations, time, and graph computations to enhance coherence and meaning. But when performed sequentially these computations become a bottleneck because the massive number of entities make space and time complexity untenable. This article presents DISCRN, or distributed spatiotemporal ConceptSearch-based storytelling, a distributed framework for performing spatiotemporal storytelling. The framework extracts entities from microblogs and event data, and links these entities using a novel ConceptSearch to derive storylines in a distributed fashion utilizing key-value pair paradigm. Performing these operations at scale allows deeper and broader analysis of storylines. The novel parallelization techniques speed up the generation and filtering of storylines on massive datasets. Experiments with microblog posts such as Twitter data and Global Database of Events, Language, and Tone events show the efficiency of the techniques in DISCRN.

Toward a theoretical framework for trustworthy cyber sensing

NASA Astrophysics Data System (ADS)

Xu, Shouhuai

2010-04-01

Cyberspace is an indispensable part of the economy and society, but has been "polluted" with many compromised computers that can be abused to launch further attacks against the others. Since it is likely that there always are compromised computers, it is important to be aware of the (dynamic) cyber security-related situation, which is however challenging because cyberspace is an extremely large-scale complex system. Our project aims to investigate a theoretical framework for trustworthy cyber sensing. With the perspective of treating cyberspace as a large-scale complex system, the core question we aim to address is: What would be a competent theoretical (mathematical and algorithmic) framework for designing, analyzing, deploying, managing, and adapting cyber sensor systems so as to provide trustworthy information or input to the higher layer of cyber situation-awareness management, even in the presence of sophisticated malicious attacks against the cyber sensor systems?

Mixing Categories and Modal Logics in the Quantum Setting

NASA Astrophysics Data System (ADS)

Cinà, Giovanni

The study of the foundations of Quantum Mechanics, especially after the advent of Quantum Computation and Information, has benefited from the application of category-theoretic tools and modal logics to the analysis of Quantum processes: we witness a wealth of theoretical frameworks casted in either of the two languages. This paper explores the interplay of the two formalisms in the peculiar context of Quantum Theory. After a review of some influential abstract frameworks, we show how different modal logic frames can be extracted from the category of finite dimensional Hilbert spaces, connecting the Categorical Quantum Mechanics approach to some modal logics that have been proposed for Quantum Computing. We then apply a general version of the same technique to two other categorical frameworks, the `topos approach' of Doering and Isham and the sheaf-theoretic work on contextuality by Abramsky and Brandenburger, suggesting how some key features can be expressed with modal languages.

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

Efficient LIDAR Point Cloud Data Managing and Processing in a Hadoop-Based Distributed Framework

NASA Astrophysics Data System (ADS)

Wang, C.; Hu, F.; Sha, D.; Han, X.

2017-10-01

Light Detection and Ranging (LiDAR) is one of the most promising technologies in surveying and mapping city management, forestry, object recognition, computer vision engineer and others. However, it is challenging to efficiently storage, query and analyze the high-resolution 3D LiDAR data due to its volume and complexity. In order to improve the productivity of Lidar data processing, this study proposes a Hadoop-based framework to efficiently manage and process LiDAR data in a distributed and parallel manner, which takes advantage of Hadoop's storage and computing ability. At the same time, the Point Cloud Library (PCL), an open-source project for 2D/3D image and point cloud processing, is integrated with HDFS and MapReduce to conduct the Lidar data analysis algorithms provided by PCL in a parallel fashion. The experiment results show that the proposed framework can efficiently manage and process big LiDAR data.

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 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.

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.

Parallel scalability and efficiency of vortex particle method for aeroelasticity analysis of bluff bodies

NASA Astrophysics Data System (ADS)

Tolba, Khaled Ibrahim; Morgenthal, Guido

2018-01-01

This paper presents an analysis of the scalability and efficiency of a simulation framework based on the vortex particle method. The code is applied for the numerical aerodynamic analysis of line-like structures. The numerical code runs on multicore CPU and GPU architectures using OpenCL framework. The focus of this paper is the analysis of the parallel efficiency and scalability of the method being applied to an engineering test case, specifically the aeroelastic response of a long-span bridge girder at the construction stage. The target is to assess the optimal configuration and the required computer architecture, such that it becomes feasible to efficiently utilise the method within the computational resources available for a regular engineering office. The simulations and the scalability analysis are performed on a regular gaming type computer.

