Dimensionality of visual complexity in computer graphics scenes

NASA Astrophysics Data System (ADS)

Ramanarayanan, Ganesh; Bala, Kavita; Ferwerda, James A.; Walter, Bruce

2008-02-01

How do human observers perceive visual complexity in images? This problem is especially relevant for computer graphics, where a better understanding of visual complexity can aid in the development of more advanced rendering algorithms. In this paper, we describe a study of the dimensionality of visual complexity in computer graphics scenes. We conducted an experiment where subjects judged the relative complexity of 21 high-resolution scenes, rendered with photorealistic methods. Scenes were gathered from web archives and varied in theme, number and layout of objects, material properties, and lighting. We analyzed the subject responses using multidimensional scaling of pooled subject responses. This analysis embedded the stimulus images in a two-dimensional space, with axes that roughly corresponded to "numerosity" and "material / lighting complexity". In a follow-up analysis, we derived a one-dimensional complexity ordering of the stimulus images. We compared this ordering with several computable complexity metrics, such as scene polygon count and JPEG compression size, and did not find them to be very correlated. Understanding the differences between these measures can lead to the design of more efficient rendering algorithms in computer graphics.

A Study of Complex Deep Learning Networks on High Performance, Neuromorphic, and Quantum Computers

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

Potok, Thomas E; Schuman, Catherine D; Young, Steven R

Current Deep Learning models use highly optimized convolutional neural networks (CNN) trained on large graphical processing units (GPU)-based computers with a fairly simple layered network topology, i.e., highly connected layers, without intra-layer connections. Complex topologies have been proposed, but are intractable to train on current systems. Building the topologies of the deep learning network requires hand tuning, and implementing the network in hardware is expensive in both cost and power. In this paper, we evaluate deep learning models using three different computing architectures to address these problems: quantum computing to train complex topologies, high performance computing (HPC) to automatically determinemore » network topology, and neuromorphic computing for a low-power hardware implementation. Due to input size limitations of current quantum computers we use the MNIST dataset for our evaluation. The results show the possibility of using the three architectures in tandem to explore complex deep learning networks that are untrainable using a von Neumann architecture. We show that a quantum computer can find high quality values of intra-layer connections and weights, while yielding a tractable time result as the complexity of the network increases; a high performance computer can find optimal layer-based topologies; and a neuromorphic computer can represent the complex topology and weights derived from the other architectures in low power memristive hardware. This represents a new capability that is not feasible with current von Neumann architecture. It potentially enables the ability to solve very complicated problems unsolvable with current computing technologies.« less

Comparing Virtual and Physical Robotics Environments for Supporting Complex Systems and Computational Thinking

ERIC Educational Resources Information Center

Berland, Matthew; Wilensky, Uri

2015-01-01

Both complex systems methods (such as agent-based modeling) and computational methods (such as programming) provide powerful ways for students to understand new phenomena. To understand how to effectively teach complex systems and computational content to younger students, we conducted a study in four urban middle school classrooms comparing…

A resource management architecture based on complex network theory in cloud computing federation

NASA Astrophysics Data System (ADS)

Zhang, Zehua; Zhang, Xuejie

2011-10-01

Cloud Computing Federation is a main trend of Cloud Computing. Resource Management has significant effect on the design, realization, and efficiency of Cloud Computing Federation. Cloud Computing Federation has the typical characteristic of the Complex System, therefore, we propose a resource management architecture based on complex network theory for Cloud Computing Federation (abbreviated as RMABC) in this paper, with the detailed design of the resource discovery and resource announcement mechanisms. Compare with the existing resource management mechanisms in distributed computing systems, a Task Manager in RMABC can use the historical information and current state data get from other Task Managers for the evolution of the complex network which is composed of Task Managers, thus has the advantages in resource discovery speed, fault tolerance and adaptive ability. The result of the model experiment confirmed the advantage of RMABC in resource discovery performance.

Atomic switch networks-nanoarchitectonic design of a complex system for natural computing.

PubMed

Demis, E C; Aguilera, R; Sillin, H O; Scharnhorst, K; Sandouk, E J; Aono, M; Stieg, A Z; Gimzewski, J K

2015-05-22

Self-organized complex systems are ubiquitous in nature, and the structural complexity of these natural systems can be used as a model to design new classes of functional nanotechnology based on highly interconnected networks of interacting units. Conventional fabrication methods for electronic computing devices are subject to known scaling limits, confining the diversity of possible architectures. This work explores methods of fabricating a self-organized complex device known as an atomic switch network and discusses its potential utility in computing. Through a merger of top-down and bottom-up techniques guided by mathematical and nanoarchitectonic design principles, we have produced functional devices comprising nanoscale elements whose intrinsic nonlinear dynamics and memorization capabilities produce robust patterns of distributed activity and a capacity for nonlinear transformation of input signals when configured in the appropriate network architecture. Their operational characteristics represent a unique potential for hardware implementation of natural computation, specifically in the area of reservoir computing-a burgeoning field that investigates the computational aptitude of complex biologically inspired systems.

CCOMP: An efficient algorithm for complex roots computation of determinantal equations

NASA Astrophysics Data System (ADS)

Zouros, Grigorios P.

2018-01-01

In this paper a free Python algorithm, entitled CCOMP (Complex roots COMPutation), is developed for the efficient computation of complex roots of determinantal equations inside a prescribed complex domain. The key to the method presented is the efficient determination of the candidate points inside the domain which, in their close neighborhood, a complex root may lie. Once these points are detected, the algorithm proceeds to a two-dimensional minimization problem with respect to the minimum modulus eigenvalue of the system matrix. In the core of CCOMP exist three sub-algorithms whose tasks are the efficient estimation of the minimum modulus eigenvalues of the system matrix inside the prescribed domain, the efficient computation of candidate points which guarantee the existence of minima, and finally, the computation of minima via bound constrained minimization algorithms. Theoretical results and heuristics support the development and the performance of the algorithm, which is discussed in detail. CCOMP supports general complex matrices, and its efficiency, applicability and validity is demonstrated to a variety of microwave applications.

Automated validation of a computer operating system

NASA Technical Reports Server (NTRS)

Dervage, M. M.; Milberg, B. A.

1970-01-01

Programs apply selected input/output loads to complex computer operating system and measure performance of that system under such loads. Technique lends itself to checkout of computer software designed to monitor automated complex industrial systems.

Technical Development and Application of Soft Computing in Agricultural and Biological Engineering

USDA-ARS?s Scientific Manuscript database

Soft computing is a set of “inexact” computing techniques, which are able to model and analyze very complex problems. For these complex problems, more conventional methods have not been able to produce cost-effective, analytical, or complete solutions. Soft computing has been extensively studied and...

Development of Soft Computing and Applications in Agricultural and Biological Engineering

USDA-ARS?s Scientific Manuscript database

Soft computing is a set of “inexact” computing techniques, which are able to model and analyze very complex problems. For these complex problems, more conventional methods have not been able to produce cost-effective, analytical, or complete solutions. Soft computing has been extensively studied and...

Robust Decision Making: The Cognitive and Computational Modeling of Team Problem Solving for Decision Making under Complex and Dynamic Conditions

DTIC Science & Technology

2015-07-14

AFRL-OSR-VA-TR-2015-0202 Robust Decision Making: The Cognitive and Computational Modeling of Team Problem Solving for Decision Making under Complex...Computational Modeling of Team Problem Solving for Decision Making Under Complex and Dynamic Conditions 5a. CONTRACT NUMBER 5b. GRANT NUMBER FA9550-12-1...functioning as they solve complex problems, and propose the means to improve the performance of teams, under changing or adversarial conditions. By

A Computer Story: Complexity from Simplicity

ERIC Educational Resources Information Center

DeLeo, Gary; Weidenhammer, Amanda; Wecht, Kristen

2012-01-01

In this technological age, digital devices are conspicuous examples of extraordinary complexity. When a user clicks on computer icons or presses calculator buttons, these devices channel electricity through a complex system of decision-making circuits. Yet, in spite of this remarkable complexity, the hearts of these devices are components that…

Complex Instruction Set Quantum Computing

NASA Astrophysics Data System (ADS)

Sanders, G. D.; Kim, K. W.; Holton, W. C.

1998-03-01

In proposed quantum computers, electromagnetic pulses are used to implement logic gates on quantum bits (qubits). Gates are unitary transformations applied to coherent qubit wavefunctions and a universal computer can be created using a minimal set of gates. By applying many elementary gates in sequence, desired quantum computations can be performed. This reduced instruction set approach to quantum computing (RISC QC) is characterized by serial application of a few basic pulse shapes and a long coherence time. However, the unitary matrix of the overall computation is ultimately a unitary matrix of the same size as any of the elementary matrices. This suggests that we might replace a sequence of reduced instructions with a single complex instruction using an optimally taylored pulse. We refer to this approach as complex instruction set quantum computing (CISC QC). One trades the requirement for long coherence times for the ability to design and generate potentially more complex pulses. We consider a model system of coupled qubits interacting through nearest neighbor coupling and show that CISC QC can reduce the time required to perform quantum computations.

VBOT: Motivating computational and complex systems fluencies with constructionist virtual/physical robotics

NASA Astrophysics Data System (ADS)

Berland, Matthew W.

As scientists use the tools of computational and complex systems theory to broaden science perspectives (e.g., Bar-Yam, 1997; Holland, 1995; Wolfram, 2002), so can middle-school students broaden their perspectives using appropriate tools. The goals of this dissertation project are to build, study, evaluate, and compare activities designed to foster both computational and complex systems fluencies through collaborative constructionist virtual and physical robotics. In these activities, each student builds an agent (e.g., a robot-bird) that must interact with fellow students' agents to generate a complex aggregate (e.g., a flock of robot-birds) in a participatory simulation environment (Wilensky & Stroup, 1999a). In a participatory simulation, students collaborate by acting in a common space, teaching each other, and discussing content with one another. As a result, the students improve both their computational fluency and their complex systems fluency, where fluency is defined as the ability to both consume and produce relevant content (DiSessa, 2000). To date, several systems have been designed to foster computational and complex systems fluencies through computer programming and collaborative play (e.g., Hancock, 2003; Wilensky & Stroup, 1999b); this study suggests that, by supporting the relevant fluencies through collaborative play, they become mutually reinforcing. In this work, I will present both the design of the VBOT virtual/physical constructionist robotics learning environment and a comparative study of student interaction with the virtual and physical environments across four middle-school classrooms, focusing on the contrast in systems perspectives differently afforded by the two environments. In particular, I found that while performance gains were similar overall, the physical environment supported agent perspectives on aggregate behavior, and the virtual environment supported aggregate perspectives on agent behavior. The primary research questions are: (1) What are the relative affordances of virtual and physical constructionist robotics systems towards computational and complex systems fluencies? (2) What can middle school students learn using computational/complex systems learning environments in a collaborative setting? (3) In what ways are these environments and activities effective in teaching students computational and complex systems fluencies?

Concept of a Cloud Service for Data Preparation and Computational Control on Custom HPC Systems in Application to Molecular Dynamics

NASA Astrophysics Data System (ADS)

Puzyrkov, Dmitry; Polyakov, Sergey; Podryga, Viktoriia; Markizov, Sergey

2018-02-01

At the present stage of computer technology development it is possible to study the properties and processes in complex systems at molecular and even atomic levels, for example, by means of molecular dynamics methods. The most interesting are problems related with the study of complex processes under real physical conditions. Solving such problems requires the use of high performance computing systems of various types, for example, GRID systems and HPC clusters. Considering the time consuming computational tasks, the need arises of software for automatic and unified monitoring of such computations. A complex computational task can be performed over different HPC systems. It requires output data synchronization between the storage chosen by a scientist and the HPC system used for computations. The design of the computational domain is also quite a problem. It requires complex software tools and algorithms for proper atomistic data generation on HPC systems. The paper describes the prototype of a cloud service, intended for design of atomistic systems of large volume for further detailed molecular dynamic calculations and computational management for this calculations, and presents the part of its concept aimed at initial data generation on the HPC systems.

On the interconnection of stable protein complexes: inter-complex hubs and their conservation in Saccharomyces cerevisiae and Homo sapiens networks.

PubMed

Guerra, Concettina

2015-01-01

Protein complexes are key molecular entities that perform a variety of essential cellular functions. The connectivity of proteins within a complex has been widely investigated with both experimental and computational techniques. We developed a computational approach to identify and characterise proteins that play a role in interconnecting complexes. We computed a measure of inter-complex centrality, the crossroad index, based on disjoint paths connecting proteins in distinct complexes and identified inter-complex hubs as proteins with a high value of the crossroad index. We applied the approach to a set of stable complexes in Saccharomyces cerevisiae and in Homo sapiens. Just as done for hubs, we evaluated the topological and biological properties of inter-complex hubs addressing the following questions. Do inter-complex hubs tend to be evolutionary conserved? What is the relation between crossroad index and essentiality? We found a good correlation between inter-complex hubs and both evolutionary conservation and essentiality.

Simulating complex intracellular processes using object-oriented computational modelling.

PubMed

Johnson, Colin G; Goldman, Jacki P; Gullick, William J

2004-11-01

The aim of this paper is to give an overview of computer modelling and simulation in cellular biology, in particular as applied to complex biochemical processes within the cell. This is illustrated by the use of the techniques of object-oriented modelling, where the computer is used to construct abstractions of objects in the domain being modelled, and these objects then interact within the computer to simulate the system and allow emergent properties to be observed. The paper also discusses the role of computer simulation in understanding complexity in biological systems, and the kinds of information which can be obtained about biology via simulation.

Systems and methods for rapid processing and storage of data

DOEpatents

Stalzer, Mark A.

2017-01-24

Systems and methods of building massively parallel computing systems using low power computing complexes in accordance with embodiments of the invention are disclosed. A massively parallel computing system in accordance with one embodiment of the invention includes at least one Solid State Blade configured to communicate via a high performance network fabric. In addition, each Solid State Blade includes a processor configured to communicate with a plurality of low power computing complexes interconnected by a router, and each low power computing complex includes at least one general processing core, an accelerator, an I/O interface, and cache memory and is configured to communicate with non-volatile solid state memory.

Atomic switch networks—nanoarchitectonic design of a complex system for natural computing

NASA Astrophysics Data System (ADS)

Demis, E. C.; Aguilera, R.; Sillin, H. O.; Scharnhorst, K.; Sandouk, E. J.; Aono, M.; Stieg, A. Z.; Gimzewski, J. K.

2015-05-01

Self-organized complex systems are ubiquitous in nature, and the structural complexity of these natural systems can be used as a model to design new classes of functional nanotechnology based on highly interconnected networks of interacting units. Conventional fabrication methods for electronic computing devices are subject to known scaling limits, confining the diversity of possible architectures. This work explores methods of fabricating a self-organized complex device known as an atomic switch network and discusses its potential utility in computing. Through a merger of top-down and bottom-up techniques guided by mathematical and nanoarchitectonic design principles, we have produced functional devices comprising nanoscale elements whose intrinsic nonlinear dynamics and memorization capabilities produce robust patterns of distributed activity and a capacity for nonlinear transformation of input signals when configured in the appropriate network architecture. Their operational characteristics represent a unique potential for hardware implementation of natural computation, specifically in the area of reservoir computing—a burgeoning field that investigates the computational aptitude of complex biologically inspired systems.

Pyrrole multimers and pyrrole-acetylene hydrogen bonded complexes studied in N2 and para-H2 matrixes using matrix isolation infrared spectroscopy and ab initio computations

NASA Astrophysics Data System (ADS)

Sarkar, Shubhra; Ramanathan, N.; Gopi, R.; Sundararajan, K.

2017-12-01

Hydrogen bonded interaction of pyrrole multimer and acetylene-pyrrole complexes were studied in N2 and p-H2 matrixes. DFT computations showed T-shaped geometry for the pyrrole dimer and cyclic complex for the trimer and tetramer were the most stable structures, stabilized by Nsbnd H⋯π interactions. The experimental vibrational wavenumbers observed in N2 and p-H2 matrixes for the pyrrole multimers were correlated with the computed wavenumbers. Computations performed at MP2/aug-cc-pVDZ level of theory showed that C2H2 and C4H5N forms 1:1 hydrogen-bonded complexes stabilized by Csbnd H⋯π interaction (Complex A), Nsbnd H⋯π interaction (Complex B) and π⋯π interaction (Complex C), where the former complex is the global minimum and latter two complexes were the first and second local minima, respectively. Experimentally, 1:1 C2H2sbnd C4H5N complexes A (global minimum) and B (first local minimum) were identified from the shifts in the Nsbnd H stretching, Nsbnd H bending, Csbnd H bending region of pyrrole and Csbnd H asymmetric stretching and bending region of C2H2 in N2 and p-H2 matrixes. Computations were also performed for the higher complexes and found two minima corresponding to the 1:2 C2H2sbnd C4H5N and three minima for the 2:1 C2H2sbnd C4H5N complexes. Experimentally the global minimum 1:2 and 2:1 C2H2sbnd C4H5N complexes were identified in N2 and p-H2 matrixes.

Closely Spaced Independent Parallel Runway Simulation.

DTIC Science & Technology

1984-10-01

facility consists of the Central Computer Facility, the Controller Laboratory, and the Simulator Pilot Complex. CENTRAL COMPUTER FACILITY. The Central... Computer Facility consists of a group of mainframes, minicomputers, and associated peripherals which host the operational and data acquisition...in the Controller Laboratory and convert their verbal directives into a keyboard entry which is transmitted to the Central Computer Complex, where

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.

On The Computational Capabilities of Physical Systems. Part 2; Relationship With Conventional Computer Science

NASA Technical Reports Server (NTRS)

Wolpert, David H.; Koga, Dennis (Technical Monitor)

2000-01-01

In the first of this pair of papers, it was proven that there cannot be a physical computer to which one can properly pose any and all computational tasks concerning the physical universe. It was then further proven that no physical computer C can correctly carry out all computational tasks that can be posed to C. As a particular example, this result means that no physical computer that can, for any physical system external to that computer, take the specification of that external system's state as input and then correctly predict its future state before that future state actually occurs; one cannot build a physical computer that can be assured of correctly "processing information faster than the universe does". These results do not rely on systems that are infinite, and/or non-classical, and/or obey chaotic dynamics. They also hold even if one uses an infinitely fast, infinitely dense computer, with computational powers greater than that of a Turing Machine. This generality is a direct consequence of the fact that a novel definition of computation - "physical computation" - is needed to address the issues considered in these papers, which concern real physical computers. While this novel definition does not fit into the traditional Chomsky hierarchy, the mathematical structure and impossibility results associated with it have parallels in the mathematics of the Chomsky hierarchy. This second paper of the pair presents a preliminary exploration of some of this mathematical structure. Analogues of Chomskian results concerning universal Turing Machines and the Halting theorem are derived, as are results concerning the (im)possibility of certain kinds of error-correcting codes. In addition, an analogue of algorithmic information complexity, "prediction complexity", is elaborated. A task-independent bound is derived on how much the prediction complexity of a computational task can differ for two different reference universal physical computers used to solve that task, a bound similar to the "encoding" bound governing how much the algorithm information complexity of a Turing machine calculation can differ for two reference universal Turing machines. Finally, it is proven that either the Hamiltonian of our universe proscribes a certain type of computation, or prediction complexity is unique (unlike algorithmic information complexity), in that there is one and only version of it that can be applicable throughout our universe.

A Simple Explanation of Complexation

ERIC Educational Resources Information Center

Elliott, J. Richard

2010-01-01

The topics of solution thermodynamics, activity coefficients, and complex formation are introduced through computational exercises and sample applications. The presentation is designed to be accessible to freshmen in a chemical engineering computations course. The MOSCED model is simplified to explain complex formation in terms of hydrogen…

Development of simulation computer complex specification

NASA Technical Reports Server (NTRS)

1973-01-01

The Training Simulation Computer Complex Study was one of three studies contracted in support of preparations for procurement of a shuttle mission simulator for shuttle crew training. The subject study was concerned with definition of the software loads to be imposed on the computer complex to be associated with the shuttle mission simulator and the development of procurement specifications based on the resulting computer requirements. These procurement specifications cover the computer hardware and system software as well as the data conversion equipment required to interface the computer to the simulator hardware. The development of the necessary hardware and software specifications required the execution of a number of related tasks which included, (1) simulation software sizing, (2) computer requirements definition, (3) data conversion equipment requirements definition, (4) system software requirements definition, (5) a simulation management plan, (6) a background survey, and (7) preparation of the specifications.

Accomplishment Summary 1968-1969. Biological Computer Laboratory.

ERIC Educational Resources Information Center

Von Foerster, Heinz; And Others

This report summarizes theoretical, applied, and experimental studies in the areas of computational principles in complex intelligent systems, cybernetics, multivalued logic, and the mechanization of cognitive processes. This work is summarized under the following topic headings: properties of complex dynamic systems; computers and the language…

Early experiences in developing and managing the neuroscience gateway.

PubMed

Sivagnanam, Subhashini; Majumdar, Amit; Yoshimoto, Kenneth; Astakhov, Vadim; Bandrowski, Anita; Martone, MaryAnn; Carnevale, Nicholas T

2015-02-01

The last few decades have seen the emergence of computational neuroscience as a mature field where researchers are interested in modeling complex and large neuronal systems and require access to high performance computing machines and associated cyber infrastructure to manage computational workflow and data. The neuronal simulation tools, used in this research field, are also implemented for parallel computers and suitable for high performance computing machines. But using these tools on complex high performance computing machines remains a challenge because of issues with acquiring computer time on these machines located at national supercomputer centers, dealing with complex user interface of these machines, dealing with data management and retrieval. The Neuroscience Gateway is being developed to alleviate and/or hide these barriers to entry for computational neuroscientists. It hides or eliminates, from the point of view of the users, all the administrative and technical barriers and makes parallel neuronal simulation tools easily available and accessible on complex high performance computing machines. It handles the running of jobs and data management and retrieval. This paper shares the early experiences in bringing up this gateway and describes the software architecture it is based on, how it is implemented, and how users can use this for computational neuroscience research using high performance computing at the back end. We also look at parallel scaling of some publicly available neuronal models and analyze the recent usage data of the neuroscience gateway.

Early experiences in developing and managing the neuroscience gateway

PubMed Central

Sivagnanam, Subhashini; Majumdar, Amit; Yoshimoto, Kenneth; Astakhov, Vadim; Bandrowski, Anita; Martone, MaryAnn; Carnevale, Nicholas. T.

2015-01-01

SUMMARY The last few decades have seen the emergence of computational neuroscience as a mature field where researchers are interested in modeling complex and large neuronal systems and require access to high performance computing machines and associated cyber infrastructure to manage computational workflow and data. The neuronal simulation tools, used in this research field, are also implemented for parallel computers and suitable for high performance computing machines. But using these tools on complex high performance computing machines remains a challenge because of issues with acquiring computer time on these machines located at national supercomputer centers, dealing with complex user interface of these machines, dealing with data management and retrieval. The Neuroscience Gateway is being developed to alleviate and/or hide these barriers to entry for computational neuroscientists. It hides or eliminates, from the point of view of the users, all the administrative and technical barriers and makes parallel neuronal simulation tools easily available and accessible on complex high performance computing machines. It handles the running of jobs and data management and retrieval. This paper shares the early experiences in bringing up this gateway and describes the software architecture it is based on, how it is implemented, and how users can use this for computational neuroscience research using high performance computing at the back end. We also look at parallel scaling of some publicly available neuronal models and analyze the recent usage data of the neuroscience gateway. PMID:26523124

Efficient 3D geometric and Zernike moments computation from unstructured surface meshes.

PubMed

Pozo, José María; Villa-Uriol, Maria-Cruz; Frangi, Alejandro F

2011-03-01

This paper introduces and evaluates a fast exact algorithm and a series of faster approximate algorithms for the computation of 3D geometric moments from an unstructured surface mesh of triangles. Being based on the object surface reduces the computational complexity of these algorithms with respect to volumetric grid-based algorithms. In contrast, it can only be applied for the computation of geometric moments of homogeneous objects. This advantage and restriction is shared with other proposed algorithms based on the object boundary. The proposed exact algorithm reduces the computational complexity for computing geometric moments up to order N with respect to previously proposed exact algorithms, from N(9) to N(6). The approximate series algorithm appears as a power series on the rate between triangle size and object size, which can be truncated at any desired degree. The higher the number and quality of the triangles, the better the approximation. This approximate algorithm reduces the computational complexity to N(3). In addition, the paper introduces a fast algorithm for the computation of 3D Zernike moments from the computed geometric moments, with a computational complexity N(4), while the previously proposed algorithm is of order N(6). The error introduced by the proposed approximate algorithms is evaluated in different shapes and the cost-benefit ratio in terms of error, and computational time is analyzed for different moment orders.

Latent Computational Complexity of Symmetry-Protected Topological Order with Fractional Symmetry.

PubMed

Miller, Jacob; Miyake, Akimasa

2018-04-27

An emerging insight is that ground states of symmetry-protected topological orders (SPTOs) possess latent computational complexity in terms of their many-body entanglement. By introducing a fractional symmetry of SPTO, which requires the invariance under 3-colorable symmetries of a lattice, we prove that every renormalization fixed-point state of 2D (Z_{2})^{m} SPTO with fractional symmetry can be utilized for universal quantum computation using only Pauli measurements, as long as it belongs to a nontrivial 2D SPTO phase. Our infinite family of fixed-point states may serve as a base model to demonstrate the idea of a "quantum computational phase" of matter, whose states share universal computational complexity ubiquitously.

Cognitive engineering models: A prerequisite to the design of human-computer interaction in complex dynamic systems

NASA Technical Reports Server (NTRS)

Mitchell, Christine M.

1993-01-01

This chapter examines a class of human-computer interaction applications, specifically the design of human-computer interaction for the operators of complex systems. Such systems include space systems (e.g., manned systems such as the Shuttle or space station, and unmanned systems such as NASA scientific satellites), aviation systems (e.g., the flight deck of 'glass cockpit' airplanes or air traffic control) and industrial systems (e.g., power plants, telephone networks, and sophisticated, e.g., 'lights out,' manufacturing facilities). The main body of human-computer interaction (HCI) research complements but does not directly address the primary issues involved in human-computer interaction design for operators of complex systems. Interfaces to complex systems are somewhat special. The 'user' in such systems - i.e., the human operator responsible for safe and effective system operation - is highly skilled, someone who in human-machine systems engineering is sometimes characterized as 'well trained, well motivated'. The 'job' or task context is paramount and, thus, human-computer interaction is subordinate to human job interaction. The design of human interaction with complex systems, i.e., the design of human job interaction, is sometimes called cognitive engineering.

Data flow modeling techniques

NASA Technical Reports Server (NTRS)

Kavi, K. M.

1984-01-01

There have been a number of simulation packages developed for the purpose of designing, testing and validating computer systems, digital systems and software systems. Complex analytical tools based on Markov and semi-Markov processes have been designed to estimate the reliability and performance of simulated systems. Petri nets have received wide acceptance for modeling complex and highly parallel computers. In this research data flow models for computer systems are investigated. Data flow models can be used to simulate both software and hardware in a uniform manner. Data flow simulation techniques provide the computer systems designer with a CAD environment which enables highly parallel complex systems to be defined, evaluated at all levels and finally implemented in either hardware or software. Inherent in data flow concept is the hierarchical handling of complex systems. In this paper we will describe how data flow can be used to model computer system.

Making classical ground-state spin computing fault-tolerant.

PubMed

Crosson, I J; Bacon, D; Brown, K R

2010-09-01

We examine a model of classical deterministic computing in which the ground state of the classical system is a spatial history of the computation. This model is relevant to quantum dot cellular automata as well as to recent universal adiabatic quantum computing constructions. In its most primitive form, systems constructed in this model cannot compute in an error-free manner when working at nonzero temperature. However, by exploiting a mapping between the partition function for this model and probabilistic classical circuits we are able to show that it is possible to make this model effectively error-free. We achieve this by using techniques in fault-tolerant classical computing and the result is that the system can compute effectively error-free if the temperature is below a critical temperature. We further link this model to computational complexity and show that a certain problem concerning finite temperature classical spin systems is complete for the complexity class Merlin-Arthur. This provides an interesting connection between the physical behavior of certain many-body spin systems and 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.

Identification and Addressing Reduction-Related Misconceptions

ERIC Educational Resources Information Center

Gal-Ezer, Judith; Trakhtenbrot, Mark

2016-01-01

Reduction is one of the key techniques used for problem-solving in computer science. In particular, in the theory of computation and complexity (TCC), mapping and polynomial reductions are used for analysis of decidability and computational complexity of problems, including the core concept of NP-completeness. Reduction is a highly abstract…

[Animal experimentation, computer simulation and surgical research].

PubMed

Carpentier, Alain

2009-11-01

We live in a digital world In medicine, computers are providing new tools for data collection, imaging, and treatment. During research and development of complex technologies and devices such as artificial hearts, computer simulation can provide more reliable information than experimentation on large animals. In these specific settings, animal experimentation should serve more to validate computer models of complex devices than to demonstrate their reliability.

Software Accelerates Computing Time for Complex Math

NASA Technical Reports Server (NTRS)

2014-01-01

Ames Research Center awarded Newark, Delaware-based EM Photonics Inc. SBIR funding to utilize graphic processing unit (GPU) technology- traditionally used for computer video games-to develop high-computing software called CULA. The software gives users the ability to run complex algorithms on personal computers with greater speed. As a result of the NASA collaboration, the number of employees at the company has increased 10 percent.

User's guide for a computer program for calculating the zero-lift wave drag of complex aircraft configurations

NASA Technical Reports Server (NTRS)

Craidon, C. B.

1983-01-01

A computer program was developed to extend the geometry input capabilities of previous versions of a supersonic zero lift wave drag computer program. The arbitrary geometry input description is flexible enough to describe almost any complex aircraft concept, so that highly accurate wave drag analysis can now be performed because complex geometries can be represented accurately and do not have to be modified to meet the requirements of a restricted input format.

DCL System Using Deep Learning Approaches for Land-Based or Ship-Based Real Time Recognition and Localization of Marine Mammals

DTIC Science & Technology

2015-09-30

Clark (2014), "Using High Performance Computing to Explore Large Complex Bioacoustic Soundscapes : Case Study for Right Whale Acoustics," Procedia...34Using High Performance Computing to Explore Large Complex Bioacoustic Soundscapes : Case Study for Right Whale Acoustics," Procedia Computer Science 20

Modeling the Internet of Things, Self-Organizing and Other Complex Adaptive Communication Networks: A Cognitive Agent-Based Computing Approach.

PubMed

Laghari, Samreen; Niazi, Muaz A

2016-01-01

Computer Networks have a tendency to grow at an unprecedented scale. Modern networks involve not only computers but also a wide variety of other interconnected devices ranging from mobile phones to other household items fitted with sensors. This vision of the "Internet of Things" (IoT) implies an inherent difficulty in modeling problems. It is practically impossible to implement and test all scenarios for large-scale and complex adaptive communication networks as part of Complex Adaptive Communication Networks and Environments (CACOONS). The goal of this study is to explore the use of Agent-based Modeling as part of the Cognitive Agent-based Computing (CABC) framework to model a Complex communication network problem. We use Exploratory Agent-based Modeling (EABM), as part of the CABC framework, to develop an autonomous multi-agent architecture for managing carbon footprint in a corporate network. To evaluate the application of complexity in practical scenarios, we have also introduced a company-defined computer usage policy. The conducted experiments demonstrated two important results: Primarily CABC-based modeling approach such as using Agent-based Modeling can be an effective approach to modeling complex problems in the domain of IoT. Secondly, the specific problem of managing the Carbon footprint can be solved using a multiagent system approach.

Optimizing Cognitive Load for Learning from Computer-Based Science Simulations

ERIC Educational Resources Information Center

Lee, Hyunjeong; Plass, Jan L.; Homer, Bruce D.

2006-01-01

How can cognitive load in visual displays of computer simulations be optimized? Middle-school chemistry students (N = 257) learned with a simulation of the ideal gas law. Visual complexity was manipulated by separating the display of the simulations in two screens (low complexity) or presenting all information on one screen (high complexity). The…

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

Marr's levels and the minimalist program.

PubMed

Johnson, Mark

2017-02-01

A simple change to a cognitive system at Marr's computational level may entail complex changes at the other levels of description of the system. The implementational level complexity of a change, rather than its computational level complexity, may be more closely related to the plausibility of a discrete evolutionary event causing that change. Thus the formal complexity of a change at the computational level may not be a good guide to the plausibility of an evolutionary event introducing that change. For example, while the Minimalist Program's Merge is a simple formal operation (Berwick & Chomsky, 2016), the computational mechanisms required to implement the language it generates (e.g., to parse the language) may be considerably more complex. This has implications for the theory of grammar: theories of grammar which involve several kinds of syntactic operations may be no less evolutionarily plausible than a theory of grammar that involves only one. A deeper understanding of human language at the algorithmic and implementational levels could strengthen Minimalist Program's account of the evolution of language.

Practical Measurement of Complexity In Dynamic Systems

DTIC Science & Technology

2012-01-01

policies that produce highly complex behaviors , yet yield no benefit. 21Jason B. Clark and David R. Jacques / Procedia Computer Science 8 (2012) 14... Procedia Computer Science 8 (2012) 14 – 21 1877-0509 © 2012 Published by Elsevier B.V. doi:10.1016/j.procs.2012.01.008 Available online at...www.sciencedirect.com Procedia Computer Science Procedia Computer Science 00 (2012) 000–000 www.elsevier.com/locate/ procedia Available online at

USSR and Eastern Europe Scientific Abstracts, Cybernetics, Computers, and Automation Technology, Number 26

DTIC Science & Technology

1977-01-26

Sisteme Matematicheskogo Obespecheniya YeS EVM [ Applied Programs in the Software System for the Unified System of Computers], by A. Ye. Fateyev, A. I...computerized systems are most effective in large production complexes , in which the level of utilization of computers can be as high as 500,000...performance of these tasks could be furthered by the complex introduction of electronic computers in automated control systems. The creation of ASU

Synthetic mixed-signal computation in living cells

PubMed Central

Rubens, Jacob R.; Selvaggio, Gianluca; Lu, Timothy K.

2016-01-01

Living cells implement complex computations on the continuous environmental signals that they encounter. These computations involve both analogue- and digital-like processing of signals to give rise to complex developmental programs, context-dependent behaviours and homeostatic activities. In contrast to natural biological systems, synthetic biological systems have largely focused on either digital or analogue computation separately. Here we integrate analogue and digital computation to implement complex hybrid synthetic genetic programs in living cells. We present a framework for building comparator gene circuits to digitize analogue inputs based on different thresholds. We then demonstrate that comparators can be predictably composed together to build band-pass filters, ternary logic systems and multi-level analogue-to-digital converters. In addition, we interface these analogue-to-digital circuits with other digital gene circuits to enable concentration-dependent logic. We expect that this hybrid computational paradigm will enable new industrial, diagnostic and therapeutic applications with engineered cells. PMID:27255669

Computational Complexity and Human Decision-Making.

PubMed

Bossaerts, Peter; Murawski, Carsten

2017-12-01

The rationality principle postulates that decision-makers always choose the best action available to them. It underlies most modern theories of decision-making. The principle does not take into account the difficulty of finding the best option. Here, we propose that computational complexity theory (CCT) provides a framework for defining and quantifying the difficulty of decisions. We review evidence showing that human decision-making is affected by computational complexity. Building on this evidence, we argue that most models of decision-making, and metacognition, are intractable from a computational perspective. To be plausible, future theories of decision-making will need to take into account both the resources required for implementing the computations implied by the theory, and the resource constraints imposed on the decision-maker by biology. Copyright © 2017 Elsevier Ltd. All rights reserved.

From, by, and for the OSSD: Software Engineering Education Using an Open Source Software Approach

ERIC Educational Resources Information Center

Huang, Kun; Dong, Yifei; Ge, Xun

2006-01-01

Computing is a complex, multidisciplinary field that requires a range of professional proficiencies. Computing students are expected to develop in-depth knowledge and skills, integrate and apply their knowledge flexibly to solve complex problems, and work successfully in teams. However, many students who graduate with degrees in computing fail to…

Robot, computer problem solving system

NASA Technical Reports Server (NTRS)

Becker, J. D.; Merriam, E. W.

1973-01-01

The TENEX computer system, the ARPA network, and computer language design technology was applied to support the complex system programs. By combining the pragmatic and theoretical aspects of robot development, an approach is created which is grounded in realism, but which also has at its disposal the power that comes from looking at complex problems from an abstract analytical point of view.

Assessment of students' ability to incorporate a computer into increasingly complex simulated patient encounters.

PubMed

Ray, Sarah; Valdovinos, Katie

Pharmacy students should be exposed to and offered opportunities to practice the skill of incorporating a computer into a patient interview in the didactic setting. Faculty sought to improve retention of student ability to incorporate computers into their patient-pharmacist communication. Students were required to utilize a computer to document clinical information gathered during a simulated patient encounter (SPE). Students utilized electronic worksheets and were evaluated by instructors on their ability to effectively incorporate a computer into a SPE using a rubric. Students received specific instruction on effective computer use during patient encounters. Students were then re-evaluated by an instructor during subsequent SPEs of increasing complexity using standardized rubrics blinded from the students. Pre-instruction, 45% of students effectively incorporated a computer into a SPE. After receiving instruction, 67% of students were effective in their use of a computer during a SPE of performing a pharmaceutical care assessment for a patient with chronic obstructive pulmonary disease (COPD) (p < 0.05 compared to pre-instruction), and 58% of students were effective in their use of a computer during a SPE of retrieving a medication list and social history from a simulated alcohol-impaired patient (p = 0.087 compared to pre-instruction). Instruction can improve pharmacy students' ability to incorporate a computer into SPEs, a critical skill in building and maintaining rapport with patients and improving efficiency of patient visits. Complex encounters may affect students' ability to utilize a computer appropriately. Students may benefit from repeated practice with this skill, especially with SPEs of increasing complexity. Copyright © 2016 Elsevier Inc. All rights reserved.

Biclustering Protein Complex Interactions with a Biclique FindingAlgorithm

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

Ding, Chris; Zhang, Anne Ya; Holbrook, Stephen

2006-12-01

Biclustering has many applications in text mining, web clickstream mining, and bioinformatics. When data entries are binary, the tightest biclusters become bicliques. We propose a flexible and highly efficient algorithm to compute bicliques. We first generalize the Motzkin-Straus formalism for computing the maximal clique from L{sub 1} constraint to L{sub p} constraint, which enables us to provide a generalized Motzkin-Straus formalism for computing maximal-edge bicliques. By adjusting parameters, the algorithm can favor biclusters with more rows less columns, or vice verse, thus increasing the flexibility of the targeted biclusters. We then propose an algorithm to solve the generalized Motzkin-Straus optimizationmore » problem. The algorithm is provably convergent and has a computational complexity of O(|E|) where |E| is the number of edges. It relies on a matrix vector multiplication and runs efficiently on most current computer architectures. Using this algorithm, we bicluster the yeast protein complex interaction network. We find that biclustering protein complexes at the protein level does not clearly reflect the functional linkage among protein complexes in many cases, while biclustering at protein domain level can reveal many underlying linkages. We show several new biologically significant results.« less

Quantum Gauss-Jordan Elimination and Simulation of Accounting Principles on Quantum Computers

NASA Astrophysics Data System (ADS)

Diep, Do Ngoc; Giang, Do Hoang; Van Minh, Nguyen

2017-06-01

The paper is devoted to a version of Quantum Gauss-Jordan Elimination and its applications. In the first part, we construct the Quantum Gauss-Jordan Elimination (QGJE) Algorithm and estimate the complexity of computation of Reduced Row Echelon Form (RREF) of N × N matrices. The main result asserts that QGJE has computation time is of order 2 N/2. The second part is devoted to a new idea of simulation of accounting by quantum computing. We first expose the actual accounting principles in a pure mathematics language. Then, we simulate the accounting principles on quantum computers. We show that, all accounting actions are exhousted by the described basic actions. The main problems of accounting are reduced to some system of linear equations in the economic model of Leontief. In this simulation, we use our constructed Quantum Gauss-Jordan Elimination to solve the problems and the complexity of quantum computing is a square root order faster than the complexity in classical computing.

Direct Comparison of a Tablet Computer and a Personal Digital Assistant for Point-of-Care Documentation in Eye Care

PubMed Central

Silvey, Garry M.; Macri, Jennifer M.; Lee, Paul P.; Lobach, David F.

2005-01-01

New mobile computing devices including personal digital assistants (PDAs) and tablet computers have emerged to facilitate data collection at the point of care. Unfortunately, little research has been reported regarding which device is optimal for a given care setting. In this study we created and compared functionally identical applications on a Palm operating system-based PDA and a Windows-based tablet computer for point-of-care documentation of clinical observations by eye care professionals when caring for patients with diabetes. Eye-care professionals compared the devices through focus group sessions and through validated usability surveys. We found that the application on the tablet computer was preferred over the PDA for documenting the complex data related to eye care. Our findings suggest that the selection of a mobile computing platform depends on the amount and complexity of the data to be entered; the tablet computer functions better for high volume, complex data entry, and the PDA, for low volume, simple data entry. PMID:16779128

Some Observations on the Current Status of Performing Finite Element Analyses

NASA Technical Reports Server (NTRS)

Raju, Ivatury S.; Knight, Norman F., Jr; Shivakumar, Kunigal N.

2015-01-01

Aerospace structures are complex high-performance structures. Advances in reliable and efficient computing and modeling tools are enabling analysts to consider complex configurations, build complex finite element models, and perform analysis rapidly. Many of the early career engineers of today are very proficient in the usage of modern computers, computing engines, complex software systems, and visualization tools. These young engineers are becoming increasingly efficient in building complex 3D models of complicated aerospace components. However, the current trends demonstrate blind acceptance of the results of the finite element analysis results. This paper is aimed at raising an awareness of this situation. Examples of the common encounters are presented. To overcome the current trends, some guidelines and suggestions for analysts, senior engineers, and educators are offered.

A fast complex integer convolution using a hybrid transform

NASA Technical Reports Server (NTRS)

Reed, I. S.; K Truong, T.

1978-01-01

It is shown that the Winograd transform can be combined with a complex integer transform over the Galois field GF(q-squared) to yield a new algorithm for computing the discrete cyclic convolution of complex number points. By this means a fast method for accurately computing the cyclic convolution of a sequence of complex numbers for long convolution lengths can be obtained. This new hybrid algorithm requires fewer multiplications than previous algorithms.

Increasing complexity with quantum physics.

PubMed

Anders, Janet; Wiesner, Karoline

2011-09-01

We argue that complex systems science and the rules of quantum physics are intricately related. We discuss a range of quantum phenomena, such as cryptography, computation and quantum phases, and the rules responsible for their complexity. We identify correlations as a central concept connecting quantum information and complex systems science. We present two examples for the power of correlations: using quantum resources to simulate the correlations of a stochastic process and to implement a classically impossible computational task.

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.

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.

Lower bound on the time complexity of local adiabatic evolution

NASA Astrophysics Data System (ADS)

Chen, Zhenghao; Koh, Pang Wei; Zhao, Yan

2006-11-01

The adiabatic theorem of quantum physics has been, in recent times, utilized in the design of local search quantum algorithms, and has been proven to be equivalent to standard quantum computation, that is, the use of unitary operators [D. Aharonov in Proceedings of the 45th Annual Symposium on the Foundations of Computer Science, 2004, Rome, Italy (IEEE Computer Society Press, New York, 2004), pp. 42-51]. Hence, the study of the time complexity of adiabatic evolution algorithms gives insight into the computational power of quantum algorithms. In this paper, we present two different approaches of evaluating the time complexity for local adiabatic evolution using time-independent parameters, thus providing effective tests (not requiring the evaluation of the entire time-dependent gap function) for the time complexity of newly developed algorithms. We further illustrate our tests by displaying results from the numerical simulation of some problems, viz. specially modified instances of the Hamming weight problem.