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.

Effect of feldspathic porcelain layering on the marginal fit of zirconia and titanium complete-arch fixed implant-supported frameworks.

PubMed

Yilmaz, Burak; Alshahrani, Faris A; Kale, Ediz; Johnston, William M

2018-02-06

Veneering with porcelain may adversely affect the marginal fit of long-span computer-aided design and computer-aided manufacturing (CAD-CAM) implant-supported fixed prostheses. Moreover, data regarding the precision of fit of CAD-CAM-fabricated implant-supported complete zirconia fixed dental prostheses (FDPs) before and after porcelain layering are limited. The purpose of this in vitro study was to evaluate the effect of porcelain layering on the marginal fit of CAD-CAM-fabricated complete-arch implant-supported, screw-retained FDPs with presintered zirconia frameworks compared with titanium. An autopolymerizing acrylic resin-fixed complete denture framework prototype was fabricated on an edentulous typodont master model (all-on-4 concept; Nobel Biocare) with 2 straight in the anterior and 2 distally tilted internal-hexagon dental implants in the posterior with multiunit abutments bilaterally in canine and first molar locations. A 3-dimensional (3D) laser scanner (S600 ARTI; Zirkonzahn) was used to digitize the prototype and the master model by using scan bodies to generate a virtual 3D CAD framework. Five presintered zirconia (ICE Zirkon Translucent - 95H16; Zirkonzahn) and 5 titanium (Titan 5 - 95H14; Zirkonzahn) frameworks were fabricated using the CAM milling unit (M1 Wet Heavy Metal Milling Unit; Zirkonzahn).The 1-screw test was applied by fixing the frameworks at the location of the maxillary left first molar abutment, and an industrial computed tomography (CT) scanner (XT H 225 - Basic Configuration; Nikon) was used to scan the framework-model complex to evaluate the passive fit of the frameworks on the master model. The scanned data were transported in standard tessellation language (STL) from Volume Graphics analysis software to PolyWorks analysis software by using the maximum-fit algorithm to fit scanned planes in order to mimic the mating surfaces in the best way. 3D virtual assessment of the marginal fit was performed at the abutment-framework interface at the maxillary right canine (gap 3) and right first molar (gap 4) abutments without prosthetic screws. The facial or buccal aspects of the teeth on frameworks were layered with corresponding porcelain (Initial Dental Ceramic System; GC) and CT-scanned again using the same protocol. Marginal fit measurements were made for 4 groups: titanium (Ti) (control), porcelain-layered titanium (Ti-P) (control), zirconia (Zr), and porcelain-layered zirconia (Zr-P). 3D discrepancy mean values were computed and calculated, and the results were analyzed with a repeated measures 3-way ANOVA using the maximum likelihood estimation method and Bonferroni adjustments for selected pairwise comparison t-tests (α=.05). The 3D fit was measured at gap 3 and gap 4. Statistically significant differences in mean 3D discrepancies were observed between Zr-P (175 μm) and Zr (89 μm) and between Zr-P and Ti-P (71 μm) (P<.001). Porcelain layering had a significant effect on the marginal fit of CAD-CAM-fabricated complete-arch implant-supported, screw-retained FDPs with partially sintered zirconia frameworks. 3D marginal discrepancy mean values for all groups were within clinically acceptable limits (<120 μm), except for the layered zirconia framework. Copyright © 2017 Editorial Council for the Journal of Prosthetic Dentistry. Published by Elsevier Inc. All rights reserved.

Demonstration of blind quantum computing.

PubMed

Barz, Stefanie; Kashefi, Elham; Broadbent, Anne; Fitzsimons, Joseph F; Zeilinger, Anton; Walther, Philip

2012-01-20

Quantum computers, besides offering substantial computational speedups, are also expected to preserve the privacy of a computation. We present an experimental demonstration of blind quantum computing in which the input, computation, and output all remain unknown to the computer. We exploit the conceptual framework of measurement-based quantum computation that enables a client to delegate a computation to a quantum server. Various blind delegated computations, including one- and two-qubit gates and the Deutsch and Grover quantum algorithms, are demonstrated. The client only needs to be able to prepare and transmit individual photonic qubits. Our demonstration is crucial for unconditionally secure quantum cloud computing and might become a key ingredient for real-life applications, especially when considering the challenges of making powerful quantum computers widely available.

Surrogate assisted multidisciplinary design optimization for an all-electric GEO satellite

NASA Astrophysics Data System (ADS)

Shi, Renhe; Liu, Li; Long, Teng; Liu, Jian; Yuan, Bin

2017-09-01

State-of-the-art all-electric geostationary earth orbit (GEO) satellites use electric thrusters to execute all propulsive duties, which significantly differ from the traditional all-chemical ones in orbit-raising, station-keeping, radiation damage protection, and power budget, etc. Design optimization task of an all-electric GEO satellite is therefore a complex multidisciplinary design optimization (MDO) problem involving unique design considerations. However, solving the all-electric GEO satellite MDO problem faces big challenges in disciplinary modeling techniques and efficient optimization strategy. To address these challenges, we presents a surrogate assisted MDO framework consisting of several modules, i.e., MDO problem definition, multidisciplinary modeling, multidisciplinary analysis (MDA), and surrogate assisted optimizer. Based on the proposed framework, the all-electric GEO satellite MDO problem is formulated to minimize the total mass of the satellite system under a number of practical constraints. Then considerable efforts are spent on multidisciplinary modeling involving geosynchronous transfer, GEO station-keeping, power, thermal control, attitude control, and structure disciplines. Since orbit dynamics models and finite element structural model are computationally expensive, an adaptive response surface surrogate based optimizer is incorporated in the proposed framework to solve the satellite MDO problem with moderate computational cost, where a response surface surrogate is gradually refined to represent the computationally expensive MDA process. After optimization, the total mass of the studied GEO satellite is decreased by 185.3 kg (i.e., 7.3% of the total mass). Finally, the optimal design is further discussed to demonstrate the effectiveness of our proposed framework to cope with the all-electric GEO satellite system design optimization problems. This proposed surrogate assisted MDO framework can also provide valuable references for other all-electric spacecraft system design.

A Hybrid CPU-GPU Accelerated Framework for Fast Mapping of High-Resolution Human Brain Connectome

PubMed Central

Ren, Ling; Xu, Mo; Xie, Teng; Gong, Gaolang; Xu, Ningyi; Yang, Huazhong; He, Yong

2013-01-01

Recently, a combination of non-invasive neuroimaging techniques and graph theoretical approaches has provided a unique opportunity for understanding the patterns of the structural and functional connectivity of the human brain (referred to as the human brain connectome). Currently, there is a very large amount of brain imaging data that have been collected, and there are very high requirements for the computational capabilities that are used in high-resolution connectome research. In this paper, we propose a hybrid CPU-GPU framework to accelerate the computation of the human brain connectome. We applied this framework to a publicly available resting-state functional MRI dataset from 197 participants. For each subject, we first computed Pearson’s Correlation coefficient between any pairs of the time series of gray-matter voxels, and then we constructed unweighted undirected brain networks with 58 k nodes and a sparsity range from 0.02% to 0.17%. Next, graphic properties of the functional brain networks were quantified, analyzed and compared with those of 15 corresponding random networks. With our proposed accelerating framework, the above process for each network cost 80∼150 minutes, depending on the network sparsity. Further analyses revealed that high-resolution functional brain networks have efficient small-world properties, significant modular structure, a power law degree distribution and highly connected nodes in the medial frontal and parietal cortical regions. These results are largely compatible with previous human brain network studies. Taken together, our proposed framework can substantially enhance the applicability and efficacy of high-resolution (voxel-based) brain network analysis, and have the potential to accelerate the mapping of the human brain connectome in normal and disease states. PMID:23675425

A data colocation grid framework for big data medical image processing: backend design

NASA Astrophysics Data System (ADS)

Bao, Shunxing; Huo, Yuankai; Parvathaneni, Prasanna; Plassard, Andrew J.; Bermudez, Camilo; Yao, Yuang; Lyu, Ilwoo; Gokhale, Aniruddha; Landman, Bennett A.