Statistical Techniques Complement UML When Developing Domain Models of Complex Dynamical Biosystems.

PubMed

Williams, Richard A; Timmis, Jon; Qwarnstrom, Eva E

2016-01-01

Computational modelling and simulation is increasingly being used to complement traditional wet-lab techniques when investigating the mechanistic behaviours of complex biological systems. In order to ensure computational models are fit for purpose, it is essential that the abstracted view of biology captured in the computational model, is clearly and unambiguously defined within a conceptual model of the biological domain (a domain model), that acts to accurately represent the biological system and to document the functional requirements for the resultant computational model. We present a domain model of the IL-1 stimulated NF-κB signalling pathway, which unambiguously defines the spatial, temporal and stochastic requirements for our future computational model. Through the development of this model, we observe that, in isolation, UML is not sufficient for the purpose of creating a domain model, and that a number of descriptive and multivariate statistical techniques provide complementary perspectives, in particular when modelling the heterogeneity of dynamics at the single-cell level. We believe this approach of using UML to define the structure and interactions within a complex system, along with statistics to define the stochastic and dynamic nature of complex systems, is crucial for ensuring that conceptual models of complex dynamical biosystems, which are developed using UML, are fit for purpose, and unambiguously define the functional requirements for the resultant computational model.

Statistical Techniques Complement UML When Developing Domain Models of Complex Dynamical Biosystems

PubMed Central

Timmis, Jon; Qwarnstrom, Eva E.

2016-01-01

Computational modelling and simulation is increasingly being used to complement traditional wet-lab techniques when investigating the mechanistic behaviours of complex biological systems. In order to ensure computational models are fit for purpose, it is essential that the abstracted view of biology captured in the computational model, is clearly and unambiguously defined within a conceptual model of the biological domain (a domain model), that acts to accurately represent the biological system and to document the functional requirements for the resultant computational model. We present a domain model of the IL-1 stimulated NF-κB signalling pathway, which unambiguously defines the spatial, temporal and stochastic requirements for our future computational model. Through the development of this model, we observe that, in isolation, UML is not sufficient for the purpose of creating a domain model, and that a number of descriptive and multivariate statistical techniques provide complementary perspectives, in particular when modelling the heterogeneity of dynamics at the single-cell level. We believe this approach of using UML to define the structure and interactions within a complex system, along with statistics to define the stochastic and dynamic nature of complex systems, is crucial for ensuring that conceptual models of complex dynamical biosystems, which are developed using UML, are fit for purpose, and unambiguously define the functional requirements for the resultant computational model. PMID:27571414

A general method for computing the total solar radiation force on complex spacecraft structures

NASA Technical Reports Server (NTRS)

Chan, F. K.

1981-01-01

The method circumvents many of the existing difficulties in computational logic presently encountered in the direct analytical or numerical evaluation of the appropriate surface integral. It may be applied to complex spacecraft structures for computing the total force arising from either specular or diffuse reflection or even from non-Lambertian reflection and re-radiation.

Fast generation of computer-generated holograms using wavelet shrinkage.

PubMed

Shimobaba, Tomoyoshi; Ito, Tomoyoshi

2017-01-09

Computer-generated holograms (CGHs) are generated by superimposing complex amplitudes emitted from a number of object points. However, this superposition process remains very time-consuming even when using the latest computers. We propose a fast calculation algorithm for CGHs that uses a wavelet shrinkage method, eliminating small wavelet coefficient values to express approximated complex amplitudes using only a few representative wavelet coefficients.

Combinatorial computational chemistry approach for materials design: applications in deNOx catalysis, Fischer-Tropsch synthesis, lanthanoid complex, and lithium ion secondary battery.

PubMed

Koyama, Michihisa; Tsuboi, Hideyuki; Endou, Akira; Takaba, Hiromitsu; Kubo, Momoji; Del Carpio, Carlos A; Miyamoto, Akira

2007-02-01

Computational chemistry can provide fundamental knowledge regarding various aspects of materials. While its impact in scientific research is greatly increasing, its contributions to industrially important issues are far from satisfactory. In order to realize industrial innovation by computational chemistry, a new concept "combinatorial computational chemistry" has been proposed by introducing the concept of combinatorial chemistry to computational chemistry. This combinatorial computational chemistry approach enables theoretical high-throughput screening for materials design. In this manuscript, we review the successful applications of combinatorial computational chemistry to deNO(x) catalysts, Fischer-Tropsch catalysts, lanthanoid complex catalysts, and cathodes of the lithium ion secondary battery.

Modeling the Internet of Things, Self-Organizing and Other Complex Adaptive Communication Networks: A Cognitive Agent-Based Computing Approach

PubMed Central

2016-01-01

Background Computer Networks have a tendency to grow at an unprecedented scale. Modern networks involve not only computers but also a wide variety of other interconnected devices ranging from mobile phones to other household items fitted with sensors. This vision of the "Internet of Things" (IoT) implies an inherent difficulty in modeling problems. Purpose It is practically impossible to implement and test all scenarios for large-scale and complex adaptive communication networks as part of Complex Adaptive Communication Networks and Environments (CACOONS). The goal of this study is to explore the use of Agent-based Modeling as part of the Cognitive Agent-based Computing (CABC) framework to model a Complex communication network problem. Method We use Exploratory Agent-based Modeling (EABM), as part of the CABC framework, to develop an autonomous multi-agent architecture for managing carbon footprint in a corporate network. To evaluate the application of complexity in practical scenarios, we have also introduced a company-defined computer usage policy. Results The conducted experiments demonstrated two important results: Primarily CABC-based modeling approach such as using Agent-based Modeling can be an effective approach to modeling complex problems in the domain of IoT. Secondly, the specific problem of managing the Carbon footprint can be solved using a multiagent system approach. PMID:26812235

The Study of Learners' Preference for Visual Complexity on Small Screens of Mobile Computers Using Neural Networks

ERIC Educational Resources Information Center

Wang, Lan-Ting; Lee, Kun-Chou

2014-01-01

The vision plays an important role in educational technologies because it can produce and communicate quite important functions in teaching and learning. In this paper, learners' preference for the visual complexity on small screens of mobile computers is studied by neural networks. The visual complexity in this study is divided into five…

JPRS Report, Science & Technology, USSR: Computers, Control Systems and Machines

DTIC Science & Technology

1989-03-14

optimizatsii slozhnykh sistem (Coding Theory and Complex System Optimization ). Alma-Ata, Nauka Press, 1977, pp. 8-16. 11. Author’s certificate number...Interpreter Specifics [0. I. Amvrosova] ............................................. 141 Creation of Modern Computer Systems for Complex Ecological...processor can be designed to decrease degradation upon failure and assure more reliable processor operation, without requiring more complex software or

Extension of the TDCR model to compute counting efficiencies for radionuclides with complex decay schemes.

PubMed

Kossert, K; Cassette, Ph; Carles, A Grau; Jörg, G; Gostomski, Christroph Lierse V; Nähle, O; Wolf, Ch

2014-05-01

The triple-to-double coincidence ratio (TDCR) method is frequently used to measure the activity of radionuclides decaying by pure β emission or electron capture (EC). Some radionuclides with more complex decays have also been studied, but accurate calculations of decay branches which are accompanied by many coincident γ transitions have not yet been investigated. This paper describes recent extensions of the model to make efficiency computations for more complex decay schemes possible. In particular, the MICELLE2 program that applies a stochastic approach of the free parameter model was extended. With an improved code, efficiencies for β(-), β(+) and EC branches with up to seven coincident γ transitions can be calculated. Moreover, a new parametrization for the computation of electron stopping powers has been implemented to compute the ionization quenching function of 10 commercial scintillation cocktails. In order to demonstrate the capabilities of the TDCR method, the following radionuclides are discussed: (166m)Ho (complex β(-)/γ), (59)Fe (complex β(-)/γ), (64)Cu (β(-), β(+), EC and EC/γ) and (229)Th in equilibrium with its progenies (decay chain with many α, β and complex β(-)/γ transitions). © 2013 Published by Elsevier Ltd.

Development of numerical methods for overset grids with applications for the integrated Space Shuttle vehicle

NASA Technical Reports Server (NTRS)

Chan, William M.

1995-01-01

Algorithms and computer code developments were performed for the overset grid approach to solving computational fluid dynamics problems. The techniques developed are applicable to compressible Navier-Stokes flow for any general complex configurations. The computer codes developed were tested on different complex configurations with the Space Shuttle launch vehicle configuration as the primary test bed. General, efficient and user-friendly codes were produced for grid generation, flow solution and force and moment computation.

Exponential rise of dynamical complexity in quantum computing through projections.

PubMed

Burgarth, Daniel Klaus; Facchi, Paolo; Giovannetti, Vittorio; Nakazato, Hiromichi; Pascazio, Saverio; Yuasa, Kazuya

2014-10-10

The ability of quantum systems to host exponentially complex dynamics has the potential to revolutionize science and technology. Therefore, much effort has been devoted to developing of protocols for computation, communication and metrology, which exploit this scaling, despite formidable technical difficulties. Here we show that the mere frequent observation of a small part of a quantum system can turn its dynamics from a very simple one into an exponentially complex one, capable of universal quantum computation. After discussing examples, we go on to show that this effect is generally to be expected: almost any quantum dynamics becomes universal once 'observed' as outlined above. Conversely, we show that any complex quantum dynamics can be 'purified' into a simpler one in larger dimensions. We conclude by demonstrating that even local noise can lead to an exponentially complex dynamics.

Insight and analysis problem solving in microbes to machines.

PubMed

Clark, Kevin B

2015-11-01

A key feature for obtaining solutions to difficult problems, insight is oftentimes vaguely regarded as a special discontinuous intellectual process and/or a cognitive restructuring of problem representation or goal approach. However, this nearly century-old state of art devised by the Gestalt tradition to explain the non-analytical or non-trial-and-error, goal-seeking aptitude of primate mentality tends to neglect problem-solving capabilities of lower animal phyla, Kingdoms other than Animalia, and advancing smart computational technologies built from biological, artificial, and composite media. Attempting to provide an inclusive, precise definition of insight, two major criteria of insight, discontinuous processing and problem restructuring, are here reframed using terminology and statistical mechanical properties of computational complexity classes. Discontinuous processing becomes abrupt state transitions in algorithmic/heuristic outcomes or in types of algorithms/heuristics executed by agents using classical and/or quantum computational models. And problem restructuring becomes combinatorial reorganization of resources, problem-type substitution, and/or exchange of computational models. With insight bounded by computational complexity, humans, ciliated protozoa, and complex technological networks, for example, show insight when restructuring time requirements, combinatorial complexity, and problem type to solve polynomial and nondeterministic polynomial decision problems. Similar effects are expected from other problem types, supporting the idea that insight might be an epiphenomenon of analytical problem solving and consequently a larger information processing framework. Thus, this computational complexity definition of insight improves the power, external and internal validity, and reliability of operational parameters with which to classify, investigate, and produce the phenomenon for computational agents ranging from microbes to man-made devices. Copyright © 2015 Elsevier Ltd. All rights reserved.

Applications of Computer Technology in Complex Craniofacial Reconstruction.

PubMed

Day, Kristopher M; Gabrick, Kyle S; Sargent, Larry A

2018-03-01

To demonstrate our use of advanced 3-dimensional (3D) computer technology in the analysis, virtual surgical planning (VSP), 3D modeling (3DM), and treatment of complex congenital and acquired craniofacial deformities. We present a series of craniofacial defects treated at a tertiary craniofacial referral center utilizing state-of-the-art 3D computer technology. All patients treated at our center using computer-assisted VSP, prefabricated custom-designed 3DMs, and/or 3D printed custom implants (3DPCI) in the reconstruction of craniofacial defects were included in this analysis. We describe the use of 3D computer technology to precisely analyze, plan, and reconstruct 31 craniofacial deformities/syndromes caused by: Pierre-Robin (7), Treacher Collins (5), Apert's (2), Pfeiffer (2), Crouzon (1) Syndromes, craniosynostosis (6), hemifacial microsomia (2), micrognathia (2), multiple facial clefts (1), and trauma (3). In select cases where the available bone was insufficient for skeletal reconstruction, 3DPCIs were fabricated using 3D printing. We used VSP in 30, 3DMs in all 31, distraction osteogenesis in 16, and 3DPCIs in 13 cases. Utilizing these technologies, the above complex craniofacial defects were corrected without significant complications and with excellent aesthetic results. Modern 3D technology allows the surgeon to better analyze complex craniofacial deformities, precisely plan surgical correction with computer simulation of results, customize osteotomies, plan distractions, and print 3DPCI, as needed. The use of advanced 3D computer technology can be applied safely and potentially improve aesthetic and functional outcomes after complex craniofacial reconstruction. These techniques warrant further study and may be reproducible in various centers of care.

Parametric Study of a YAV-8B Harrier in Ground Effect Using Time-Dependent Navier-Stokes Computations

NASA Technical Reports Server (NTRS)

Shishir, Pandya; Chaderjian, Neal; Ahmad, Jsaim; Kwak, Dochan (Technical Monitor)

2001-01-01

Flow simulations using the time-dependent Navier-Stokes equations remain a challenge for several reasons. Principal among them are the difficulty to accurately model complex flows, and the time needed to perform the computations. A parametric study of such complex problems is not considered practical due to the large cost associated with computing many time-dependent solutions. The computation time for each solution must be reduced in order to make a parametric study possible. With successful reduction of computation time, the issue of accuracy, and appropriateness of turbulence models will become more tractable.

Low-complexity R-peak detection in ECG signals: a preliminary step towards ambulatory fetal monitoring.

PubMed

Rooijakkers, Michiel; Rabotti, Chiara; Bennebroek, Martijn; van Meerbergen, Jef; Mischi, Massimo

2011-01-01

Non-invasive fetal health monitoring during pregnancy has become increasingly important. Recent advances in signal processing technology have enabled fetal monitoring during pregnancy, using abdominal ECG recordings. Ubiquitous ambulatory monitoring for continuous fetal health measurement is however still unfeasible due to the computational complexity of noise robust solutions. In this paper an ECG R-peak detection algorithm for ambulatory R-peak detection is proposed, as part of a fetal ECG detection algorithm. The proposed algorithm is optimized to reduce computational complexity, while increasing the R-peak detection quality compared to existing R-peak detection schemes. Validation of the algorithm is performed on two manually annotated datasets, the MIT/BIH Arrhythmia database and an in-house abdominal database. Both R-peak detection quality and computational complexity are compared to state-of-the-art algorithms as described in the literature. With a detection error rate of 0.22% and 0.12% on the MIT/BIH Arrhythmia and in-house databases, respectively, the quality of the proposed algorithm is comparable to the best state-of-the-art algorithms, at a reduced computational complexity.

[Soft- and hardware support for the setup for computer tracking of radiation teletherapy].

PubMed

Tarutin, I G; Piliavets, V I; Strakh, A G; Minenko, V F; Golubovskiĭ, A I

1983-06-01

A hard and soft ware computer assisted complex has been worked out for gamma-beam therapy. The complex included all radiotherapeutic units, including a Siemens program controlled betatron with an energy of 42 MEV computer ES-1022, a Medigraf system of the processing of graphic information, a Mars-256 system for control over the homogeneity of distribution of dose rate on the field of irradiation and a package of mathematical programs to select a plan of irradiation of various tumor sites. The prospects of the utilization of such complexes in the dosimetric support of radiation therapy are discussed.

Quantitative ROESY analysis of computational models: structural studies of citalopram and β-cyclodextrin complexes by (1) H-NMR and computational methods.

PubMed

Ali, Syed Mashhood; Shamim, Shazia

2015-07-01

Complexation of racemic citalopram with β-cyclodextrin (β-CD) in aqueous medium was investigated to determine atom-accurate structure of the inclusion complexes. (1) H-NMR chemical shift change data of β-CD cavity protons in the presence of citalopram confirmed the formation of 1 : 1 inclusion complexes. ROESY spectrum confirmed the presence of aromatic ring in the β-CD cavity but whether one of the two or both rings was not clear. Molecular mechanics and molecular dynamic calculations showed the entry of fluoro-ring from wider side of β-CD cavity as the most favored mode of inclusion. Minimum energy computational models were analyzed for their accuracy in atomic coordinates by comparison of calculated and experimental intermolecular ROESY peak intensities, which were not found in agreement. Several least energy computational models were refined and analyzed till calculated and experimental intensities were compatible. The results demonstrate that computational models of CD complexes need to be analyzed for atom-accuracy and quantitative ROESY analysis is a promising method. Moreover, the study also validates that the quantitative use of ROESY is feasible even with longer mixing times if peak intensity ratios instead of absolute intensities are used. Copyright © 2015 John Wiley & Sons, Ltd.

Computational complexities and storage requirements of some Riccati equation solvers

NASA Technical Reports Server (NTRS)

Utku, Senol; Garba, John A.; Ramesh, A. V.

1989-01-01

The linear optimal control problem of an nth-order time-invariant dynamic system with a quadratic performance functional is usually solved by the Hamilton-Jacobi approach. This leads to the solution of the differential matrix Riccati equation with a terminal condition. The bulk of the computation for the optimal control problem is related to the solution of this equation. There are various algorithms in the literature for solving the matrix Riccati equation. However, computational complexities and storage requirements as a function of numbers of state variables, control variables, and sensors are not available for all these algorithms. In this work, the computational complexities and storage requirements for some of these algorithms are given. These expressions show the immensity of the computational requirements of the algorithms in solving the Riccati equation for large-order systems such as the control of highly flexible space structures. The expressions are also needed to compute the speedup and efficiency of any implementation of these algorithms on concurrent machines.

Complexity control algorithm based on adaptive mode selection for interframe coding in high efficiency video coding

NASA Astrophysics Data System (ADS)

Chen, Gang; Yang, Bing; Zhang, Xiaoyun; Gao, Zhiyong

2017-07-01

The latest high efficiency video coding (HEVC) standard significantly increases the encoding complexity for improving its coding efficiency. Due to the limited computational capability of handheld devices, complexity constrained video coding has drawn great attention in recent years. A complexity control algorithm based on adaptive mode selection is proposed for interframe coding in HEVC. Considering the direct proportionality between encoding time and computational complexity, the computational complexity is measured in terms of encoding time. First, complexity is mapped to a target in terms of prediction modes. Then, an adaptive mode selection algorithm is proposed for the mode decision process. Specifically, the optimal mode combination scheme that is chosen through offline statistics is developed at low complexity. If the complexity budget has not been used up, an adaptive mode sorting method is employed to further improve coding efficiency. The experimental results show that the proposed algorithm achieves a very large complexity control range (as low as 10%) for the HEVC encoder while maintaining good rate-distortion performance. For the lowdelayP condition, compared with the direct resource allocation method and the state-of-the-art method, an average gain of 0.63 and 0.17 dB in BDPSNR is observed for 18 sequences when the target complexity is around 40%.

Ordinal optimization and its application to complex deterministic problems

NASA Astrophysics Data System (ADS)

Yang, Mike Shang-Yu

1998-10-01

We present in this thesis a new perspective to approach a general class of optimization problems characterized by large deterministic complexities. Many problems of real-world concerns today lack analyzable structures and almost always involve high level of difficulties and complexities in the evaluation process. Advances in computer technology allow us to build computer models to simulate the evaluation process through numerical means, but the burden of high complexities remains to tax the simulation with an exorbitant computing cost for each evaluation. Such a resource requirement makes local fine-tuning of a known design difficult under most circumstances, let alone global optimization. Kolmogorov equivalence of complexity and randomness in computation theory is introduced to resolve this difficulty by converting the complex deterministic model to a stochastic pseudo-model composed of a simple deterministic component and a white-noise like stochastic term. The resulting randomness is then dealt with by a noise-robust approach called Ordinal Optimization. Ordinal Optimization utilizes Goal Softening and Ordinal Comparison to achieve an efficient and quantifiable selection of designs in the initial search process. The approach is substantiated by a case study in the turbine blade manufacturing process. The problem involves the optimization of the manufacturing process of the integrally bladed rotor in the turbine engines of U.S. Air Force fighter jets. The intertwining interactions among the material, thermomechanical, and geometrical changes makes the current FEM approach prohibitively uneconomical in the optimization process. The generalized OO approach to complex deterministic problems is applied here with great success. Empirical results indicate a saving of nearly 95% in the computing cost.

Computation of the Complex Probability Function

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

Trainer, Amelia Jo; Ledwith, Patrick John

The complex probability function is important in many areas of physics and many techniques have been developed in an attempt to compute it for some z quickly and e ciently. Most prominent are the methods that use Gauss-Hermite quadrature, which uses the roots of the n th degree Hermite polynomial and corresponding weights to approximate the complex probability function. This document serves as an overview and discussion of the use, shortcomings, and potential improvements on the Gauss-Hermite quadrature for the complex probability function.

The Complexity Analysis Tool

DTIC Science & Technology

1988-10-01

overview of the complexity analysis tool ( CAT ), an automated tool which will analyze mission critical computer resources (MCCR) software. CAT is based...84 MAR UNCLASSIFIED SECURITY CLASSIFICATION OF THIS PAGE 19. ABSTRACT: (cont) CAT automates the metric for BASIC (HP-71), ATLAS (EQUATE), Ada (subset...UNIX 5.2). CAT analyzes source code and computes complexity on a module basis. CAT also generates graphic representations of the logic flow paths and

Statistical Field Estimation for Complex Coastal Regions and Archipelagos (PREPRINT)

DTIC Science & Technology

2011-04-09

and study the computational properties of these schemes. Specifically, we extend a multiscale Objective Analysis (OA) approach to complex coastal...computational properties of these schemes. Specifically, we extend a multiscale Objective Analysis (OA) approach to complex coastal regions and... multiscale free-surface code builds on the primitive-equation model of the Harvard Ocean Predic- tion System (HOPS, Haley et al. (2009)). Additionally

COED Transactions, Vol. IX, No. 3, March 1977. Evaluation of a Complex Variable Using Analog/Hybrid Computation Techniques.

ERIC Educational Resources Information Center

Marcovitz, Alan B., Ed.

Described is the use of an analog/hybrid computer installation to study those physical phenomena that can be described through the evaluation of an algebraic function of a complex variable. This is an alternative way to study such phenomena on an interactive graphics terminal. The typical problem used, involving complex variables, is that of…

Complexity, action, and black holes

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

Brown, Adam R.; Roberts, Daniel A.; Susskind, Leonard

In an earlier paper "Complexity Equals Action" we conjectured that the quantum computational complexity of a holographic state is given by the classical action of a region in the bulk (the `Wheeler-DeWitt' patch). We provide calculations for the results quoted in that paper, explain how it fits into a broader (tensor) network of ideas, and elaborate on the hypothesis that black holes are the fastest computers in nature.

Complexity, action, and black holes

DOE PAGES

Brown, Adam R.; Roberts, Daniel A.; Susskind, Leonard; ...

2016-04-18

In an earlier paper "Complexity Equals Action" we conjectured that the quantum computational complexity of a holographic state is given by the classical action of a region in the bulk (the `Wheeler-DeWitt' patch). We provide calculations for the results quoted in that paper, explain how it fits into a broader (tensor) network of ideas, and elaborate on the hypothesis that black holes are the fastest computers in nature.

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

PubMed

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

2016-12-13

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

Acetonitrile-water hydrogen-bonded interaction: Matrix-isolation infrared and ab initio computation

NASA Astrophysics Data System (ADS)

Gopi, R.; Ramanathan, N.; Sundararajan, K.

2015-08-01

The 1:1 hydrogen-bonded complex of acetonitrile (CH3CN) and water (H2O) was trapped in Ar and N2 matrices and studied using infrared technique. Ab initio computations showed two types of complexes formed between CH3CN and H2O, a linear complex A with a Ctbnd N⋯H interaction between nitrogen of CH3CN and hydrogen of H2O and a cyclic complex B, in which the interactions are between the hydrogen of CH3CN with oxygen of H2O and hydrogen of H2O with π cloud of sbnd Ctbnd N of CH3CN. Vibrational wavenumber calculations revealed that both the complexes A and B were minima on the potential energy surface. Interaction energies computed at B3LYP/6-311++G(d,p) showed that linear complex A is more stable than cyclic complex B. Computations identified a blue shift of ∼11.5 cm-1 and a red shift of ∼6.5 cm-1 in the CN stretching mode for the complexes A and B, respectively. Experimentally, we observed a blue shift of ∼15.0 and ∼8.3 cm-1 in N2 and Ar matrices, respectively, in the CN stretching mode of CH3CN, which supports the formation of complex A. The Onsager Self Consistent Reaction Field (SCRF) model was used to explain the influence of matrices on the complexes A and B. To understand the nature of the interactions, Atoms in Molecules (AIM) and Natural Bond Orbital (NBO) analyses were carried out for the complexes A and B.

Computer Analysis of Air Pollution from Highways, Streets, and Complex Interchanges

DOT National Transportation Integrated Search

1974-03-01

A detailed computer analysis of air quality for a complex highway interchange was prepared, using an in-house version of the Environmental Protection Agency's Gaussian Highway Line Source Model. This analysis showed that the levels of air pollution n...

Synthetic Analog and Digital Circuits for Cellular Computation and Memory

PubMed Central

Purcell, Oliver; Lu, Timothy K.

2014-01-01

Biological computation is a major area of focus in synthetic biology because it has the potential to enable a wide range of applications. Synthetic biologists have applied engineering concepts to biological systems in order to construct progressively more complex gene circuits capable of processing information in living cells. Here, we review the current state of computational genetic circuits and describe artificial gene circuits that perform digital and analog computation. We then discuss recent progress in designing gene circuits that exhibit memory, and how memory and computation have been integrated to yield more complex systems that can both process and record information. Finally, we suggest new directions for engineering biological circuits capable of computation. PMID:24794536

Overview of Sensitivity Analysis and Shape Optimization for Complex Aerodynamic Configurations

NASA Technical Reports Server (NTRS)

Newman, Perry A.; Newman, James C., III; Barnwell, Richard W.; Taylor, Arthur C., III; Hou, Gene J.-W.

1998-01-01

This paper presents a brief overview of some of the more recent advances in steady aerodynamic shape-design sensitivity analysis and optimization, based on advanced computational fluid dynamics. The focus here is on those methods particularly well- suited to the study of geometrically complex configurations and their potentially complex associated flow physics. When nonlinear state equations are considered in the optimization process, difficulties are found in the application of sensitivity analysis. Some techniques for circumventing such difficulties are currently being explored and are included here. Attention is directed to methods that utilize automatic differentiation to obtain aerodynamic sensitivity derivatives for both complex configurations and complex flow physics. Various examples of shape-design sensitivity analysis for unstructured-grid computational fluid dynamics algorithms are demonstrated for different formulations of the sensitivity equations. Finally, the use of advanced, unstructured-grid computational fluid dynamics in multidisciplinary analyses and multidisciplinary sensitivity analyses within future optimization processes is recommended and encouraged.

Accurate complex scaling of three dimensional numerical potentials

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

Cerioni, Alessandro; Genovese, Luigi; Duchemin, Ivan

2013-05-28

The complex scaling method, which consists in continuing spatial coordinates into the complex plane, is a well-established method that allows to compute resonant eigenfunctions of the time-independent Schroedinger operator. Whenever it is desirable to apply the complex scaling to investigate resonances in physical systems defined on numerical discrete grids, the most direct approach relies on the application of a similarity transformation to the original, unscaled Hamiltonian. We show that such an approach can be conveniently implemented in the Daubechies wavelet basis set, featuring a very promising level of generality, high accuracy, and no need for artificial convergence parameters. Complex scalingmore » of three dimensional numerical potentials can be efficiently and accurately performed. By carrying out an illustrative resonant state computation in the case of a one-dimensional model potential, we then show that our wavelet-based approach may disclose new exciting opportunities in the field of computational non-Hermitian quantum mechanics.« less

Computer-Assisted Monitoring Of A Complex System

NASA Technical Reports Server (NTRS)

Beil, Bob J.; Mickelson, Eric M.; Sterritt, John M.; Costantino, Rob W.; Houvener, Bob C.; Super, Mike A.

1995-01-01

Propulsion System Advisor (PSA) computer-based system assists engineers and technicians in analyzing masses of sensory data indicative of operating conditions of space shuttle propulsion system during pre-launch and launch activities. Designed solely for monitoring; does not perform any control functions. Although PSA developed for highly specialized application, serves as prototype of noncontrolling, computer-based subsystems for monitoring other complex systems like electric-power-distribution networks and factories.

A synthetic computational environment: To control the spread of respiratory infections in a virtual university

NASA Astrophysics Data System (ADS)

Ge, Yuanzheng; Chen, Bin; liu, Liang; Qiu, Xiaogang; Song, Hongbin; Wang, Yong

2018-02-01

Individual-based computational environment provides an effective solution to study complex social events by reconstructing scenarios. Challenges remain in reconstructing the virtual scenarios and reproducing the complex evolution. In this paper, we propose a framework to reconstruct a synthetic computational environment, reproduce the epidemic outbreak, and evaluate management interventions in a virtual university. The reconstructed computational environment includes 4 fundamental components: the synthetic population, behavior algorithms, multiple social networks, and geographic campus environment. In the virtual university, influenza H1N1 transmission experiments are conducted, and gradually enhanced interventions are evaluated and compared quantitatively. The experiment results indicate that the reconstructed virtual environment provides a solution to reproduce complex emergencies and evaluate policies to be executed in the real world.

Vibronic Coupling Investigation to Compute Phosphorescence Spectra of Pt(II) Complexes.

PubMed

Vazart, Fanny; Latouche, Camille; Bloino, Julien; Barone, Vincenzo

2015-06-01

The present paper reports a comprehensive quantum mechanical investigation on the luminescence properties of several mono- and dinuclear platinum(II) complexes. The electronic structures and geometric parameters are briefly analyzed together with the absorption bands of all complexes. In all cases agreement with experiment is remarkable. Next, emission (phosphorescence) spectra from the first triplet states have been investigated by comparing different computational approaches and taking into account also vibronic effects. Once again, agreement with experiment is good, especially using unrestricted electronic computations coupled to vibronic contributions. Together with the intrinsic interest of the results, the robustness and generality of the approach open the opportunity for computationally oriented chemists to provide accurate results for the screening of large targets which could be of interest in molecular materials design.

Advances in computer simulation of genome evolution: toward more realistic evolutionary genomics analysis by approximate bayesian computation.

PubMed

Arenas, Miguel

2015-04-01

NGS technologies present a fast and cheap generation of genomic data. Nevertheless, ancestral genome inference is not so straightforward due to complex evolutionary processes acting on this material such as inversions, translocations, and other genome rearrangements that, in addition to their implicit complexity, can co-occur and confound ancestral inferences. Recently, models of genome evolution that accommodate such complex genomic events are emerging. This letter explores these novel evolutionary models and proposes their incorporation into robust statistical approaches based on computer simulations, such as approximate Bayesian computation, that may produce a more realistic evolutionary analysis of genomic data. Advantages and pitfalls in using these analytical methods are discussed. Potential applications of these ancestral genomic inferences are also pointed out.

Charge transfer complex between 2,3-diaminopyridine with chloranilic acid. Synthesis, characterization and DFT, TD-DFT computational studies

NASA Astrophysics Data System (ADS)

Al-Ahmary, Khairia M.; Habeeb, Moustafa M.; Al-Obidan, Areej H.

2018-05-01

New charge transfer complex (CTC) between the electron donor 2,3-diaminopyridine (DAP) with the electron acceptor chloranilic (CLA) acid has been synthesized and characterized experimentally and theoretically using a variety of physicochemical techniques. The experimental work included the use of elemental analysis, UV-vis, IR and 1H NMR studies to characterize the complex. Electronic spectra have been carried out in different hydrogen bonded solvents, methanol (MeOH), acetonitrile (AN) and 1:1 mixture from AN-MeOH. The molecular composition of the complex was identified to be 1:1 from Jobs and molar ratio methods. The stability constant was determined using minimum-maximum absorbances method where it recorded high values confirming the high stability of the formed complex. The solid complex was prepared and characterized by elemental analysis that confirmed its formation in 1:1 stoichiometric ratio. Both IR and NMR studies asserted the existence of proton and charge transfers in the formed complex. For supporting the experimental results, DFT computations were carried out using B3LYP/6-31G(d,p) method to compute the optimized structures of the reactants and complex, their geometrical parameters, reactivity parameters, molecular electrostatic potential map and frontier molecular orbitals. The analysis of DFT results strongly confirmed the high stability of the formed complex based on existing charge transfer beside proton transfer hydrogen bonding concordant with experimental results. The origin of electronic spectra was analyzed using TD-DFT method where the observed λmax are strongly consisted with the computed ones. TD-DFT showed the contributed states for various electronic transitions.

Algorithmic complexity of quantum capacity

NASA Astrophysics Data System (ADS)

Oskouei, Samad Khabbazi; Mancini, Stefano

2018-04-01

We analyze the notion of quantum capacity from the perspective of algorithmic (descriptive) complexity. To this end, we resort to the concept of semi-computability in order to describe quantum states and quantum channel maps. We introduce algorithmic entropies (like algorithmic quantum coherent information) and derive relevant properties for them. Then we show that quantum capacity based on semi-computable concept equals the entropy rate of algorithmic coherent information, which in turn equals the standard quantum capacity. Thanks to this, we finally prove that the quantum capacity, for a given semi-computable channel, is limit computable.

Computer modeling and simulation of human movement. Applications in sport and rehabilitation.

PubMed

Neptune, R R

2000-05-01

Computer modeling and simulation of human movement plays an increasingly important role in sport and rehabilitation, with applications ranging from sport equipment design to understanding pathologic gait. The complex dynamic interactions within the musculoskeletal and neuromuscular systems make analyzing human movement with existing experimental techniques difficult but computer modeling and simulation allows for the identification of these complex interactions and causal relationships between input and output variables. This article provides an overview of computer modeling and simulation and presents an example application in the field of rehabilitation.

Computing quantum hashing in the model of quantum branching programs

NASA Astrophysics Data System (ADS)

Ablayev, Farid; Ablayev, Marat; Vasiliev, Alexander

2018-02-01

We investigate the branching program complexity of quantum hashing. We consider a quantum hash function that maps elements of a finite field into quantum states. We require that this function is preimage-resistant and collision-resistant. We consider two complexity measures for Quantum Branching Programs (QBP): a number of qubits and a number of compu-tational steps. We show that the quantum hash function can be computed efficiently. Moreover, we prove that such QBP construction is optimal. That is, we prove lower bounds that match the constructed quantum hash function computation.

Costs and benefits of integrating information between the cerebral hemispheres: a computational perspective.

PubMed

Belger, A; Banich, M T

1998-07-01

Because interaction of the cerebral hemispheres has been found to aid task performance under demanding conditions, the present study examined how this effect is moderated by computational complexity, the degree of lateralization for a task, and individual differences in asymmetric hemispheric activation (AHA). Computational complexity was manipulated across tasks either by increasing the number of inputs to be processed or by increasing the number of steps to a decision. Comparison of within- and across-hemisphere trials indicated that the size of the between-hemisphere advantage increased as a function of task complexity, except for a highly lateralized rhyme decision task that can only be performed by the left hemisphere. Measures of individual differences in AHA revealed that when task demands and an individual's AHA both load on the same hemisphere, the ability to divide the processing between the hemispheres is limited. Thus, interhemispheric division of processing improves performance at higher levels of computational complexity only when the required operations can be divided between the hemispheres.

Fast H.264/AVC FRExt intra coding using belief propagation.

PubMed

Milani, Simone

2011-01-01

In the H.264/AVC FRExt coder, the coding performance of Intra coding significantly overcomes the previous still image coding standards, like JPEG2000, thanks to a massive use of spatial prediction. Unfortunately, the adoption of an extensive set of predictors induces a significant increase of the computational complexity required by the rate-distortion optimization routine. The paper presents a complexity reduction strategy that aims at reducing the computational load of the Intra coding with a small loss in the compression performance. The proposed algorithm relies on selecting a reduced set of prediction modes according to their probabilities, which are estimated adopting a belief-propagation procedure. Experimental results show that the proposed method permits saving up to 60 % of the coding time required by an exhaustive rate-distortion optimization method with a negligible loss in performance. Moreover, it permits an accurate control of the computational complexity unlike other methods where the computational complexity depends upon the coded sequence.

Direct migration motion estimation and mode decision to decoder for a low-complexity decoder Wyner-Ziv video coding

NASA Astrophysics Data System (ADS)

Lei, Ted Chih-Wei; Tseng, Fan-Shuo

2017-07-01

This paper addresses the problem of high-computational complexity decoding in traditional Wyner-Ziv video coding (WZVC). The key focus is the migration of two traditionally high-computationally complex encoder algorithms, namely motion estimation and mode decision. In order to reduce the computational burden in this process, the proposed architecture adopts the partial boundary matching algorithm and four flexible types of block mode decision at the decoder. This approach does away with the need for motion estimation and mode decision at the encoder. The experimental results show that the proposed padding block-based WZVC not only decreases decoder complexity to approximately one hundredth that of the state-of-the-art DISCOVER decoding but also outperforms DISCOVER codec by up to 3 to 4 dB.

Hierarchical coordinate systems for understanding complexity and its evolution, with applications to genetic regulatory networks.

PubMed

Egri-Nagy, Attila; Nehaniv, Chrystopher L

2008-01-01

Beyond complexity measures, sometimes it is worthwhile in addition to investigate how complexity changes structurally, especially in artificial systems where we have complete knowledge about the evolutionary process. Hierarchical decomposition is a useful way of assessing structural complexity changes of organisms modeled as automata, and we show how recently developed computational tools can be used for this purpose, by computing holonomy decompositions and holonomy complexity. To gain insight into the evolution of complexity, we investigate the smoothness of the landscape structure of complexity under minimal transitions. As a proof of concept, we illustrate how the hierarchical complexity analysis reveals symmetries and irreversible structure in biological networks by applying the methods to the lac operon mechanism in the genetic regulatory network of Escherichia coli.

A low-power and high-quality implementation of the discrete cosine transformation

NASA Astrophysics Data System (ADS)

Heyne, B.; Götze, J.

2007-06-01

In this paper a computationally efficient and high-quality preserving DCT architecture is presented. It is obtained by optimizing the Loeffler DCT based on the Cordic algorithm. The computational complexity is reduced from 11 multiply and 29 add operations (Loeffler DCT) to 38 add and 16 shift operations (which is similar to the complexity of the binDCT). The experimental results show that the proposed DCT algorithm not only reduces the computational complexity significantly, but also retains the good transformation quality of the Loeffler DCT. Therefore, the proposed Cordic based Loeffler DCT is especially suited for low-power and high-quality CODECs in battery-based systems.

BeeSim: Leveraging Wearable Computers in Participatory Simulations with Young Children

ERIC Educational Resources Information Center

Peppler, Kylie; Danish, Joshua; Zaitlen, Benjamin; Glosson, Diane; Jacobs, Alexander; Phelps, David

2010-01-01

New technologies have enabled students to become active participants in computational simulations of dynamic and complex systems (called Participatory Simulations), providing a "first-person"perspective on complex systems. However, most existing Participatory Simulations have targeted older children, teens, and adults assuming that such concepts…

Interhemispheric Resource Sharing: Decreasing Benefits with Increasing Processing Efficiency

ERIC Educational Resources Information Center

Maertens, M.; Pollmann, S.

2005-01-01

Visual matches are sometimes faster when stimuli are presented across visual hemifields, compared to within-field matching. Using a cued geometric figure matching task, we investigated the influence of computational complexity vs. processing efficiency on this bilateral distribution advantage (BDA). Computational complexity was manipulated by…

Efficient computation of the joint sample frequency spectra for multiple populations.

PubMed

Kamm, John A; Terhorst, Jonathan; Song, Yun S

2017-01-01

A wide range of studies in population genetics have employed the sample frequency spectrum (SFS), a summary statistic which describes the distribution of mutant alleles at a polymorphic site in a sample of DNA sequences and provides a highly efficient dimensional reduction of large-scale population genomic variation data. Recently, there has been much interest in analyzing the joint SFS data from multiple populations to infer parameters of complex demographic histories, including variable population sizes, population split times, migration rates, admixture proportions, and so on. SFS-based inference methods require accurate computation of the expected SFS under a given demographic model. Although much methodological progress has been made, existing methods suffer from numerical instability and high computational complexity when multiple populations are involved and the sample size is large. In this paper, we present new analytic formulas and algorithms that enable accurate, efficient computation of the expected joint SFS for thousands of individuals sampled from hundreds of populations related by a complex demographic model with arbitrary population size histories (including piecewise-exponential growth). Our results are implemented in a new software package called momi (MOran Models for Inference). Through an empirical study we demonstrate our improvements to numerical stability and computational complexity.

Efficient computation of the joint sample frequency spectra for multiple populations

PubMed Central

Kamm, John A.; Terhorst, Jonathan; Song, Yun S.

2016-01-01

A wide range of studies in population genetics have employed the sample frequency spectrum (SFS), a summary statistic which describes the distribution of mutant alleles at a polymorphic site in a sample of DNA sequences and provides a highly efficient dimensional reduction of large-scale population genomic variation data. Recently, there has been much interest in analyzing the joint SFS data from multiple populations to infer parameters of complex demographic histories, including variable population sizes, population split times, migration rates, admixture proportions, and so on. SFS-based inference methods require accurate computation of the expected SFS under a given demographic model. Although much methodological progress has been made, existing methods suffer from numerical instability and high computational complexity when multiple populations are involved and the sample size is large. In this paper, we present new analytic formulas and algorithms that enable accurate, efficient computation of the expected joint SFS for thousands of individuals sampled from hundreds of populations related by a complex demographic model with arbitrary population size histories (including piecewise-exponential growth). Our results are implemented in a new software package called momi (MOran Models for Inference). Through an empirical study we demonstrate our improvements to numerical stability and computational complexity. PMID:28239248

A mechanistic study and computational prediction of iron, cobalt and manganese cyclopentadienone complexes for hydrogenation of carbon dioxide.

PubMed

Ge, Hongyu; Chen, Xiangyang; Yang, Xinzheng

2016-10-13

A series of cobalt and manganese cyclopentadienone complexes are proposed and examined computationally as promising catalysts for hydrogenation of CO 2 to formic acid with total free energies as low as 20.0 kcal mol -1 in aqueous solution. Density functional theory study of the newly designed cobalt and manganese complexes and experimentally reported iron cyclopentadienone complexes reveals a stepwise hydride transfer mechanism with a water or a methanol molecule assisted proton transfer for the cleavage of H 2 as the rate-determining step.

Encapsulating model complexity and landscape-scale analyses of state-and-transition simulation models: an application of ecoinformatics and juniper encroachment in sagebrush steppe ecosystems

USGS Publications Warehouse

O'Donnell, Michael

2015-01-01

State-and-transition simulation modeling relies on knowledge of vegetation composition and structure (states) that describe community conditions, mechanistic feedbacks such as fire that can affect vegetation establishment, and ecological processes that drive community conditions as well as the transitions between these states. However, as the need for modeling larger and more complex landscapes increase, a more advanced awareness of computing resources becomes essential. The objectives of this study include identifying challenges of executing state-and-transition simulation models, identifying common bottlenecks of computing resources, developing a workflow and software that enable parallel processing of Monte Carlo simulations, and identifying the advantages and disadvantages of different computing resources. To address these objectives, this study used the ApexRMS® SyncroSim software and embarrassingly parallel tasks of Monte Carlo simulations on a single multicore computer and on distributed computing systems. The results demonstrated that state-and-transition simulation models scale best in distributed computing environments, such as high-throughput and high-performance computing, because these environments disseminate the workloads across many compute nodes, thereby supporting analysis of larger landscapes, higher spatial resolution vegetation products, and more complex models. Using a case study and five different computing environments, the top result (high-throughput computing versus serial computations) indicated an approximate 96.6% decrease of computing time. With a single, multicore compute node (bottom result), the computing time indicated an 81.8% decrease relative to using serial computations. These results provide insight into the tradeoffs of using different computing resources when research necessitates advanced integration of ecoinformatics incorporating large and complicated data inputs and models. - See more at: http://aimspress.com/aimses/ch/reader/view_abstract.aspx?file_no=Environ2015030&flag=1#sthash.p1XKDtF8.dpuf

Computational complexity of ecological and evolutionary spatial dynamics

PubMed Central

Ibsen-Jensen, Rasmus; Chatterjee, Krishnendu; Nowak, Martin A.

2015-01-01

There are deep, yet largely unexplored, connections between computer science and biology. Both disciplines examine how information proliferates in time and space. Central results in computer science describe the complexity of algorithms that solve certain classes of problems. An algorithm is deemed efficient if it can solve a problem in polynomial time, which means the running time of the algorithm is a polynomial function of the length of the input. There are classes of harder problems for which the fastest possible algorithm requires exponential time. Another criterion is the space requirement of the algorithm. There is a crucial distinction between algorithms that can find a solution, verify a solution, or list several distinct solutions in given time and space. The complexity hierarchy that is generated in this way is the foundation of theoretical computer science. Precise complexity results can be notoriously difficult. The famous question whether polynomial time equals nondeterministic polynomial time (i.e., P = NP) is one of the hardest open problems in computer science and all of mathematics. Here, we consider simple processes of ecological and evolutionary spatial dynamics. The basic question is: What is the probability that a new invader (or a new mutant) will take over a resident population? We derive precise complexity results for a variety of scenarios. We therefore show that some fundamental questions in this area cannot be answered by simple equations (assuming that P is not equal to NP). PMID:26644569

Complex facial deformity reconstruction with a surgical guide incorporating a built-in occlusal stent as the positioning reference.

PubMed

Fang, Jing-Jing; Liu, Jia-Kuang; Wu, Tzu-Chieh; Lee, Jing-Wei; Kuo, Tai-Hong

2013-05-01

Computer-aided design has gained increasing popularity in clinical practice, and the advent of rapid prototyping technology has further enhanced the quality and predictability of surgical outcomes. It provides target guides for complex bony reconstruction during surgery. Therefore, surgeons can efficiently and precisely target fracture restorations. Based on three-dimensional models generated from a computed tomographic scan, precise preoperative planning simulation on a computer is possible. Combining the interdisciplinary knowledge of surgeons and engineers, this study proposes a novel surgical guidance method that incorporates a built-in occlusal wafer that serves as the positioning reference.Two patients with complex facial deformity suffering from severe facial asymmetry problems were recruited. In vitro facial reconstruction was first rehearsed on physical models, where a customized surgical guide incorporating a built-in occlusal stent as the positioning reference was designed to implement the surgery plan. This study is intended to present the authors' preliminary experience in a complex facial reconstruction procedure. It suggests that in regions with less information, where intraoperative computed tomographic scans or navigation systems are not available, our approach could be an effective, expedient, straightforward aid to enhance surgical outcome in a complex facial repair.

Synthetic analog and digital circuits for cellular computation and memory.

PubMed

Purcell, Oliver; Lu, Timothy K

2014-10-01

Biological computation is a major area of focus in synthetic biology because it has the potential to enable a wide range of applications. Synthetic biologists have applied engineering concepts to biological systems in order to construct progressively more complex gene circuits capable of processing information in living cells. Here, we review the current state of computational genetic circuits and describe artificial gene circuits that perform digital and analog computation. We then discuss recent progress in designing gene networks that exhibit memory, and how memory and computation have been integrated to yield more complex systems that can both process and record information. Finally, we suggest new directions for engineering biological circuits capable of computation. Copyright © 2014 The Authors. Published by Elsevier Ltd.. All rights reserved.

A study of complex scaling transformation using the Wigner representation of wavefunctions.

PubMed

Kaprálová-Ždánská, Petra Ruth

2011-05-28

The complex scaling operator exp(-θ ̂x̂p/ℏ), being a foundation of the complex scaling method for resonances, is studied in the Wigner phase-space representation. It is shown that the complex scaling operator behaves similarly to the squeezing operator, rotating and amplifying Wigner quasi-probability distributions of the respective wavefunctions. It is disclosed that the distorting effect of the complex scaling transformation is correlated with increased numerical errors of computed resonance energies and widths. The behavior of the numerical error is demonstrated for a computation of CO(2+) vibronic resonances. © 2011 American Institute of Physics

Hot spot computational identification: Application to the complex formed between the hen egg white lysozyme (HEL) and the antibody HyHEL-10

NASA Astrophysics Data System (ADS)

Moreira, I. S.; Fernandes, P. A.; Ramos, M. J.

The definition and comprehension of the hot spots in an interface is a subject of primary interest for a variety of fields, including structure-based drug design. Therefore, to achieve an alanine mutagenesis computational approach that is at the same time accurate and predictive, capable of reproducing the experimental mutagenesis values is a major challenge in the computational biochemistry field. Antibody/protein antigen complexes provide one of the greatest models to study protein-protein recognition process because they have three fundamentally features: specificity, high complementary association and a small epitope restricted to the diminutive complementary determining regions (CDR) region, while the remainder of the antibody is largely invariant. Thus, we apply a computational mutational methodological approach to the study of the antigen-antibody complex formed between the hen egg white lysozyme (HEL) and the antibody HyHEL-10. A critical evaluation that focuses essentially on the limitations and advantages between different computational methods for hot spot determination, as well as between experimental and computational methodological approaches, is presented.

Parallel algorithms for mapping pipelined and parallel computations

NASA Technical Reports Server (NTRS)

Nicol, David M.

1988-01-01

Many computational problems in image processing, signal processing, and scientific computing are naturally structured for either pipelined or parallel computation. When mapping such problems onto a parallel architecture it is often necessary to aggregate an obvious problem decomposition. Even in this context the general mapping problem is known to be computationally intractable, but recent advances have been made in identifying classes of problems and architectures for which optimal solutions can be found in polynomial time. Among these, the mapping of pipelined or parallel computations onto linear array, shared memory, and host-satellite systems figures prominently. This paper extends that work first by showing how to improve existing serial mapping algorithms. These improvements have significantly lower time and space complexities: in one case a published O(nm sup 3) time algorithm for mapping m modules onto n processors is reduced to an O(nm log m) time complexity, and its space requirements reduced from O(nm sup 2) to O(m). Run time complexity is further reduced with parallel mapping algorithms based on these improvements, which run on the architecture for which they create the mappings.

Modeling Cognitive Strategies during Complex Task Performing Process

ERIC Educational Resources Information Center

Mazman, Sacide Guzin; Altun, Arif

2012-01-01

The purpose of this study is to examine individuals' computer based complex task performing processes and strategies in order to determine the reasons of failure by cognitive task analysis method and cued retrospective think aloud with eye movement data. Study group was five senior students from Computer Education and Instructional Technologies…

Capturing, Codifying and Scoring Complex Data for Innovative, Computer-Based Items.

ERIC Educational Resources Information Center

Luecht, Richard M.

The Microsoft Certification Program (MCP) includes many new computer-based item types, based on complex cases involving the Windows 2000 (registered) operating system. This Innovative Item Technology (IIT) has presented challenges beyond traditional psychometric considerations such as capturing and storing the relevant response data from…

A Program of Continuing Research on Representing, Manipulating, and Reasoning about Physical Objects

DTIC Science & Technology

1991-09-30

graphics with the goal of automatically converting complex graphics models into forms more appropriate for radiosity computation. 2.4 Least Constraint We...to computer graphics with the goal of automatically 7 converting complex graphics models into forms more appropriate for radiosity com- putation. 8 4

Automated Instructional Monitors for Complex Operational Tasks. Final Report.

ERIC Educational Resources Information Center

Feurzeig, Wallace

A computer-based instructional system is described which incorporates diagnosis of students difficulties in acquiring complex concepts and skills. A computer automatically generated a simulated display. It then monitored and analyzed a student's work in the performance of assigned training tasks. Two major tasks were studied. The first,…

Development of Onboard Computer Complex for Russian Segment of ISS

NASA Technical Reports Server (NTRS)

Branets, V.; Brand, G.; Vlasov, R.; Graf, I.; Clubb, J.; Mikrin, E.; Samitov, R.

1998-01-01

Report present a description of the Onboard Computer Complex (CC) that was developed during the period of 1994-1998 for the Russian Segment of ISS. The system was developed in co-operation with NASA and ESA. ESA developed a new computation system under the RSC Energia Technical Assignment, called DMS-R. The CC also includes elements developed by Russian experts and organizations. A general architecture of the computer system and the characteristics of primary elements of this system are described. The system was integrated at RSC Energia with the participation of American and European specialists. The report contains information on software simulators, verification and de-bugging facilities witch were been developed for both stand-alone and integrated tests and verification. This CC serves as the basis for the Russian Segment Onboard Control Complex on ISS.

On the Computational Capabilities of Physical Systems. Part 1; The Impossibility of Infallible Computation

NASA Technical Reports Server (NTRS)

Wolpert, David H.; Koga, Dennis (Technical Monitor)

2000-01-01

In this first of two papers, strong limits on the accuracy of physical computation are established. First it is proven that there cannot be a physical computer C to which one can pose any and all computational tasks concerning the physical universe. Next it is proven that no physical computer C can correctly carry out any computational task in the subset of such tasks that can be posed to C. This result holds whether the computational tasks concern a system that is physically isolated from C, or instead concern a system that is coupled to C. As a particular example, this result means that there cannot be a physical computer that can, for any physical system external to that computer, take the specification of that external system's state as input and then correctly predict its future state before that future state actually occurs; one cannot build a physical computer that can be assured of correctly 'processing information faster than the universe does'. The results also mean that there cannot exist an infallible, general-purpose observation apparatus, and that there cannot be an infallible, general-purpose control apparatus. These results do not rely on systems that are infinite, and/or non-classical, and/or obey chaotic dynamics. They also hold even if one uses an infinitely fast, infinitely dense computer, with computational powers greater than that of a Turing Machine. This generality is a direct consequence of the fact that a novel definition of computation - a definition of 'physical computation' - is needed to address the issues considered in these papers. While this definition does not fit into the traditional Chomsky hierarchy, the mathematical structure and impossibility results associated with it have parallels in the mathematics of the Chomsky hierarchy. The second in this pair of papers presents a preliminary exploration of some of this mathematical structure, including in particular that of prediction complexity, which is a 'physical computation analogue' of algorithmic information complexity. It is proven in that second paper that either the Hamiltonian of our universe proscribes a certain type of computation, or prediction complexity is unique (unlike algorithmic information complexity), in that there is one and only version of it that can be applicable throughout our universe.

MOLNs: A CLOUD PLATFORM FOR INTERACTIVE, REPRODUCIBLE, AND SCALABLE SPATIAL STOCHASTIC COMPUTATIONAL EXPERIMENTS IN SYSTEMS BIOLOGY USING PyURDME.

PubMed

Drawert, Brian; Trogdon, Michael; Toor, Salman; Petzold, Linda; Hellander, Andreas

2016-01-01

Computational experiments using spatial stochastic simulations have led to important new biological insights, but they require specialized tools and a complex software stack, as well as large and scalable compute and data analysis resources due to the large computational cost associated with Monte Carlo computational workflows. The complexity of setting up and managing a large-scale distributed computation environment to support productive and reproducible modeling can be prohibitive for practitioners in systems biology. This results in a barrier to the adoption of spatial stochastic simulation tools, effectively limiting the type of biological questions addressed by quantitative modeling. In this paper, we present PyURDME, a new, user-friendly spatial modeling and simulation package, and MOLNs, a cloud computing appliance for distributed simulation of stochastic reaction-diffusion models. MOLNs is based on IPython and provides an interactive programming platform for development of sharable and reproducible distributed parallel computational experiments.

Quantum vertex model for reversible classical computing.

PubMed

Chamon, C; Mucciolo, E R; Ruckenstein, A E; Yang, Z-C

2017-05-12

Mappings of classical computation onto statistical mechanics models have led to remarkable successes in addressing some complex computational problems. However, such mappings display thermodynamic phase transitions that may prevent reaching solution even for easy problems known to be solvable in polynomial time. Here we map universal reversible classical computations onto a planar vertex model that exhibits no bulk classical thermodynamic phase transition, independent of the computational circuit. Within our approach the solution of the computation is encoded in the ground state of the vertex model and its complexity is reflected in the dynamics of the relaxation of the system to its ground state. We use thermal annealing with and without 'learning' to explore typical computational problems. We also construct a mapping of the vertex model into the Chimera architecture of the D-Wave machine, initiating an approach to reversible classical computation based on state-of-the-art implementations of quantum annealing.

Quantum vertex model for reversible classical computing

NASA Astrophysics Data System (ADS)

Chamon, C.; Mucciolo, E. R.; Ruckenstein, A. E.; Yang, Z.-C.

2017-05-01

Mappings of classical computation onto statistical mechanics models have led to remarkable successes in addressing some complex computational problems. However, such mappings display thermodynamic phase transitions that may prevent reaching solution even for easy problems known to be solvable in polynomial time. Here we map universal reversible classical computations onto a planar vertex model that exhibits no bulk classical thermodynamic phase transition, independent of the computational circuit. Within our approach the solution of the computation is encoded in the ground state of the vertex model and its complexity is reflected in the dynamics of the relaxation of the system to its ground state. We use thermal annealing with and without `learning' to explore typical computational problems. We also construct a mapping of the vertex model into the Chimera architecture of the D-Wave machine, initiating an approach to reversible classical computation based on state-of-the-art implementations of quantum annealing.

Engineering and Computing Portal to Solve Environmental Problems

NASA Astrophysics Data System (ADS)

Gudov, A. M.; Zavozkin, S. Y.; Sotnikov, I. Y.

2018-01-01

This paper describes architecture and services of the Engineering and Computing Portal, which is considered to be a complex solution that provides access to high-performance computing resources, enables to carry out computational experiments, teach parallel technologies and solve computing tasks, including technogenic safety ones.

USSR and Eastern Europe Scientific Abstracts, Cybernetics, Computers and Automation Technology, Number 29.

DTIC Science & Technology

1978-01-17

approach to designing computers: Formal mathematical methods were applied and computers themselves began to be widely used in designing other...capital, labor resources and the funds of consumers. Analysis of the model indicates that at the present time the average complexity of production of...ALGORITHMIC COMPLETENESS AND COMPLEXITY OF MICROPROGRAMS Kiev KIBERNETIKA in Russian No 3, May/Jun 77 pp 1-15 manuscript received 22 Dec 76 G0LUNK0V

Computationally efficient algorithm for high sampling-frequency operation of active noise control

NASA Astrophysics Data System (ADS)

Rout, Nirmal Kumar; Das, Debi Prasad; Panda, Ganapati

2015-05-01

In high sampling-frequency operation of active noise control (ANC) system the length of the secondary path estimate and the ANC filter are very long. This increases the computational complexity of the conventional filtered-x least mean square (FXLMS) algorithm. To reduce the computational complexity of long order ANC system using FXLMS algorithm, frequency domain block ANC algorithms have been proposed in past. These full block frequency domain ANC algorithms are associated with some disadvantages such as large block delay, quantization error due to computation of large size transforms and implementation difficulties in existing low-end DSP hardware. To overcome these shortcomings, the partitioned block ANC algorithm is newly proposed where the long length filters in ANC are divided into a number of equal partitions and suitably assembled to perform the FXLMS algorithm in the frequency domain. The complexity of this proposed frequency domain partitioned block FXLMS (FPBFXLMS) algorithm is quite reduced compared to the conventional FXLMS algorithm. It is further reduced by merging one fast Fourier transform (FFT)-inverse fast Fourier transform (IFFT) combination to derive the reduced structure FPBFXLMS (RFPBFXLMS) algorithm. Computational complexity analysis for different orders of filter and partition size are presented. Systematic computer simulations are carried out for both the proposed partitioned block ANC algorithms to show its accuracy compared to the time domain FXLMS algorithm.

Distinguishing humans from computers in the game of go: A complex network approach

NASA Astrophysics Data System (ADS)

Coquidé, C.; Georgeot, B.; Giraud, O.

2017-08-01

We compare complex networks built from the game of go and obtained from databases of human-played games with those obtained from computer-played games. Our investigations show that statistical features of the human-based networks and the computer-based networks differ, and that these differences can be statistically significant on a relatively small number of games using specific estimators. We show that the deterministic or stochastic nature of the computer algorithm playing the game can also be distinguished from these quantities. This can be seen as a tool to implement a Turing-like test for go simulators.

Improved neutron activation prediction code system development

NASA Technical Reports Server (NTRS)

Saqui, R. M.

1971-01-01

Two integrated neutron activation prediction code systems have been developed by modifying and integrating existing computer programs to perform the necessary computations to determine neutron induced activation gamma ray doses and dose rates in complex geometries. Each of the two systems is comprised of three computational modules. The first program module computes the spatial and energy distribution of the neutron flux from an input source and prepares input data for the second program which performs the reaction rate, decay chain and activation gamma source calculations. A third module then accepts input prepared by the second program to compute the cumulative gamma doses and/or dose rates at specified detector locations in complex, three-dimensional geometries.

Jungle Computing: Distributed Supercomputing Beyond Clusters, Grids, and Clouds

NASA Astrophysics Data System (ADS)

Seinstra, Frank J.; Maassen, Jason; van Nieuwpoort, Rob V.; Drost, Niels; van Kessel, Timo; van Werkhoven, Ben; Urbani, Jacopo; Jacobs, Ceriel; Kielmann, Thilo; Bal, Henri E.

In recent years, the application of high-performance and distributed computing in scientific practice has become increasingly wide spread. Among the most widely available platforms to scientists are clusters, grids, and cloud systems. Such infrastructures currently are undergoing revolutionary change due to the integration of many-core technologies, providing orders-of-magnitude speed improvements for selected compute kernels. With high-performance and distributed computing systems thus becoming more heterogeneous and hierarchical, programming complexity is vastly increased. Further complexities arise because urgent desire for scalability and issues including data distribution, software heterogeneity, and ad hoc hardware availability commonly force scientists into simultaneous use of multiple platforms (e.g., clusters, grids, and clouds used concurrently). A true computing jungle.

A rapid parallelization of cone-beam projection and back-projection operator based on texture fetching interpolation

NASA Astrophysics Data System (ADS)

Xie, Lizhe; Hu, Yining; Chen, Yang; Shi, Luyao

2015-03-01

Projection and back-projection are the most computational consuming parts in Computed Tomography (CT) reconstruction. Parallelization strategies using GPU computing techniques have been introduced. We in this paper present a new parallelization scheme for both projection and back-projection. The proposed method is based on CUDA technology carried out by NVIDIA Corporation. Instead of build complex model, we aimed on optimizing the existing algorithm and make it suitable for CUDA implementation so as to gain fast computation speed. Besides making use of texture fetching operation which helps gain faster interpolation speed, we fixed sampling numbers in the computation of projection, to ensure the synchronization of blocks and threads, thus prevents the latency caused by inconsistent computation complexity. Experiment results have proven the computational efficiency and imaging quality of the proposed method.

An Attractor-Based Complexity Measurement for Boolean Recurrent Neural Networks

PubMed Central

Cabessa, Jérémie; Villa, Alessandro E. P.

2014-01-01

We provide a novel refined attractor-based complexity measurement for Boolean recurrent neural networks that represents an assessment of their computational power in terms of the significance of their attractor dynamics. This complexity measurement is achieved by first proving a computational equivalence between Boolean recurrent neural networks and some specific class of -automata, and then translating the most refined classification of -automata to the Boolean neural network context. As a result, a hierarchical classification of Boolean neural networks based on their attractive dynamics is obtained, thus providing a novel refined attractor-based complexity measurement for Boolean recurrent neural networks. These results provide new theoretical insights to the computational and dynamical capabilities of neural networks according to their attractive potentialities. An application of our findings is illustrated by the analysis of the dynamics of a simplified model of the basal ganglia-thalamocortical network simulated by a Boolean recurrent neural network. This example shows the significance of measuring network complexity, and how our results bear new founding elements for the understanding of the complexity of real brain circuits. PMID:24727866

Real-time optical correlator using computer-generated holographic filter on a liquid crystal light valve

NASA Technical Reports Server (NTRS)

Chao, Tien-Hsin; Yu, Jeffrey

1990-01-01

Limitations associated with the binary phase-only filter often used in optical correlators are presently circumvented in the writing of complex-valued data on a gray-scale spatial light modulator through the use of a computer-generated hologram (CGH) algorithm. The CGH encodes complex-valued data into nonnegative real CGH data in such a way that it may be encoded in any of the available gray-scale spatial light modulators. A CdS liquid-crystal light valve is used for the complex-valued CGH encoding; computer simulations and experimental results are compared, and the use of such a CGH filter as the synapse hologram in a holographic optical neural net is discussed.

Dynamic properties of epidemic spreading on finite size complex networks

NASA Astrophysics Data System (ADS)

Li, Ying; Liu, Yang; Shan, Xiu-Ming; Ren, Yong; Jiao, Jian; Qiu, Ben

2005-11-01

The Internet presents a complex topological structure, on which computer viruses can easily spread. By using theoretical analysis and computer simulation methods, the dynamic process of disease spreading on finite size networks with complex topological structure is investigated. On the finite size networks, the spreading process of SIS (susceptible-infected-susceptible) model is a finite Markov chain with an absorbing state. Two parameters, the survival probability and the conditional infecting probability, are introduced to describe the dynamic properties of disease spreading on finite size networks. Our results can help understanding computer virus epidemics and other spreading phenomena on communication and social networks. Also, knowledge about the dynamic character of virus spreading is helpful for adopting immunity policy.

Diffraction scattering computed tomography: a window into the structures of complex nanomaterials

PubMed Central

Birkbak, M. E.; Leemreize, H.; Frølich, S.; Stock, S. R.

2015-01-01

Modern functional nanomaterials and devices are increasingly composed of multiple phases arranged in three dimensions over several length scales. Therefore there is a pressing demand for improved methods for structural characterization of such complex materials. An excellent emerging technique that addresses this problem is diffraction/scattering computed tomography (DSCT). DSCT combines the merits of diffraction and/or small angle scattering with computed tomography to allow imaging the interior of materials based on the diffraction or small angle scattering signals. This allows, e.g., one to distinguish the distributions of polymorphs in complex mixtures. Here we review this technique and give examples of how it can shed light on modern nanoscale materials. PMID:26505175

Potent New Small-Molecule Inhibitor of Botulinum Neurotoxin Serotype A Endopeptidase Developed by Synthesis-Based Computer-Aided Molecular Design

DTIC Science & Technology

2009-11-01

dynamics of the complex predicted by multiple molecular dynamics simulations , and discuss further structural optimization to achieve better in vivo efficacy...complex with BoNTAe and the dynamics of the complex predicted by multiple molecular dynamics simulations (MMDSs). On the basis of the 3D model, we discuss...is unlimited whereas AHP exhibited 54% inhibition under the same conditions (Table 1). Computer Simulation Twenty different molecular dynamics

The Computational Ecologist’s Toolbox

EPA Science Inventory

Computational ecology, nestled in the broader field of data science, is an interdisciplinary field that attempts to improve our understanding of complex ecological systems through the use of modern computational methods. Computational ecology is based on a union of competence in...

Boom. Bust. Build.

ERIC Educational Resources Information Center

Kite, Vance; Park, Soonhye

2018-01-01

In 2006 Jeanette Wing, a professor of computer science at Carnegie Mellon University, proposed computational thinking (CT) as a literacy just as important as reading, writing, and mathematics. Wing defined CT as a set of skills and strategies computer scientists use to solve complex, computational problems (Wing 2006). The computer science and…

Experimental evidence for blue-shifted hydrogen bonding in the fluoroform-hydrogen chloride complex: a matrix-isolation infrared and ab initio study.

PubMed

Gopi, R; Ramanathan, N; Sundararajan, K

2014-07-24

The 1:1 hydrogen-bonded complex of fluoroform and hydrogen chloride was studied using matrix-isolation infrared spectroscopy and ab initio computations. Using B3LYP and MP2 levels of theory with 6-311++G(d,p) and aug-cc-pVDZ basis sets, the structures of the complexes and their energies were computed. For the 1:1 CHF3-HCl complexes, ab initio computations showed two minima, one cyclic and the other acyclic. The cyclic complex was found to have C-H · · · Cl and C-F · · · H interactions, where CHF3 and HCl sub-molecules act as proton donor and proton acceptor, respectively. The second minimum corresponded to an acyclic complex stabilized only by the C-F · · · H interaction, in which CHF3 is the proton acceptor. Experimentally, we could trap the 1:1 CHF3-HCl cyclic complex in an argon matrix, where a blue-shift in the C-H stretching mode of the CHF3 sub-molecule was observed. To understand the nature of the interactions, Atoms in Molecules and Natural Bond Orbital analyses were carried out to unravel the reasons for blue-shifting of the C-H stretching frequency in these complexes.

Multigrid Methods for Aerodynamic Problems in Complex Geometries

NASA Technical Reports Server (NTRS)

Caughey, David A.

1995-01-01

Work has been directed at the development of efficient multigrid methods for the solution of aerodynamic problems involving complex geometries, including the development of computational methods for the solution of both inviscid and viscous transonic flow problems. The emphasis is on problems of complex, three-dimensional geometry. The methods developed are based upon finite-volume approximations to both the Euler and the Reynolds-Averaged Navier-Stokes equations. The methods are developed for use on multi-block grids using diagonalized implicit multigrid methods to achieve computational efficiency. The work is focused upon aerodynamic problems involving complex geometries, including advanced engine inlets.

Human Skill in a Computerized Society: Complex Skills and Their Acquisition.

ERIC Educational Resources Information Center

Lesgold, Alan M.

1986-01-01

This paper discusses some of the issues raised for cognitive psychologists by the computer revolution together with the role that psychologists with computer training ought to play, especially in the study of how people acquire complex skills. The issues addressed include: (1) the competition between humans and intelligent machines; (2) the…

Identification of Factors That Affect Software Complexity.

ERIC Educational Resources Information Center

Kaiser, Javaid

A survey of computer scientists was conducted to identify factors that affect software complexity. A total of 160 items were selected from the literature to include in a questionnaire sent to 425 individuals who were employees of computer-related businesses in Lawrence and Kansas City. The items were grouped into nine categories called system…

Students' Explanations in Complex Learning of Disciplinary Programming

ERIC Educational Resources Information Center

Vieira, Camilo

2016-01-01

Computational Science and Engineering (CSE) has been denominated as the third pillar of science and as a set of important skills to solve the problems of a global society. Along with the theoretical and the experimental approaches, computation offers a third alternative to solve complex problems that require processing large amounts of data, or…

Computational Nonlinear Morphology with Emphasis on Semitic Languages. Studies in Natural Language Processing.

ERIC Educational Resources Information Center

Kiraz, George Anton

This book presents a tractable computational model that can cope with complex morphological operations, especially in Semitic languages, and less complex morphological systems present in Western languages. It outlines a new generalized regular rewrite rule system that uses multiple finite-state automata to cater to root-and-pattern morphology,…

Teaching Inorganic Photophysics and Photochemistry with Three Ruthenium(II) Polypyridyl Complexes: A Computer-Based Exercise

ERIC Educational Resources Information Center

Garino, Claudio; Terenzi, Alessio; Barone, Giampaolo; Salassa, Luca

2016-01-01

Among computational methods, DFT (density functional theory) and TD-DFT (time-dependent DFT) are widely used in research to describe, "inter alia," the optical properties of transition metal complexes. Inorganic/physical chemistry courses for undergraduate students treat such methods, but quite often only from the theoretical point of…

Environmental Factors Affecting Computer Assisted Language Learning Success: A Complex Dynamic Systems Conceptual Model

ERIC Educational Resources Information Center

Marek, Michael W.; Wu, Wen-Chi Vivian

2014-01-01

This conceptual, interdisciplinary inquiry explores Complex Dynamic Systems as the concept relates to the internal and external environmental factors affecting computer assisted language learning (CALL). Based on the results obtained by de Rosnay ["World Futures: The Journal of General Evolution", 67(4/5), 304-315 (2011)], who observed…

Challenges in Integrating a Complex Systems Computer Simulation in Class: An Educational Design Research

ERIC Educational Resources Information Center

Loke, Swee-Kin; Al-Sallami, Hesham S.; Wright, Daniel F. B.; McDonald, Jenny; Jadhav, Sheetal; Duffull, Stephen B.

2012-01-01

Complex systems are typically difficult for students to understand and computer simulations offer a promising way forward. However, integrating such simulations into conventional classes presents numerous challenges. Framed within an educational design research, we studied the use of an in-house built simulation of the coagulation network in four…

ASIC For Complex Fixed-Point Arithmetic

NASA Technical Reports Server (NTRS)

Petilli, Stephen G.; Grimm, Michael J.; Olson, Erlend M.

1995-01-01

Application-specific integrated circuit (ASIC) performs 24-bit, fixed-point arithmetic operations on arrays of complex-valued input data. High-performance, wide-band arithmetic logic unit (ALU) designed for use in computing fast Fourier transforms (FFTs) and for performing ditigal filtering functions. Other applications include general computations involved in analysis of spectra and digital signal processing.

Autonomous control systems: applications to remote sensing and image processing

NASA Astrophysics Data System (ADS)

Jamshidi, Mohammad

2001-11-01

One of the main challenges of any control (or image processing) paradigm is being able to handle complex systems under unforeseen uncertainties. A system may be called complex here if its dimension (order) is too high and its model (if available) is nonlinear, interconnected, and information on the system is uncertain such that classical techniques cannot easily handle the problem. Examples of complex systems are power networks, space robotic colonies, national air traffic control system, and integrated manufacturing plant, the Hubble Telescope, the International Space Station, etc. Soft computing, a consortia of methodologies such as fuzzy logic, neuro-computing, genetic algorithms and genetic programming, has proven to be powerful tools for adding autonomy and semi-autonomy to many complex systems. For such systems the size of soft computing control architecture will be nearly infinite. In this paper new paradigms using soft computing approaches are utilized to design autonomous controllers and image enhancers for a number of application areas. These applications are satellite array formations for synthetic aperture radar interferometry (InSAR) and enhancement of analog and digital images.

EMILiO: a fast algorithm for genome-scale strain design.

PubMed

Yang, Laurence; Cluett, William R; Mahadevan, Radhakrishnan

2011-05-01

Systems-level design of cell metabolism is becoming increasingly important for renewable production of fuels, chemicals, and drugs. Computational models are improving in the accuracy and scope of predictions, but are also growing in complexity. Consequently, efficient and scalable algorithms are increasingly important for strain design. Previous algorithms helped to consolidate the utility of computational modeling in this field. To meet intensifying demands for high-performance strains, both the number and variety of genetic manipulations involved in strain construction are increasing. Existing algorithms have experienced combinatorial increases in computational complexity when applied toward the design of such complex strains. Here, we present EMILiO, a new algorithm that increases the scope of strain design to include reactions with individually optimized fluxes. Unlike existing approaches that would experience an explosion in complexity to solve this problem, we efficiently generated numerous alternate strain designs producing succinate, l-glutamate and l-serine. This was enabled by successive linear programming, a technique new to the area of computational strain design. Copyright © 2011 Elsevier Inc. All rights reserved.

A full computation-relevant topological dynamics classification of elementary cellular automata.

PubMed

Schüle, Martin; Stoop, Ruedi

2012-12-01

Cellular automata are both computational and dynamical systems. We give a complete classification of the dynamic behaviour of elementary cellular automata (ECA) in terms of fundamental dynamic system notions such as sensitivity and chaoticity. The "complex" ECA emerge to be sensitive, but not chaotic and not eventually weakly periodic. Based on this classification, we conjecture that elementary cellular automata capable of carrying out complex computations, such as needed for Turing-universality, are at the "edge of chaos."

USSR and Eastern Europe Scientific Abstracts, Cybernetics, Computers, and Automation Technology, Number 27

DTIC Science & Technology

1977-05-10

apply this method of forecast- ing in the solution of all major scientific-technical problems of the na- tional economy. Citing the slow...the future, however, computers will "mature" and learn to recognize patterns in what amounts to a much more complex language—the language of visual...images. Photoelectronic tracking devices or "eyes" will allow the computer to take in information in a much more complex form and to perform opera

Queueing Network Models for Parallel Processing of Task Systems: an Operational Approach

NASA Technical Reports Server (NTRS)

Mak, Victor W. K.

1986-01-01

Computer performance modeling of possibly complex computations running on highly concurrent systems is considered. Earlier works in this area either dealt with a very simple program structure or resulted in methods with exponential complexity. An efficient procedure is developed to compute the performance measures for series-parallel-reducible task systems using queueing network models. The procedure is based on the concept of hierarchical decomposition and a new operational approach. Numerical results for three test cases are presented and compared to those of simulations.

Computational fluency and strategy choice predict individual and cross-national differences in complex arithmetic.

PubMed

Vasilyeva, Marina; Laski, Elida V; Shen, Chen

2015-10-01

The present study tested the hypothesis that children's fluency with basic number facts and knowledge of computational strategies, derived from early arithmetic experience, predicts their performance on complex arithmetic problems. First-grade students from United States and Taiwan (N = 152, mean age: 7.3 years) were presented with problems that differed in difficulty: single-, mixed-, and double-digit addition. Children's strategy use varied as a function of problem difficulty, consistent with Siegler's theory of strategy choice. The use of decomposition strategy interacted with computational fluency in predicting the accuracy of double-digit addition. Further, the frequency of decomposition and computational fluency fully mediated cross-national differences in accuracy on these complex arithmetic problems. The results indicate the importance of both fluency with basic number facts and the decomposition strategy for later arithmetic performance. (c) 2015 APA, all rights reserved).

Noise Estimation in Electroencephalogram Signal by Using Volterra Series Coefficients

PubMed Central

Hassani, Malihe; Karami, Mohammad Reza

2015-01-01

The Volterra model is widely used for nonlinearity identification in practical applications. In this paper, we employed Volterra model to find the nonlinearity relation between electroencephalogram (EEG) signal and the noise that is a novel approach to estimate noise in EEG signal. We show that by employing this method. We can considerably improve the signal to noise ratio by the ratio of at least 1.54. An important issue in implementing Volterra model is its computation complexity, especially when the degree of nonlinearity is increased. Hence, in many applications it is urgent to reduce the complexity of computation. In this paper, we use the property of EEG signal and propose a new and good approximation of delayed input signal to its adjacent samples in order to reduce the computation of finding Volterra series coefficients. The computation complexity is reduced by the ratio of at least 1/3 when the filter memory is 3. PMID:26284176

Computer-assisted innovations in craniofacial surgery.

PubMed

Rudman, Kelli; Hoekzema, Craig; Rhee, John

2011-08-01

Reconstructive surgery for complex craniofacial defects challenges even the most experienced surgeons. Preoperative reconstructive planning requires consideration of both functional and aesthetic properties of the mandible, orbit, and midface. Technological innovations allow for computer-assisted preoperative planning, computer-aided manufacturing of patient-specific implants (PSIs), and computer-assisted intraoperative navigation. Although many case reports discuss computer-assisted preoperative planning and creation of custom implants, a general overview of computer-assisted innovations is not readily available. This article reviews innovations in computer-assisted reconstructive surgery including anatomic considerations when using PSIs, technologies available for preoperative planning, work flow and process of obtaining a PSI, and implant materials available for PSIs. A case example follows illustrating the use of this technology in the reconstruction of an orbital-frontal-temporal defect with a PSI. Computer-assisted reconstruction of complex craniofacial defects provides the reconstructive surgeon with innovative options for challenging reconstructive cases. As technology advances, applications of computer-assisted reconstruction will continue to expand. © Thieme Medical Publishers.

How to Compute Labile Metal-Ligand Equilibria

ERIC Educational Resources Information Center

de Levie, Robert

2007-01-01

The different methods used for computing labile metal-ligand complexes, which are suitable for an iterative computer solution, are illustrated. The ligand function has allowed students to relegate otherwise tedious iterations to a computer, while retaining complete control over what is calculated.

Applications of complex systems theory in nursing education, research, and practice.

PubMed

Clancy, Thomas R; Effken, Judith A; Pesut, Daniel

2008-01-01

The clinical and administrative processes in today's healthcare environment are becoming increasingly complex. Multiple providers, new technology, competition, and the growing ubiquity of information all contribute to the notion of health care as a complex system. A complex system (CS) is characterized by a highly connected network of entities (e.g., physical objects, people or groups of people) from which higher order behavior emerges. Research in the transdisciplinary field of CS has focused on the use of computational modeling and simulation as a methodology for analyzing CS behavior. The creation of virtual worlds through computer simulation allows researchers to analyze multiple variables simultaneously and begin to understand behaviors that are common regardless of the discipline. The application of CS principles, mediated through computer simulation, informs nursing practice of the benefits and drawbacks of new procedures, protocols and practices before having to actually implement them. The inclusion of new computational tools and their applications in nursing education is also gaining attention. For example, education in CSs and applied computational applications has been endorsed by The Institute of Medicine, the American Organization of Nurse Executives and the American Association of Colleges of Nursing as essential training of nurse leaders. The purpose of this article is to review current research literature regarding CS science within the context of expert practice and implications for the education of nurse leadership roles. The article focuses on 3 broad areas: CS defined, literature review and exemplars from CS research and applications of CS theory in nursing leadership education. The article also highlights the key role nursing informaticists play in integrating emerging computational tools in the analysis of complex nursing systems.

Second order Møller-Plesset and coupled cluster singles and doubles methods with complex basis functions for resonances in electron-molecule scattering

DOE PAGES

White, Alec F.; Epifanovsky, Evgeny; McCurdy, C. William; ...

2017-06-21

The method of complex basis functions is applied to molecular resonances at correlated levels of theory. Møller-Plesset perturbation theory at second order and equation-of-motion electron attachment coupled-cluster singles and doubles (EOM-EA-CCSD) methods based on a non-Hermitian self-consistent-field reference are used to compute accurate Siegert energies for shape resonances in small molecules including N 2 - , CO - , CO 2 - , and CH 2 O - . Analytic continuation of complex θ-trajectories is used to compute Siegert energies, and the θ-trajectories of energy differences are found to yield more consistent results than those of total energies.more » Furthermore, the ability of such methods to accurately compute complex potential energy surfaces is investigated, and the possibility of using EOM-EA-CCSD for Feshbach resonances is explored in the context of e-helium scattering.« less

A low complexity reweighted proportionate affine projection algorithm with memory and row action projection

NASA Astrophysics Data System (ADS)

Liu, Jianming; Grant, Steven L.; Benesty, Jacob

2015-12-01

A new reweighted proportionate affine projection algorithm (RPAPA) with memory and row action projection (MRAP) is proposed in this paper. The reweighted PAPA is derived from a family of sparseness measures, which demonstrate performance similar to mu-law and the l 0 norm PAPA but with lower computational complexity. The sparseness of the channel is taken into account to improve the performance for dispersive system identification. Meanwhile, the memory of the filter's coefficients is combined with row action projections (RAP) to significantly reduce computational complexity. Simulation results demonstrate that the proposed RPAPA MRAP algorithm outperforms both the affine projection algorithm (APA) and PAPA, and has performance similar to l 0 PAPA and mu-law PAPA, in terms of convergence speed and tracking ability. Meanwhile, the proposed RPAPA MRAP has much lower computational complexity than PAPA, mu-law PAPA, and l 0 PAPA, etc., which makes it very appealing for real-time implementation.

Second order Møller-Plesset and coupled cluster singles and doubles methods with complex basis functions for resonances in electron-molecule scattering

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

White, Alec F.; Epifanovsky, Evgeny; McCurdy, C. William

The method of complex basis functions is applied to molecular resonances at correlated levels of theory. Møller-Plesset perturbation theory at second order and equation-of-motion electron attachment coupled-cluster singles and doubles (EOM-EA-CCSD) methods based on a non-Hermitian self-consistent-field reference are used to compute accurate Siegert energies for shape resonances in small molecules including N 2 - , CO - , CO 2 - , and CH 2 O - . Analytic continuation of complex θ-trajectories is used to compute Siegert energies, and the θ-trajectories of energy differences are found to yield more consistent results than those of total energies.more » Furthermore, the ability of such methods to accurately compute complex potential energy surfaces is investigated, and the possibility of using EOM-EA-CCSD for Feshbach resonances is explored in the context of e-helium scattering.« less

GBA manager: an online tool for querying low-complexity regions in proteins.

PubMed

Bandyopadhyay, Nirmalya; Kahveci, Tamer

2010-01-01

Abstract We developed GBA Manager, an online software that facilitates the Graph-Based Algorithm (GBA) we proposed in our earlier work. GBA identifies the low-complexity regions (LCR) of protein sequences. GBA exploits a similarity matrix, such as BLOSUM62, to compute the complexity of the subsequences of the input protein sequence. It uses a graph-based algorithm to accurately compute the regions that have low complexities. GBA Manager is a user friendly web-service that enables online querying of protein sequences using GBA. In addition to querying capabilities of the existing GBA algorithm, GBA Manager computes the p-values of the LCR identified. The p-value gives an estimate of the possibility that the region appears by chance. GBA Manager presents the output in three different understandable formats. GBA Manager is freely accessible at http://bioinformatics.cise.ufl.edu/GBA/GBA.htm .

Sorting on STAR. [CDC computer algorithm timing comparison

NASA Technical Reports Server (NTRS)

Stone, H. S.

1978-01-01

Timing comparisons are given for three sorting algorithms written for the CDC STAR computer. One algorithm is Hoare's (1962) Quicksort, which is the fastest or nearly the fastest sorting algorithm for most computers. A second algorithm is a vector version of Quicksort that takes advantage of the STAR's vector operations. The third algorithm is an adaptation of Batcher's (1968) sorting algorithm, which makes especially good use of vector operations but has a complexity of N(log N)-squared as compared with a complexity of N log N for the Quicksort algorithms. In spite of its worse complexity, Batcher's sorting algorithm is competitive with the serial version of Quicksort for vectors up to the largest that can be treated by STAR. Vector Quicksort outperforms the other two algorithms and is generally preferred. These results indicate that unusual instruction sets can introduce biases in program execution time that counter results predicted by worst-case asymptotic complexity analysis.

An efficient hybrid technique in RCS predictions of complex targets at high frequencies

NASA Astrophysics Data System (ADS)

Algar, María-Jesús; Lozano, Lorena; Moreno, Javier; González, Iván; Cátedra, Felipe

2017-09-01

Most computer codes in Radar Cross Section (RCS) prediction use Physical Optics (PO) and Physical theory of Diffraction (PTD) combined with Geometrical Optics (GO) and Geometrical Theory of Diffraction (GTD). The latter approaches are computationally cheaper and much more accurate for curved surfaces, but not applicable for the computation of the RCS of all surfaces of a complex object due to the presence of caustic problems in the analysis of concave surfaces or flat surfaces in the far field. The main contribution of this paper is the development of a hybrid method based on a new combination of two asymptotic techniques: GTD and PO, considering the advantages and avoiding the disadvantages of each of them. A very efficient and accurate method to analyze the RCS of complex structures at high frequencies is obtained with the new combination. The proposed new method has been validated comparing RCS results obtained for some simple cases using the proposed approach and RCS using the rigorous technique of Method of Moments (MoM). Some complex cases have been examined at high frequencies contrasting the results with PO. This study shows the accuracy and the efficiency of the hybrid method and its suitability for the computation of the RCS at really large and complex targets at high frequencies.