2018-03-01

When processing large medical imaging studies, adopting high performance grid computing resources rapidly becomes important. We recently presented a "medical image processing-as-a-service" grid framework that offers promise in utilizing the Apache Hadoop ecosystem and HBase for data colocation by moving computation close to medical image storage. However, the framework has not yet proven to be easy to use in a heterogeneous hardware environment. Furthermore, the system has not yet validated when considering variety of multi-level analysis in medical imaging. Our target design criteria are (1) improving the framework's performance in a heterogeneous cluster, (2) performing population based summary statistics on large datasets, and (3) introducing a table design scheme for rapid NoSQL query. In this paper, we present a heuristic backend interface application program interface (API) design for Hadoop and HBase for Medical Image Processing (HadoopBase-MIP). The API includes: Upload, Retrieve, Remove, Load balancer (for heterogeneous cluster) and MapReduce templates. A dataset summary statistic model is discussed and implemented by MapReduce paradigm. We introduce a HBase table scheme for fast data query to better utilize the MapReduce model. Briefly, 5153 T1 images were retrieved from a university secure, shared web database and used to empirically access an in-house grid with 224 heterogeneous CPU cores. Three empirical experiments results are presented and discussed: (1) load balancer wall-time improvement of 1.5-fold compared with a framework with built-in data allocation strategy, (2) a summary statistic model is empirically verified on grid framework and is compared with the cluster when deployed with a standard Sun Grid Engine (SGE), which reduces 8-fold of wall clock time and 14-fold of resource time, and (3) the proposed HBase table scheme improves MapReduce computation with 7 fold reduction of wall time compare with a naïve scheme when datasets are relative small. The source code and interfaces have been made publicly available.

A Data Colocation Grid Framework for Big Data Medical Image Processing: Backend Design.

PubMed

Bao, Shunxing; Huo, Yuankai; Parvathaneni, Prasanna; Plassard, Andrew J; Bermudez, Camilo; Yao, Yuang; Lyu, Ilwoo; Gokhale, Aniruddha; Landman, Bennett A

2018-03-01

When processing large medical imaging studies, adopting high performance grid computing resources rapidly becomes important. We recently presented a "medical image processing-as-a-service" grid framework that offers promise in utilizing the Apache Hadoop ecosystem and HBase for data colocation by moving computation close to medical image storage. However, the framework has not yet proven to be easy to use in a heterogeneous hardware environment. Furthermore, the system has not yet validated when considering variety of multi-level analysis in medical imaging. Our target design criteria are (1) improving the framework's performance in a heterogeneous cluster, (2) performing population based summary statistics on large datasets, and (3) introducing a table design scheme for rapid NoSQL query. In this paper, we present a heuristic backend interface application program interface (API) design for Hadoop & HBase for Medical Image Processing (HadoopBase-MIP). The API includes: Upload, Retrieve, Remove, Load balancer (for heterogeneous cluster) and MapReduce templates. A dataset summary statistic model is discussed and implemented by MapReduce paradigm. We introduce a HBase table scheme for fast data query to better utilize the MapReduce model. Briefly, 5153 T1 images were retrieved from a university secure, shared web database and used to empirically access an in-house grid with 224 heterogeneous CPU cores. Three empirical experiments results are presented and discussed: (1) load balancer wall-time improvement of 1.5-fold compared with a framework with built-in data allocation strategy, (2) a summary statistic model is empirically verified on grid framework and is compared with the cluster when deployed with a standard Sun Grid Engine (SGE), which reduces 8-fold of wall clock time and 14-fold of resource time, and (3) the proposed HBase table scheme improves MapReduce computation with 7 fold reduction of wall time compare with a naïve scheme when datasets are relative small. The source code and interfaces have been made publicly available.

The SCEC Unified Community Velocity Model (UCVM) Software Framework for Distributing and Querying Seismic Velocity Models

NASA Astrophysics Data System (ADS)

Maechling, P. J.; Taborda, R.; Callaghan, S.; Shaw, J. H.; Plesch, A.; Olsen, K. B.; Jordan, T. H.; Goulet, C. A.