Final Report: A Broad Research Project on the Sciences of Complexity, September 15, 1994 - November 15, 1999

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

None

2000-02-01

DOE support for a broad research program in the sciences of complexity permitted the Santa Fe Institute to initiate new collaborative research within its integrative core activities as well as to host visitors to participate in research on specific topics that serve as motivation and testing ground for the study of the general principles of complex systems. Results are presented on computational biology, biodiversity and ecosystem research, and advanced computing and simulation.

Algorithms for computing solvents of unilateral second-order matrix polynomials over prime finite fields using lambda-matrices

NASA Astrophysics Data System (ADS)

Burtyka, Filipp

2018-01-01

The paper considers algorithms for finding diagonalizable and non-diagonalizable roots (so called solvents) of monic arbitrary unilateral second-order matrix polynomial over prime finite field. These algorithms are based on polynomial matrices (lambda-matrices). This is an extension of existing general methods for computing solvents of matrix polynomials over field of complex numbers. We analyze how techniques for complex numbers can be adapted for finite field and estimate asymptotic complexity of the obtained algorithms.

FLAME: A platform for high performance computing of complex systems, applied for three case studies

DOE PAGES

Kiran, Mariam; Bicak, Mesude; Maleki-Dizaji, Saeedeh; ...

2011-01-01

FLAME allows complex models to be automatically parallelised on High Performance Computing (HPC) grids enabling large number of agents to be simulated over short periods of time. Modellers are hindered by complexities of porting models on parallel platforms and time taken to run large simulations on a single machine, which FLAME overcomes. Three case studies from different disciplines were modelled using FLAME, and are presented along with their performance results on a grid.

Computational path planner for product assembly in complex environments

NASA Astrophysics Data System (ADS)

Shang, Wei; Liu, Jianhua; Ning, Ruxin; Liu, Mi

2013-03-01

Assembly path planning is a crucial problem in assembly related design and manufacturing processes. Sampling based motion planning algorithms are used for computational assembly path planning. However, the performance of such algorithms may degrade much in environments with complex product structure, narrow passages or other challenging scenarios. A computational path planner for automatic assembly path planning in complex 3D environments is presented. The global planning process is divided into three phases based on the environment and specific algorithms are proposed and utilized in each phase to solve the challenging issues. A novel ray test based stochastic collision detection method is proposed to evaluate the intersection between two polyhedral objects. This method avoids fake collisions in conventional methods and degrades the geometric constraint when a part has to be removed with surface contact with other parts. A refined history based rapidly-exploring random tree (RRT) algorithm which bias the growth of the tree based on its planning history is proposed and employed in the planning phase where the path is simple but the space is highly constrained. A novel adaptive RRT algorithm is developed for the path planning problem with challenging scenarios and uncertain environment. With extending values assigned on each tree node and extending schemes applied, the tree can adapts its growth to explore complex environments more efficiently. Experiments on the key algorithms are carried out and comparisons are made between the conventional path planning algorithms and the presented ones. The comparing results show that based on the proposed algorithms, the path planner can compute assembly path in challenging complex environments more efficiently and with higher success. This research provides the references to the study of computational assembly path planning under complex environments.

Quantum Computing: Solving Complex Problems

ScienceCinema

DiVincenzo, David

2018-05-22

One of the motivating ideas of quantum computation was that there could be a new kind of machine that would solve hard problems in quantum mechanics. There has been significant progress towards the experimental realization of these machines (which I will review), but there are still many questions about how such a machine could solve computational problems of interest in quantum physics. New categorizations of the complexity of computational problems have now been invented to describe quantum simulation. The bad news is that some of these problems are believed to be intractable even on a quantum computer, falling into a quantum analog of the NP class. The good news is that there are many other new classifications of tractability that may apply to several situations of physical interest.

A review of computer-aided oral and maxillofacial surgery: planning, simulation and navigation.

PubMed

Chen, Xiaojun; Xu, Lu; Sun, Yi; Politis, Constantinus

2016-11-01

Currently, oral and maxillofacial surgery (OMFS) still poses a significant challenge for surgeons due to the anatomic complexity and limited field of view of the oral cavity. With the great development of computer technologies, he computer-aided surgery has been widely used for minimizing the risks and improving the precision of surgery. Areas covered: The major goal of this paper is to provide a comprehensive reference source of current and future development of computer-aided OMFS including surgical planning, simulation and navigation for relevant researchers. Expert commentary: Compared with the traditional OMFS, computer-aided OMFS overcomes the disadvantage that the treatment on the region of anatomically complex maxillofacial depends almost exclusively on the experience of the surgeon.

Epidemic modeling in complex realities.

PubMed

Colizza, Vittoria; Barthélemy, Marc; Barrat, Alain; Vespignani, Alessandro

2007-04-01

In our global world, the increasing complexity of social relations and transport infrastructures are key factors in the spread of epidemics. In recent years, the increasing availability of computer power has enabled both to obtain reliable data allowing one to quantify the complexity of the networks on which epidemics may propagate and to envision computational tools able to tackle the analysis of such propagation phenomena. These advances have put in evidence the limits of homogeneous assumptions and simple spatial diffusion approaches, and stimulated the inclusion of complex features and heterogeneities relevant in the description of epidemic diffusion. In this paper, we review recent progresses that integrate complex systems and networks analysis with epidemic modelling and focus on the impact of the various complex features of real systems on the dynamics of epidemic spreading.

Causal Learning with Local Computations

ERIC Educational Resources Information Center

Fernbach, Philip M.; Sloman, Steven A.

2009-01-01

The authors proposed and tested a psychological theory of causal structure learning based on local computations. Local computations simplify complex learning problems via cues available on individual trials to update a single causal structure hypothesis. Structural inferences from local computations make minimal demands on memory, require…

Adjoint-Based Aerodynamic Design of Complex Aerospace Configurations

NASA Technical Reports Server (NTRS)

Nielsen, Eric J.

2016-01-01

An overview of twenty years of adjoint-based aerodynamic design research at NASA Langley Research Center is presented. Adjoint-based algorithms provide a powerful tool for efficient sensitivity analysis of complex large-scale computational fluid dynamics (CFD) simulations. Unlike alternative approaches for which computational expense generally scales with the number of design parameters, adjoint techniques yield sensitivity derivatives of a simulation output with respect to all input parameters at the cost of a single additional simulation. With modern large-scale CFD applications often requiring millions of compute hours for a single analysis, the efficiency afforded by adjoint methods is critical in realizing a computationally tractable design optimization capability for such applications.

In silico Interrogation of Insect Central Complex Suggests Computational Roles for the Ellipsoid Body in Spatial Navigation.

PubMed

Fiore, Vincenzo G; Kottler, Benjamin; Gu, Xiaosi; Hirth, Frank

2017-01-01

The central complex in the insect brain is a composite of midline neuropils involved in processing sensory cues and mediating behavioral outputs to orchestrate spatial navigation. Despite recent advances, however, the neural mechanisms underlying sensory integration and motor action selections have remained largely elusive. In particular, it is not yet understood how the central complex exploits sensory inputs to realize motor functions associated with spatial navigation. Here we report an in silico interrogation of central complex-mediated spatial navigation with a special emphasis on the ellipsoid body. Based on known connectivity and function, we developed a computational model to test how the local connectome of the central complex can mediate sensorimotor integration to guide different forms of behavioral outputs. Our simulations show integration of multiple sensory sources can be effectively performed in the ellipsoid body. This processed information is used to trigger continuous sequences of action selections resulting in self-motion, obstacle avoidance and the navigation of simulated environments of varying complexity. The motor responses to perceived sensory stimuli can be stored in the neural structure of the central complex to simulate navigation relying on a collective of guidance cues, akin to sensory-driven innate or habitual behaviors. By comparing behaviors under different conditions of accessible sources of input information, we show the simulated insect computes visual inputs and body posture to estimate its position in space. Finally, we tested whether the local connectome of the central complex might also allow the flexibility required to recall an intentional behavioral sequence, among different courses of actions. Our simulations suggest that the central complex can encode combined representations of motor and spatial information to pursue a goal and thus successfully guide orientation behavior. Together, the observed computational features identify central complex circuitry, and especially the ellipsoid body, as a key neural correlate involved in spatial navigation.

In silico Interrogation of Insect Central Complex Suggests Computational Roles for the Ellipsoid Body in Spatial Navigation

PubMed Central

Fiore, Vincenzo G.; Kottler, Benjamin; Gu, Xiaosi; Hirth, Frank

2017-01-01

The central complex in the insect brain is a composite of midline neuropils involved in processing sensory cues and mediating behavioral outputs to orchestrate spatial navigation. Despite recent advances, however, the neural mechanisms underlying sensory integration and motor action selections have remained largely elusive. In particular, it is not yet understood how the central complex exploits sensory inputs to realize motor functions associated with spatial navigation. Here we report an in silico interrogation of central complex-mediated spatial navigation with a special emphasis on the ellipsoid body. Based on known connectivity and function, we developed a computational model to test how the local connectome of the central complex can mediate sensorimotor integration to guide different forms of behavioral outputs. Our simulations show integration of multiple sensory sources can be effectively performed in the ellipsoid body. This processed information is used to trigger continuous sequences of action selections resulting in self-motion, obstacle avoidance and the navigation of simulated environments of varying complexity. The motor responses to perceived sensory stimuli can be stored in the neural structure of the central complex to simulate navigation relying on a collective of guidance cues, akin to sensory-driven innate or habitual behaviors. By comparing behaviors under different conditions of accessible sources of input information, we show the simulated insect computes visual inputs and body posture to estimate its position in space. Finally, we tested whether the local connectome of the central complex might also allow the flexibility required to recall an intentional behavioral sequence, among different courses of actions. Our simulations suggest that the central complex can encode combined representations of motor and spatial information to pursue a goal and thus successfully guide orientation behavior. Together, the observed computational features identify central complex circuitry, and especially the ellipsoid body, as a key neural correlate involved in spatial navigation. PMID:28824390

Novel functionalized pyridine-containing DTPA-like ligand. Synthesis, computational studies and characterization of the corresponding Gd(III) complex.

PubMed

Artali, Roberto; Botta, Mauro; Cavallotti, Camilla; Giovenzana, Giovanni B; Palmisano, Giovanni; Sisti, Massimo

2007-08-07

A novel pyridine-containing DTPA-like ligand, carrying additional hydroxymethyl groups on the pyridine side-arms, was synthesized in 5 steps. The corresponding Gd(III) complex, potentially useful as an MRI contrast agent, was prepared and characterized in detail by relaxometric methods and its structure modeled by computational methods.

Computational Fluency and Strategy Choice Predict Individual and Cross-National Differences in Complex Arithmetic

ERIC Educational Resources Information Center

Vasilyeva, Marina; Laski, Elida V.; Shen, Chen

2015-01-01

The present study tested the hypothesis that children's fluency with basic number facts and knowledge of computational strategies, derived from early arithmetic experience, predicts their performance on complex arithmetic problems. First-grade students from United States and Taiwan (N = 152, mean age: 7.3 years) were presented with problems that…

The Difficult Process of Scientific Modelling: An Analysis Of Novices' Reasoning During Computer-Based Modelling

ERIC Educational Resources Information Center

Sins, Patrick H. M.; Savelsbergh, Elwin R.; van Joolingen, Wouter R.

2005-01-01

Although computer modelling is widely advocated as a way to offer students a deeper understanding of complex phenomena, the process of modelling is rather complex itself and needs scaffolding. In order to offer adequate support, a thorough understanding of the reasoning processes students employ and of difficulties they encounter during a…

The method of complex characteristics for design of transonic blade sections

NASA Technical Reports Server (NTRS)

Bledsoe, M. R.

1986-01-01

A variety of computational methods were developed to obtain shockless or near shockless flow past two-dimensional airfoils. The approach used was the method of complex characteristics, which determines smooth solutions to the transonic flow equations based on an input speed distribution. General results from fluid mechanics are presented. An account of the method of complex characteristics is given including a description of the particular spaces and coordinates, conformal transformations, and numerical procedures that are used. The operation of the computer program COMPRES is presented along with examples of blade sections designed with the code. A user manual is included with a glossary to provide additional information which may be helpful. The computer program in Fortran, including numerous comment cards is listed.

Computing with dynamical systems based on insulator-metal-transition oscillators

NASA Astrophysics Data System (ADS)

Parihar, Abhinav; Shukla, Nikhil; Jerry, Matthew; Datta, Suman; Raychowdhury, Arijit

2017-04-01

In this paper, we review recent work on novel computing paradigms using coupled oscillatory dynamical systems. We explore systems of relaxation oscillators based on linear state transitioning devices, which switch between two discrete states with hysteresis. By harnessing the dynamics of complex, connected systems, we embrace the philosophy of "let physics do the computing" and demonstrate how complex phase and frequency dynamics of such systems can be controlled, programmed, and observed to solve computationally hard problems. Although our discussion in this paper is limited to insulator-to-metallic state transition devices, the general philosophy of such computing paradigms can be translated to other mediums including optical systems. We present the necessary mathematical treatments necessary to understand the time evolution of these systems and demonstrate through recent experimental results the potential of such computational primitives.

Use of a Computer Language in Teaching Dynamic Programming. Final Report.

ERIC Educational Resources Information Center

Trimble, C. J.; And Others

Most optimization problems of any degree of complexity must be solved using a computer. In the teaching of dynamic programing courses, it is often desirable to use a computer in problem solution. The solution process involves conceptual formulation and computational Solution. Generalized computer codes for dynamic programing problem solution…

Computational Aspects of Heat Transfer in Structures

NASA Technical Reports Server (NTRS)

Adelman, H. M. (Compiler)

1982-01-01

Techniques for the computation of heat transfer and associated phenomena in complex structures are examined with an emphasis on reentry flight vehicle structures. Analysis methods, computer programs, thermal analysis of large space structures and high speed vehicles, and the impact of computer systems are addressed.

Teaching CAD on the Apple Computer.

ERIC Educational Resources Information Center

Norton, Robert L.

1984-01-01

Describes a course designed to teach engineers how to accomplish computer graphics techniques on a limited scale with the Apple computer. The same mathematics and program code will also function for larger and more complex computers. Course content, instructional strategies, student evaluation, and recommendations are considered. (JN)

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.

Protecting Information

NASA Astrophysics Data System (ADS)

Loepp, Susan; Wootters, William K.

2006-09-01

For many everyday transmissions, it is essential to protect digital information from noise or eavesdropping. This undergraduate introduction to error correction and cryptography is unique in devoting several chapters to quantum cryptography and quantum computing, thus providing a context in which ideas from mathematics and physics meet. By covering such topics as Shor's quantum factoring algorithm, this text informs the reader about current thinking in quantum information theory and encourages an appreciation of the connections between mathematics and science.Of particular interest are the potential impacts of quantum physics:(i) a quantum computer, if built, could crack our currently used public-key cryptosystems; and (ii) quantum cryptography promises to provide an alternative to these cryptosystems, basing its security on the laws of nature rather than on computational complexity. No prior knowledge of quantum mechanics is assumed, but students should have a basic knowledge of complex numbers, vectors, and matrices. Accessible to readers familiar with matrix algebra, vector spaces and complex numbers First undergraduate text to cover cryptography, error-correction, and quantum computation together Features exercises designed to enhance understanding, including a number of computational problems, available from www.cambridge.org/9780521534765

MOLNs: A CLOUD PLATFORM FOR INTERACTIVE, REPRODUCIBLE, AND SCALABLE SPATIAL STOCHASTIC COMPUTATIONAL EXPERIMENTS IN SYSTEMS BIOLOGY USING PyURDME

PubMed Central

Drawert, Brian; Trogdon, Michael; Toor, Salman; Petzold, Linda; Hellander, Andreas

2017-01-01

Computational experiments using spatial stochastic simulations have led to important new biological insights, but they require specialized tools and a complex software stack, as well as large and scalable compute and data analysis resources due to the large computational cost associated with Monte Carlo computational workflows. The complexity of setting up and managing a large-scale distributed computation environment to support productive and reproducible modeling can be prohibitive for practitioners in systems biology. This results in a barrier to the adoption of spatial stochastic simulation tools, effectively limiting the type of biological questions addressed by quantitative modeling. In this paper, we present PyURDME, a new, user-friendly spatial modeling and simulation package, and MOLNs, a cloud computing appliance for distributed simulation of stochastic reaction-diffusion models. MOLNs is based on IPython and provides an interactive programming platform for development of sharable and reproducible distributed parallel computational experiments. PMID:28190948

Computing quantum discord is NP-complete

NASA Astrophysics Data System (ADS)

Huang, Yichen

2014-03-01

We study the computational complexity of quantum discord (a measure of quantum correlation beyond entanglement), and prove that computing quantum discord is NP-complete. Therefore, quantum discord is computationally intractable: the running time of any algorithm for computing quantum discord is believed to grow exponentially with the dimension of the Hilbert space so that computing quantum discord in a quantum system of moderate size is not possible in practice. As by-products, some entanglement measures (namely entanglement cost, entanglement of formation, relative entropy of entanglement, squashed entanglement, classical squashed entanglement, conditional entanglement of mutual information, and broadcast regularization of mutual information) and constrained Holevo capacity are NP-hard/NP-complete to compute. These complexity-theoretic results are directly applicable in common randomness distillation, quantum state merging, entanglement distillation, superdense coding, and quantum teleportation; they may offer significant insights into quantum information processing. Moreover, we prove the NP-completeness of two typical problems: linear optimization over classical states and detecting classical states in a convex set, providing evidence that working with classical states is generically computationally intractable.

Oligomerization of G protein-coupled receptors: computational methods.

PubMed

Selent, J; Kaczor, A A

2011-01-01

Recent research has unveiled the complexity of mechanisms involved in G protein-coupled receptor (GPCR) functioning in which receptor dimerization/oligomerization may play an important role. Although the first high-resolution X-ray structure for a likely functional chemokine receptor dimer has been deposited in the Protein Data Bank, the interactions and mechanisms of dimer formation are not yet fully understood. In this respect, computational methods play a key role for predicting accurate GPCR complexes. This review outlines computational approaches focusing on sequence- and structure-based methodologies as well as discusses their advantages and limitations. Sequence-based approaches that search for possible protein-protein interfaces in GPCR complexes have been applied with success in several studies, but did not yield always consistent results. Structure-based methodologies are a potent complement to sequence-based approaches. For instance, protein-protein docking is a valuable method especially when guided by experimental constraints. Some disadvantages like limited receptor flexibility and non-consideration of the membrane environment have to be taken into account. Molecular dynamics simulation can overcome these drawbacks giving a detailed description of conformational changes in a native-like membrane. Successful prediction of GPCR complexes using computational approaches combined with experimental efforts may help to understand the role of dimeric/oligomeric GPCR complexes for fine-tuning receptor signaling. Moreover, since such GPCR complexes have attracted interest as potential drug target for diverse diseases, unveiling molecular determinants of dimerization/oligomerization can provide important implications for drug discovery.

Iterative Minimum Variance Beamformer with Low Complexity for Medical Ultrasound Imaging.

PubMed

Deylami, Ali Mohades; Asl, Babak Mohammadzadeh

2018-06-04

Minimum variance beamformer (MVB) improves the resolution and contrast of medical ultrasound images compared with delay and sum (DAS) beamformer. The weight vector of this beamformer should be calculated for each imaging point independently, with a cost of increasing computational complexity. The large number of necessary calculations limits this beamformer to application in real-time systems. A beamformer is proposed based on the MVB with lower computational complexity while preserving its advantages. This beamformer avoids matrix inversion, which is the most complex part of the MVB, by solving the optimization problem iteratively. The received signals from two imaging points close together do not vary much in medical ultrasound imaging. Therefore, using the previously optimized weight vector for one point as initial weight vector for the new neighboring point can improve the convergence speed and decrease the computational complexity. The proposed method was applied on several data sets, and it has been shown that the method can regenerate the results obtained by the MVB while the order of complexity is decreased from O(L 3 ) to O(L 2 ). Copyright © 2018 World Federation for Ultrasound in Medicine and Biology. Published by Elsevier Inc. All rights reserved.

Utility Computing: Reality and Beyond

NASA Astrophysics Data System (ADS)

Ivanov, Ivan I.

Utility Computing is not a new concept. It involves organizing and providing a wide range of computing-related services as public utilities. Much like water, gas, electricity and telecommunications, the concept of computing as public utility was announced in 1955. Utility Computing remained a concept for near 50 years. Now some models and forms of Utility Computing are emerging such as storage and server virtualization, grid computing, and automated provisioning. Recent trends in Utility Computing as a complex technology involve business procedures that could profoundly transform the nature of companies' IT services, organizational IT strategies and technology infrastructure, and business models. In the ultimate Utility Computing models, organizations will be able to acquire as much IT services as they need, whenever and wherever they need them. Based on networked businesses and new secure online applications, Utility Computing would facilitate "agility-integration" of IT resources and services within and between virtual companies. With the application of Utility Computing there could be concealment of the complexity of IT, reduction of operational expenses, and converting of IT costs to variable `on-demand' services. How far should technology, business and society go to adopt Utility Computing forms, modes and models?

Science Notes.

ERIC Educational Resources Information Center

School Science Review, 1985

1985-01-01

Presents biology, chemistry, physics, and health activities, experiments, demonstrations, and computer programs. Includes mechanism of stomatal opening, using aquatic plants to help demonstrate chemical buffering, microbial activity/contamination in milk samples, computer computation of fitness scores, reservoir project, complexes of transition…

Stored program concept for analog computers

NASA Technical Reports Server (NTRS)

Hannauer, G., III; Patmore, J. R.

1971-01-01

Optimization of three-stage matrices, modularization, and black boxes design techniques provides for automatically interconnecting computing component inputs and outputs in general purpose analog computer. Design also produces relatively inexpensive and less complex automatic patching system.

Research approaches to mass casualty incidents response: development from routine perspectives to complexity science.

PubMed

Shen, Weifeng; Jiang, Libing; Zhang, Mao; Ma, Yuefeng; Jiang, Guanyu; He, Xiaojun

2014-01-01

To review the research methods of mass casualty incident (MCI) systematically and introduce the concept and characteristics of complexity science and artificial system, computational experiments and parallel execution (ACP) method. We searched PubMed, Web of Knowledge, China Wanfang and China Biology Medicine (CBM) databases for relevant studies. Searches were performed without year or language restrictions and used the combinations of the following key words: "mass casualty incident", "MCI", "research method", "complexity science", "ACP", "approach", "science", "model", "system" and "response". Articles were searched using the above keywords and only those involving the research methods of mass casualty incident (MCI) were enrolled. Research methods of MCI have increased markedly over the past few decades. For now, dominating research methods of MCI are theory-based approach, empirical approach, evidence-based science, mathematical modeling and computer simulation, simulation experiment, experimental methods, scenario approach and complexity science. This article provides an overview of the development of research methodology for MCI. The progresses of routine research approaches and complexity science are briefly presented in this paper. Furthermore, the authors conclude that the reductionism underlying the exact science is not suitable for MCI complex systems. And the only feasible alternative is complexity science. Finally, this summary is followed by a review that ACP method combining artificial systems, computational experiments and parallel execution provides a new idea to address researches for complex MCI.

Computer-assisted surgery planning in children with complex liver tumors identifies variability of the classical Couinaud classification.

PubMed

Warmann, Steven W; Schenk, Andrea; Schaefer, Juergen F; Ebinger, Martin; Blumenstock, Gunnar; Tsiflikas, Ilias; Fuchs, Joerg

2016-11-01

In complex malignant pediatric liver tumors there is an ongoing discussion regarding surgical strategy; for example, primary organ transplantation versus extended resection in hepatoblastoma involving 3 or 4 sectors of the liver. We evaluated the possible role of computer-assisted surgery planning in children with complex hepatic tumors. Between May 2004 and March 2016, 24 Children with complex liver tumors underwent standard multislice helical CT scan or MRI scan at our institution. Imaging data were processed using the software assistant LiverAnalyzer (Fraunhofer Institute for Medical Image Computing MEVIS, Bremen, Germany). Results were provided as Portable Document Format (PDF) with embedded interactive 3-dimensional surface mesh models. Median age of patients was 33months. Diagnoses were hepatoblastoma (n=14), sarcoma (n=3), benign parenchyma alteration (n=2), as well as hepatocellular carcinoma, rhabdoid tumor, focal nodular hyperplasia, hemangioendothelioma, or multiple hepatic metastases of a pancreas carcinoma (each n=1). Volumetry of liver segments identified remarkable variations and substantial aberrances from the Couinaud classification. Computer-assisted surgery planning was used to determine surgical strategies in 20/24 children; this was especially relevant in tumors affecting 3 or 4 liver sectors. Primary liver transplantation could be avoided in 12 of 14 hepaoblastoma patients who theoretically were candidates for this approach. Computer-assisted surgery planning substantially contributed to the decision for surgical strategies in children with complex hepatic tumors. This tool possibly allows determination of specific surgical procedures such as extended surgical resection instead of primary transplantation in certain conditions. Copyright © 2016. Published by Elsevier Inc.

A Low Complexity System Based on Multiple Weighted Decision Trees for Indoor Localization

PubMed Central

Sánchez-Rodríguez, David; Hernández-Morera, Pablo; Quinteiro, José Ma.; Alonso-González, Itziar

2015-01-01

Indoor position estimation has become an attractive research topic due to growing interest in location-aware services. Nevertheless, satisfying solutions have not been found with the considerations of both accuracy and system complexity. From the perspective of lightweight mobile devices, they are extremely important characteristics, because both the processor power and energy availability are limited. Hence, an indoor localization system with high computational complexity can cause complete battery drain within a few hours. In our research, we use a data mining technique named boosting to develop a localization system based on multiple weighted decision trees to predict the device location, since it has high accuracy and low computational complexity. The localization system is built using a dataset from sensor fusion, which combines the strength of radio signals from different wireless local area network access points and device orientation information from a digital compass built-in mobile device, so that extra sensors are unnecessary. Experimental results indicate that the proposed system leads to substantial improvements on computational complexity over the widely-used traditional fingerprinting methods, and it has a better accuracy than they have. PMID:26110413

Computer-aided programming for message-passing system; Problems and a solution

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

Wu, M.Y.; Gajski, D.D.

1989-12-01

As the number of processors and the complexity of problems to be solved increase, programming multiprocessing systems becomes more difficult and error-prone. Program development tools are necessary since programmers are not able to develop complex parallel programs efficiently. Parallel models of computation, parallelization problems, and tools for computer-aided programming (CAP) are discussed. As an example, a CAP tool that performs scheduling and inserts communication primitives automatically is described. It also generates the performance estimates and other program quality measures to help programmers in improving their algorithms and programs.

Art and Technology: Computers in the Studio?

ERIC Educational Resources Information Center

Ruby-Baird, Janet

1997-01-01

Because the graphic industry demands graduates with computer skills, art students want college programs that include complex computer technologies. However, students can produce good computer art only if they have mastered traditional drawing and design skills. Discusses designing an art curriculum including both technology and traditional course…

Distributed processor allocation for launching applications in a massively connected processors complex

DOEpatents

Pedretti, Kevin

2008-11-18

A compute processor allocator architecture for allocating compute processors to run applications in a multiple processor computing apparatus is distributed among a subset of processors within the computing apparatus. Each processor of the subset includes a compute processor allocator. The compute processor allocators can share a common database of information pertinent to compute processor allocation. A communication path permits retrieval of information from the database independently of the compute processor allocators.

Complex Functions with GeoGebra

ERIC Educational Resources Information Center

Breda, Ana Maria D'azevedo; Dos Santos, José Manuel Dos Santos

2016-01-01

Complex functions, generally feature some interesting peculiarities, seen as extensions of real functions. The visualization of complex functions properties usually requires the simultaneous visualization of two-dimensional spaces. The multiple Windows of GeoGebra, combined with its ability of algebraic computation with complex numbers, allow the…

The services-oriented architecture: ecosystem services as a framework for diagnosing change in social ecological systems

Treesearch

Philip A. Loring; F. Stuart Chapin; S. Craig Gerlach

2008-01-01

Computational thinking (CT) is a way to solve problems and understand complex systems that draws on concepts fundamental to computer science and is well suited to the challenges that face researchers of complex, linked social-ecological systems. This paper explores CT's usefulness to sustainability science through the application of the services-oriented...

Optimal shield mass distribution for space radiation protection

NASA Technical Reports Server (NTRS)

Billings, M. P.

1972-01-01

Computational methods have been developed and successfully used for determining the optimum distribution of space radiation shielding on geometrically complex space vehicles. These methods have been incorporated in computer program SWORD for dose evaluation in complex geometry, and iteratively calculating the optimum distribution for (minimum) shield mass satisfying multiple acute and protected dose constraints associated with each of several body organs.

How Does Viewing One Computer Animation Affect Students' Interpretations of Another Animation Depicting the Same Oxidation-Reduction Reaction?

ERIC Educational Resources Information Center

Rosenthal, Deborah P.; Sanger, Michael J.

2013-01-01

Two groups of students were shown unnarrated versions of two different particulate-level computer animations of varying complexity depicting the oxidation-reduction reaction of aqueous silver nitrate and solid copper metal; one group saw the more simplified animation first and the more complex animation second while the other group saw these…

Geometry of Quantum Computation with Qudits

PubMed Central

Luo, Ming-Xing; Chen, Xiu-Bo; Yang, Yi-Xian; Wang, Xiaojun

2014-01-01

The circuit complexity of quantum qubit system evolution as a primitive problem in quantum computation has been discussed widely. We investigate this problem in terms of qudit system. Using the Riemannian geometry the optimal quantum circuits are equivalent to the geodetic evolutions in specially curved parametrization of SU(dn). And the quantum circuit complexity is explicitly dependent of controllable approximation error bound. PMID:24509710

Student Misinterpretations and Misconceptions Based on Their Explanations of Two Computer Animations of Varying Complexity Depicting the Same Oxidation-Reduction Reaction

ERIC Educational Resources Information Center

Rosenthal, Deborah P.; Sanger, Michael J.

2012-01-01

A group of 55 students were shown unnarrated versions of two different particulate-level computer animations of varying complexity depicting the oxidation-reduction reaction of aqueous silver nitrate and solid copper metal. These students were asked to explain their understanding of the chemical reaction based on their interpretations of these…

Applications in Data-Intensive Computing

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

Shah, Anuj R.; Adkins, Joshua N.; Baxter, Douglas J.

2010-04-01

This book chapter, to be published in Advances in Computers, Volume 78, in 2010 describes applications of data intensive computing (DIC). This is an invited chapter resulting from a previous publication on DIC. This work summarizes efforts coming out of the PNNL's Data Intensive Computing Initiative. Advances in technology have empowered individuals with the ability to generate digital content with mouse clicks and voice commands. Digital pictures, emails, text messages, home videos, audio, and webpages are common examples of digital content that are generated on a regular basis. Data intensive computing facilitates human understanding of complex problems. Data-intensive applications providemore » timely and meaningful analytical results in response to exponentially growing data complexity and associated analysis requirements through the development of new classes of software, algorithms, and hardware.« less

COMPUTATIONAL METHODOLOGIES for REAL-SPACE STRUCTURAL REFINEMENT of LARGE MACROMOLECULAR COMPLEXES

PubMed Central

Goh, Boon Chong; Hadden, Jodi A.; Bernardi, Rafael C.; Singharoy, Abhishek; McGreevy, Ryan; Rudack, Till; Cassidy, C. Keith; Schulten, Klaus

2017-01-01

The rise of the computer as a powerful tool for model building and refinement has revolutionized the field of structure determination for large biomolecular systems. Despite the wide availability of robust experimental methods capable of resolving structural details across a range of spatiotemporal resolutions, computational hybrid methods have the unique ability to integrate the diverse data from multimodal techniques such as X-ray crystallography and electron microscopy into consistent, fully atomistic structures. Here, commonly employed strategies for computational real-space structural refinement are reviewed, and their specific applications are illustrated for several large macromolecular complexes: ribosome, virus capsids, chemosensory array, and photosynthetic chromatophore. The increasingly important role of computational methods in large-scale structural refinement, along with current and future challenges, is discussed. PMID:27145875

The Nash Equilibrium Revisited: Chaos and Complexity Hidden in Simplicity

NASA Astrophysics Data System (ADS)

Fellman, Philip V.

The Nash Equilibrium is a much discussed, deceptively complex, method for the analysis of non-cooperative games (McLennan and Berg, 2005). If one reads many of the commonly available definitions the description of the Nash Equilibrium is deceptively simple in appearance. Modern research has discovered a number of new and important complex properties of the Nash Equilibrium, some of which remain as contemporary conundrums of extraordinary difficulty and complexity (Quint and Shubik, 1997). Among the recently discovered features which the Nash Equilibrium exhibits under various conditions are heteroclinic Hamiltonian dynamics, a very complex asymptotic structure in the context of two-player bi-matrix games and a number of computationally complex or computationally intractable features in other settings (Sato, Akiyama and Farmer, 2002). This paper reviews those findings and then suggests how they may inform various market prediction strategies.

Design of convolutional tornado code

NASA Astrophysics Data System (ADS)

Zhou, Hui; Yang, Yao; Gao, Hongmin; Tan, Lu

2017-09-01

As a linear block code, the traditional tornado (tTN) code is inefficient in burst-erasure environment and its multi-level structure may lead to high encoding/decoding complexity. This paper presents a convolutional tornado (cTN) code which is able to improve the burst-erasure protection capability by applying the convolution property to the tTN code, and reduce computational complexity by abrogating the multi-level structure. The simulation results show that cTN code can provide a better packet loss protection performance with lower computation complexity than tTN code.

General Electromagnetic Model for the Analysis of Complex Systems (GEMACS) Computer Code Documentation (Version 3). Volume 3, Part 4.

DTIC Science & Technology

1983-09-01

6ENFRAL. ELECTROMAGNETIC MODEL FOR THE ANALYSIS OF COMPLEX SYSTEMS **%(GEMA CS) Computer Code Documentation ii( Version 3 ). A the BDM Corporation Dr...ANALYSIS FnlTcnclRpr F COMPLEX SYSTEM (GmCS) February 81 - July 83- I TR CODE DOCUMENTATION (Version 3 ) 6.PROMN N.REPORT NUMBER 5. CONTRACT ORGAT97...the ti and t2 directions on the source patch. 3 . METHOD: The electric field at a segment observation point due to the source patch j is given by 1-- lnA

Hafnium-Based Contrast Agents for X-ray Computed Tomography.

PubMed

Berger, Markus; Bauser, Marcus; Frenzel, Thomas; Hilger, Christoph Stephan; Jost, Gregor; Lauria, Silvia; Morgenstern, Bernd; Neis, Christian; Pietsch, Hubertus; Sülzle, Detlev; Hegetschweiler, Kaspar

2017-05-15

Heavy-metal-based contrast agents (CAs) offer enhanced X-ray absorption for X-ray computed tomography (CT) compared to the currently used iodinated CAs. We report the discovery of new lanthanide and hafnium azainositol complexes and their optimization with respect to high water solubility and stability. Our efforts culminated in the synthesis of BAY-576, an uncharged hafnium complex with 3:2 stoichiometry and broken complex symmetry. The superior properties of this asymmetrically substituted hafnium CA were demonstrated by a CT angiography study in rabbits that revealed excellent signal contrast enhancement.

Computational modelling of oxygenation processes in enzymes and biomimetic model complexes.

PubMed

de Visser, Sam P; Quesne, Matthew G; Martin, Bodo; Comba, Peter; Ryde, Ulf

2014-01-11

With computational resources becoming more efficient and more powerful and at the same time cheaper, computational methods have become more and more popular for studies on biochemical and biomimetic systems. Although large efforts from the scientific community have gone into exploring the possibilities of computational methods for studies on large biochemical systems, such studies are not without pitfalls and often cannot be routinely done but require expert execution. In this review we summarize and highlight advances in computational methodology and its application to enzymatic and biomimetic model complexes. In particular, we emphasize on topical and state-of-the-art methodologies that are able to either reproduce experimental findings, e.g., spectroscopic parameters and rate constants, accurately or make predictions of short-lived intermediates and fast reaction processes in nature. Moreover, we give examples of processes where certain computational methods dramatically fail.

Collaborative Working Architecture for IoT-Based Applications.

PubMed

Mora, Higinio; Signes-Pont, María Teresa; Gil, David; Johnsson, Magnus

2018-05-23

The new sensing applications need enhanced computing capabilities to handle the requirements of complex and huge data processing. The Internet of Things (IoT) concept brings processing and communication features to devices. In addition, the Cloud Computing paradigm provides resources and infrastructures for performing the computations and outsourcing the work from the IoT devices. This scenario opens new opportunities for designing advanced IoT-based applications, however, there is still much research to be done to properly gear all the systems for working together. This work proposes a collaborative model and an architecture to take advantage of the available computing resources. The resulting architecture involves a novel network design with different levels which combines sensing and processing capabilities based on the Mobile Cloud Computing (MCC) paradigm. An experiment is included to demonstrate that this approach can be used in diverse real applications. The results show the flexibility of the architecture to perform complex computational tasks of advanced applications.

The dynamics of discrete-time computation, with application to recurrent neural networks and finite state machine extraction.

PubMed

Casey, M

1996-08-15

Recurrent neural networks (RNNs) can learn to perform finite state computations. It is shown that an RNN performing a finite state computation must organize its state space to mimic the states in the minimal deterministic finite state machine that can perform that computation, and a precise description of the attractor structure of such systems is given. This knowledge effectively predicts activation space dynamics, which allows one to understand RNN computation dynamics in spite of complexity in activation dynamics. This theory provides a theoretical framework for understanding finite state machine (FSM) extraction techniques and can be used to improve training methods for RNNs performing FSM computations. This provides an example of a successful approach to understanding a general class of complex systems that has not been explicitly designed, e.g., systems that have evolved or learned their internal structure.

[Computer game addiction: a psychopathological symptom complex in adolescence].

PubMed

Wölfling, Klaus; Thalemann, Ralf; Grüsser-Sinopoli, Sabine M

2008-07-01

Cases of excessive computer gaming are increasingly reported by practitioners in the psychiatric field. Since there is no standardized definition of this symptom complex, the aim of this study is to access excessive computer gaming in German adolescents as an addictive disorder and its potential negative consequences. Psychopathological computer gaming behavior was diagnosed by applying the adapted diagnostic criteria of substance-related-addictions as defined by the ICD-10. At the same time demographic variables, state of clinical anxiety and underlying cognitive mechanisms were analyzed. 6.3 % of the 221 participating pupils - mostly boys with a low educational background - fulfilled the diagnostic criteria of a behavioral addiction. Clinically diagnosed adolescents exhibited limited cognitive flexibility and were identified to utilize computer gaming as a mood management strategy. These results can be interpreted as a first hint for a prevalence estimation of psychopathological computer gaming in German adolescents.

The emergence of mind and brain: an evolutionary, computational, and philosophical approach.

PubMed

Mainzer, Klaus

2008-01-01

Modern philosophy of mind cannot be understood without recent developments in computer science, artificial intelligence (AI), robotics, neuroscience, biology, linguistics, and psychology. Classical philosophy of formal languages as well as symbolic AI assume that all kinds of knowledge must explicitly be represented by formal or programming languages. This assumption is limited by recent insights into the biology of evolution and developmental psychology of the human organism. Most of our knowledge is implicit and unconscious. It is not formally represented, but embodied knowledge, which is learnt by doing and understood by bodily interacting with changing environments. That is true not only for low-level skills, but even for high-level domains of categorization, language, and abstract thinking. The embodied mind is considered an emergent capacity of the brain as a self-organizing complex system. Actually, self-organization has been a successful strategy of evolution to handle the increasing complexity of the world. Genetic programs are not sufficient and cannot prepare the organism for all kinds of complex situations in the future. Self-organization and emergence are fundamental concepts in the theory of complex dynamical systems. They are also applied in organic computing as a recent research field of computer science. Therefore, cognitive science, AI, and robotics try to model the embodied mind in an artificial evolution. The paper analyzes these approaches in the interdisciplinary framework of complex dynamical systems and discusses their philosophical impact.

Simulated parallel annealing within a neighborhood for optimization of biomechanical systems.

PubMed

Higginson, J S; Neptune, R R; Anderson, F C

2005-09-01

Optimization problems for biomechanical systems have become extremely complex. Simulated annealing (SA) algorithms have performed well in a variety of test problems and biomechanical applications; however, despite advances in computer speed, convergence to optimal solutions for systems of even moderate complexity has remained prohibitive. The objective of this study was to develop a portable parallel version of a SA algorithm for solving optimization problems in biomechanics. The algorithm for simulated parallel annealing within a neighborhood (SPAN) was designed to minimize interprocessor communication time and closely retain the heuristics of the serial SA algorithm. The computational speed of the SPAN algorithm scaled linearly with the number of processors on different computer platforms for a simple quadratic test problem and for a more complex forward dynamic simulation of human pedaling.

Overset grid applications on distributed memory MIMD computers

NASA Technical Reports Server (NTRS)

Chawla, Kalpana; Weeratunga, Sisira

1994-01-01

Analysis of modern aerospace vehicles requires the computation of flowfields about complex three dimensional geometries composed of regions with varying spatial resolution requirements. Overset grid methods allow the use of proven structured grid flow solvers to address the twin issues of geometrical complexity and the resolution variation by decomposing the complex physical domain into a collection of overlapping subdomains. This flexibility is accompanied by the need for irregular intergrid boundary communication among the overlapping component grids. This study investigates a strategy for implementing such a static overset grid implicit flow solver on distributed memory, MIMD computers; i.e., the 128 node Intel iPSC/860 and the 208 node Intel Paragon. Performance data for two composite grid configurations characteristic of those encountered in present day aerodynamic analysis are also presented.