2017-12-01

Crustal seismic velocity models and datasets play a key role in regional three-dimensional numerical earthquake ground-motion simulation, full waveform tomography, modern physics-based probabilistic earthquake hazard analysis, as well as in other related fields including geophysics, seismology, and earthquake engineering. The standard material properties provided by a seismic velocity model are P- and S-wave velocities and density for any arbitrary point within the geographic volume for which the model is defined. Many seismic velocity models and datasets are constructed by synthesizing information from multiple sources and the resulting models are delivered to users in multiple file formats, such as text files, binary files, HDF-5 files, structured and unstructured grids, and through computer applications that allow for interactive querying of material properties. The Southern California Earthquake Center (SCEC) has developed the Unified Community Velocity Model (UCVM) software framework to facilitate the registration and distribution of existing and future seismic velocity models to the SCEC community. The UCVM software framework is designed to provide a standard query interface to multiple, alternative velocity models, even if the underlying velocity models are defined in different formats or use different geographic projections. The UCVM framework provides a comprehensive set of open-source tools for querying seismic velocity model properties, combining regional 3D models and 1D background models, visualizing 3D models, and generating computational models in the form of regular grids or unstructured meshes that can be used as inputs for ground-motion simulations. The UCVM framework helps researchers compare seismic velocity models and build equivalent simulation meshes from alternative velocity models. These capabilities enable researchers to evaluate the impact of alternative velocity models in ground-motion simulations and seismic hazard analysis applications. In this poster, we summarize the key components of the UCVM framework and describe the impact it has had in various computational geoscientific applications.

The New Feedback Control System of RFX-mod Based on the MARTe Real-Time Framework

NASA Astrophysics Data System (ADS)

Manduchi, G.; Luchetta, A.; Soppelsa, A.; Taliercio, C.

2014-06-01

A real-time system has been successfully used since 2004 in the RFX-mod nuclear fusion experiment to control the position of the plasma and its Magneto Hydrodynamic (MHD) modes. However, its latency and the limited computation power of the used processors prevented the usage of more aggressive control algorithms. Therefore a new hardware and software architecture has been designed to overcome such limitations and to provide a shorter latency and a much increased computation power. The new system is based on a Linux multi-core server and uses MARTe, a framework for real-time control which is gaining interest in the fusion community.

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.

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.

Processing Solutions for Big Data in Astronomy

NASA Astrophysics Data System (ADS)

Fillatre, L.; Lepiller, D.

2016-09-01

This paper gives a simple introduction to processing solutions applied to massive amounts of data. It proposes a general presentation of the Big Data paradigm. The Hadoop framework, which is considered as the pioneering processing solution for Big Data, is described together with YARN, the integrated Hadoop tool for resource allocation. This paper also presents the main tools for the management of both the storage (NoSQL solutions) and computing capacities (MapReduce parallel processing schema) of a cluster of machines. Finally, more recent processing solutions like Spark are discussed. Big Data frameworks are now able to run complex applications while keeping the programming simple and greatly improving the computing speed.

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.

An automated tuberculosis screening strategy combining X-ray-based computer-aided detection and clinical information

NASA Astrophysics Data System (ADS)

Melendez, Jaime; Sánchez, Clara I.; Philipsen, Rick H. H. M.; Maduskar, Pragnya; Dawson, Rodney; Theron, Grant; Dheda, Keertan; van Ginneken, Bram

2016-04-01

Lack of human resources and radiological interpretation expertise impair tuberculosis (TB) screening programmes in TB-endemic countries. Computer-aided detection (CAD) constitutes a viable alternative for chest radiograph (CXR) reading. However, no automated techniques that exploit the additional clinical information typically available during screening exist. To address this issue and optimally exploit this information, a machine learning-based combination framework is introduced. We have evaluated this framework on a database containing 392 patient records from suspected TB subjects prospectively recruited in Cape Town, South Africa. Each record comprised a CAD score, automatically computed from a CXR, and 12 clinical features. Comparisons with strategies relying on either CAD scores or clinical information alone were performed. Our results indicate that the combination framework outperforms the individual strategies in terms of the area under the receiving operating characteristic curve (0.84 versus 0.78 and 0.72), specificity at 95% sensitivity (49% versus 24% and 31%) and negative predictive value (98% versus 95% and 96%). Thus, it is believed that combining CAD and clinical information to estimate the risk of active disease is a promising tool for TB screening.

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