Computational Thinking in the Wild: Uncovering Complex Collaborative Thinking through Gameplay

ERIC Educational Resources Information Center

Berland, Matthew; Duncan, Sean

2016-01-01

Surprisingly few empirical studies address how computational thinking works "in the wild" or how games and simulations can support developing computational thinking skills. In this article, the authors report results from a study of computational thinking (CT) as evinced through player discussions around the collaborative board game…

Teaching Reductive Thinking

ERIC Educational Resources Information Center

Armoni, Michal; Gal-Ezer, Judith

2005-01-01

When dealing with a complex problem, solving it by reduction to simpler problems, or problems for which the solution is already known, is a common method in mathematics and other scientific disciplines, as in computer science and, specifically, in the field of computability. However, when teaching computational models (as part of computability)…

On Evaluating Human Problem Solving of Computationally Hard Problems

ERIC Educational Resources Information Center

Carruthers, Sarah; Stege, Ulrike

2013-01-01

This article is concerned with how computer science, and more exactly computational complexity theory, can inform cognitive science. In particular, we suggest factors to be taken into account when investigating how people deal with computational hardness. This discussion will address the two upper levels of Marr's Level Theory: the computational…

Analysis of Software Systems for Specialized Computers,

DTIC Science & Technology

computer) with given computer hardware and software . The object of study is the software system of a computer, designed for solving a fixed complex of...purpose of the analysis is to find parameters that characterize the system and its elements during operation, i.e., when servicing the given requirement flow. (Author)

Fast computation of derivative based sensitivities of PSHA models via algorithmic differentiation

NASA Astrophysics Data System (ADS)

Leövey, Hernan; Molkenthin, Christian; Scherbaum, Frank; Griewank, Andreas; Kuehn, Nicolas; Stafford, Peter

2015-04-01

Probabilistic seismic hazard analysis (PSHA) is the preferred tool for estimation of potential ground-shaking hazard due to future earthquakes at a site of interest. A modern PSHA represents a complex framework which combines different models with possible many inputs. Sensitivity analysis is a valuable tool for quantifying changes of a model output as inputs are perturbed, identifying critical input parameters and obtaining insight in the model behavior. Differential sensitivity analysis relies on calculating first-order partial derivatives of the model output with respect to its inputs. Moreover, derivative based global sensitivity measures (Sobol' & Kucherenko '09) can be practically used to detect non-essential inputs of the models, thus restricting the focus of attention to a possible much smaller set of inputs. Nevertheless, obtaining first-order partial derivatives of complex models with traditional approaches can be very challenging, and usually increases the computation complexity linearly with the number of inputs appearing in the models. In this study we show how Algorithmic Differentiation (AD) tools can be used in a complex framework such as PSHA to successfully estimate derivative based sensitivities, as is the case in various other domains such as meteorology or aerodynamics, without no significant increase in the computation complexity required for the original computations. First we demonstrate the feasibility of the AD methodology by comparing AD derived sensitivities to analytically derived sensitivities for a basic case of PSHA using a simple ground-motion prediction equation. In a second step, we derive sensitivities via AD for a more complex PSHA study using a ground motion attenuation relation based on a stochastic method to simulate strong motion. The presented approach is general enough to accommodate more advanced PSHA studies of higher complexity.

Petascale self-consistent electromagnetic computations using scalable and accurate algorithms for complex structures

NASA Astrophysics Data System (ADS)

Cary, John R.; Abell, D.; Amundson, J.; Bruhwiler, D. L.; Busby, R.; Carlsson, J. A.; Dimitrov, D. A.; Kashdan, E.; Messmer, P.; Nieter, C.; Smithe, D. N.; Spentzouris, P.; Stoltz, P.; Trines, R. M.; Wang, H.; Werner, G. R.

2006-09-01

As the size and cost of particle accelerators escalate, high-performance computing plays an increasingly important role; optimization through accurate, detailed computermodeling increases performance and reduces costs. But consequently, computer simulations face enormous challenges. Early approximation methods, such as expansions in distance from the design orbit, were unable to supply detailed accurate results, such as in the computation of wake fields in complex cavities. Since the advent of message-passing supercomputers with thousands of processors, earlier approximations are no longer necessary, and it is now possible to compute wake fields, the effects of dampers, and self-consistent dynamics in cavities accurately. In this environment, the focus has shifted towards the development and implementation of algorithms that scale to large numbers of processors. So-called charge-conserving algorithms evolve the electromagnetic fields without the need for any global solves (which are difficult to scale up to many processors). Using cut-cell (or embedded) boundaries, these algorithms can simulate the fields in complex accelerator cavities with curved walls. New implicit algorithms, which are stable for any time-step, conserve charge as well, allowing faster simulation of structures with details small compared to the characteristic wavelength. These algorithmic and computational advances have been implemented in the VORPAL7 Framework, a flexible, object-oriented, massively parallel computational application that allows run-time assembly of algorithms and objects, thus composing an application on the fly.

Digitized adiabatic quantum computing with a superconducting circuit.

PubMed

Barends, R; Shabani, A; Lamata, L; Kelly, J; Mezzacapo, A; Las Heras, U; Babbush, R; Fowler, A G; Campbell, B; Chen, Yu; Chen, Z; Chiaro, B; Dunsworth, A; Jeffrey, E; Lucero, E; Megrant, A; Mutus, J Y; Neeley, M; Neill, C; O'Malley, P J J; Quintana, C; Roushan, P; Sank, D; Vainsencher, A; Wenner, J; White, T C; Solano, E; Neven, H; Martinis, John M

2016-06-09

Quantum mechanics can help to solve complex problems in physics and chemistry, provided they can be programmed in a physical device. In adiabatic quantum computing, a system is slowly evolved from the ground state of a simple initial Hamiltonian to a final Hamiltonian that encodes a computational problem. The appeal of this approach lies in the combination of simplicity and generality; in principle, any problem can be encoded. In practice, applications are restricted by limited connectivity, available interactions and noise. A complementary approach is digital quantum computing, which enables the construction of arbitrary interactions and is compatible with error correction, but uses quantum circuit algorithms that are problem-specific. Here we combine the advantages of both approaches by implementing digitized adiabatic quantum computing in a superconducting system. We tomographically probe the system during the digitized evolution and explore the scaling of errors with system size. We then let the full system find the solution to random instances of the one-dimensional Ising problem as well as problem Hamiltonians that involve more complex interactions. This digital quantum simulation of the adiabatic algorithm consists of up to nine qubits and up to 1,000 quantum logic gates. The demonstration of digitized adiabatic quantum computing in the solid state opens a path to synthesizing long-range correlations and solving complex computational problems. When combined with fault-tolerance, our approach becomes a general-purpose algorithm that is scalable.

Does Cloud Computing in the Atmospheric Sciences Make Sense? A case study of hybrid cloud computing at NASA Langley Research Center

NASA Astrophysics Data System (ADS)

Nguyen, L.; Chee, T.; Minnis, P.; Spangenberg, D.; Ayers, J. K.; Palikonda, R.; Vakhnin, A.; Dubois, R.; Murphy, P. R.

2014-12-01

The processing, storage and dissemination of satellite cloud and radiation products produced at NASA Langley Research Center are key activities for the Climate Science Branch. A constellation of systems operates in sync to accomplish these goals. Because of the complexity involved with operating such intricate systems, there are both high failure rates and high costs for hardware and system maintenance. Cloud computing has the potential to ameliorate cost and complexity issues. Over time, the cloud computing model has evolved and hybrid systems comprising off-site as well as on-site resources are now common. Towards our mission of providing the highest quality research products to the widest audience, we have explored the use of the Amazon Web Services (AWS) Cloud and Storage and present a case study of our results and efforts. This project builds upon NASA Langley Cloud and Radiation Group's experience with operating large and complex computing infrastructures in a reliable and cost effective manner to explore novel ways to leverage cloud computing resources in the atmospheric science environment. Our case study presents the project requirements and then examines the fit of AWS with the LaRC computing model. We also discuss the evaluation metrics, feasibility, and outcomes and close the case study with the lessons we learned that would apply to others interested in exploring the implementation of the AWS system in their own atmospheric science computing environments.

Minimized state complexity of quantum-encoded cryptic processes

NASA Astrophysics Data System (ADS)

Riechers, Paul M.; Mahoney, John R.; Aghamohammadi, Cina; Crutchfield, James P.

2016-05-01

The predictive information required for proper trajectory sampling of a stochastic process can be more efficiently transmitted via a quantum channel than a classical one. This recent discovery allows quantum information processing to drastically reduce the memory necessary to simulate complex classical stochastic processes. It also points to a new perspective on the intrinsic complexity that nature must employ in generating the processes we observe. The quantum advantage increases with codeword length: the length of process sequences used in constructing the quantum communication scheme. In analogy with the classical complexity measure, statistical complexity, we use this reduced communication cost as an entropic measure of state complexity in the quantum representation. Previously difficult to compute, the quantum advantage is expressed here in closed form using spectral decomposition. This allows for efficient numerical computation of the quantum-reduced state complexity at all encoding lengths, including infinite. Additionally, it makes clear how finite-codeword reduction in state complexity is controlled by the classical process's cryptic order, and it allows asymptotic analysis of infinite-cryptic-order processes.

Improving the analysis, storage and sharing of neuroimaging data using relational databases and distributed computing.

PubMed

Hasson, Uri; Skipper, Jeremy I; Wilde, Michael J; Nusbaum, Howard C; Small, Steven L

2008-01-15

The increasingly complex research questions addressed by neuroimaging research impose substantial demands on computational infrastructures. These infrastructures need to support management of massive amounts of data in a way that affords rapid and precise data analysis, to allow collaborative research, and to achieve these aims securely and with minimum management overhead. Here we present an approach that overcomes many current limitations in data analysis and data sharing. This approach is based on open source database management systems that support complex data queries as an integral part of data analysis, flexible data sharing, and parallel and distributed data processing using cluster computing and Grid computing resources. We assess the strengths of these approaches as compared to current frameworks based on storage of binary or text files. We then describe in detail the implementation of such a system and provide a concrete description of how it was used to enable a complex analysis of fMRI time series data.

Mathematical and Computational Modeling in Complex Biological Systems

PubMed Central

Li, Wenyang; Zhu, Xiaoliang

2017-01-01

The biological process and molecular functions involved in the cancer progression remain difficult to understand for biologists and clinical doctors. Recent developments in high-throughput technologies urge the systems biology to achieve more precise models for complex diseases. Computational and mathematical models are gradually being used to help us understand the omics data produced by high-throughput experimental techniques. The use of computational models in systems biology allows us to explore the pathogenesis of complex diseases, improve our understanding of the latent molecular mechanisms, and promote treatment strategy optimization and new drug discovery. Currently, it is urgent to bridge the gap between the developments of high-throughput technologies and systemic modeling of the biological process in cancer research. In this review, we firstly studied several typical mathematical modeling approaches of biological systems in different scales and deeply analyzed their characteristics, advantages, applications, and limitations. Next, three potential research directions in systems modeling were summarized. To conclude, this review provides an update of important solutions using computational modeling approaches in systems biology. PMID:28386558

Mathematical and Computational Modeling in Complex Biological Systems.

PubMed

Ji, Zhiwei; Yan, Ke; Li, Wenyang; Hu, Haigen; Zhu, Xiaoliang

2017-01-01

The biological process and molecular functions involved in the cancer progression remain difficult to understand for biologists and clinical doctors. Recent developments in high-throughput technologies urge the systems biology to achieve more precise models for complex diseases. Computational and mathematical models are gradually being used to help us understand the omics data produced by high-throughput experimental techniques. The use of computational models in systems biology allows us to explore the pathogenesis of complex diseases, improve our understanding of the latent molecular mechanisms, and promote treatment strategy optimization and new drug discovery. Currently, it is urgent to bridge the gap between the developments of high-throughput technologies and systemic modeling of the biological process in cancer research. In this review, we firstly studied several typical mathematical modeling approaches of biological systems in different scales and deeply analyzed their characteristics, advantages, applications, and limitations. Next, three potential research directions in systems modeling were summarized. To conclude, this review provides an update of important solutions using computational modeling approaches in systems biology.

Improving the Analysis, Storage and Sharing of Neuroimaging Data using Relational Databases and Distributed Computing

PubMed Central

Hasson, Uri; Skipper, Jeremy I.; Wilde, Michael J.; Nusbaum, Howard C.; Small, Steven L.

2007-01-01

The increasingly complex research questions addressed by neuroimaging research impose substantial demands on computational infrastructures. These infrastructures need to support management of massive amounts of data in a way that affords rapid and precise data analysis, to allow collaborative research, and to achieve these aims securely and with minimum management overhead. Here we present an approach that overcomes many current limitations in data analysis and data sharing. This approach is based on open source database management systems that support complex data queries as an integral part of data analysis, flexible data sharing, and parallel and distributed data processing using cluster computing and Grid computing resources. We assess the strengths of these approaches as compared to current frameworks based on storage of binary or text files. We then describe in detail the implementation of such a system and provide a concrete description of how it was used to enable a complex analysis of fMRI time series data. PMID:17964812

Adiabatic quantum computation

NASA Astrophysics Data System (ADS)

Albash, Tameem; Lidar, Daniel A.

2018-01-01

Adiabatic quantum computing (AQC) started as an approach to solving optimization problems and has evolved into an important universal alternative to the standard circuit model of quantum computing, with deep connections to both classical and quantum complexity theory and condensed matter physics. This review gives an account of the major theoretical developments in the field, while focusing on the closed-system setting. The review is organized around a series of topics that are essential to an understanding of the underlying principles of AQC, its algorithmic accomplishments and limitations, and its scope in the more general setting of computational complexity theory. Several variants are presented of the adiabatic theorem, the cornerstone of AQC, and examples are given of explicit AQC algorithms that exhibit a quantum speedup. An overview of several proofs of the universality of AQC and related Hamiltonian quantum complexity theory is given. Considerable space is devoted to stoquastic AQC, the setting of most AQC work to date, where obstructions to success and their possible resolutions are discussed.

Parallel Markov chain Monte Carlo - bridging the gap to high-performance Bayesian computation in animal breeding and genetics.

PubMed

Wu, Xiao-Lin; Sun, Chuanyu; Beissinger, Timothy M; Rosa, Guilherme Jm; Weigel, Kent A; Gatti, Natalia de Leon; Gianola, Daniel

2012-09-25

Most Bayesian models for the analysis of complex traits are not analytically tractable and inferences are based on computationally intensive techniques. This is true of Bayesian models for genome-enabled selection, which uses whole-genome molecular data to predict the genetic merit of candidate animals for breeding purposes. In this regard, parallel computing can overcome the bottlenecks that can arise from series computing. Hence, a major goal of the present study is to bridge the gap to high-performance Bayesian computation in the context of animal breeding and genetics. Parallel Monte Carlo Markov chain algorithms and strategies are described in the context of animal breeding and genetics. Parallel Monte Carlo algorithms are introduced as a starting point including their applications to computing single-parameter and certain multiple-parameter models. Then, two basic approaches for parallel Markov chain Monte Carlo are described: one aims at parallelization within a single chain; the other is based on running multiple chains, yet some variants are discussed as well. Features and strategies of the parallel Markov chain Monte Carlo are illustrated using real data, including a large beef cattle dataset with 50K SNP genotypes. Parallel Markov chain Monte Carlo algorithms are useful for computing complex Bayesian models, which does not only lead to a dramatic speedup in computing but can also be used to optimize model parameters in complex Bayesian models. Hence, we anticipate that use of parallel Markov chain Monte Carlo will have a profound impact on revolutionizing the computational tools for genomic selection programs.

Parallel Markov chain Monte Carlo - bridging the gap to high-performance Bayesian computation in animal breeding and genetics

PubMed Central

2012-01-01

Background Most Bayesian models for the analysis of complex traits are not analytically tractable and inferences are based on computationally intensive techniques. This is true of Bayesian models for genome-enabled selection, which uses whole-genome molecular data to predict the genetic merit of candidate animals for breeding purposes. In this regard, parallel computing can overcome the bottlenecks that can arise from series computing. Hence, a major goal of the present study is to bridge the gap to high-performance Bayesian computation in the context of animal breeding and genetics. Results Parallel Monte Carlo Markov chain algorithms and strategies are described in the context of animal breeding and genetics. Parallel Monte Carlo algorithms are introduced as a starting point including their applications to computing single-parameter and certain multiple-parameter models. Then, two basic approaches for parallel Markov chain Monte Carlo are described: one aims at parallelization within a single chain; the other is based on running multiple chains, yet some variants are discussed as well. Features and strategies of the parallel Markov chain Monte Carlo are illustrated using real data, including a large beef cattle dataset with 50K SNP genotypes. Conclusions Parallel Markov chain Monte Carlo algorithms are useful for computing complex Bayesian models, which does not only lead to a dramatic speedup in computing but can also be used to optimize model parameters in complex Bayesian models. Hence, we anticipate that use of parallel Markov chain Monte Carlo will have a profound impact on revolutionizing the computational tools for genomic selection programs. PMID:23009363

Computation of scattering matrix elements of large and complex shaped absorbing particles with multilevel fast multipole algorithm

NASA Astrophysics Data System (ADS)

Wu, Yueqian; Yang, Minglin; Sheng, Xinqing; Ren, Kuan Fang

2015-05-01

Light scattering properties of absorbing particles, such as the mineral dusts, attract a wide attention due to its importance in geophysical and environment researches. Due to the absorbing effect, light scattering properties of particles with absorption differ from those without absorption. Simple shaped absorbing particles such as spheres and spheroids have been well studied with different methods but little work on large complex shaped particles has been reported. In this paper, the surface Integral Equation (SIE) with Multilevel Fast Multipole Algorithm (MLFMA) is applied to study scattering properties of large non-spherical absorbing particles. SIEs are carefully discretized with piecewise linear basis functions on triangle patches to model whole surface of the particle, hence computation resource needs increase much more slowly with the particle size parameter than the volume discretized methods. To improve further its capability, MLFMA is well parallelized with Message Passing Interface (MPI) on distributed memory computer platform. Without loss of generality, we choose the computation of scattering matrix elements of absorbing dust particles as an example. The comparison of the scattering matrix elements computed by our method and the discrete dipole approximation method (DDA) for an ellipsoid dust particle shows that the precision of our method is very good. The scattering matrix elements of large ellipsoid dusts with different aspect ratios and size parameters are computed. To show the capability of the presented algorithm for complex shaped particles, scattering by asymmetry Chebyshev particle with size parameter larger than 600 of complex refractive index m = 1.555 + 0.004 i and different orientations are studied.

Computational Models of Consumer Confidence from Large-Scale Online Attention Data: Crowd-Sourcing Econometrics

PubMed Central

2015-01-01

Economies are instances of complex socio-technical systems that are shaped by the interactions of large numbers of individuals. The individual behavior and decision-making of consumer agents is determined by complex psychological dynamics that include their own assessment of present and future economic conditions as well as those of others, potentially leading to feedback loops that affect the macroscopic state of the economic system. We propose that the large-scale interactions of a nation's citizens with its online resources can reveal the complex dynamics of their collective psychology, including their assessment of future system states. Here we introduce a behavioral index of Chinese Consumer Confidence (C3I) that computationally relates large-scale online search behavior recorded by Google Trends data to the macroscopic variable of consumer confidence. Our results indicate that such computational indices may reveal the components and complex dynamics of consumer psychology as a collective socio-economic phenomenon, potentially leading to improved and more refined economic forecasting. PMID:25826692

Low-complexity R-peak detection for ambulatory fetal monitoring.

PubMed

Rooijakkers, Michael J; Rabotti, Chiara; Oei, S Guid; Mischi, Massimo

2012-07-01

Non-invasive fetal health monitoring during pregnancy is becoming increasingly important because of the increasing number of high-risk pregnancies. Despite recent advances in signal-processing technology, which have enabled fetal monitoring during pregnancy using abdominal electrocardiogram (ECG) recordings, ubiquitous fetal health monitoring is still unfeasible due to the computational complexity of noise-robust solutions. In this paper, an ECG R-peak detection algorithm for ambulatory R-peak detection is proposed, as part of a fetal ECG detection algorithm. The proposed algorithm is optimized to reduce computational complexity, without reducing the R-peak detection performance compared to the existing R-peak detection schemes. Validation of the algorithm is performed on three manually annotated datasets. With a detection error rate of 0.23%, 1.32% and 9.42% on the MIT/BIH Arrhythmia and in-house maternal and fetal databases, respectively, the detection rate of the proposed algorithm is comparable to the best state-of-the-art algorithms, at a reduced computational complexity.

Computational models of consumer confidence from large-scale online attention data: crowd-sourcing econometrics.

PubMed

Dong, Xianlei; Bollen, Johan

2015-01-01

Economies are instances of complex socio-technical systems that are shaped by the interactions of large numbers of individuals. The individual behavior and decision-making of consumer agents is determined by complex psychological dynamics that include their own assessment of present and future economic conditions as well as those of others, potentially leading to feedback loops that affect the macroscopic state of the economic system. We propose that the large-scale interactions of a nation's citizens with its online resources can reveal the complex dynamics of their collective psychology, including their assessment of future system states. Here we introduce a behavioral index of Chinese Consumer Confidence (C3I) that computationally relates large-scale online search behavior recorded by Google Trends data to the macroscopic variable of consumer confidence. Our results indicate that such computational indices may reveal the components and complex dynamics of consumer psychology as a collective socio-economic phenomenon, potentially leading to improved and more refined economic forecasting.

PANORAMA: An approach to performance modeling and diagnosis of extreme-scale workflows

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

Deelman, Ewa; Carothers, Christopher; Mandal, Anirban

Here we report that computational science is well established as the third pillar of scientific discovery and is on par with experimentation and theory. However, as we move closer toward the ability to execute exascale calculations and process the ensuing extreme-scale amounts of data produced by both experiments and computations alike, the complexity of managing the compute and data analysis tasks has grown beyond the capabilities of domain scientists. Therefore, workflow management systems are absolutely necessary to ensure current and future scientific discoveries. A key research question for these workflow management systems concerns the performance optimization of complex calculation andmore » data analysis tasks. The central contribution of this article is a description of the PANORAMA approach for modeling and diagnosing the run-time performance of complex scientific workflows. This approach integrates extreme-scale systems testbed experimentation, structured analytical modeling, and parallel systems simulation into a comprehensive workflow framework called Pegasus for understanding and improving the overall performance of complex scientific workflows.« less

Visual saliency-based fast intracoding algorithm for high efficiency video coding

NASA Astrophysics Data System (ADS)

Zhou, Xin; Shi, Guangming; Zhou, Wei; Duan, Zhemin

2017-01-01

Intraprediction has been significantly improved in high efficiency video coding over H.264/AVC with quad-tree-based coding unit (CU) structure from size 64×64 to 8×8 and more prediction modes. However, these techniques cause a dramatic increase in computational complexity. An intracoding algorithm is proposed that consists of perceptual fast CU size decision algorithm and fast intraprediction mode decision algorithm. First, based on the visual saliency detection, an adaptive and fast CU size decision method is proposed to alleviate intraencoding complexity. Furthermore, a fast intraprediction mode decision algorithm with step halving rough mode decision method and early modes pruning algorithm is presented to selectively check the potential modes and effectively reduce the complexity of computation. Experimental results show that our proposed fast method reduces the computational complexity of the current HM to about 57% in encoding time with only 0.37% increases in BD rate. Meanwhile, the proposed fast algorithm has reasonable peak signal-to-noise ratio losses and nearly the same subjective perceptual quality.

Simple and complex mental subtraction: strategy choice and speed-of-processing differences in younger and older adults.

PubMed

Geary, D C; Frensch, P A; Wiley, J G

1993-06-01

Thirty-six younger adults (10 male, 26 female; ages 18 to 38 years) and 36 older adults (14 male, 22 female; ages 61 to 80 years) completed simple and complex paper-and-pencil subtraction tests and solved a series of simple and complex computer-presented subtraction problems. For the computer task, strategies and solution times were recorded on a trial-by-trial basis. Older Ss used a developmentally more mature mix of problem-solving strategies to solve both simple and complex subtraction problems. Analyses of component scores derived from the solution times suggest that the older Ss are slower at number encoding and number production but faster at executing the borrow procedure. In contrast, groups did not appear to differ in the speed of subtraction fact retrieval. Results from a computational simulation are consistent with the interpretation that older adults' advantage for strategy choices and for the speed of executing the borrow procedure might result from more practice solving subtraction problems.

A High-Order Immersed Boundary Method for Acoustic Wave Scattering and Low-Mach Number Flow-Induced Sound in Complex Geometries

PubMed Central

Seo, Jung Hee; Mittal, Rajat

2010-01-01

A new sharp-interface immersed boundary method based approach for the computation of low-Mach number flow-induced sound around complex geometries is described. The underlying approach is based on a hydrodynamic/acoustic splitting technique where the incompressible flow is first computed using a second-order accurate immersed boundary solver. This is followed by the computation of sound using the linearized perturbed compressible equations (LPCE). The primary contribution of the current work is the development of a versatile, high-order accurate immersed boundary method for solving the LPCE in complex domains. This new method applies the boundary condition on the immersed boundary to a high-order by combining the ghost-cell approach with a weighted least-squares error method based on a high-order approximating polynomial. The method is validated for canonical acoustic wave scattering and flow-induced noise problems. Applications of this technique to relatively complex cases of practical interest are also presented. PMID:21318129

A complex guided spectral transform Lanczos method for studying quantum resonance states

DOE PAGES

Yu, Hua-Gen

2014-12-28

A complex guided spectral transform Lanczos (cGSTL) algorithm is proposed to compute both bound and resonance states including energies, widths and wavefunctions. The algorithm comprises of two layers of complex-symmetric Lanczos iterations. A short inner layer iteration produces a set of complex formally orthogonal Lanczos (cFOL) polynomials. They are used to span the guided spectral transform function determined by a retarded Green operator. An outer layer iteration is then carried out with the transform function to compute the eigen-pairs of the system. The guided spectral transform function is designed to have the same wavefunctions as the eigenstates of the originalmore » Hamiltonian in the spectral range of interest. Therefore the energies and/or widths of bound or resonance states can be easily computed with their wavefunctions or by using a root-searching method from the guided spectral transform surface. The new cGSTL algorithm is applied to bound and resonance states of HO₂, and compared to previous calculations.« less

PANORAMA: An approach to performance modeling and diagnosis of extreme-scale workflows

DOE PAGES

Deelman, Ewa; Carothers, Christopher; Mandal, Anirban; ...

2015-07-14

Here we report that computational science is well established as the third pillar of scientific discovery and is on par with experimentation and theory. However, as we move closer toward the ability to execute exascale calculations and process the ensuing extreme-scale amounts of data produced by both experiments and computations alike, the complexity of managing the compute and data analysis tasks has grown beyond the capabilities of domain scientists. Therefore, workflow management systems are absolutely necessary to ensure current and future scientific discoveries. A key research question for these workflow management systems concerns the performance optimization of complex calculation andmore » data analysis tasks. The central contribution of this article is a description of the PANORAMA approach for modeling and diagnosing the run-time performance of complex scientific workflows. This approach integrates extreme-scale systems testbed experimentation, structured analytical modeling, and parallel systems simulation into a comprehensive workflow framework called Pegasus for understanding and improving the overall performance of complex scientific workflows.« less

Advanced computer architecture for large-scale real-time applications.

DOT National Transportation Integrated Search

1973-04-01

Air traffic control automation is identified as a crucial problem which provides a complex, real-time computer application environment. A novel computer architecture in the form of a pipeline associative processor is conceived to achieve greater perf...

Artificial Intelligence and the Teaching of Reading and Writing by Computers.

ERIC Educational Resources Information Center

Balajthy, Ernest

1985-01-01

Discusses how computers can "converse" with students for teaching purposes, demonstrates how these interactions are becoming more complex, and explains how the computer's role is becoming more "human" in giving intelligent responses to students. (HOD)

Limits on efficient computation in the physical world

NASA Astrophysics Data System (ADS)

Aaronson, Scott Joel

More than a speculative technology, quantum computing seems to challenge our most basic intuitions about how the physical world should behave. In this thesis I show that, while some intuitions from classical computer science must be jettisoned in the light of modern physics, many others emerge nearly unscathed; and I use powerful tools from computational complexity theory to help determine which are which. In the first part of the thesis, I attack the common belief that quantum computing resembles classical exponential parallelism, by showing that quantum computers would face serious limitations on a wider range of problems than was previously known. In particular, any quantum algorithm that solves the collision problem---that of deciding whether a sequence of n integers is one-to-one or two-to-one---must query the sequence O (n1/5) times. This resolves a question that was open for years; previously no lower bound better than constant was known. A corollary is that there is no "black-box" quantum algorithm to break cryptographic hash functions or solve the Graph Isomorphism problem in polynomial time. I also show that relative to an oracle, quantum computers could not solve NP-complete problems in polynomial time, even with the help of nonuniform "quantum advice states"; and that any quantum algorithm needs O (2n/4/n) queries to find a local minimum of a black-box function on the n-dimensional hypercube. Surprisingly, the latter result also leads to new classical lower bounds for the local search problem. Finally, I give new lower bounds on quantum one-way communication complexity, and on the quantum query complexity of total Boolean functions and recursive Fourier sampling. The second part of the thesis studies the relationship of the quantum computing model to physical reality. I first examine the arguments of Leonid Levin, Stephen Wolfram, and others who believe quantum computing to be fundamentally impossible. I find their arguments unconvincing without a "Sure/Shor separator"---a criterion that separates the already-verified quantum states from those that appear in Shor's factoring algorithm. I argue that such a separator should be based on a complexity classification of quantum states, and go on to create such a classification. Next I ask what happens to the quantum computing model if we take into account that the speed of light is finite---and in particular, whether Grover's algorithm still yields a quadratic speedup for searching a database. Refuting a claim by Benioff, I show that the surprising answer is yes. Finally, I analyze hypothetical models of computation that go even beyond quantum computing. I show that many such models would be as powerful as the complexity class PP, and use this fact to give a simple, quantum computing based proof that PP is closed under intersection. On the other hand, I also present one model---wherein we could sample the entire history of a hidden variable---that appears to be more powerful than standard quantum computing, but only slightly so.

Reconfigurable Computing for Computational Science: A New Focus in High Performance Computing

DTIC Science & Technology

2006-11-01

in the past decade. Researchers are regularly employing the power of large computing systems and parallel processing to tackle larger and more...complex problems in all of the physical sciences. For the past decade or so, most of this growth in computing power has been “free” with increased...the scientific computing community as a means to continued growth in computing capability. This paper offers a glimpse of the hardware and

Computation in generalised probabilisitic theories

NASA Astrophysics Data System (ADS)

Lee, Ciarán M.; Barrett, Jonathan

2015-08-01

From the general difficulty of simulating quantum systems using classical systems, and in particular the existence of an efficient quantum algorithm for factoring, it is likely that quantum computation is intrinsically more powerful than classical computation. At present, the best upper bound known for the power of quantum computation is that {{BQP}}\\subseteq {{AWPP}}, where {{AWPP}} is a classical complexity class (known to be included in {{PP}}, hence {{PSPACE}}). This work investigates limits on computational power that are imposed by simple physical, or information theoretic, principles. To this end, we define a circuit-based model of computation in a class of operationally-defined theories more general than quantum theory, and ask: what is the minimal set of physical assumptions under which the above inclusions still hold? We show that given only an assumption of tomographic locality (roughly, that multipartite states and transformations can be characterized by local measurements), efficient computations are contained in {{AWPP}}. This inclusion still holds even without assuming a basic notion of causality (where the notion is, roughly, that probabilities for outcomes cannot depend on future measurement choices). Following Aaronson, we extend the computational model by allowing post-selection on measurement outcomes. Aaronson showed that the corresponding quantum complexity class, {{PostBQP}}, is equal to {{PP}}. Given only the assumption of tomographic locality, the inclusion in {{PP}} still holds for post-selected computation in general theories. Hence in a world with post-selection, quantum theory is optimal for computation in the space of all operational theories. We then consider whether one can obtain relativized complexity results for general theories. It is not obvious how to define a sensible notion of a computational oracle in the general framework that reduces to the standard notion in the quantum case. Nevertheless, it is possible to define computation relative to a ‘classical oracle’. Then, we show there exists a classical oracle relative to which efficient computation in any theory satisfying the causality assumption does not include {{NP}}.

An Approach to Experimental Design for the Computer Analysis of Complex Phenomenon

NASA Technical Reports Server (NTRS)

Rutherford, Brian

2000-01-01

The ability to make credible system assessments, predictions and design decisions related to engineered systems and other complex phenomenon is key to a successful program for many large-scale investigations in government and industry. Recently, many of these large-scale analyses have turned to computational simulation to provide much of the required information. Addressing specific goals in the computer analysis of these complex phenomenon is often accomplished through the use of performance measures that are based on system response models. The response models are constructed using computer-generated responses together with physical test results where possible. They are often based on probabilistically defined inputs and generally require estimation of a set of response modeling parameters. As a consequence, the performance measures are themselves distributed quantities reflecting these variabilities and uncertainties. Uncertainty in the values of the performance measures leads to uncertainties in predicted performance and can cloud the decisions required of the analysis. A specific goal of this research has been to develop methodology that will reduce this uncertainty in an analysis environment where limited resources and system complexity together restrict the number of simulations that can be performed. An approach has been developed that is based on evaluation of the potential information provided for each "intelligently selected" candidate set of computer runs. Each candidate is evaluated by partitioning the performance measure uncertainty into two components - one component that could be explained through the additional computational simulation runs and a second that would remain uncertain. The portion explained is estimated using a probabilistic evaluation of likely results for the additional computational analyses based on what is currently known about the system. The set of runs indicating the largest potential reduction in uncertainty is then selected and the computational simulations are performed. Examples are provided to demonstrate this approach on small scale problems. These examples give encouraging results. Directions for further research are indicated.

Biomechanics of compensatory mechanisms in spinal-pelvic complex

NASA Astrophysics Data System (ADS)

Ivanov, D. V.; Hominets, V. V.; Kirillova, I. V.; Kossovich, L. Yu; Kudyashev, A. L.; Teremshonok, A. V.

2018-04-01

3D geometric solid computer model of spinal-pelvic complex was constructed on the basis of computed tomography and full body X-ray in standing position data. The constructed model was used for biomechanical analysis of compensatory mechanisms arising in the spine with anteversion and retroversion of the pelvis. The results of numerical biomechanical 3D modeling are in good agreement with the clinical data.

On the number of multiplications necessary to compute a length-2 exp n DFT

NASA Technical Reports Server (NTRS)

Heideman, M. T.; Burrus, C. S.

1986-01-01

The number of multiplications necessary and sufficient to compute a length-2 exp n DFT is determined. The method of derivation is shown to apply to the multiplicative complexity results of Winograd (1980, 1981) for a length-p exp n DFT, for p an odd prime number. The multiplicative complexity of the one-dimensional DFT is summarized for many possible lengths.

Computer analysis of potentiometric data of complexes formation in the solution

NASA Astrophysics Data System (ADS)

Jastrzab, Renata; Kaczmarek, Małgorzata T.; Tylkowski, Bartosz; Odani, Akira

2018-02-01

The determination of equilibrium constants is an important process for many branches of chemistry. In this review we provide the readers with a discussion on computer methods which have been applied for elaboration of potentiometric experimental data generated during complexes formation in solution. The review describes both: general basis of modeling tools and examples of the use of calculated stability constants.

On the recognition of complex structures: Computer software using artificial intelligence applied to pattern recognition

NASA Technical Reports Server (NTRS)

Yakimovsky, Y.

1974-01-01

An approach to simultaneous interpretation of objects in complex structures so as to maximize a combined utility function is presented. Results of the application of a computer software system to assign meaning to regions in a segmented image based on the principles described in this paper and on a special interactive sequential classification learning system, which is referenced, are demonstrated.

Theoretical modeling of multiprotein complexes by iSPOT: Integration of small-angle X-ray scattering, hydroxyl radical footprinting, and computational docking.

PubMed

Huang, Wei; Ravikumar, Krishnakumar M; Parisien, Marc; Yang, Sichun

2016-12-01

Structural determination of protein-protein complexes such as multidomain nuclear receptors has been challenging for high-resolution structural techniques. Here, we present a combined use of multiple biophysical methods, termed iSPOT, an integration of shape information from small-angle X-ray scattering (SAXS), protection factors probed by hydroxyl radical footprinting, and a large series of computationally docked conformations from rigid-body or molecular dynamics (MD) simulations. Specifically tested on two model systems, the power of iSPOT is demonstrated to accurately predict the structures of a large protein-protein complex (TGFβ-FKBP12) and a multidomain nuclear receptor homodimer (HNF-4α), based on the structures of individual components of the complexes. Although neither SAXS nor footprinting alone can yield an unambiguous picture for each complex, the combination of both, seamlessly integrated in iSPOT, narrows down the best-fit structures that are about 3.2Å and 4.2Å in RMSD from their corresponding crystal structures, respectively. Furthermore, this proof-of-principle study based on the data synthetically derived from available crystal structures shows that the iSPOT-using either rigid-body or MD-based flexible docking-is capable of overcoming the shortcomings of standalone computational methods, especially for HNF-4α. By taking advantage of the integration of SAXS-based shape information and footprinting-based protection/accessibility as well as computational docking, this iSPOT platform is set to be a powerful approach towards accurate integrated modeling of many challenging multiprotein complexes. Copyright © 2016 Elsevier Inc. All rights reserved.

Parallel approach in RDF query processing

NASA Astrophysics Data System (ADS)

Vajgl, Marek; Parenica, Jan

2017-07-01

Parallel approach is nowadays a very cheap solution to increase computational power due to possibility of usage of multithreaded computational units. This hardware became typical part of nowadays personal computers or notebooks and is widely spread. This contribution deals with experiments how evaluation of computational complex algorithm of the inference over RDF data can be parallelized over graphical cards to decrease computational time.

Novel physical constraints on implementation of computational processes

NASA Astrophysics Data System (ADS)

Wolpert, David; Kolchinsky, Artemy

Non-equilibrium statistical physics permits us to analyze computational processes, i.e., ways to drive a physical system such that its coarse-grained dynamics implements some desired map. It is now known how to implement any such desired computation without dissipating work, and what the minimal (dissipationless) work is that such a computation will require (the so-called generalized Landauer bound\\x9D). We consider how these analyses change if we impose realistic constraints on the computational process. First, we analyze how many degrees of freedom of the system must be controlled, in addition to the ones specifying the information-bearing degrees of freedom, in order to avoid dissipating work during a given computation, when local detailed balance holds. We analyze this issue for deterministic computations, deriving a state-space vs. speed trade-off, and use our results to motivate a measure of the complexity of a computation. Second, we consider computations that are implemented with logic circuits, in which only a small numbers of degrees of freedom are coupled at a time. We show that the way a computation is implemented using circuits affects its minimal work requirements, and relate these minimal work requirements to information-theoretic measures of complexity.

omniClassifier: a Desktop Grid Computing System for Big Data Prediction Modeling

PubMed Central

Phan, John H.; Kothari, Sonal; Wang, May D.

2016-01-01

Robust prediction models are important for numerous science, engineering, and biomedical applications. However, best-practice procedures for optimizing prediction models can be computationally complex, especially when choosing models from among hundreds or thousands of parameter choices. Computational complexity has further increased with the growth of data in these fields, concurrent with the era of “Big Data”. Grid computing is a potential solution to the computational challenges of Big Data. Desktop grid computing, which uses idle CPU cycles of commodity desktop machines, coupled with commercial cloud computing resources can enable research labs to gain easier and more cost effective access to vast computing resources. We have developed omniClassifier, a multi-purpose prediction modeling application that provides researchers with a tool for conducting machine learning research within the guidelines of recommended best-practices. omniClassifier is implemented as a desktop grid computing system using the Berkeley Open Infrastructure for Network Computing (BOINC) middleware. In addition to describing implementation details, we use various gene expression datasets to demonstrate the potential scalability of omniClassifier for efficient and robust Big Data prediction modeling. A prototype of omniClassifier can be accessed at http://omniclassifier.bme.gatech.edu/. PMID:27532062

Drawing the PDB: Protein-Ligand Complexes in Two Dimensions.

PubMed

Stierand, Katrin; Rarey, Matthias

2010-12-09

The two-dimensional representation of molecules is a popular communication medium in chemistry and the associated scientific fields. Computational methods for drawing small molecules with and without manual investigation are well-established and widely spread in terms of numerous software tools. Concerning the planar depiction of molecular complexes, there is considerably less choice. We developed the software PoseView, which automatically generates two-dimensional diagrams of macromolecular complexes, showing the ligand, the interactions, and the interacting residues. All depicted molecules are drawn on an atomic level as structure diagrams; thus, the output plots are clearly structured and easily readable for the scientist. We tested the performance of PoseView in a large-scale application on nearly all druglike complexes of the PDB (approximately 200000 complexes); for more than 92% of the complexes considered for drawing, a layout could be computed. In the following, we will present the results of this application study.

An electrostatic model for the determination of magnetic anisotropy in dysprosium complexes.

PubMed

Chilton, Nicholas F; Collison, David; McInnes, Eric J L; Winpenny, Richard E P; Soncini, Alessandro

2013-01-01

Understanding the anisotropic electronic structure of lanthanide complexes is important in areas as diverse as magnetic resonance imaging, luminescent cell labelling and quantum computing. Here we present an intuitive strategy based on a simple electrostatic method, capable of predicting the magnetic anisotropy of dysprosium(III) complexes, even in low symmetry. The strategy relies only on knowing the X-ray structure of the complex and the well-established observation that, in the absence of high symmetry, the ground state of dysprosium(III) is a doublet quantized along the anisotropy axis with an angular momentum quantum number mJ=±(15)/2. The magnetic anisotropy axis of 14 low-symmetry monometallic dysprosium(III) complexes computed via high-level ab initio calculations are very well reproduced by our electrostatic model. Furthermore, we show that the magnetic anisotropy is equally well predicted in a selection of low-symmetry polymetallic complexes.

HyperForest: A high performance multi-processor architecture for real-time intelligent systems

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

Garcia, P. Jr.; Rebeil, J.P.; Pollard, H.

1997-04-01

Intelligent Systems are characterized by the intensive use of computer power. The computer revolution of the last few years is what has made possible the development of the first generation of Intelligent Systems. Software for second generation Intelligent Systems will be more complex and will require more powerful computing engines in order to meet real-time constraints imposed by new robots, sensors, and applications. A multiprocessor architecture was developed that merges the advantages of message-passing and shared-memory structures: expendability and real-time compliance. The HyperForest architecture will provide an expandable real-time computing platform for computationally intensive Intelligent Systems and open the doorsmore » for the application of these systems to more complex tasks in environmental restoration and cleanup projects, flexible manufacturing systems, and DOE`s own production and disassembly activities.« less

Parametric bicubic spline and CAD tools for complex targets shape modelling in physical optics radar cross section prediction

NASA Astrophysics Data System (ADS)

Delogu, A.; Furini, F.

1991-09-01

Increasing interest in radar cross section (RCS) reduction is placing new demands on theoretical, computation, and graphic techniques for calculating scattering properties of complex targets. In particular, computer codes capable of predicting the RCS of an entire aircraft at high frequency and of achieving RCS control with modest structural changes, are becoming of paramount importance in stealth design. A computer code, evaluating the RCS of arbitrary shaped metallic objects that are computer aided design (CAD) generated, and its validation with measurements carried out using ALENIA RCS test facilities are presented. The code, based on the physical optics method, is characterized by an efficient integration algorithm with error control, in order to contain the computer time within acceptable limits, and by an accurate parametric representation of the target surface in terms of bicubic splines.

Clinical application of computer-designed polystyrene models in complex severe spinal deformities: a pilot study

PubMed Central

Mao, Keya; Xiao, Songhua; Liu, Zhengsheng; Zhang, Yonggang; Zhang, Xuesong; Wang, Zheng; Lu, Ning; Shourong, Zhu; Xifeng, Zhang; Geng, Cui; Baowei, Liu

2010-01-01

Surgical treatment of complex severe spinal deformity, involving a scoliosis Cobb angle of more than 90° and kyphosis or vertebral and rib deformity, is challenging. Preoperative two-dimensional images resulting from plain film radiography, computed tomography (CT) and magnetic resonance imaging provide limited morphometric information. Although the three-dimensional (3D) reconstruction CT with special software can view the stereo and rotate the spinal image on the screen, it cannot show the full-scale spine and cannot directly be used on the operation table. This study was conducted to investigate the application of computer-designed polystyrene models in the treatment of complex severe spinal deformity. The study involved 16 cases of complex severe spinal deformity treated in our hospital between 1 May 2004 and 31 December 2007; the mean ± SD preoperative scoliosis Cobb angle was 118° ± 27°. The CT scanning digital imaging and communication in medicine (DICOM) data sets of the affected spinal segments were collected for 3D digital reconstruction and rapid prototyping to prepare computer-designed polystyrene models, which were applied in the treatment of these cases. The computer-designed polystyrene models allowed 3D observation and measurement of the deformities directly, which helped the surgeon to perform morphological assessment and communicate with the patient and colleagues. Furthermore, the models also guided the choice and placement of pedicle screws. Moreover, the models were used to aid in virtual surgery and guide the actual surgical procedure. The mean ± SD postoperative scoliosis Cobb angle was 42° ± 32°, and no serious complications such as spinal cord or major vascular injury occurred. The use of computer-designed polystyrene models could provide more accurate morphometric information and facilitate surgical correction of complex severe spinal deformity. PMID:20213294

Changing a Generation's Way of Thinking: Teaching Computational Thinking through Programming

ERIC Educational Resources Information Center

Buitrago Flórez, Francisco; Casallas, Rubby; Hernández, Marcela; Reyes, Alejandro; Restrepo, Silvia; Danies, Giovanna

2017-01-01

Computational thinking (CT) uses concepts that are essential to computing and information science to solve problems, design and evaluate complex systems, and understand human reasoning and behavior. This way of thinking has important implications in computer sciences as well as in almost every other field. Therefore, we contend that CT should be…

Building an adiabatic quantum computer simulation in the classroom

NASA Astrophysics Data System (ADS)

Rodríguez-Laguna, Javier; Santalla, Silvia N.

2018-05-01

We present a didactic introduction to adiabatic quantum computation (AQC) via the explicit construction of a classical simulator of quantum computers. This constitutes a suitable route to introduce several important concepts for advanced undergraduates in physics: quantum many-body systems, quantum phase transitions, disordered systems, spin-glasses, and computational complexity theory.

Remote control system for high-perfomance computer simulation of crystal growth by the PFC method

NASA Astrophysics Data System (ADS)

Pavlyuk, Evgeny; Starodumov, Ilya; Osipov, Sergei

2017-04-01

Modeling of crystallization process by the phase field crystal method (PFC) - one of the important directions of modern computational materials science. In this paper, the practical side of the computer simulation of the crystallization process by the PFC method is investigated. To solve problems using this method, it is necessary to use high-performance computing clusters, data storage systems and other often expensive complex computer systems. Access to such resources is often limited, unstable and accompanied by various administrative problems. In addition, the variety of software and settings of different computing clusters sometimes does not allow researchers to use unified program code. There is a need to adapt the program code for each configuration of the computer complex. The practical experience of the authors has shown that the creation of a special control system for computing with the possibility of remote use can greatly simplify the implementation of simulations and increase the performance of scientific research. In current paper we show the principal idea of such a system and justify its efficiency.

"Attention on the flight deck": what ambulatory care providers can learn from pilots about complex coordinated actions.

PubMed

Frankel, Richard M; Saleem, Jason J

2013-12-01

Technical and interpersonal challenges of using electronic health records (EHRs) in ambulatory care persist. We use cockpit communication as an example of highly coordinated complex activity during flight and compare it with providers' communication when computers are used in the exam room. Maximum variation sampling was used to identify two videotapes from a parent study of primary care physicians' exam room computer demonstrating the greatest variation. We then produced and analyzed visualizations of the time providers spent looking at the computer and looking at the patient. Unlike the cockpit which is engineered to optimize joint attention on complex coordinated activities, we found polar extremes in the use of joint focus of attention to manage the medical encounter. We conclude that there is a great deal of room for improving the balance of interpersonal and technical attention that occurs in routine ambulatory visits in which computers are present in the exam room. Using well-known aviation practices can help primary care providers become more aware of the opportunities and challenges for enhancing the physician patient relationship in an era of exam room computing. Published by Elsevier Ireland Ltd.

Streamwise Vorticity Generation in Laminar and Turbulent Jets

NASA Technical Reports Server (NTRS)

Demuren, Aodeji O.; Wilson, Robert V.

1999-01-01

Complex streamwise vorticity fields are observed in the evolution of non-circular jets. Generation mechanisms are investigated via Reynolds-averaged (RANS), large-eddy (LES) and direct numerical (DNS) simulations of laminar and turbulent rectangular jets. Complex vortex interactions are found in DNS of laminar jets, but axis-switching is observed only when a single instability mode is present in the incoming mixing layer. With several modes present, the structures are not coherent and no axis-switching occurs, RANS computations also produce no axis-switching. On the other hand, LES of high Reynolds number turbulent jets produce axis-switching even for cases with several instability modes in the mixing layer. Analysis of the source terms of the mean streamwise vorticity equation through post-processing of the instantaneous results shows that, complex interactions of gradients of the normal and shear Reynolds stresses are responsible for the generation of streamwise vorticity which leads to axis-switching. RANS computations confirm these results. k - epsilon turbulence model computations fail to reproduce the phenomenon, whereas algebraic Reynolds stress model (ASM) computations, in which the secondary normal and shear stresses are computed explicitly, succeeded in reproducing the phenomenon accurately.

A method of extracting ontology module using concept relations for sharing knowledge in mobile cloud computing environment.

PubMed

Lee, Keonsoo; Rho, Seungmin; Lee, Seok-Won

2014-01-01

In mobile cloud computing environment, the cooperation of distributed computing objects is one of the most important requirements for providing successful cloud services. To satisfy this requirement, all the members, who are employed in the cooperation group, need to share the knowledge for mutual understanding. Even if ontology can be the right tool for this goal, there are several issues to make a right ontology. As the cost and complexity of managing knowledge increase according to the scale of the knowledge, reducing the size of ontology is one of the critical issues. In this paper, we propose a method of extracting ontology module to increase the utility of knowledge. For the given signature, this method extracts the ontology module, which is semantically self-contained to fulfill the needs of the service, by considering the syntactic structure and semantic relation of concepts. By employing this module, instead of the original ontology, the cooperation of computing objects can be performed with less computing load and complexity. In particular, when multiple external ontologies need to be combined for more complex services, this method can be used to optimize the size of shared knowledge.

High throughput computing: a solution for scientific analysis

USGS Publications Warehouse

O'Donnell, M.

2011-01-01

handle job failures due to hardware, software, or network interruptions (obviating the need to manually resubmit the job after each stoppage); be affordable; and most importantly, allow us to complete very large, complex analyses that otherwise would not even be possible. In short, we envisioned a job-management system that would take advantage of unused FORT CPUs within a local area network (LAN) to effectively distribute and run highly complex analytical processes. What we found was a solution that uses High Throughput Computing (HTC) and High Performance Computing (HPC) systems to do exactly that (Figure 1).

Equation-free and variable free modeling for complex/multiscale systems. Coarse-grained computation in science and engineering using fine-grained models

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

Kevrekidis, Ioannis G.

The work explored the linking of modern developing machine learning techniques (manifold learning and in particular diffusion maps) with traditional PDE modeling/discretization/scientific computation techniques via the equation-free methodology developed by the PI. The result (in addition to several PhD degrees, two of them by CSGF Fellows) was a sequence of strong developments - in part on the algorithmic side, linking data mining with scientific computing, and in part on applications, ranging from PDE discretizations to molecular dynamics and complex network dynamics.

A tool for modeling concurrent real-time computation

NASA Technical Reports Server (NTRS)

Sharma, D. D.; Huang, Shie-Rei; Bhatt, Rahul; Sridharan, N. S.

1990-01-01

Real-time computation is a significant area of research in general, and in AI in particular. The complexity of practical real-time problems demands use of knowledge-based problem solving techniques while satisfying real-time performance constraints. Since the demands of a complex real-time problem cannot be predicted (owing to the dynamic nature of the environment) powerful dynamic resource control techniques are needed to monitor and control the performance. A real-time computation model for a real-time tool, an implementation of the QP-Net simulator on a Symbolics machine, and an implementation on a Butterfly multiprocessor machine are briefly described.

Modelling DC responses of 3D complex fracture networks

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

Beskardes, Gungor Didem; Weiss, Chester Joseph

Here, the determination of the geometrical properties of fractures plays a critical role in many engineering problems to assess the current hydrological and mechanical states of geological media and to predict their future states. However, numerical modeling of geoelectrical responses in realistic fractured media has been challenging due to the explosive computational cost imposed by the explicit discretizations of fractures at multiple length scales, which often brings about a tradeoff between computational efficiency and geologic realism. Here, we use the hierarchical finite element method to model electrostatic response of realistically complex 3D conductive fracture networks with minimal computational cost.

Modelling DC responses of 3D complex fracture networks

DOE PAGES

Beskardes, Gungor Didem; Weiss, Chester Joseph

2018-03-01

Here, the determination of the geometrical properties of fractures plays a critical role in many engineering problems to assess the current hydrological and mechanical states of geological media and to predict their future states. However, numerical modeling of geoelectrical responses in realistic fractured media has been challenging due to the explosive computational cost imposed by the explicit discretizations of fractures at multiple length scales, which often brings about a tradeoff between computational efficiency and geologic realism. Here, we use the hierarchical finite element method to model electrostatic response of realistically complex 3D conductive fracture networks with minimal computational cost.

Computer Program for Calculation of Complex Chemical Equilibrium Compositions, Rocket Performance, Incident and Reflected Shocks, and Chapman-Jouguet Detonations. Interim Revision, March 1976

NASA Technical Reports Server (NTRS)

Gordon, S.; Mcbride, B. J.

1976-01-01

A detailed description of the equations and computer program for computations involving chemical equilibria in complex systems is given. A free-energy minimization technique is used. The program permits calculations such as (1) chemical equilibrium for assigned thermodynamic states (T,P), (H,P), (S,P), (T,V), (U,V), or (S,V), (2) theoretical rocket performance for both equilibrium and frozen compositions during expansion, (3) incident and reflected shock properties, and (4) Chapman-Jouguet detonation properties. The program considers condensed species as well as gaseous species.

Visual Complexity in Orthographic Learning: Modeling Learning across Writing System Variations

ERIC Educational Resources Information Center

Chang, Li-Yun; Plaut, David C.; Perfetti, Charles A.

2016-01-01

The visual complexity of orthographies varies across writing systems. Prior research has shown that complexity strongly influences the initial stage of reading development: the perceptual learning of grapheme forms. This study presents a computational simulation that examines the degree to which visual complexity leads to grapheme learning…

Logic circuits based on molecular spider systems.

PubMed

Mo, Dandan; Lakin, Matthew R; Stefanovic, Darko

2016-08-01

Spatial locality brings the advantages of computation speed-up and sequence reuse to molecular computing. In particular, molecular walkers that undergo localized reactions are of interest for implementing logic computations at the nanoscale. We use molecular spider walkers to implement logic circuits. We develop an extended multi-spider model with a dynamic environment wherein signal transmission is triggered via localized reactions, and use this model to implement three basic gates (AND, OR, NOT) and a cascading mechanism. We develop an algorithm to automatically generate the layout of the circuit. We use a kinetic Monte Carlo algorithm to simulate circuit computations, and we analyze circuit complexity: our design scales linearly with formula size and has a logarithmic time complexity. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

The engineering design integration (EDIN) system. [digital computer program complex

NASA Technical Reports Server (NTRS)

Glatt, C. R.; Hirsch, G. N.; Alford, G. E.; Colquitt, W. N.; Reiners, S. J.

1974-01-01

A digital computer program complex for the evaluation of aerospace vehicle preliminary designs is described. The system consists of a Univac 1100 series computer and peripherals using the Exec 8 operating system, a set of demand access terminals of the alphanumeric and graphics types, and a library of independent computer programs. Modification of the partial run streams, data base maintenance and construction, and control of program sequencing are provided by a data manipulation program called the DLG processor. The executive control of library program execution is performed by the Univac Exec 8 operating system through a user established run stream. A combination of demand and batch operations is employed in the evaluation of preliminary designs. Applications accomplished with the EDIN system are described.

TOSCA-based orchestration of complex clusters at the IaaS level

NASA Astrophysics Data System (ADS)

Caballer, M.; Donvito, G.; Moltó, G.; Rocha, R.; Velten, M.

2017-10-01

This paper describes the adoption and extension of the TOSCA standard by the INDIGO-DataCloud project for the definition and deployment of complex computing clusters together with the required support in both OpenStack and OpenNebula, carried out in close collaboration with industry partners such as IBM. Two examples of these clusters are described in this paper, the definition of an elastic computing cluster to support the Galaxy bioinformatics application where the nodes are dynamically added and removed from the cluster to adapt to the workload, and the definition of an scalable Apache Mesos cluster for the execution of batch jobs and support for long-running services. The coupling of TOSCA with Ansible Roles to perform automated installation has resulted in the definition of high-level, deterministic templates to provision complex computing clusters across different Cloud sites.

Computational Modeling of Liquid and Gaseous Control Valves

NASA Technical Reports Server (NTRS)

Daines, Russell; Ahuja, Vineet; Hosangadi, Ashvin; Shipman, Jeremy; Moore, Arden; Sulyma, Peter

2005-01-01

In this paper computational modeling efforts undertaken at NASA Stennis Space Center in support of rocket engine component testing are discussed. Such analyses include structurally complex cryogenic liquid valves and gas valves operating at high pressures and flow rates. Basic modeling and initial successes are documented, and other issues that make valve modeling at SSC somewhat unique are also addressed. These include transient behavior, valve stall, and the determination of flow patterns in LOX valves. Hexahedral structured grids are used for valves that can be simplifies through the use of axisymmetric approximation. Hybrid unstructured methodology is used for structurally complex valves that have disparate length scales and complex flow paths that include strong swirl, local recirculation zones/secondary flow effects. Hexahedral (structured), unstructured, and hybrid meshes are compared for accuracy and computational efficiency. Accuracy is determined using verification and validation techniques.

[Analysis of Conformational Features of Watson-Crick Duplex Fragments by Molecular Mechanics and Quantum Mechanics Methods].

PubMed

Poltev, V I; Anisimov, V M; Sanchez, C; Deriabina, A; Gonzalez, E; Garcia, D; Rivas, F; Polteva, N A

2016-01-01

It is generally accepted that the important characteristic features of the Watson-Crick duplex originate from the molecular structure of its subunits. However, it still remains to elucidate what properties of each subunit are responsible for the significant characteristic features of the DNA structure. The computations of desoxydinucleoside monophosphates complexes with Na-ions using density functional theory revealed a pivotal role of DNA conformational properties of single-chain minimal fragments in the development of unique features of the Watson-Crick duplex. We found that directionality of the sugar-phosphate backbone and the preferable ranges of its torsion angles, combined with the difference between purines and pyrimidines. in ring bases, define the dependence of three-dimensional structure of the Watson-Crick duplex on nucleotide base sequence. In this work, we extended these density functional theory computations to the minimal' fragments of DNA duplex, complementary desoxydinucleoside monophosphates complexes with Na-ions. Using several computational methods and various functionals, we performed a search for energy minima of BI-conformation for complementary desoxydinucleoside monophosphates complexes with different nucleoside sequences. Two sequences are optimized using ab initio method at the MP2/6-31++G** level of theory. The analysis of torsion angles, sugar ring puckering and mutual base positions of optimized structures demonstrates that the conformational characteristic features of complementary desoxydinucleoside monophosphates complexes with Na-ions remain within BI ranges and become closer to the corresponding characteristic features of the Watson-Crick duplex crystals. Qualitatively, the main characteristic features of each studied complementary desoxydinucleoside monophosphates complex remain invariant when different computational methods are used, although the quantitative values of some conformational parameters could vary lying within the limits typical for the corresponding family. We observe that popular functionals in density functional theory calculations lead to the overestimated distances between base pairs, while MP2 computations and the newer complex functionals produce the structures that have too close atom-atom contacts. A detailed study of some complementary desoxydinucleoside monophosphate complexes with Na-ions highlights the existence of several energy minima corresponding to BI-conformations, in other words, the complexity of the relief pattern of the potential energy surface of complementary desoxydinucleoside monophosphate complexes. This accounts for variability of conformational parameters of duplex fragments with the same base sequence. Popular molecular mechanics force fields AMBER and CHARMM reproduce most of the conformational characteristics of desoxydinucleoside monophosphates and their complementary complexes with Na-ions but fail to reproduce some details of the dependence of the Watson-Crick duplex conformation on the nucleotide sequence.

Complex energies and the polyelectronic Stark problem

NASA Astrophysics Data System (ADS)

Themelis, Spyros I.; Nicolaides, Cleanthes A.

2000-12-01

The problem of computing the energy shifts and widths of ground or excited N-electron atomic states perturbed by weak or strong static electric fields is dealt with by formulating a state-specific complex eigenvalue Schrödinger equation (CESE), where the complex energy contains the field-induced shift and width. The CESE is solved to all orders nonperturbatively, by using separately optimized N-electron function spaces, composed of real and complex one-electron functions, the latter being functions of a complex coordinate. The use of such spaces is a salient characteristic of the theory, leading to economy and manageability of calculation in terms of a two-step computational procedure. The first step involves only Hermitian matrices. The second adds complex functions and the overall computation becomes non-Hermitian. Aspects of the formalism and of computational strategy are compared with those of the complex absorption potential (CAP) method, which was recently applied for the calculation of field-induced complex energies in H and Li. Also compared are the numerical results of the two methods, and the questions of accuracy and convergence that were posed by Sahoo and Ho (Sahoo S and Ho Y K 2000 J. Phys. B: At. Mol. Opt. Phys. 33 2195) are explored further. We draw attention to the fact that, because in the region where the field strength is weak the tunnelling rate (imaginary part of the complex eigenvalue) diminishes exponentially, it is possible for even large-scale nonperturbative complex eigenvalue calculations either to fail completely or to produce seemingly stable results which, however, are wrong. It is in this context that the discrepancy in the width of Li 1s22s 2S between results obtained by the CAP method and those obtained by the CESE method is interpreted. We suggest that the very-weak-field regime must be computed by the golden rule, provided the continuum is represented accurately. In this respect, existing one-particle semiclassical formulae seem to be sufficient. In addition to the aforementioned comparisons and conclusions, we present a number of new results from the application of the state-specific CESE theory to the calculation of field-induced shifts and widths of the H n = 3 levels and of the prototypical Be 1s22s2 1S state, for a range of field strengths. Using the H n = 3 manifold as the example, it is shown how errors may occur for small values of the field, unless the function spaces are optimized carefully for each level.

Comparison of computed tomography and complex motion tomography in the evaluation of cholesteatoma

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

Shaffer, K.A.

1984-08-01

High-resolution axial and coronal computed tomographic (CT) scans were compared with coronal and sagittal complex motion tomograms in patients with suspected middle ear cholesteatomas. Information on CT scans equaled or exceeded that on conventional complex motion tomograms in 16 of 17 patients, and in 11 it provided additional information. Soft-tissue resolution was superior with CT. In 14 patients who underwent surgery, CT provided information that was valuable to the surgeon. On the basis of this study, high-resolution CT is recommended as the preferred method for evaluating most patients with cholesteatomas of the temporal bone.

Investigation of anticancer properties of caffeinated complexes via computational chemistry methods

NASA Astrophysics Data System (ADS)

Sayin, Koray; Üngördü, Ayhan

2018-03-01

Computational investigations were performed for 1,3,7-trimethylpurine-2,6-dione, 3,7-dimethylpurine-2,6-dione, their Ru(II) and Os(III) complexes. B3LYP/6-311 ++G(d,p)(LANL2DZ) level was used in numerical calculations. Geometric parameters, IR spectrum, 1H-, 13C and 15N NMR spectrum were examined in detail. Additionally, contour diagram of frontier molecular orbitals (FMOs), molecular electrostatic potential (MEP) maps, MEP contour and some quantum chemical descriptors were used in the determination of reactivity rankings and active sites. The electron density on the surface was similar to each other in studied complexes. Quantum chemical descriptors were investigated and the anticancer activity of complexes were more than cisplatin and their ligands. Additionally, molecular docking calculations were performed in water between related complexes and a protein (ID: 3WZE). The most interact complex was found as Os complex. The interaction energy was calculated as 342.9 kJ/mol.

Krylov Subspace Methods for Complex Non-Hermitian Linear Systems. Thesis

NASA Technical Reports Server (NTRS)

Freund, Roland W.

1991-01-01

We consider Krylov subspace methods for the solution of large sparse linear systems Ax = b with complex non-Hermitian coefficient matrices. Such linear systems arise in important applications, such as inverse scattering, numerical solution of time-dependent Schrodinger equations, underwater acoustics, eddy current computations, numerical computations in quantum chromodynamics, and numerical conformal mapping. Typically, the resulting coefficient matrices A exhibit special structures, such as complex symmetry, or they are shifted Hermitian matrices. In this paper, we first describe a Krylov subspace approach with iterates defined by a quasi-minimal residual property, the QMR method, for solving general complex non-Hermitian linear systems. Then, we study special Krylov subspace methods designed for the two families of complex symmetric respectively shifted Hermitian linear systems. We also include some results concerning the obvious approach to general complex linear systems by solving equivalent real linear systems for the real and imaginary parts of x. Finally, numerical experiments for linear systems arising from the complex Helmholtz equation are reported.

Muscle tension line concept in nasolabial muscle complex--based on 3-dimensional reconstruction of nasolabial muscle fibers.

PubMed

Yin, Ningbei; Wu, Jiajun; Chen, Bo; Song, Tao; Ma, Hengyuan; Zhao, Zhenmin; Wang, Yongqian; Li, Haidong; Wu, Di

2015-03-01

Plastic surgeons have attempted various ways to rebuild the aesthetic subunits of the upper lip in patients with cleft lip with less than perfect results in most cases. We propose that repairing the 3 muscle tension line groups in the nasolabial complex will have improved aesthetic results. Micro-computed tomographic scans were performed on the nasolabial tissues of 5 normal aborted fetuses and used to construct a 3-dimensional model to study the nasolabial muscle complex structure. The micro-computed tomographic (CT) scans showed the close relationship and interaction between the muscle fibers of nasalis, pars peripheralis, levator labii superioris, and pars marginalis. Based on the 2-dimensional images obtained from the micro-computed tomographic scans, we suggest the concept of nasolabial muscle complex and muscle tension line group theory: there is a close relationship among the alar part of the nasalis, depressor septi muscle, orbicularis oris muscle, and levator labii superioris alaeque nasi. The tension line groups are 3 tension line structures in the nasolabial muscle complex that interlock with each other at the intersections and maintain the specific shape and aesthetics of the lip and nose.

Computational structure analysis of biomacromolecule complexes by interface geometry.

PubMed

Mahdavi, Sedigheh; Salehzadeh-Yazdi, Ali; Mohades, Ali; Masoudi-Nejad, Ali

2013-12-01

The ability to analyze and compare protein-nucleic acid and protein-protein interaction interface has critical importance in understanding the biological function and essential processes occurring in the cells. Since high-resolution three-dimensional (3D) structures of biomacromolecule complexes are available, computational characterizing of the interface geometry become an important research topic in the field of molecular biology. In this study, the interfaces of a set of 180 protein-nucleic acid and protein-protein complexes are computed to understand the principles of their interactions. The weighted Voronoi diagram of the atoms and the Alpha complex has provided an accurate description of the interface atoms. Our method is implemented in the presence and absence of water molecules. A comparison among the three types of interaction interfaces show that RNA-protein complexes have the largest size of an interface. The results show a high correlation coefficient between our method and the PISA server in the presence and absence of water molecules in the Voronoi model and the traditional model based on solvent accessibility and the high validation parameters in comparison to the classical model. Copyright © 2013 Elsevier Ltd. All rights reserved.

Interplay between theory and experiment: computational organometallic and transition metal chemistry.

PubMed

Lin, Zhenyang

2010-05-18

Computational and theoretical chemistry provide fundamental insights into the structures, properties, and reactivities of molecules. As a result, theoretical calculations have become indispensable in various fields of chemical research and development. In this Account, we present our research in the area of computational transition metal chemistry, using examples to illustrate how theory impacts our understanding of experimental results and how close collaboration between theoreticians and experimental chemists can be mutually beneficial. We begin by examining the use of computational chemistry to elucidate the details of some unusual chemical bonds. We consider the three-center, two-electron bonding in titanocene sigma-borane complexes and the five-center, four-electron bonding in a rhodium-bismuth complex. The bonding in metallabenzene complexes is also examined. In each case, theoretical calculations provide particular insight into the electronic structure of the chemical bonds. We then give an example of how theoretical calculations aided the structural determination of a kappa(2)-N,N chelate ruthenium complex formed upon heating an intermediate benzonitrile-coordinated complex. An initial X-ray diffraction structure proposed on the basis of a reasonable mechanism appeared to fit well, with an apparently acceptable R value of 0.0478. But when DFT calculations were applied, the optimized geometry differed significantly from the experimental data. By combining experimental and theoretical outlooks, we posited a new structure. Remarkably, a re-refining of the X-ray diffraction data based on the new structure resulted in a slightly lower R value of 0.0453. We further examine the use of computational chemistry in providing new insight into C-H bond activation mechanisms and in understanding the reactivity properties of nucleophilic boryl ligands, addressing experimental difficulties with calculations and vice versa. Finally, we consider the impact of theoretical insights in three very specific experimental studies of chemical reactions, illustrating how theoretical results prompt further experimental studies: (i) diboration of aldehydes catalyzed by copper(I) boryl complexes, (ii) ruthenium-catalyzed C-H amination of arylazides, and (iii) zinc reduction of a vinylcarbyne complex. The concepts and examples presented here are intended for nonspecialists, particularly experimentalists. Together, they illustrate some of the achievements that are possible with a fruitful union of experiment and theory.

Notebook Computers Increase Communication.

ERIC Educational Resources Information Center

Carey, Doris M.; Sale, Paul

1994-01-01

Project FIT (Full Inclusion through Technology) provides notebook computers for children with severe disabilities. The computers offer many input and output options. Assessing the students' equipment needs is a complex process, requiring determination of communication goals and baseline abilities, and consideration of equipment features such as…

Computer simulation of functioning of elements of security systems

NASA Astrophysics Data System (ADS)

Godovykh, A. V.; Stepanov, B. P.; Sheveleva, A. A.

2017-01-01

The article is devoted to issues of development of the informational complex for simulation of functioning of the security system elements. The complex is described from the point of view of main objectives, a design concept and an interrelation of main elements. The proposed conception of the computer simulation provides an opportunity to simulate processes of security system work for training security staff during normal and emergency operation.

Simplified microprocessor design for VLSI control applications

NASA Technical Reports Server (NTRS)

Cameron, K.

1991-01-01

A design technique for microprocessors combining the simplicity of reduced instruction set computers (RISC's) with the richer instruction sets of complex instruction set computers (CISC's) is presented. They utilize the pipelined instruction decode and datapaths common to RISC's. Instruction invariant data processing sequences which transparently support complex addressing modes permit the formulation of simple control circuitry. Compact implementations are possible since neither complicated controllers nor large register sets are required.

WE-D-303-00: Computational Phantoms

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

Lewis, John; Brigham and Women’s Hospital and Dana-Farber Cancer Institute, Boston, MA

2015-06-15

Modern medical physics deals with complex problems such as 4D radiation therapy and imaging quality optimization. Such problems involve a large number of radiological parameters, and anatomical and physiological breathing patterns. A major challenge is how to develop, test, evaluate and compare various new imaging and treatment techniques, which often involves testing over a large range of radiological parameters as well as varying patient anatomies and motions. It would be extremely challenging, if not impossible, both ethically and practically, to test every combination of parameters and every task on every type of patient under clinical conditions. Computer-based simulation using computationalmore » phantoms offers a practical technique with which to evaluate, optimize, and compare imaging technologies and methods. Within simulation, the computerized phantom provides a virtual model of the patient’s anatomy and physiology. Imaging data can be generated from it as if it was a live patient using accurate models of the physics of the imaging and treatment process. With sophisticated simulation algorithms, it is possible to perform virtual experiments entirely on the computer. By serving as virtual patients, computational phantoms hold great promise in solving some of the most complex problems in modern medical physics. In this proposed symposium, we will present the history and recent developments of computational phantom models, share experiences in their application to advanced imaging and radiation applications, and discuss their promises and limitations. Learning Objectives: Understand the need and requirements of computational phantoms in medical physics research Discuss the developments and applications of computational phantoms Know the promises and limitations of computational phantoms in solving complex problems.« less

What Can Quantum Optics Say about Computational Complexity Theory?

NASA Astrophysics Data System (ADS)

Rahimi-Keshari, Saleh; Lund, Austin P.; Ralph, Timothy C.

2015-02-01

Considering the problem of sampling from the output photon-counting probability distribution of a linear-optical network for input Gaussian states, we obtain results that are of interest from both quantum theory and the computational complexity theory point of view. We derive a general formula for calculating the output probabilities, and by considering input thermal states, we show that the output probabilities are proportional to permanents of positive-semidefinite Hermitian matrices. It is believed that approximating permanents of complex matrices in general is a #P-hard problem. However, we show that these permanents can be approximated with an algorithm in the BPPNP complexity class, as there exists an efficient classical algorithm for sampling from the output probability distribution. We further consider input squeezed-vacuum states and discuss the complexity of sampling from the probability distribution at the output.

The computational complexity of elliptic curve integer sub-decomposition (ISD) method

NASA Astrophysics Data System (ADS)

Ajeena, Ruma Kareem K.; Kamarulhaili, Hailiza

2014-07-01

The idea of the GLV method of Gallant, Lambert and Vanstone (Crypto 2001) is considered a foundation stone to build a new procedure to compute the elliptic curve scalar multiplication. This procedure, that is integer sub-decomposition (ISD), will compute any multiple kP of elliptic curve point P which has a large prime order n with two low-degrees endomorphisms ψ1 and ψ2 of elliptic curve E over prime field Fp. The sub-decomposition of values k1 and k2, not bounded by ±C√n , gives us new integers k11, k12, k21 and k22 which are bounded by ±C√n and can be computed through solving the closest vector problem in lattice. The percentage of a successful computation for the scalar multiplication increases by ISD method, which improved the computational efficiency in comparison with the general method for computing scalar multiplication in elliptic curves over the prime fields. This paper will present the mechanism of ISD method and will shed light mainly on the computation complexity of the ISD approach that will be determined by computing the cost of operations. These operations include elliptic curve operations and finite field operations.

A Computational Workflow for the Automated Generation of Models of Genetic Designs.

PubMed

Misirli, Göksel; Nguyen, Tramy; McLaughlin, James Alastair; Vaidyanathan, Prashant; Jones, Timothy S; Densmore, Douglas; Myers, Chris; Wipat, Anil

2018-06-05

Computational models are essential to engineer predictable biological systems and to scale up this process for complex systems. Computational modeling often requires expert knowledge and data to build models. Clearly, manual creation of models is not scalable for large designs. Despite several automated model construction approaches, computational methodologies to bridge knowledge in design repositories and the process of creating computational models have still not been established. This paper describes a workflow for automatic generation of computational models of genetic circuits from data stored in design repositories using existing standards. This workflow leverages the software tool SBOLDesigner to build structural models that are then enriched by the Virtual Parts Repository API using Systems Biology Open Language (SBOL) data fetched from the SynBioHub design repository. The iBioSim software tool is then utilized to convert this SBOL description into a computational model encoded using the Systems Biology Markup Language (SBML). Finally, this SBML model can be simulated using a variety of methods. This workflow provides synthetic biologists with easy to use tools to create predictable biological systems, hiding away the complexity of building computational models. This approach can further be incorporated into other computational workflows for design automation.

Fast calculation of the `ILC norm' in iterative learning control

NASA Astrophysics Data System (ADS)

Rice, Justin K.; van Wingerden, Jan-Willem

2013-06-01

In this paper, we discuss and demonstrate a method for the exploitation of matrix structure in computations for iterative learning control (ILC). In Barton, Bristow, and Alleyne [International Journal of Control, 83(2), 1-8 (2010)], a special insight into the structure of the lifted convolution matrices involved in ILC is used along with a modified Lanczos method to achieve very fast computational bounds on the learning convergence, by calculating the 'ILC norm' in ? computational complexity. In this paper, we show how their method is equivalent to a special instance of the sequentially semi-separable (SSS) matrix arithmetic, and thus can be extended to many other computations in ILC, and specialised in some cases to even faster methods. Our SSS-based methodology will be demonstrated on two examples: a linear time-varying example resulting in the same ? complexity as in Barton et al., and a linear time-invariant example where our approach reduces the computational complexity to ?, thus decreasing the computation time, for an example, from the literature by a factor of almost 100. This improvement is achieved by transforming the norm computation via a linear matrix inequality into a check of positive definiteness - which allows us to further exploit the almost-Toeplitz properties of the matrix, and additionally provides explicit upper and lower bounds on the norm of the matrix, instead of the indirect Ritz estimate. These methods are now implemented in a MATLAB toolbox, freely available on the Internet.

Communication complexity and information complexity

NASA Astrophysics Data System (ADS)

Pankratov, Denis

Information complexity enables the use of information-theoretic tools in communication complexity theory. Prior to the results presented in this thesis, information complexity was mainly used for proving lower bounds and direct-sum theorems in the setting of communication complexity. We present three results that demonstrate new connections between information complexity and communication complexity. In the first contribution we thoroughly study the information complexity of the smallest nontrivial two-party function: the AND function. While computing the communication complexity of AND is trivial, computing its exact information complexity presents a major technical challenge. In overcoming this challenge, we reveal that information complexity gives rise to rich geometrical structures. Our analysis of information complexity relies on new analytic techniques and new characterizations of communication protocols. We also uncover a connection of information complexity to the theory of elliptic partial differential equations. Once we compute the exact information complexity of AND, we can compute exact communication complexity of several related functions on n-bit inputs with some additional technical work. Previous combinatorial and algebraic techniques could only prove bounds of the form theta( n). Interestingly, this level of precision is typical in the area of information theory, so our result demonstrates that this meta-property of precise bounds carries over to information complexity and in certain cases even to communication complexity. Our result does not only strengthen the lower bound on communication complexity of disjointness by making it more exact, but it also shows that information complexity provides the exact upper bound on communication complexity. In fact, this result is more general and applies to a whole class of communication problems. In the second contribution, we use self-reduction methods to prove strong lower bounds on the information complexity of two of the most studied functions in the communication complexity literature: Gap Hamming Distance (GHD) and Inner Product mod 2 (IP). In our first result we affirm the conjecture that the information complexity of GHD is linear even under the uniform distribution. This strengthens the O(n) bound shown by Kerenidis et al. (2012) and answers an open problem by Chakrabarti et al. (2012). We also prove that the information complexity of IP is arbitrarily close to the trivial upper bound n as the permitted error tends to zero, again strengthening the O(n) lower bound proved by Braverman and Weinstein (2011). More importantly, our proofs demonstrate that self-reducibility makes the connection between information complexity and communication complexity lower bounds a two-way connection. Whereas numerous results in the past used information complexity techniques to derive new communication complexity lower bounds, we explore a generic way, in which communication complexity lower bounds imply information complexity lower bounds in a black-box manner. In the third contribution we consider the roles that private and public randomness play in the definition of information complexity. In communication complexity, private randomness can be trivially simulated by public randomness. Moreover, the communication cost of simulating public randomness with private randomness is well understood due to Newman's theorem (1991). In information complexity, the roles of public and private randomness are reversed: public randomness can be trivially simulated by private randomness. However, the information cost of simulating private randomness with public randomness is not understood. We show that protocols that use only public randomness admit a rather strong compression. In particular, efficient simulation of private randomness by public randomness would imply a version of a direct sum theorem in the setting of communication complexity. This establishes a yet another connection between the two areas. (Abstract shortened by UMI.).

A new decision sciences for complex systems.

PubMed

Lempert, Robert J

2002-05-14

Models of complex systems can capture much useful information but can be difficult to apply to real-world decision-making because the type of information they contain is often inconsistent with that required for traditional decision analysis. New approaches, which use inductive reasoning over large ensembles of computational experiments, now make possible systematic comparison of alternative policy options using models of complex systems. This article describes Computer-Assisted Reasoning, an approach to decision-making under conditions of deep uncertainty that is ideally suited to applying complex systems to policy analysis. The article demonstrates the approach on the policy problem of global climate change, with a particular focus on the role of technology policies in a robust, adaptive strategy for greenhouse gas abatement.

Playable Serious Games for Studying and Programming Computational STEM and Informatics Applications of Distributed and Parallel Computer Architectures

ERIC Educational Resources Information Center

Amenyo, John-Thones

2012-01-01

Carefully engineered playable games can serve as vehicles for students and practitioners to learn and explore the programming of advanced computer architectures to execute applications, such as high performance computing (HPC) and complex, inter-networked, distributed systems. The article presents families of playable games that are grounded in…

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.

Hypercluster Parallel Processor

NASA Technical Reports Server (NTRS)

Blech, Richard A.; Cole, Gary L.; Milner, Edward J.; Quealy, Angela

1992-01-01

Hypercluster computer system includes multiple digital processors, operation of which coordinated through specialized software. Configurable according to various parallel-computing architectures of shared-memory or distributed-memory class, including scalar computer, vector computer, reduced-instruction-set computer, and complex-instruction-set computer. Designed as flexible, relatively inexpensive system that provides single programming and operating environment within which one can investigate effects of various parallel-computing architectures and combinations on performance in solution of complicated problems like those of three-dimensional flows in turbomachines. Hypercluster software and architectural concepts are in public domain.

Tutorial: Parallel Computing of Simulation Models for Risk Analysis.

PubMed

Reilly, Allison C; Staid, Andrea; Gao, Michael; Guikema, Seth D

2016-10-01

Simulation models are widely used in risk analysis to study the effects of uncertainties on outcomes of interest in complex problems. Often, these models are computationally complex and time consuming to run. This latter point may be at odds with time-sensitive evaluations or may limit the number of parameters that are considered. In this article, we give an introductory tutorial focused on parallelizing simulation code to better leverage modern computing hardware, enabling risk analysts to better utilize simulation-based methods for quantifying uncertainty in practice. This article is aimed primarily at risk analysts who use simulation methods but do not yet utilize parallelization to decrease the computational burden of these models. The discussion is focused on conceptual aspects of embarrassingly parallel computer code and software considerations. Two complementary examples are shown using the languages MATLAB and R. A brief discussion of hardware considerations is located in the Appendix. © 2016 Society for Risk Analysis.

Fast hydrological model calibration based on the heterogeneous parallel computing accelerated shuffled complex evolution method

NASA Astrophysics Data System (ADS)

Kan, Guangyuan; He, Xiaoyan; Ding, Liuqian; Li, Jiren; Hong, Yang; Zuo, Depeng; Ren, Minglei; Lei, Tianjie; Liang, Ke

2018-01-01

Hydrological model calibration has been a hot issue for decades. The shuffled complex evolution method developed at the University of Arizona (SCE-UA) has been proved to be an effective and robust optimization approach. However, its computational efficiency deteriorates significantly when the amount of hydrometeorological data increases. In recent years, the rise of heterogeneous parallel computing has brought hope for the acceleration of hydrological model calibration. This study proposed a parallel SCE-UA method and applied it to the calibration of a watershed rainfall-runoff model, the Xinanjiang model. The parallel method was implemented on heterogeneous computing systems using OpenMP and CUDA. Performance testing and sensitivity analysis were carried out to verify its correctness and efficiency. Comparison results indicated that heterogeneous parallel computing-accelerated SCE-UA converged much more quickly than the original serial version and possessed satisfactory accuracy and stability for the task of fast hydrological model calibration.

Potential implementation of reservoir computing models based on magnetic skyrmions

NASA Astrophysics Data System (ADS)

Bourianoff, George; Pinna, Daniele; Sitte, Matthias; Everschor-Sitte, Karin

2018-05-01

Reservoir Computing is a type of recursive neural network commonly used for recognizing and predicting spatio-temporal events relying on a complex hierarchy of nested feedback loops to generate a memory functionality. The Reservoir Computing paradigm does not require any knowledge of the reservoir topology or node weights for training purposes and can therefore utilize naturally existing networks formed by a wide variety of physical processes. Most efforts to implement reservoir computing prior to this have focused on utilizing memristor techniques to implement recursive neural networks. This paper examines the potential of magnetic skyrmion fabrics and the complex current patterns which form in them as an attractive physical instantiation for Reservoir Computing. We argue that their nonlinear dynamical interplay resulting from anisotropic magnetoresistance and spin-torque effects allows for an effective and energy efficient nonlinear processing of spatial temporal events with the aim of event recognition and prediction.

Computed intraoperative navigation guidance--a preliminary report on a new technique.

PubMed

Enislidis, G; Wagner, A; Ploder, O; Ewers, R

1997-08-01

To assess the value of a computer-assisted three-dimensional guidance system (Virtual Patient System) in maxillofacial operations. Laboratory and open clinical study. Teaching Hospital, Austria. 6 patients undergoing various procedures including removal of foreign body (n=3) and biopsy, maxillary advancement, and insertion of implants (n=1 each). Storage of computed tomographic (CT) pictures on an optical disc, and imposition of intraoperative video images on to these. The resulting display is shown to the surgeon on a micromonitor in his head-up display for guidance during the operations. To improve orientation during complex or minimally invasive maxillofacial procedures and to make such operations easier and less traumatic. Successful transferral of computed navigation technology into an operation room environment and positive evaluation of the method by the surgeons involved. Computer-assisted three-dimensional guidance systems have the potential for making complex or minimally invasive procedures easier to do, thereby reducing postoperative morbidity.

Beyond CMOS computing with spin and polarization

NASA Astrophysics Data System (ADS)

Manipatruni, Sasikanth; Nikonov, Dmitri E.; Young, Ian A.

2018-04-01

Spintronic and multiferroic systems are leading candidates for achieving attojoule-class logic gates for computing, thereby enabling the continuation of Moore's law for transistor scaling. However, shifting the materials focus of computing towards oxides and topological materials requires a holistic approach addressing energy, stochasticity and complexity.

Design consideration in constructing high performance embedded Knowledge-Based Systems (KBS)

NASA Technical Reports Server (NTRS)

Dalton, Shelly D.; Daley, Philip C.

1988-01-01

As the hardware trends for artificial intelligence (AI) involve more and more complexity, the process of optimizing the computer system design for a particular problem will also increase in complexity. Space applications of knowledge based systems (KBS) will often require an ability to perform both numerically intensive vector computations and real time symbolic computations. Although parallel machines can theoretically achieve the speeds necessary for most of these problems, if the application itself is not highly parallel, the machine's power cannot be utilized. A scheme is presented which will provide the computer systems engineer with a tool for analyzing machines with various configurations of array, symbolic, scaler, and multiprocessors. High speed networks and interconnections make customized, distributed, intelligent systems feasible for the application of AI in space. The method presented can be used to optimize such AI system configurations and to make comparisons between existing computer systems. It is an open question whether or not, for a given mission requirement, a suitable computer system design can be constructed for any amount of money.

Acceleration of the matrix multiplication of Radiance three phase daylighting simulations with parallel computing on heterogeneous hardware of personal computer

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

Zuo, Wangda; McNeil, Andrew; Wetter, Michael

2013-05-23

Building designers are increasingly relying on complex fenestration systems to reduce energy consumed for lighting and HVAC in low energy buildings. Radiance, a lighting simulation program, has been used to conduct daylighting simulations for complex fenestration systems. Depending on the configurations, the simulation can take hours or even days using a personal computer. This paper describes how to accelerate the matrix multiplication portion of a Radiance three-phase daylight simulation by conducting parallel computing on heterogeneous hardware of a personal computer. The algorithm was optimized and the computational part was implemented in parallel using OpenCL. The speed of new approach wasmore » evaluated using various daylighting simulation cases on a multicore central processing unit and a graphics processing unit. Based on the measurements and analysis of the time usage for the Radiance daylighting simulation, further speedups can be achieved by using fast I/O devices and storing the data in a binary format.« less

Computational Approaches to Nucleic Acid Origami.

PubMed

Jabbari, Hosna; Aminpour, Maral; Montemagno, Carlo

2015-10-12

Recent advances in experimental DNA origami have dramatically expanded the horizon of DNA nanotechnology. Complex 3D suprastructures have been designed and developed using DNA origami with applications in biomaterial science, nanomedicine, nanorobotics, and molecular computation. Ribonucleic acid (RNA) origami has recently been realized as a new approach. Similar to DNA, RNA molecules can be designed to form complex 3D structures through complementary base pairings. RNA origami structures are, however, more compact and more thermodynamically stable due to RNA's non-canonical base pairing and tertiary interactions. With all these advantages, the development of RNA origami lags behind DNA origami by a large gap. Furthermore, although computational methods have proven to be effective in designing DNA and RNA origami structures and in their evaluation, advances in computational nucleic acid origami is even more limited. In this paper, we review major milestones in experimental and computational DNA and RNA origami and present current challenges in these fields. We believe collaboration between experimental nanotechnologists and computer scientists are critical for advancing these new research paradigms.

Optimized Materials From First Principles Simulations: Are We There Yet?

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

Galli, G; Gygi, F

2005-07-26

In the past thirty years, the use of scientific computing has become pervasive in all disciplines: collection and interpretation of most experimental data is carried out using computers, and physical models in computable form, with various degrees of complexity and sophistication, are utilized in all fields of science. However, full prediction of physical and chemical phenomena based on the basic laws of Nature, using computer simulations, is a revolution still in the making, and it involves some formidable theoretical and computational challenges. We illustrate the progress and successes obtained in recent years in predicting fundamental properties of materials in condensedmore » phases and at the nanoscale, using ab-initio, quantum simulations. We also discuss open issues related to the validation of the approximate, first principles theories used in large scale simulations, and the resulting complex interplay between computation and experiment. Finally, we describe some applications, with focus on nanostructures and liquids, both at ambient and under extreme conditions.« less

Predicting Development of Mathematical Word Problem Solving Across the Intermediate Grades

PubMed Central

Tolar, Tammy D.; Fuchs, Lynn; Cirino, Paul T.; Fuchs, Douglas; Hamlett, Carol L.; Fletcher, Jack M.

2012-01-01

This study addressed predictors of the development of word problem solving (WPS) across the intermediate grades. At beginning of 3rd grade, 4 cohorts of students (N = 261) were measured on computation, language, nonverbal reasoning skills, and attentive behavior and were assessed 4 times from beginning of 3rd through end of 5th grade on 2 measures of WPS at low and high levels of complexity. Language skills were related to initial performance at both levels of complexity and did not predict growth at either level. Computational skills had an effect on initial performance in low- but not high-complexity problems and did not predict growth at either level of complexity. Attentive behavior did not predict initial performance but did predict growth in low-complexity, whereas it predicted initial performance but not growth for high-complexity problems. Nonverbal reasoning predicted initial performance and growth for low-complexity WPS, but only growth for high-complexity WPS. This evidence suggests that although mathematical structure is fixed, different cognitive resources may act as limiting factors in WPS development when the WPS context is varied. PMID:23325985

The value and cost of complexity in predictive modelling: role of tissue anisotropic conductivity and fibre tracts in neuromodulation

NASA Astrophysics Data System (ADS)

Salman Shahid, Syed; Bikson, Marom; Salman, Humaira; Wen, Peng; Ahfock, Tony

2014-06-01

Objectives. Computational methods are increasingly used to optimize transcranial direct current stimulation (tDCS) dose strategies and yet complexities of existing approaches limit their clinical access. Since predictive modelling indicates the relevance of subject/pathology based data and hence the need for subject specific modelling, the incremental clinical value of increasingly complex modelling methods must be balanced against the computational and clinical time and costs. For example, the incorporation of multiple tissue layers and measured diffusion tensor (DTI) based conductivity estimates increase model precision but at the cost of clinical and computational resources. Costs related to such complexities aggregate when considering individual optimization and the myriad of potential montages. Here, rather than considering if additional details change current-flow prediction, we consider when added complexities influence clinical decisions. Approach. Towards developing quantitative and qualitative metrics of value/cost associated with computational model complexity, we considered field distributions generated by two 4 × 1 high-definition montages (m1 = 4 × 1 HD montage with anode at C3 and m2 = 4 × 1 HD montage with anode at C1) and a single conventional (m3 = C3-Fp2) tDCS electrode montage. We evaluated statistical methods, including residual error (RE) and relative difference measure (RDM), to consider the clinical impact and utility of increased complexities, namely the influence of skull, muscle and brain anisotropic conductivities in a volume conductor model. Main results. Anisotropy modulated current-flow in a montage and region dependent manner. However, significant statistical changes, produced within montage by anisotropy, did not change qualitative peak and topographic comparisons across montages. Thus for the examples analysed, clinical decision on which dose to select would not be altered by the omission of anisotropic brain conductivity. Significance. Results illustrate the need to rationally balance the role of model complexity, such as anisotropy in detailed current flow analysis versus value in clinical dose design. However, when extending our analysis to include axonal polarization, the results provide presumably clinically meaningful information. Hence the importance of model complexity may be more relevant with cellular level predictions of neuromodulation.

Application of advanced grid generation techniques for flow field computations about complex configurations

NASA Technical Reports Server (NTRS)

Kathong, Monchai; Tiwari, Surendra N.

1988-01-01

In the computation of flowfields about complex configurations, it is very difficult to construct a boundary-fitted coordinate system. An alternative approach is to use several grids at once, each of which is generated independently. This procedure is called the multiple grids or zonal grids approach; its applications are investigated. The method conservative providing conservation of fluxes at grid interfaces. The Euler equations are solved numerically on such grids for various configurations. The numerical scheme used is the finite-volume technique with a three-stage Runge-Kutta time integration. The code is vectorized and programmed to run on the CDC VPS-32 computer. Steady state solutions of the Euler equations are presented and discussed. The solutions include: low speed flow over a sphere, high speed flow over a slender body, supersonic flow through a duct, and supersonic internal/external flow interaction for an aircraft configuration at various angles of attack. The results demonstrate that the multiple grids approach along with the conservative interfacing is capable of computing the flows about the complex configurations where the use of a single grid system is not possible.

[Automated procedures for microscopic analyses of blood smears: medical testing a MECOS-Ts2 complex].

PubMed

Pliasunova, S A; Balugian, R Sh; Khmel'nitskiĭ, K E; Medovyĭ, V S; Parpara, A A; Piatnitskiĭ, A M; Sokolinskiĭ, B Z; Dem'ianov, V L; Nikolaenko, D S

2006-10-01

The paper presents the results of medical tests of a group of computer-aided procedures for microscopic analysis by means of a MECOS-Ts2 complex (ZAO "MECOS", Russia), which have been conducted at the Republican Children's Clinical Hospital, the Research Institute of Emergency Pediatric Surgery and Traumatology, and Moscow City Clinical Hospital No. 23. Computer-aided procedures for calculating the differential count and for analyzing the morphology of red blood cells were tested on blood smears from a total of 443 patients and donors, computer-aided calculation of the count of reticulocytes was tested on 318 smears. The tests were carried out under the US standard NCCLS-H20A. Manual microscopy (443 smears) and flow blood analysis on a Coulter GEN*S (125 smears) were used as reference methods. The quality of collection of samples and laboriousness were additionally assessed. The certified MECOS-Ts2 subsystems were additionally used as reference tools. The tests indicated the advantage of computer-aided MECOS-Tsl2 complex microscopy over manual microscopy.

Numerical information processing under the global rule expressed by the Euler-Riemann ζ function defined in the complex plane

NASA Astrophysics Data System (ADS)

Chatelin, Françoise

2010-09-01

When nonzero, the ζ function is intimately connected with numerical information processing. Two other functions play a key role, namely, η(s )=∑n ≥1(-1)n +1/ns and λ(s )=∑n ≥01/(2n+1)s. The paper opens on a survey of some of the seminal work of Euler [Mémoires Acad. Sci., Berlin 1768, 83 (1749)] and of the amazing theorem by Voronin [Math. USSR, Izv. 9, 443 (1975)] Then, as a follow-up of Chatelin [Qualitative Computing. A Computational Journey into Nonlinearity (World Scientific, Singapore, in press)], we present a fresh look at the triple (η ,ζ,λ) which suggests an elementary analysis based on the distances of the three complex numbers z, z /2, and 2/z to 0 and 1. This metric approach is used to contextualize any nonlinear computation when it is observed at a point describing a complex plane. The results applied to ζ, η, and λ shed a new epistemological light about the critical line. The suggested interpretation related to ζ carries computational significance.

Sparsity-based fast CGH generation using layer-based approach for 3D point cloud model

NASA Astrophysics Data System (ADS)

Kim, Hak Gu; Jeong, Hyunwook; Ro, Yong Man

2017-03-01

Computer generated hologram (CGH) is becoming increasingly important for a 3-D display in various applications including virtual reality. In the CGH, holographic fringe patterns are generated by numerically calculating them on computer simulation systems. However, a heavy computational cost is required to calculate the complex amplitude on CGH plane for all points of 3D objects. This paper proposes a new fast CGH generation based on the sparsity of CGH for 3D point cloud model. The aim of the proposed method is to significantly reduce computational complexity while maintaining the quality of the holographic fringe patterns. To that end, we present a new layer-based approach for calculating the complex amplitude distribution on the CGH plane by using sparse FFT (sFFT). We observe the CGH of a layer of 3D objects is sparse so that dominant CGH is rapidly generated from a small set of signals by sFFT. Experimental results have shown that the proposed method is one order of magnitude faster than recently reported fast CGH generation.

Methods for protein complex prediction and their contributions towards understanding the organisation, function and dynamics of complexes.

PubMed

Srihari, Sriganesh; Yong, Chern Han; Patil, Ashwini; Wong, Limsoon

2015-09-14

Complexes of physically interacting proteins constitute fundamental functional units responsible for driving biological processes within cells. A faithful reconstruction of the entire set of complexes is therefore essential to understand the functional organisation of cells. In this review, we discuss the key contributions of computational methods developed till date (approximately between 2003 and 2015) for identifying complexes from the network of interacting proteins (PPI network). We evaluate in depth the performance of these methods on PPI datasets from yeast, and highlight their limitations and challenges, in particular at detecting sparse and small or sub-complexes and discerning overlapping complexes. We describe methods for integrating diverse information including expression profiles and 3D structures of proteins with PPI networks to understand the dynamics of complex formation, for instance, of time-based assembly of complex subunits and formation of fuzzy complexes from intrinsically disordered proteins. Finally, we discuss methods for identifying dysfunctional complexes in human diseases, an application that is proving invaluable to understand disease mechanisms and to discover novel therapeutic targets. We hope this review aptly commemorates a decade of research on computational prediction of complexes and constitutes a valuable reference for further advancements in this exciting area. Copyright © 2015 Federation of European Biochemical Societies. Published by Elsevier B.V. All rights reserved.

Chromatin Computation

PubMed Central

Bryant, Barbara

2012-01-01

In living cells, DNA is packaged along with protein and RNA into chromatin. Chemical modifications to nucleotides and histone proteins are added, removed and recognized by multi-functional molecular complexes. Here I define a new computational model, in which chromatin modifications are information units that can be written onto a one-dimensional string of nucleosomes, analogous to the symbols written onto cells of a Turing machine tape, and chromatin-modifying complexes are modeled as read-write rules that operate on a finite set of adjacent nucleosomes. I illustrate the use of this “chromatin computer” to solve an instance of the Hamiltonian path problem. I prove that chromatin computers are computationally universal – and therefore more powerful than the logic circuits often used to model transcription factor control of gene expression. Features of biological chromatin provide a rich instruction set for efficient computation of nontrivial algorithms in biological time scales. Modeling chromatin as a computer shifts how we think about chromatin function, suggests new approaches to medical intervention, and lays the groundwork for the engineering of a new class of biological computing machines. PMID:22567109

Experimental and Computational Study of Sonic and Supersonic Jet Plumes

NASA Technical Reports Server (NTRS)

Venkatapathy, E.; Naughton, J. W.; Fletcher, D. G.; Edwards, Thomas A. (Technical Monitor)

1994-01-01

Study of sonic and supersonic jet plumes are relevant to understanding such phenomenon as jet-noise, plume signatures, and rocket base-heating and radiation. Jet plumes are simple to simulate and yet, have complex flow structures such as Mach disks, triple points, shear-layers, barrel shocks, shock-shear-layer interaction, etc. Experimental and computational simulation of sonic and supersonic jet plumes have been performed for under- and over-expanded, axisymmetric plume conditions. The computational simulation compare very well with the experimental observations of schlieren pictures. Experimental data such as temperature measurements with hot-wire probes are yet to be measured and will be compared with computed values. Extensive analysis of the computational simulations presents a clear picture of how the complex flow structure develops and the conditions under which self-similar flow structures evolve. From the computations, the plume structure can be further classified into many sub-groups. In the proposed paper, detail results from the experimental and computational simulations for single, axisymmetric, under- and over-expanded, sonic and supersonic plumes will be compared and the fluid dynamic aspects of flow structures will be discussed.

Students' explanations in complex learning of disciplinary programming

NASA Astrophysics Data System (ADS)

Vieira, Camilo

Computational Science and Engineering (CSE) has been denominated as the third pillar of science and as a set of important skills to solve the problems of a global society. Along with the theoretical and the experimental approaches, computation offers a third alternative to solve complex problems that require processing large amounts of data, or representing complex phenomena that are not easy to experiment with. Despite the relevance of CSE, current professionals and scientists are not well prepared to take advantage of this set of tools and methods. Computation is usually taught in an isolated way from engineering disciplines, and therefore, engineers do not know how to exploit CSE affordances. This dissertation intends to introduce computational tools and methods contextualized within the Materials Science and Engineering curriculum. Considering that learning how to program is a complex task, the dissertation explores effective pedagogical practices that can support student disciplinary and computational learning. Two case studies will be evaluated to identify the characteristics of effective worked examples in the context of CSE. Specifically, this dissertation explores students explanations of these worked examples in two engineering courses with different levels of transparency: a programming course in materials science and engineering glass box and a thermodynamics course involving computational representations black box. Results from this study suggest that students benefit in different ways from writing in-code comments. These benefits include but are not limited to: connecting xv individual lines of code to the overall problem, getting familiar with the syntax, learning effective algorithm design strategies, and connecting computation with their discipline. Students in the glass box context generate higher quality explanations than students in the black box context. These explanations are related to students prior experiences. Specifically, students with low ability to do programming engage in a more thorough explanation process than students with high ability. This dissertation concludes proposing an adaptation to the instructional principles of worked-examples for the context of CSE education.

Connectionist Models and Parallelism in High Level Vision.

DTIC Science & Technology

1985-01-01

GRANT NUMBER(s) Jerome A. Feldman N00014-82-K-0193 9. PERFORMING ORGANIZATION NAME AND ADDRESS 10. PROGRAM ELEMENt. PROJECT, TASK Computer Science...Connectionist Models 2.1 Background and Overviev % Computer science is just beginning to look seriously at parallel computation : it may turn out that...the chair. The program includes intermediate level networks that compute more complex joints and ones that compute parallelograms in the image. These

The Differential Effects of Two Types of Task Repetition on the Complexity, Accuracy, and Fluency in Computer-Mediated L2 Written Production: A Focus on Computer Anxiety

ERIC Educational Resources Information Center

Amiryousefi, Mohammad

2016-01-01

Previous task repetition studies have primarily focused on how task repetition characteristics affect the complexity, accuracy, and fluency in L2 oral production with little attention to L2 written production. The main purpose of the study reported in this paper was to examine the effects of task repetition versus procedural repetition on the…

Computational Characterization of Electromagnetic Field Propagation in Complex Structures

DTIC Science & Technology

1998-04-10

34Computational characterization of electromagnetic field propagation in complex structures", DAAH01-91-D-ROOS D.O. 59. Dr. Michael Scalora performed the...Development, and Engineering Center, Bldg. 7804, Room 242 Redstone Arsenal, Alabama 35898-5248 USA Dr. Michael Scalora Quantum Optics Group Tel:(205...scheduled to appear. They are: (1) M. Scalora , J.P. Dowling, A.S. Manka, CM. Bowden, and J.W. Haus, Pulse Propagation Near Highly Reflective

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.

Novel Image Quality Control Systems(Add-On). Innovative Computational Methods for Inverse Problems in Optical and SAR Imaging

DTIC Science & Technology

2007-02-28

Iterative Ultrasonic Signal and Image Deconvolution for Estimation of the Complex Medium Response, International Journal of Imaging Systems and...1767-1782, 2006. 31. Z. Mu, R. Plemmons, and P. Santago. Iterative Ultrasonic Signal and Image Deconvolution for Estimation of the Complex...rigorous mathematical and computational research on inverse problems in optical imaging of direct interest to the Army and also the intelligence agencies

AstroGrid: Taverna in the Virtual Observatory .

NASA Astrophysics Data System (ADS)

Benson, K. M.; Walton, N. A.

This paper reports on the implementation of the Taverna workbench by AstroGrid, a tool for designing and executing workflows of tasks in the Virtual Observatory. The workflow approach helps astronomers perform complex task sequences with little technical effort. Visual approach to workflow construction streamlines highly complex analysis over public and private data and uses computational resources as minimal as a desktop computer. Some integration issues and future work are discussed in this article.

Perspective: Quantum mechanical methods in biochemistry and biophysics.

PubMed

Cui, Qiang

2016-10-14

In this perspective article, I discuss several research topics relevant to quantum mechanical (QM) methods in biophysical and biochemical applications. Due to the immense complexity of biological problems, the key is to develop methods that are able to strike the proper balance of computational efficiency and accuracy for the problem of interest. Therefore, in addition to the development of novel ab initio and density functional theory based QM methods for the study of reactive events that involve complex motifs such as transition metal clusters in metalloenzymes, it is equally important to develop inexpensive QM methods and advanced classical or quantal force fields to describe different physicochemical properties of biomolecules and their behaviors in complex environments. Maintaining a solid connection of these more approximate methods with rigorous QM methods is essential to their transferability and robustness. Comparison to diverse experimental observables helps validate computational models and mechanistic hypotheses as well as driving further development of computational methodologies.

Computational intelligence in bioinformatics: SNP/haplotype data in genetic association study for common diseases.

PubMed

Kelemen, Arpad; Vasilakos, Athanasios V; Liang, Yulan

2009-09-01

Comprehensive evaluation of common genetic variations through association of single-nucleotide polymorphism (SNP) structure with common complex disease in the genome-wide scale is currently a hot area in human genome research due to the recent development of the Human Genome Project and HapMap Project. Computational science, which includes computational intelligence (CI), has recently become the third method of scientific enquiry besides theory and experimentation. There have been fast growing interests in developing and applying CI in disease mapping using SNP and haplotype data. Some of the recent studies have demonstrated the promise and importance of CI for common complex diseases in genomic association study using SNP/haplotype data, especially for tackling challenges, such as gene-gene and gene-environment interactions, and the notorious "curse of dimensionality" problem. This review provides coverage of recent developments of CI approaches for complex diseases in genetic association study with SNP/haplotype data.

Strategies for concurrent processing of complex algorithms in data driven architectures

NASA Technical Reports Server (NTRS)

Stoughton, John W.; Mielke, Roland R.

1988-01-01

The purpose is to document research to develop strategies for concurrent processing of complex algorithms in data driven architectures. The problem domain consists of decision-free algorithms having large-grained, computationally complex primitive operations. Such are often found in signal processing and control applications. The anticipated multiprocessor environment is a data flow architecture containing between two and twenty computing elements. Each computing element is a processor having local program memory, and which communicates with a common global data memory. A new graph theoretic model called ATAMM which establishes rules for relating a decomposed algorithm to its execution in a data flow architecture is presented. The ATAMM model is used to determine strategies to achieve optimum time performance and to develop a system diagnostic software tool. In addition, preliminary work on a new multiprocessor operating system based on the ATAMM specifications is described.

PEM-PCA: a parallel expectation-maximization PCA face recognition architecture.

PubMed

Rujirakul, Kanokmon; So-In, Chakchai; Arnonkijpanich, Banchar

2014-01-01

Principal component analysis or PCA has been traditionally used as one of the feature extraction techniques in face recognition systems yielding high accuracy when requiring a small number of features. However, the covariance matrix and eigenvalue decomposition stages cause high computational complexity, especially for a large database. Thus, this research presents an alternative approach utilizing an Expectation-Maximization algorithm to reduce the determinant matrix manipulation resulting in the reduction of the stages' complexity. To improve the computational time, a novel parallel architecture was employed to utilize the benefits of parallelization of matrix computation during feature extraction and classification stages including parallel preprocessing, and their combinations, so-called a Parallel Expectation-Maximization PCA architecture. Comparing to a traditional PCA and its derivatives, the results indicate lower complexity with an insignificant difference in recognition precision leading to high speed face recognition systems, that is, the speed-up over nine and three times over PCA and Parallel PCA.

Biocellion: accelerating computer simulation of multicellular biological system models

PubMed Central

Kang, Seunghwa; Kahan, Simon; McDermott, Jason; Flann, Nicholas; Shmulevich, Ilya

2014-01-01

Motivation: Biological system behaviors are often the outcome of complex interactions among a large number of cells and their biotic and abiotic environment. Computational biologists attempt to understand, predict and manipulate biological system behavior through mathematical modeling and computer simulation. Discrete agent-based modeling (in combination with high-resolution grids to model the extracellular environment) is a popular approach for building biological system models. However, the computational complexity of this approach forces computational biologists to resort to coarser resolution approaches to simulate large biological systems. High-performance parallel computers have the potential to address the computing challenge, but writing efficient software for parallel computers is difficult and time-consuming. Results: We have developed Biocellion, a high-performance software framework, to solve this computing challenge using parallel computers. To support a wide range of multicellular biological system models, Biocellion asks users to provide their model specifics by filling the function body of pre-defined model routines. Using Biocellion, modelers without parallel computing expertise can efficiently exploit parallel computers with less effort than writing sequential programs from scratch. We simulate cell sorting, microbial patterning and a bacterial system in soil aggregate as case studies. Availability and implementation: Biocellion runs on x86 compatible systems with the 64 bit Linux operating system and is freely available for academic use. Visit http://biocellion.com for additional information. Contact: seunghwa.kang@pnnl.gov PMID:25064572

Computational science: shifting the focus from tools to models

PubMed Central

Hinsen, Konrad

2014-01-01

Computational techniques have revolutionized many aspects of scientific research over the last few decades. Experimentalists use computation for data analysis, processing ever bigger data sets. Theoreticians compute predictions from ever more complex models. However, traditional articles do not permit the publication of big data sets or complex models. As a consequence, these crucial pieces of information no longer enter the scientific record. Moreover, they have become prisoners of scientific software: many models exist only as software implementations, and the data are often stored in proprietary formats defined by the software. In this article, I argue that this emphasis on software tools over models and data is detrimental to science in the long term, and I propose a means by which this can be reversed. PMID:25309728

Conservative zonal schemes for patched grids in 2 and 3 dimensions

NASA Technical Reports Server (NTRS)

Hessenius, Kristin A.

1987-01-01

The computation of flow over complex geometries, such as realistic aircraft configurations, poses difficult grid generation problems for computational aerodynamicists. The creation of a traditional, single-module grid of acceptable quality about an entire configuration may be impossible even with the most sophisticated of grid generation techniques. A zonal approach, wherein the flow field is partitioned into several regions within which grids are independently generated, is a practical alternative for treating complicated geometries. This technique not only alleviates the problems of discretizing a complex region, but also facilitates a block processing approach to computation thereby circumventing computer memory limitations. The use of such a zonal scheme, however, requires the development of an interfacing procedure that ensures a stable, accurate, and conservative calculation for the transfer of information across the zonal borders.

Remote sensing image ship target detection method based on visual attention model

NASA Astrophysics Data System (ADS)

Sun, Yuejiao; Lei, Wuhu; Ren, Xiaodong

2017-11-01

The traditional methods of detecting ship targets in remote sensing images mostly use sliding window to search the whole image comprehensively. However, the target usually occupies only a small fraction of the image. This method has high computational complexity for large format visible image data. The bottom-up selective attention mechanism can selectively allocate computing resources according to visual stimuli, thus improving the computational efficiency and reducing the difficulty of analysis. Considering of that, a method of ship target detection in remote sensing images based on visual attention model was proposed in this paper. The experimental results show that the proposed method can reduce the computational complexity while improving the detection accuracy, and improve the detection efficiency of ship targets in remote sensing images.

[Towards computer-aided catalyst design: Three effective core potential studies of C-H activation]. Final report

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

NONE

1998-12-31

Research in the initial grant period focused on computational studies relevant to the selective activation of methane, the prime component of natural gas. Reaction coordinates for methane activation by experimental models were delineated, as well as the bonding and structure of complexes that effect this important reaction. This research, highlighted in the following sections, also provided the impetus for further development, and application of methods for modeling metal-containing catalysts. Sections of the report describe the following: methane activation by multiple-bonded transition metal complexes; computational lanthanide chemistry; and methane activation by non-imido, multiple-bonded ligands.

Editorial [Special issue on software defined networks and infrastructures, network function virtualisation, autonomous systems and network management

DOE PAGES

Biswas, Amitava; Liu, Chen; Monga, Inder; ...

2016-01-01

For last few years, there has been a tremendous growth in data traffic due to high adoption rate of mobile devices and cloud computing. Internet of things (IoT) will stimulate even further growth. This is increasing scale and complexity of telecom/internet service provider (SP) and enterprise data centre (DC) compute and network infrastructures. As a result, managing these large network-compute converged infrastructures is becoming complex and cumbersome. To cope up, network and DC operators are trying to automate network and system operations, administrations and management (OAM) functions. OAM includes all non-functional mechanisms which keep the network running.

Block-structured grids for complex aerodynamic configurations: Current status

NASA Technical Reports Server (NTRS)

Vatsa, Veer N.; Sanetrik, Mark D.; Parlette, Edward B.

1995-01-01

The status of CFD methods based on the use of block-structured grids for analyzing viscous flows over complex configurations is examined. The objective of the present study is to make a realistic assessment of the usability of such grids for routine computations typically encountered in the aerospace industry. It is recognized at the very outset that the total turnaround time, from the moment the configuration is identified until the computational results have been obtained and postprocessed, is more important than just the computational time. Pertinent examples will be cited to demonstrate the feasibility of solving flow over practical configurations of current interest on block-structured grids.

Improving the Aircraft Design Process Using Web-Based Modeling and Simulation

NASA Technical Reports Server (NTRS)

Reed, John A.; Follen, Gregory J.; Afjeh, Abdollah A.; Follen, Gregory J. (Technical Monitor)

2000-01-01

Designing and developing new aircraft systems is time-consuming and expensive. Computational simulation is a promising means for reducing design cycle times, but requires a flexible software environment capable of integrating advanced multidisciplinary and multifidelity analysis methods, dynamically managing data across heterogeneous computing platforms, and distributing computationally complex tasks. Web-based simulation, with its emphasis on collaborative composition of simulation models, distributed heterogeneous execution, and dynamic multimedia documentation, has the potential to meet these requirements. This paper outlines the current aircraft design process, highlighting its problems and complexities, and presents our vision of an aircraft design process using Web-based modeling and simulation.

Improving the Aircraft Design Process Using Web-based Modeling and Simulation

NASA Technical Reports Server (NTRS)

Reed, John A.; Follen, Gregory J.; Afjeh, Abdollah A.

2003-01-01

Designing and developing new aircraft systems is time-consuming and expensive. Computational simulation is a promising means for reducing design cycle times, but requires a flexible software environment capable of integrating advanced multidisciplinary and muitifidelity analysis methods, dynamically managing data across heterogeneous computing platforms, and distributing computationally complex tasks. Web-based simulation, with its emphasis on collaborative composition of simulation models, distributed heterogeneous execution, and dynamic multimedia documentation, has the potential to meet these requirements. This paper outlines the current aircraft design process, highlighting its problems and complexities, and presents our vision of an aircraft design process using Web-based modeling and simulation.

Artificial neural networks using complex numbers and phase encoded weights.

PubMed

Michel, Howard E; Awwal, Abdul Ahad S

2010-04-01

The model of a simple perceptron using phase-encoded inputs and complex-valued weights is proposed. The aggregation function, activation function, and learning rule for the proposed neuron are derived and applied to Boolean logic functions and simple computer vision tasks. The complex-valued neuron (CVN) is shown to be superior to traditional perceptrons. An improvement of 135% over the theoretical maximum of 104 linearly separable problems (of three variables) solvable by conventional perceptrons is achieved without additional logic, neuron stages, or higher order terms such as those required in polynomial logic gates. The application of CVN in distortion invariant character recognition and image segmentation is demonstrated. Implementation details are discussed, and the CVN is shown to be very attractive for optical implementation since optical computations are naturally complex. The cost of the CVN is less in all cases than the traditional neuron when implemented optically. Therefore, all the benefits of the CVN can be obtained without additional cost. However, on those implementations dependent on standard serial computers, CVN will be more cost effective only in those applications where its increased power can offset the requirement for additional neurons.

Quasi-analytical treatment of spatially averaged radiation transfer in complex terrain

NASA Astrophysics Data System (ADS)

Löwe, H.; Helbig, N.

2012-04-01

We provide a new quasi-analytical method to compute the topographic influence on the effective albedo of complex topography as required for meteorological, land-surface or climate models. We investigate radiative transfer in complex terrain via the radiosity equation on isotropic Gaussian random fields. Under controlled approximations we derive expressions for domain averages of direct, diffuse and terrain radiation and the sky view factor. Domain averaged quantities are related to a type of level-crossing probability of the random field which is approximated by longstanding results developed for acoustic scattering at ocean boundaries. This allows us to express all non-local horizon effects in terms of a local terrain parameter, namely the mean squared slope. Emerging integrals are computed numerically and fit formulas are given for practical purposes. As an implication of our approach we provide an expression for the effective albedo of complex terrain in terms of the sun elevation angle, mean squared slope, the area averaged surface albedo, and the direct-to-diffuse ratio of solar radiation. As an application, we compute the effective albedo for the Swiss Alps and discuss possible generalizations of the method.

The FuturICT education accelerator

NASA Astrophysics Data System (ADS)

Johnson, J.; Buckingham Shum, S.; Willis, A.; Bishop, S.; Zamenopoulos, T.; Swithenby, S.; MacKay, R.; Merali, Y.; Lorincz, A.; Costea, C.; Bourgine, P.; Louçã, J.; Kapenieks, A.; Kelley, P.; Caird, S.; Bromley, J.; Deakin Crick, R.; Goldspink, C.; Collet, P.; Carbone, A.; Helbing, D.

2012-11-01

Education is a major force for economic and social wellbeing. Despite high aspirations, education at all levels can be expensive and ineffective. Three Grand Challenges are identified: (1) enable people to learn orders of magnitude more effectively, (2) enable people to learn at orders of magnitude less cost, and (3) demonstrate success by exemplary interdisciplinary education in complex systems science. A ten year `man-on-the-moon' project is proposed in which FuturICT's unique combination of Complexity, Social and Computing Sciences could provide an urgently needed transdisciplinary language for making sense of educational systems. In close dialogue with educational theory and practice, and grounded in the emerging data science and learning analytics paradigms, this will translate into practical tools (both analytical and computational) for researchers, practitioners and leaders; generative principles for resilient educational ecosystems; and innovation for radically scalable, yet personalised, learner engagement and assessment. The proposed Education Accelerator will serve as a `wind tunnel' for testing these ideas in the context of real educational programmes, with an international virtual campus delivering complex systems education exploiting the new understanding of complex, social, computationally enhanced organisational structure developed within FuturICT.

Efficient calculation of open quantum system dynamics and time-resolved spectroscopy with distributed memory HEOM (DM-HEOM).

PubMed

Kramer, Tobias; Noack, Matthias; Reinefeld, Alexander; Rodríguez, Mirta; Zelinskyy, Yaroslav

2018-06-11

Time- and frequency-resolved optical signals provide insights into the properties of light-harvesting molecular complexes, including excitation energies, dipole strengths and orientations, as well as in the exciton energy flow through the complex. The hierarchical equations of motion (HEOM) provide a unifying theory, which allows one to study the combined effects of system-environment dissipation and non-Markovian memory without making restrictive assumptions about weak or strong couplings or separability of vibrational and electronic degrees of freedom. With increasing system size the exact solution of the open quantum system dynamics requires memory and compute resources beyond a single compute node. To overcome this barrier, we developed a scalable variant of HEOM. Our distributed memory HEOM, DM-HEOM, is a universal tool for open quantum system dynamics. It is used to accurately compute all experimentally accessible time- and frequency-resolved processes in light-harvesting molecular complexes with arbitrary system-environment couplings for a wide range of temperatures and complex sizes. © 2018 Wiley Periodicals, Inc. © 2018 Wiley Periodicals, Inc.

Is Model-Based Development a Favorable Approach for Complex and Safety-Critical Computer Systems on Commercial Aircraft?

NASA Technical Reports Server (NTRS)

Torres-Pomales, Wilfredo

2014-01-01

A system is safety-critical if its failure can endanger human life or cause significant damage to property or the environment. State-of-the-art computer systems on commercial aircraft are highly complex, software-intensive, functionally integrated, and network-centric systems of systems. Ensuring that such systems are safe and comply with existing safety regulations is costly and time-consuming as the level of rigor in the development process, especially the validation and verification activities, is determined by considerations of system complexity and safety criticality. A significant degree of care and deep insight into the operational principles of these systems is required to ensure adequate coverage of all design implications relevant to system safety. Model-based development methodologies, methods, tools, and techniques facilitate collaboration and enable the use of common design artifacts among groups dealing with different aspects of the development of a system. This paper examines the application of model-based development to complex and safety-critical aircraft computer systems. Benefits and detriments are identified and an overall assessment of the approach is given.

Design considerations for computationally constrained two-way real-time video communication

NASA Astrophysics Data System (ADS)

Bivolarski, Lazar M.; Saunders, Steven E.; Ralston, John D.

2009-08-01

Today's video codecs have evolved primarily to meet the requirements of the motion picture and broadcast industries, where high-complexity studio encoding can be utilized to create highly-compressed master copies that are then broadcast one-way for playback using less-expensive, lower-complexity consumer devices for decoding and playback. Related standards activities have largely ignored the computational complexity and bandwidth constraints of wireless or Internet based real-time video communications using devices such as cell phones or webcams. Telecommunications industry efforts to develop and standardize video codecs for applications such as video telephony and video conferencing have not yielded image size, quality, and frame-rate performance that match today's consumer expectations and market requirements for Internet and mobile video services. This paper reviews the constraints and the corresponding video codec requirements imposed by real-time, 2-way mobile video applications. Several promising elements of a new mobile video codec architecture are identified, and more comprehensive computational complexity metrics and video quality metrics are proposed in order to support the design, testing, and standardization of these new mobile video codecs.

Computer Diagnostics.

ERIC Educational Resources Information Center

Tondow, Murray

The report deals with the influence of computer technology on education, particularly guidance. The need for computers is a result of increasing complexity which is defined as: (1) an exponential increase of information; (2) an exponential increase in dissemination capabilities; and (3) an accelerating curve of change. Listed are five functions of…

Estimating the Reliability of the CITAR Computer Courseware Evaluation System.

ERIC Educational Resources Information Center

Micceri, Theodore

In today's complex computer-based teaching (CBT)/computer-assisted instruction market, flashy presentations frequently prove the most important purchasing element, while instructional design and content are secondary to form. Courseware purchasers must base decisions upon either a vendor's presentation or some published evaluator rating.…

Demographic Computer Library.

ERIC Educational Resources Information Center

Shaw, David C.; Johnson, Dorothy M.

The complete comprehension of this paper requires a firm grasp of both mathematical demography and FORTRAN programming. The paper aims at the establishment of a language with which complex demographic manipulations can be briefly expressed in a form intelligible both to demographic analysts and to computers. The Demographic Computer Library (DCL)…

SIGMA--A Graphical Approach to Teaching Simulation.

ERIC Educational Resources Information Center

Schruben, Lee W.

1992-01-01

SIGMA (Simulation Graphical Modeling and Analysis) is a computer graphics environment for building, testing, and experimenting with discrete event simulation models on personal computers. It uses symbolic representations (computer animation) to depict the logic of large, complex discrete event systems for easier understanding and has proven itself…

Theoretical studies of UO(2)(OH)(H(2)O)(n) (+), UO(2)(OH)(2)(H(2)O)(n), NpO(2)(OH)(H(2)O)(n), and PuO(2)(OH)(H(2)O)(n) (+) (n

PubMed

Cao, Zhiji; Balasubramanian, K

2009-10-28

Extensive ab initio calculations have been carried out to study equilibrium structures, vibrational frequencies, and the nature of chemical bonds of hydrated UO(2)(OH)(+), UO(2)(OH)(2), NpO(2)(OH), and PuO(2)(OH)(+) complexes that contain up to 21 water molecules both in first and second hydration spheres in both aqueous solution and the gas phase. The structures have been further optimized by considering long-range solvent effects through a polarizable continuum dielectric model. The hydrolysis reaction Gibbs free energy of UO(2)(H(2)O)(5) (2+) is computed to be 8.11 kcal/mol at the MP2 level in good agreement with experiments. Our results reveal that it is necessary to include water molecules bound to the complex in the first hydration sphere for proper treatment of the hydrated complex and the dielectric cavity although water molecules in the second hydration sphere do not change the coordination complex. Structural reoptimization of the complex in a dielectric cavity seems inevitable to seek subtle structural variations in the solvent and to correlate with the observed spectra and thermodynamic properties in the aqueous environment. Our computations reveal dramatically different equilibrium structures in the gas phase and solution and also confirm the observed facile exchanges between the complex and bulk solvent. Complete active space multiconfiguration self-consistent field followed by multireference singles+doubles CI (MRSDCI) computations on smaller complexes confirm predominantly single-configurational nature of these species and the validity of B3LYP and MP2 techniques for these complexes in their ground states.

2.5D complex resistivity modeling and inversion using unstructured grids

NASA Astrophysics Data System (ADS)

Xu, Kaijun; Sun, Jie

2016-04-01

The characteristic of complex resistivity on rock and ore has been recognized by people for a long time. Generally we have used the Cole-Cole Model(CCM) to describe complex resistivity. It has been proved that the electrical anomaly of geologic body can be quantitative estimated by CCM parameters such as direct resistivity(ρ0), chargeability(m), time constant(τ) and frequency dependence(c). Thus it is very important to obtain the complex parameters of geologic body. It is difficult to approximate complex structures and terrain using traditional rectangular grid. In order to enhance the numerical accuracy and rationality of modeling and inversion, we use an adaptive finite-element algorithm for forward modeling of the frequency-domain 2.5D complex resistivity and implement the conjugate gradient algorithm in the inversion of 2.5D complex resistivity. An adaptive finite element method is applied for solving the 2.5D complex resistivity forward modeling of horizontal electric dipole source. First of all, the CCM is introduced into the Maxwell's equations to calculate the complex resistivity electromagnetic fields. Next, the pseudo delta function is used to distribute electric dipole source. Then the electromagnetic fields can be expressed in terms of the primary fields caused by layered structure and the secondary fields caused by inhomogeneities anomalous conductivity. At last, we calculated the electromagnetic fields response of complex geoelectric structures such as anticline, syncline, fault. The modeling results show that adaptive finite-element methods can automatically improve mesh generation and simulate complex geoelectric models using unstructured grids. The 2.5D complex resistivity invertion is implemented based the conjugate gradient algorithm.The conjugate gradient algorithm doesn't need to compute the sensitivity matrix but directly computes the sensitivity matrix or its transpose multiplying vector. In addition, the inversion target zones are segmented with fine grids and the background zones are segmented with big grid, the method can reduce the grid amounts of inversion, it is very helpful to improve the computational efficiency. The inversion results verify the validity and stability of conjugate gradient inversion algorithm. The results of theoretical calculation indicate that the modeling and inversion of 2.5D complex resistivity using unstructured grids are feasible. Using unstructured grids can improve the accuracy of modeling, but the large number of grids inversion is extremely time-consuming, so the parallel computation for the inversion is necessary. Acknowledgments: We thank to the support of the National Natural Science Foundation of China(41304094).

Geometric modeling of subcellular structures, organelles, and multiprotein complexes

PubMed Central

Feng, Xin; Xia, Kelin; Tong, Yiying; Wei, Guo-Wei

2013-01-01

SUMMARY Recently, the structure, function, stability, and dynamics of subcellular structures, organelles, and multi-protein complexes have emerged as a leading interest in structural biology. Geometric modeling not only provides visualizations of shapes for large biomolecular complexes but also fills the gap between structural information and theoretical modeling, and enables the understanding of function, stability, and dynamics. This paper introduces a suite of computational tools for volumetric data processing, information extraction, surface mesh rendering, geometric measurement, and curvature estimation of biomolecular complexes. Particular emphasis is given to the modeling of cryo-electron microscopy data. Lagrangian-triangle meshes are employed for the surface presentation. On the basis of this representation, algorithms are developed for surface area and surface-enclosed volume calculation, and curvature estimation. Methods for volumetric meshing have also been presented. Because the technological development in computer science and mathematics has led to multiple choices at each stage of the geometric modeling, we discuss the rationales in the design and selection of various algorithms. Analytical models are designed to test the computational accuracy and convergence of proposed algorithms. Finally, we select a set of six cryo-electron microscopy data representing typical subcellular complexes to demonstrate the efficacy of the proposed algorithms in handling biomolecular surfaces and explore their capability of geometric characterization of binding targets. This paper offers a comprehensive protocol for the geometric modeling of subcellular structures, organelles, and multiprotein complexes. PMID:23212797

40-Gb/s PAM4 with low-complexity equalizers for next-generation PON systems

NASA Astrophysics Data System (ADS)

Tang, Xizi; Zhou, Ji; Guo, Mengqi; Qi, Jia; Hu, Fan; Qiao, Yaojun; Lu, Yueming

2018-01-01

In this paper, we demonstrate 40-Gb/s four-level pulse amplitude modulation (PAM4) transmission with 10 GHz devices and low-complexity equalizers for next-generation passive optical network (PON) systems. Simple feed-forward equalizer (FFE) and decision feedback equalizer (DFE) enable 20 km fiber transmission while high-complexity Volterra algorithm in combination with FFE and DFE can extend the transmission distance to 40 km. A simplified Volterra algorithm is proposed for reducing computational complexity. Simulation results show that the simplified Volterra algorithm reduces up to ∼75% computational complexity at a relatively low cost of only 0.4 dB power budget. At a forward error correction (FEC) threshold of 10-3 , we achieve 31.2 dB and 30.8 dB power budget over 40 km fiber transmission using traditional FFE-DFE-Volterra and our simplified FFE-DFE-Volterra, respectively.

Implementation of Complex Biological Logic Circuits Using Spatially Distributed Multicellular Consortia

PubMed Central

Urrios, Arturo; de Nadal, Eulàlia; Solé, Ricard; Posas, Francesc

2016-01-01

Engineered synthetic biological devices have been designed to perform a variety of functions from sensing molecules and bioremediation to energy production and biomedicine. Notwithstanding, a major limitation of in vivo circuit implementation is the constraint associated to the use of standard methodologies for circuit design. Thus, future success of these devices depends on obtaining circuits with scalable complexity and reusable parts. Here we show how to build complex computational devices using multicellular consortia and space as key computational elements. This spatial modular design grants scalability since its general architecture is independent of the circuit’s complexity, minimizes wiring requirements and allows component reusability with minimal genetic engineering. The potential use of this approach is demonstrated by implementation of complex logical functions with up to six inputs, thus demonstrating the scalability and flexibility of this method. The potential implications of our results are outlined. PMID:26829588

Diagonalization of complex symmetric matrices: Generalized Householder reflections, iterative deflation and implicit shifts

NASA Astrophysics Data System (ADS)

Noble, J. H.; Lubasch, M.; Stevens, J.; Jentschura, U. D.

2017-12-01

We describe a matrix diagonalization algorithm for complex symmetric (not Hermitian) matrices, A ̲ =A̲T, which is based on a two-step algorithm involving generalized Householder reflections based on the indefinite inner product 〈 u ̲ , v ̲ 〉 ∗ =∑iuivi. This inner product is linear in both arguments and avoids complex conjugation. The complex symmetric input matrix is transformed to tridiagonal form using generalized Householder transformations (first step). An iterative, generalized QL decomposition of the tridiagonal matrix employing an implicit shift converges toward diagonal form (second step). The QL algorithm employs iterative deflation techniques when a machine-precision zero is encountered "prematurely" on the super-/sub-diagonal. The algorithm allows for a reliable and computationally efficient computation of resonance and antiresonance energies which emerge from complex-scaled Hamiltonians, and for the numerical determination of the real energy eigenvalues of pseudo-Hermitian and PT-symmetric Hamilton matrices. Numerical reference values are provided.

Multiscale computing.

PubMed

Kobayashi, M; Irino, T; Sweldens, W

2001-10-23

Multiscale computing (MSC) involves the computation, manipulation, and analysis of information at different resolution levels. Widespread use of MSC algorithms and the discovery of important relationships between different approaches to implementation were catalyzed, in part, by the recent interest in wavelets. We present two examples that demonstrate how MSC can help scientists understand complex data. The first is from acoustical signal processing and the second is from computer graphics.

Grid Computing in K-12 Schools. Soapbox Digest. Volume 3, Number 2, Fall 2004

ERIC Educational Resources Information Center

AEL, 2004

2004-01-01

Grid computing allows large groups of computers (either in a lab, or remote and connected only by the Internet) to extend extra processing power to each individual computer to work on components of a complex request. Grid middleware, recognizing priorities set by systems administrators, allows the grid to identify and use this power without…

Resolution of Infinite-Loop in Hyperincursive and Nonlocal Cellular Automata: Introduction to Slime Mold Computing

NASA Astrophysics Data System (ADS)

Aono, Masashi; Gunji, Yukio-Pegio

2004-08-01

How can non-algorithmic/non-deterministic computational syntax be computed? "The hyperincursive system" introduced by Dubois is an anticipatory system embracing the contradiction/uncertainty. Although it may provide a novel viewpoint for the understanding of complex systems, conventional digital computers cannot run faithfully as the hyperincursive computational syntax specifies, in a strict sense. Then is it an imaginary story? In this paper we try to argue that it is not. We show that a model of complex systems "Elementary Conflictable Cellular Automata (ECCA)" proposed by Aono and Gunji is embracing the hyperincursivity and the nonlocality. ECCA is based on locality-only type settings basically as well as other CA models, and/but at the same time, each cell is required to refer to globality-dominant regularity. Due to this contradictory locality-globality loop, the time evolution equation specifies that the system reaches the deadlock/infinite-loop. However, we show that there is a possibility of the resolution of these problems if the computing system has parallel and/but non-distributed property like an amoeboid organism. This paper is an introduction to "the slime mold computing" that is an attempt to cultivate an unconventional notion of computation.

A new order-theoretic characterisation of the polytime computable functions☆

PubMed Central

Avanzini, Martin; Eguchi, Naohi; Moser, Georg

2015-01-01

We propose a new order-theoretic characterisation of the class of polytime computable functions. To this avail we define the small polynomial path order (sPOP⁎ for short). This termination order entails a new syntactic method to analyse the innermost runtime complexity of term rewrite systems fully automatically: for any rewrite system compatible with sPOP⁎ that employs recursion up to depth d, the (innermost) runtime complexity is polynomially bounded of degree d. This bound is tight. Thus we obtain a direct correspondence between a syntactic (and easily verifiable) condition of a program and the asymptotic worst-case complexity of the program. PMID:26412933

Fast parallel approach for 2-D DHT-based real-valued discrete Gabor transform.

PubMed

Tao, Liang; Kwan, Hon Keung

2009-12-01

Two-dimensional fast Gabor transform algorithms are useful for real-time applications due to the high computational complexity of the traditional 2-D complex-valued discrete Gabor transform (CDGT). This paper presents two block time-recursive algorithms for 2-D DHT-based real-valued discrete Gabor transform (RDGT) and its inverse transform and develops a fast parallel approach for the implementation of the two algorithms. The computational complexity of the proposed parallel approach is analyzed and compared with that of the existing 2-D CDGT algorithms. The results indicate that the proposed parallel approach is attractive for real time image processing.

A chimera grid scheme. [multiple overset body-conforming mesh system for finite difference adaptation to complex aircraft configurations

NASA Technical Reports Server (NTRS)

Steger, J. L.; Dougherty, F. C.; Benek, J. A.

1983-01-01

A mesh system composed of multiple overset body-conforming grids is described for adapting finite-difference procedures to complex aircraft configurations. In this so-called 'chimera mesh,' a major grid is generated about a main component of the configuration and overset minor grids are used to resolve all other features. Methods for connecting overset multiple grids and modifications of flow-simulation algorithms are discussed. Computational tests in two dimensions indicate that the use of multiple overset grids can simplify the task of grid generation without an adverse effect on flow-field algorithms and computer code complexity.

Mg co-ordination with potential carcinogenic molecule acrylamide: Spectroscopic, computational and cytotoxicity studies

NASA Astrophysics Data System (ADS)

Singh, Ranjana; Mishra, Vijay K.; Singh, Hemant K.; Sharma, Gunjan; Koch, Biplob; Singh, Bachcha; Singh, Ranjan K.

2018-03-01

Acrylamide (acr) is a potential toxic molecule produced in thermally processed food stuff. Acr-Mg complex has been synthesized chemically and characterized by spectroscopic techniques. The binding sites of acr with Mg were identified by experimental and computational methods. Both experimental and theoretical results suggest that Mg coordinated with the oxygen atom of Cdbnd O group of acr. In-vitro cytotoxicity studies revealed significant decrease in the toxic level of acr-Mg complex as compared to pure acr. The decrease in toxicity on complexation with Mg may be a useful step for future research to reduce the toxicity of acr.

Event- and Time-Driven Techniques Using Parallel CPU-GPU Co-processing for Spiking Neural Networks

PubMed Central

Naveros, Francisco; Garrido, Jesus A.; Carrillo, Richard R.; Ros, Eduardo; Luque, Niceto R.

2017-01-01

Modeling and simulating the neural structures which make up our central neural system is instrumental for deciphering the computational neural cues beneath. Higher levels of biological plausibility usually impose higher levels of complexity in mathematical modeling, from neural to behavioral levels. This paper focuses on overcoming the simulation problems (accuracy and performance) derived from using higher levels of mathematical complexity at a neural level. This study proposes different techniques for simulating neural models that hold incremental levels of mathematical complexity: leaky integrate-and-fire (LIF), adaptive exponential integrate-and-fire (AdEx), and Hodgkin-Huxley (HH) neural models (ranged from low to high neural complexity). The studied techniques are classified into two main families depending on how the neural-model dynamic evaluation is computed: the event-driven or the time-driven families. Whilst event-driven techniques pre-compile and store the neural dynamics within look-up tables, time-driven techniques compute the neural dynamics iteratively during the simulation time. We propose two modifications for the event-driven family: a look-up table recombination to better cope with the incremental neural complexity together with a better handling of the synchronous input activity. Regarding the time-driven family, we propose a modification in computing the neural dynamics: the bi-fixed-step integration method. This method automatically adjusts the simulation step size to better cope with the stiffness of the neural model dynamics running in CPU platforms. One version of this method is also implemented for hybrid CPU-GPU platforms. Finally, we analyze how the performance and accuracy of these modifications evolve with increasing levels of neural complexity. We also demonstrate how the proposed modifications which constitute the main contribution of this study systematically outperform the traditional event- and time-driven techniques under increasing levels of neural complexity. PMID:28223930

[AERA. Dream machines and computing practices at the Mathematical Center].

PubMed

Alberts, Gerard; De Beer, Huub T

2008-01-01

Dream machines may be just as effective as the ones materialised. Their symbolic thrust can be quite powerful. The Amsterdam 'Mathematisch Centrum' (Mathematical Center), founded February 11, 1946, created a Computing Department in an effort to realise its goal of serving society. When Aad van Wijngaarden was appointed as head of the Computing Department, however, he claimed space for scientific research and computer construction, next to computing as a service. Still, the computing service following the five stage style of Hartree's numerical analysis remained a dominant characteristic of the work of the Computing Department. The high level of ambition held by Aad van Wijngaarden lead to ever renewed projections of big automatic computers, symbolised by the never-built AERA. Even a machine that was actually constructed, the ARRA which followed A.D. Booth's design of the ARC, never made it into real operation. It did serve Van Wijngaarden to bluff his way into the computer age by midsummer 1952. Not until January 1954 did the computing department have a working stored program computer, which for reasons of policy went under the same name: ARRA. After just one other machine, the ARMAC, had been produced, a separate company, Electrologica, was set up for the manufacture of computers, which produced the rather successful X1 computer. The combination of ambition and absence of a working machine lead to a high level of work on programming, way beyond the usual ideas of libraries of subroutines. Edsger W. Dijkstra in particular led the way to an emphasis on the duties of the programmer within the pattern of numerical analysis. Programs generating programs, known elsewhere as autocoding systems, were at the 'Mathematisch Centrum' called 'superprograms'. Practical examples were usually called a 'complex', in Dutch, where in English one might say 'system'. Historically, this is where software begins. Dekker's matrix complex, Dijkstra's interrupt system, Dijkstra and Zonneveld's ALGOL compiler--which for housekeeping contained 'the complex'--were actual examples of such super programs. In 1960 this compiler gave the Mathematical Center a leading edge in the early development of software.

Mononuclear nickel (II) and copper (II) coordination complexes supported by bispicen ligand derivatives: Experimental and computational studies

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

Singh, Nirupama; Niklas, Jens; Poluektov, Oleg

2017-01-01

The synthesis, characterization and density functional theory calculations of mononuclear Ni and Cu complexes supported by the N,N’-Dimethyl-N,N’-bis-(pyridine-2-ylmethyl)-1,2-diaminoethane ligand and its derivatives are reported. The complexes were characterized by X-ray crystallography as well as by UV-visible absorption spectroscopy and EPR spectroscopy. The solid state structure of these coordination complexes revealed that the geometry of the complex depended on the identity of the metal center. Solution phase characterization data are in accord with the solid phase structure, indicating minimal structural changes in solution. Optical spectroscopy revealed that all of the complexes exhibit color owing to d-d transition bands in the visiblemore » region. Magnetic parameters obtained from EPR spectroscopy with other structural data suggest that the Ni(II) complexes are in pseudo-octahedral geometry and Cu(II) complexes are in a distorted square pyramidal geometry. In order to understand in detail how ligand sterics and electronics affect complex topology detailed computational studies were performed. The series of complexes reported in this article will add significant value in the field of coordination chemistry as Ni(II) and Cu(II) complexes supported by tetradentate pyridyl based ligands are rather scarce.« less

Offdiagonal complexity: A computationally quick complexity measure for graphs and networks

NASA Astrophysics Data System (ADS)

Claussen, Jens Christian

2007-02-01

A vast variety of biological, social, and economical networks shows topologies drastically differing from random graphs; yet the quantitative characterization remains unsatisfactory from a conceptual point of view. Motivated from the discussion of small scale-free networks, a biased link distribution entropy is defined, which takes an extremum for a power-law distribution. This approach is extended to the node-node link cross-distribution, whose nondiagonal elements characterize the graph structure beyond link distribution, cluster coefficient and average path length. From here a simple (and computationally cheap) complexity measure can be defined. This offdiagonal complexity (OdC) is proposed as a novel measure to characterize the complexity of an undirected graph, or network. While both for regular lattices and fully connected networks OdC is zero, it takes a moderately low value for a random graph and shows high values for apparently complex structures as scale-free networks and hierarchical trees. The OdC approach is applied to the Helicobacter pylori protein interaction network and randomly rewired surrogates.

Research on application of intelligent computation based LUCC model in urbanization process

NASA Astrophysics Data System (ADS)

Chen, Zemin

2007-06-01

Global change study is an interdisciplinary and comprehensive research activity with international cooperation, arising in 1980s, with the largest scopes. The interaction between land use and cover change, as a research field with the crossing of natural science and social science, has become one of core subjects of global change study as well as the front edge and hot point of it. It is necessary to develop research on land use and cover change in urbanization process and build an analog model of urbanization to carry out description, simulation and analysis on dynamic behaviors in urban development change as well as to understand basic characteristics and rules of urbanization process. This has positive practical and theoretical significance for formulating urban and regional sustainable development strategy. The effect of urbanization on land use and cover change is mainly embodied in the change of quantity structure and space structure of urban space, and LUCC model in urbanization process has been an important research subject of urban geography and urban planning. In this paper, based upon previous research achievements, the writer systematically analyzes the research on land use/cover change in urbanization process with the theories of complexity science research and intelligent computation; builds a model for simulating and forecasting dynamic evolution of urban land use and cover change, on the basis of cellular automation model of complexity science research method and multi-agent theory; expands Markov model, traditional CA model and Agent model, introduces complexity science research theory and intelligent computation theory into LUCC research model to build intelligent computation-based LUCC model for analog research on land use and cover change in urbanization research, and performs case research. The concrete contents are as follows: 1. Complexity of LUCC research in urbanization process. Analyze urbanization process in combination with the contents of complexity science research and the conception of complexity feature to reveal the complexity features of LUCC research in urbanization process. Urban space system is a complex economic and cultural phenomenon as well as a social process, is the comprehensive characterization of urban society, economy and culture, and is a complex space system formed by society, economy and nature. It has dissipative structure characteristics, such as opening, dynamics, self-organization, non-balance etc. Traditional model cannot simulate these social, economic and natural driving forces of LUCC including main feedback relation from LUCC to driving force. 2. Establishment of Markov extended model of LUCC analog research in urbanization process. Firstly, use traditional LUCC research model to compute change speed of regional land use through calculating dynamic degree, exploitation degree and consumption degree of land use; use the theory of fuzzy set to rewrite the traditional Markov model, establish structure transfer matrix of land use, forecast and analyze dynamic change and development trend of land use, and present noticeable problems and corresponding measures in urbanization process according to research results. 3. Application of intelligent computation research and complexity science research method in LUCC analog model in urbanization process. On the basis of detailed elaboration of the theory and the model of LUCC research in urbanization process, analyze the problems of existing model used in LUCC research (namely, difficult to resolve many complexity phenomena in complex urban space system), discuss possible structure realization forms of LUCC analog research in combination with the theories of intelligent computation and complexity science research. Perform application analysis on BP artificial neural network and genetic algorithms of intelligent computation and CA model and MAS technology of complexity science research, discuss their theoretical origins and their own characteristics in detail, elaborate the feasibility of them in LUCC analog research, and bring forward improvement methods and measures on existing problems of this kind of model. 4. Establishment of LUCC analog model in urbanization process based on theories of intelligent computation and complexity science. Based on the research on abovementioned BP artificial neural network, genetic algorithms, CA model and multi-agent technology, put forward improvement methods and application assumption towards their expansion on geography, build LUCC analog model in urbanization process based on CA model and Agent model, realize the combination of learning mechanism of BP artificial neural network and fuzzy logic reasoning, express the regulation with explicit formula, and amend the initial regulation through self study; optimize network structure of LUCC analog model and methods and procedures of model parameters with genetic algorithms. In this paper, I introduce research theory and methods of complexity science into LUCC analog research and presents LUCC analog model based upon CA model and MAS theory. Meanwhile, I carry out corresponding expansion on traditional Markov model and introduce the theory of fuzzy set into data screening and parameter amendment of improved model to improve the accuracy and feasibility of Markov model in the research on land use/cover change.

New Pedagogies on Teaching Science with Computer Simulations

ERIC Educational Resources Information Center

Khan, Samia

2011-01-01

Teaching science with computer simulations is a complex undertaking. This case study examines how an experienced science teacher taught chemistry using computer simulations and the impact of his teaching on his students. Classroom observations over 3 semesters, teacher interviews, and student surveys were collected. The data was analyzed for (1)…

Implications of Windowing Techniques for CAI.

ERIC Educational Resources Information Center

Heines, Jesse M.; Grinstein, Georges G.

This paper discusses the use of a technique called windowing in computer assisted instruction to allow independent control of functional areas in complex CAI displays and simultaneous display of output from a running computer program and coordinated instructional material. Two obstacles to widespread use of CAI in computer science courses are…

Digital Maps, Matrices and Computer Algebra

ERIC Educational Resources Information Center

Knight, D. G.

2005-01-01

The way in which computer algebra systems, such as Maple, have made the study of complex problems accessible to undergraduate mathematicians with modest computational skills is illustrated by some large matrix calculations, which arise from representing the Earth's surface by digital elevation models. Such problems are often considered to lie in…

Classical versus Computer Algebra Methods in Elementary Geometry

ERIC Educational Resources Information Center

Pech, Pavel

2005-01-01

Computer algebra methods based on results of commutative algebra like Groebner bases of ideals and elimination of variables make it possible to solve complex, elementary and non elementary problems of geometry, which are difficult to solve using a classical approach. Computer algebra methods permit the proof of geometric theorems, automatic…

2016 Annual Report - Argonne Leadership Computing Facility

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

Collins, Jim; Papka, Michael E.; Cerny, Beth A.

The Argonne Leadership Computing Facility (ALCF) helps researchers solve some of the world’s largest and most complex problems, while also advancing the nation’s efforts to develop future exascale computing systems. This report presents some of the ALCF’s notable achievements in key strategic areas over the past year.

Using Real-Life Experiences to Teach Computer Concepts

ERIC Educational Resources Information Center

Read, Alexis

2012-01-01

Teaching computer concepts to individuals with visual impairments (that is, those who are blind or visually impaired) presents some unique challenges. Students often have difficulty remembering to perform certain steps or have difficulty remembering specific keystrokes when using computers. Many cannot visualize the way in which complex computing…

Examination of the Computational Thinking Skills of Students

ERIC Educational Resources Information Center

Korucu, Agah Tugrul; Gencturk, Abdullah Tarik; Gundogdu, Mustafa Mucahit

2017-01-01

Computational thinking is generally considered as a kind of analytical way of thinking. According to Wings (2008) it shares with mathematical thinking, engineering thinking and scientific thinking in the general ways in which we may use for solving a problem, designing and evaluating complex systems or understanding computability and intelligence…

Integrating Computational Science Tools into a Thermodynamics Course

ERIC Educational Resources Information Center

Vieira, Camilo; Magana, Alejandra J.; García, R. Edwin; Jana, Aniruddha; Krafcik, Matthew

2018-01-01

Computational tools and methods have permeated multiple science and engineering disciplines, because they enable scientists and engineers to process large amounts of data, represent abstract phenomena, and to model and simulate complex concepts. In order to prepare future engineers with the ability to use computational tools in the context of…

Building Cognition: The Construction of Computational Representations for Scientific Discovery

ERIC Educational Resources Information Center

Chandrasekharan, Sanjay; Nersessian, Nancy J.

2015-01-01

Novel computational representations, such as simulation models of complex systems and video games for scientific discovery (Foldit, EteRNA etc.), are dramatically changing the way discoveries emerge in science and engineering. The cognitive roles played by such computational representations in discovery are not well understood. We present a…

Complex Systems Simulation and Optimization | Computational Science | NREL

Science.gov Websites

account. Stochastic Optimization and Control: Formulation and implementation of advanced optimization and account uncertainty. Contact Wesley Jones Group Manager, Complex Systems Simulation and Optimiziation

Processing power limits social group size: computational evidence for the cognitive costs of sociality

PubMed Central

Dávid-Barrett, T.; Dunbar, R. I. M.

2013-01-01

Sociality is primarily a coordination problem. However, the social (or communication) complexity hypothesis suggests that the kinds of information that can be acquired and processed may limit the size and/or complexity of social groups that a species can maintain. We use an agent-based model to test the hypothesis that the complexity of information processed influences the computational demands involved. We show that successive increases in the kinds of information processed allow organisms to break through the glass ceilings that otherwise limit the size of social groups: larger groups can only be achieved at the cost of more sophisticated kinds of information processing that are disadvantageous when optimal group size is small. These results simultaneously support both the social brain and the social complexity hypotheses. PMID:23804623

Computing Optimal Stochastic Portfolio Execution Strategies: A Parametric Approach Using Simulations

NASA Astrophysics Data System (ADS)

Moazeni, Somayeh; Coleman, Thomas F.; Li, Yuying

2010-09-01

Computing optimal stochastic portfolio execution strategies under appropriate risk consideration presents great computational challenge. We investigate a parametric approach for computing optimal stochastic strategies using Monte Carlo simulations. This approach allows reduction in computational complexity by computing coefficients for a parametric representation of a stochastic dynamic strategy based on static optimization. Using this technique, constraints can be similarly handled using appropriate penalty functions. We illustrate the proposed approach to minimize the expected execution cost and Conditional Value-at-Risk (CVaR).

Metabolic flexibility of mitochondrial respiratory chain disorders predicted by computer modelling.

PubMed

Zieliński, Łukasz P; Smith, Anthony C; Smith, Alexander G; Robinson, Alan J

2016-11-01

Mitochondrial respiratory chain dysfunction causes a variety of life-threatening diseases affecting about 1 in 4300 adults. These diseases are genetically heterogeneous, but have the same outcome; reduced activity of mitochondrial respiratory chain complexes causing decreased ATP production and potentially toxic accumulation of metabolites. Severity and tissue specificity of these effects varies between patients by unknown mechanisms and treatment options are limited. So far most research has focused on the complexes themselves, and the impact on overall cellular metabolism is largely unclear. To illustrate how computer modelling can be used to better understand the potential impact of these disorders and inspire new research directions and treatments, we simulated them using a computer model of human cardiomyocyte mitochondrial metabolism containing over 300 characterised reactions and transport steps with experimental parameters taken from the literature. Overall, simulations were consistent with patient symptoms, supporting their biological and medical significance. These simulations predicted: complex I deficiencies could be compensated using multiple pathways; complex II deficiencies had less metabolic flexibility due to impacting both the TCA cycle and the respiratory chain; and complex III and IV deficiencies caused greatest decreases in ATP production with metabolic consequences that parallel hypoxia. Our study demonstrates how results from computer models can be compared to a clinical phenotype and used as a tool for hypothesis generation for subsequent experimental testing. These simulations can enhance understanding of dysfunctional mitochondrial metabolism and suggest new avenues for research into treatment of mitochondrial disease and other areas of mitochondrial dysfunction. Copyright © 2016 The Authors. Published by Elsevier B.V. All rights reserved.

Statistical mechanics of complex neural systems and high dimensional data

NASA Astrophysics Data System (ADS)

Advani, Madhu; Lahiri, Subhaneil; Ganguli, Surya

2013-03-01

Recent experimental advances in neuroscience have opened new vistas into the immense complexity of neuronal networks. This proliferation of data challenges us on two parallel fronts. First, how can we form adequate theoretical frameworks for understanding how dynamical network processes cooperate across widely disparate spatiotemporal scales to solve important computational problems? Second, how can we extract meaningful models of neuronal systems from high dimensional datasets? To aid in these challenges, we give a pedagogical review of a collection of ideas and theoretical methods arising at the intersection of statistical physics, computer science and neurobiology. We introduce the interrelated replica and cavity methods, which originated in statistical physics as powerful ways to quantitatively analyze large highly heterogeneous systems of many interacting degrees of freedom. We also introduce the closely related notion of message passing in graphical models, which originated in computer science as a distributed algorithm capable of solving large inference and optimization problems involving many coupled variables. We then show how both the statistical physics and computer science perspectives can be applied in a wide diversity of contexts to problems arising in theoretical neuroscience and data analysis. Along the way we discuss spin glasses, learning theory, illusions of structure in noise, random matrices, dimensionality reduction and compressed sensing, all within the unified formalism of the replica method. Moreover, we review recent conceptual connections between message passing in graphical models, and neural computation and learning. Overall, these ideas illustrate how statistical physics and computer science might provide a lens through which we can uncover emergent computational functions buried deep within the dynamical complexities of neuronal networks.

JMS: An Open Source Workflow Management System and Web-Based Cluster Front-End for High Performance Computing.

PubMed

Brown, David K; Penkler, David L; Musyoka, Thommas M; Bishop, Özlem Tastan

2015-01-01

Complex computational pipelines are becoming a staple of modern scientific research. Often these pipelines are resource intensive and require days of computing time. In such cases, it makes sense to run them over high performance computing (HPC) clusters where they can take advantage of the aggregated resources of many powerful computers. In addition to this, researchers often want to integrate their workflows into their own web servers. In these cases, software is needed to manage the submission of jobs from the web interface to the cluster and then return the results once the job has finished executing. We have developed the Job Management System (JMS), a workflow management system and web interface for high performance computing (HPC). JMS provides users with a user-friendly web interface for creating complex workflows with multiple stages. It integrates this workflow functionality with the resource manager, a tool that is used to control and manage batch jobs on HPC clusters. As such, JMS combines workflow management functionality with cluster administration functionality. In addition, JMS provides developer tools including a code editor and the ability to version tools and scripts. JMS can be used by researchers from any field to build and run complex computational pipelines and provides functionality to include these pipelines in external interfaces. JMS is currently being used to house a number of bioinformatics pipelines at the Research Unit in Bioinformatics (RUBi) at Rhodes University. JMS is an open-source project and is freely available at https://github.com/RUBi-ZA/JMS.

JMS: An Open Source Workflow Management System and Web-Based Cluster Front-End for High Performance Computing

PubMed Central

Brown, David K.; Penkler, David L.; Musyoka, Thommas M.; Bishop, Özlem Tastan

2015-01-01

Complex computational pipelines are becoming a staple of modern scientific research. Often these pipelines are resource intensive and require days of computing time. In such cases, it makes sense to run them over high performance computing (HPC) clusters where they can take advantage of the aggregated resources of many powerful computers. In addition to this, researchers often want to integrate their workflows into their own web servers. In these cases, software is needed to manage the submission of jobs from the web interface to the cluster and then return the results once the job has finished executing. We have developed the Job Management System (JMS), a workflow management system and web interface for high performance computing (HPC). JMS provides users with a user-friendly web interface for creating complex workflows with multiple stages. It integrates this workflow functionality with the resource manager, a tool that is used to control and manage batch jobs on HPC clusters. As such, JMS combines workflow management functionality with cluster administration functionality. In addition, JMS provides developer tools including a code editor and the ability to version tools and scripts. JMS can be used by researchers from any field to build and run complex computational pipelines and provides functionality to include these pipelines in external interfaces. JMS is currently being used to house a number of bioinformatics pipelines at the Research Unit in Bioinformatics (RUBi) at Rhodes University. JMS is an open-source project and is freely available at https://github.com/RUBi-ZA/JMS. PMID:26280450

Algorithmic Complexity. Volume II.

DTIC Science & Technology

1982-06-01

digital computers, this improvement will go unnoticed if only a few complex products are to be taken, however it can become increasingly important as...computed in the reverse order. If the products are formed moving from the top of the tree downward, and then the divisions are performed going from the...the reverse order, going up the tree. (r- a mod m means that r is the remainder when a is divided by M.) The overall running time of the algorithm is

Energy conservation and analysis and evaluation. [specifically at Slidell Computer Complex

NASA Technical Reports Server (NTRS)

1976-01-01

The survey assembled and made recommendations directed at conserving utilities and reducing the use of energy at the Slidell Computer Complex. Specific items included were: (1) scheduling and controlling the use of gas and electricity, (2) building modifications to reduce energy, (3) replacement of old, inefficient equipment, (4) modifications to control systems, (5) evaluations of economizer cycles in HVAC systems, and (6) corrective settings for thermostats, ductstats, and other temperature and pressure control devices.

[The P300-based brain-computer interface: presentation of the complex "flash + movement" stimuli].

PubMed

Ganin, I P; Kaplan, A Ia

2014-01-01

The P300 based brain-computer interface requires the detection of P300 wave of brain event-related potentials. Most of its users learn the BCI control in several minutes and after the short classifier training they can type a text on the computer screen or assemble an image of separate fragments in simple BCI-based video games. Nevertheless, insufficient attractiveness for users and conservative stimuli organization in this BCI may restrict its integration into real information processes control. At the same time initial movement of object (motion-onset stimuli) may be an independent factor that induces P300 wave. In current work we checked the hypothesis that complex "flash + movement" stimuli together with drastic and compact stimuli organization on the computer screen may be much more attractive for user while operating in P300 BCI. In 20 subjects research we showed the effectiveness of our interface. Both accuracy and P300 amplitude were higher for flashing stimuli and complex "flash + movement" stimuli compared to motion-onset stimuli. N200 amplitude was maximal for flashing stimuli, while for "flash + movement" stimuli and motion-onset stimuli it was only a half of it. Similar BCI with complex stimuli may be embedded into compact control systems requiring high level of user attention under impact of negative external effects obstructing the BCI control.

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

Perumalla, Kalyan S.; Yoginath, Srikanth B.

Problems such as fault tolerance and scalable synchronization can be efficiently solved using reversibility of applications. Making applications reversible by relying on computation rather than on memory is ideal for large scale parallel computing, especially for the next generation of supercomputers in which memory is expensive in terms of latency, energy, and price. In this direction, a case study is presented here in reversing a computational core, namely, Basic Linear Algebra Subprograms, which is widely used in scientific applications. A new Reversible BLAS (RBLAS) library interface has been designed, and a prototype has been implemented with two modes: (1) amore » memory-mode in which reversibility is obtained by checkpointing to memory in forward and restoring from memory in reverse, and (2) a computational-mode in which nothing is saved in the forward, but restoration is done entirely via inverse computation in reverse. The article is focused on detailed performance benchmarking to evaluate the runtime dynamics and performance effects, comparing reversible computation with checkpointing on both traditional CPU platforms and recent GPU accelerator platforms. For BLAS Level-1 subprograms, data indicates over an order of magnitude better speed of reversible computation compared to checkpointing. For BLAS Level-2 and Level-3, a more complex tradeoff is observed between reversible computation and checkpointing, depending on computational and memory complexities of the subprograms.« less

Pseudoracemic amino acid complexes: blind predictions for flexible two-component crystals.

PubMed

Görbitz, Carl Henrik; Dalhus, Bjørn; Day, Graeme M

2010-08-14

Ab initio prediction of the crystal packing in complexes between two flexible molecules is a particularly challenging computational chemistry problem. In this work we present results of single crystal structure determinations as well as theoretical predictions for three 1 ratio 1 complexes between hydrophobic l- and d-amino acids (pseudoracemates), known from previous crystallographic work to form structures with one of two alternative hydrogen bonding arrangements. These are accurately reproduced in the theoretical predictions together with a series of patterns that have never been observed experimentally. In this bewildering forest of potential polymorphs, hydrogen bonding arrangements and molecular conformations, the theoretical predictions succeeded, for all three complexes, in finding the correct hydrogen bonding pattern. For two of the complexes, the calculations also reproduce the exact space group and side chain orientations in the best ranked predicted structure. This includes one complex for which the observed crystal packing clearly contradicted previous experience based on experimental data for a substantial number of related amino acid complexes. The results highlight the significant recent advances that have been made in computational methods for crystal structure prediction.

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

PubMed

Drawert, Brian; Engblom, Stefan; Hellander, Andreas

2012-06-22

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

Fluid/Structure Interaction Studies of Aircraft Using High Fidelity Equations on Parallel Computers

NASA Technical Reports Server (NTRS)

Guruswamy, Guru; VanDalsem, William (Technical Monitor)

1994-01-01

Abstract Aeroelasticity which involves strong coupling of fluids, structures and controls is an important element in designing an aircraft. Computational aeroelasticity using low fidelity methods such as the linear aerodynamic flow equations coupled with the modal structural equations are well advanced. Though these low fidelity approaches are computationally less intensive, they are not adequate for the analysis of modern aircraft such as High Speed Civil Transport (HSCT) and Advanced Subsonic Transport (AST) which can experience complex flow/structure interactions. HSCT can experience vortex induced aeroelastic oscillations whereas AST can experience transonic buffet associated structural oscillations. Both aircraft may experience a dip in the flutter speed at the transonic regime. For accurate aeroelastic computations at these complex fluid/structure interaction situations, high fidelity equations such as the Navier-Stokes for fluids and the finite-elements for structures are needed. Computations using these high fidelity equations require large computational resources both in memory and speed. Current conventional super computers have reached their limitations both in memory and speed. As a result, parallel computers have evolved to overcome the limitations of conventional computers. This paper will address the transition that is taking place in computational aeroelasticity from conventional computers to parallel computers. The paper will address special techniques needed to take advantage of the architecture of new parallel computers. Results will be illustrated from computations made on iPSC/860 and IBM SP2 computer by using ENSAERO code that directly couples the Euler/Navier-Stokes flow equations with high resolution finite-element structural equations.

Computing Mass Properties From AutoCAD

NASA Technical Reports Server (NTRS)

Jones, A.

1990-01-01

Mass properties of structures computed from data in drawings. AutoCAD to Mass Properties (ACTOMP) computer program developed to facilitate quick calculations of mass properties of structures containing many simple elements in such complex configurations as trusses or sheet-metal containers. Mathematically modeled in AutoCAD or compatible computer-aided design (CAD) system in minutes by use of three-dimensional elements. Written in Microsoft Quick-Basic (Version 2.0).

Hardware-based Artificial Neural Networks for Size, Weight, and Power Constrained Platforms (Preprint)

DTIC Science & Technology

2012-11-01

few sensors/complex computations, and many sensors/simple computation. II. CHALLENGES WITH NANO-ENABLED NEUROMORPHIC CHIPS A wide variety of...scenarios. Neuromorphic processors, which are based on the highly parallelized computing architecture of the mammalian brain, show great promise in...in the brain. This fundamentally different approach, frequently referred to as neuromorphic computing, is thought to be better able to solve fuzzy

DETAIL VIEW OF COMPUTER PANELS, ROOM 8A Cape Canaveral ...

Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

DETAIL VIEW OF COMPUTER PANELS, ROOM 8A - Cape Canaveral Air Force Station, Launch Complex 39, Mobile Launcher Platforms, Launcher Road, East of Kennedy Parkway North, Cape Canaveral, Brevard County, FL

Identifying Dynamic Protein Complexes Based on Gene Expression Profiles and PPI Networks

PubMed Central

Li, Min; Chen, Weijie; Wang, Jianxin; Pan, Yi

2014-01-01

Identification of protein complexes from protein-protein interaction networks has become a key problem for understanding cellular life in postgenomic era. Many computational methods have been proposed for identifying protein complexes. Up to now, the existing computational methods are mostly applied on static PPI networks. However, proteins and their interactions are dynamic in reality. Identifying dynamic protein complexes is more meaningful and challenging. In this paper, a novel algorithm, named DPC, is proposed to identify dynamic protein complexes by integrating PPI data and gene expression profiles. According to Core-Attachment assumption, these proteins which are always active in the molecular cycle are regarded as core proteins. The protein-complex cores are identified from these always active proteins by detecting dense subgraphs. Final protein complexes are extended from the protein-complex cores by adding attachments based on a topological character of “closeness” and dynamic meaning. The protein complexes produced by our algorithm DPC contain two parts: static core expressed in all the molecular cycle and dynamic attachments short-lived. The proposed algorithm DPC was applied on the data of Saccharomyces cerevisiae and the experimental results show that DPC outperforms CMC, MCL, SPICi, HC-PIN, COACH, and Core-Attachment based on the validation of matching with known complexes and hF-measures. PMID:24963481

A fast D.F.T. algorithm using complex integer transforms

NASA Technical Reports Server (NTRS)

Reed, I. S.; Truong, T. K.

1978-01-01

Winograd (1976) has developed a new class of algorithms which depend heavily on the computation of a cyclic convolution for computing the conventional DFT (discrete Fourier transform); this new algorithm, for a few hundred transform points, requires substantially fewer multiplications than the conventional FFT algorithm. Reed and Truong have defined a special class of finite Fourier-like transforms over GF(q squared), where q = 2 to the p power minus 1 is a Mersenne prime for p = 2, 3, 5, 7, 13, 17, 19, 31, 61. In the present paper it is shown that Winograd's algorithm can be combined with the aforementioned Fourier-like transform to yield a new algorithm for computing the DFT. A fast method for accurately computing the DFT of a sequence of complex numbers of very long transform-lengths is thus obtained.

Multithreaded Model for Dynamic Load Balancing Parallel Adaptive PDE Computations

NASA Technical Reports Server (NTRS)

Chrisochoides, Nikos

1995-01-01

We present a multithreaded model for the dynamic load-balancing of numerical, adaptive computations required for the solution of Partial Differential Equations (PDE's) on multiprocessors. Multithreading is used as a means of exploring concurrency in the processor level in order to tolerate synchronization costs inherent to traditional (non-threaded) parallel adaptive PDE solvers. Our preliminary analysis for parallel, adaptive PDE solvers indicates that multithreading can be used an a mechanism to mask overheads required for the dynamic balancing of processor workloads with computations required for the actual numerical solution of the PDE's. Also, multithreading can simplify the implementation of dynamic load-balancing algorithms, a task that is very difficult for traditional data parallel adaptive PDE computations. Unfortunately, multithreading does not always simplify program complexity, often makes code re-usability not an easy task, and increases software complexity.

Animated computer graphics models of space and earth sciences data generated via the massively parallel processor

NASA Technical Reports Server (NTRS)

Treinish, Lloyd A.; Gough, Michael L.; Wildenhain, W. David

1987-01-01

The capability was developed of rapidly producing visual representations of large, complex, multi-dimensional space and earth sciences data sets via the implementation of computer graphics modeling techniques on the Massively Parallel Processor (MPP) by employing techniques recently developed for typically non-scientific applications. Such capabilities can provide a new and valuable tool for the understanding of complex scientific data, and a new application of parallel computing via the MPP. A prototype system with such capabilities was developed and integrated into the National Space Science Data Center's (NSSDC) Pilot Climate Data System (PCDS) data-independent environment for computer graphics data display to provide easy access to users. While developing these capabilities, several problems had to be solved independently of the actual use of the MPP, all of which are outlined.

Computationally efficient algorithm for Gaussian Process regression in case of structured samples

NASA Astrophysics Data System (ADS)

Belyaev, M.; Burnaev, E.; Kapushev, Y.

2016-04-01

Surrogate modeling is widely used in many engineering problems. Data sets often have Cartesian product structure (for instance factorial design of experiments with missing points). In such case the size of the data set can be very large. Therefore, one of the most popular algorithms for approximation-Gaussian Process regression-can be hardly applied due to its computational complexity. In this paper a computationally efficient approach for constructing Gaussian Process regression in case of data sets with Cartesian product structure is presented. Efficiency is achieved by using a special structure of the data set and operations with tensors. Proposed algorithm has low computational as well as memory complexity compared to existing algorithms. In this work we also introduce a regularization procedure allowing to take into account anisotropy of the data set and avoid degeneracy of regression model.

Use of Multiple GPUs to Speedup the Execution of a Three-Dimensional Computational Model of the Innate Immune System

NASA Astrophysics Data System (ADS)

Xavier, M. P.; do Nascimento, T. M.; dos Santos, R. W.; Lobosco, M.

2014-03-01

The development of computational systems that mimics the physiological response of organs or even the entire body is a complex task. One of the issues that makes this task extremely complex is the huge computational resources needed to execute the simulations. For this reason, the use of parallel computing is mandatory. In this work, we focus on the simulation of temporal and spatial behaviour of some human innate immune system cells and molecules in a small three-dimensional section of a tissue. To perform this simulation, we use multiple Graphics Processing Units (GPUs) in a shared-memory environment. Despite of high initialization and communication costs imposed by the use of GPUs, the techniques used to implement the HIS simulator have shown to be very effective to achieve this purpose.

Computational physics of the mind

NASA Astrophysics Data System (ADS)

Duch, Włodzisław

1996-08-01

In the XIX century and earlier physicists such as Newton, Mayer, Hooke, Helmholtz and Mach were actively engaged in the research on psychophysics, trying to relate psychological sensations to intensities of physical stimuli. Computational physics allows to simulate complex neural processes giving a chance to answer not only the original psychophysical questions but also to create models of the mind. In this paper several approaches relevant to modeling of the mind are outlined. Since direct modeling of the brain functions is rather limited due to the complexity of such models a number of approximations is introduced. The path from the brain, or computational neurosciences, to the mind, or cognitive sciences, is sketched, with emphasis on higher cognitive functions such as memory and consciousness. No fundamental problems in understanding of the mind seem to arise. From a computational point of view realistic models require massively parallel architectures.

Approach to Computer Implementation of Mathematical Model of 3-Phase Induction Motor

NASA Astrophysics Data System (ADS)

Pustovetov, M. Yu

2018-03-01

This article discusses the development of the computer model of an induction motor based on the mathematical model in a three-phase stator reference frame. It uses an approach that allows combining during preparation of the computer model dual methods: means of visual programming circuitry (in the form of electrical schematics) and logical one (in the form of block diagrams). The approach enables easy integration of the model of an induction motor as part of more complex models of electrical complexes and systems. The developed computer model gives the user access to the beginning and the end of a winding of each of the three phases of the stator and rotor. This property is particularly important when considering the asymmetric modes of operation or when powered by the special circuitry of semiconductor converters.

Mathematical Description of Complex Chemical Kinetics and Application to CFD Modeling Codes

NASA Technical Reports Server (NTRS)

Bittker, D. A.

1993-01-01

A major effort in combustion research at the present time is devoted to the theoretical modeling of practical combustion systems. These include turbojet and ramjet air-breathing engines as well as ground-based gas-turbine power generating systems. The ability to use computational modeling extensively in designing these products not only saves time and money, but also helps designers meet the quite rigorous environmental standards that have been imposed on all combustion devices. The goal is to combine the very complex solution of the Navier-Stokes flow equations with realistic turbulence and heat-release models into a single computer code. Such a computational fluid-dynamic (CFD) code simulates the coupling of fluid mechanics with the chemistry of combustion to describe the practical devices. This paper will focus on the task of developing a simplified chemical model which can predict realistic heat-release rates as well as species composition profiles, and is also computationally rapid. We first discuss the mathematical techniques used to describe a complex, multistep fuel oxidation chemical reaction and develop a detailed mechanism for the process. We then show how this mechanism may be reduced and simplified to give an approximate model which adequately predicts heat release rates and a limited number of species composition profiles, but is computationally much faster than the original one. Only such a model can be incorporated into a CFD code without adding significantly to long computation times. Finally, we present some of the recent advances in the development of these simplified chemical mechanisms.

Mathematical description of complex chemical kinetics and application to CFD modeling codes

NASA Technical Reports Server (NTRS)

Bittker, D. A.

1993-01-01

A major effort in combustion research at the present time is devoted to the theoretical modeling of practical combustion systems. These include turbojet and ramjet air-breathing engines as well as ground-based gas-turbine power generating systems. The ability to use computational modeling extensively in designing these products not only saves time and money, but also helps designers meet the quite rigorous environmental standards that have been imposed on all combustion devices. The goal is to combine the very complex solution of the Navier-Stokes flow equations with realistic turbulence and heat-release models into a single computer code. Such a computational fluid-dynamic (CFD) code simulates the coupling of fluid mechanics with the chemistry of combustion to describe the practical devices. This paper will focus on the task of developing a simplified chemical model which can predict realistic heat-release rates as well as species composition profiles, and is also computationally rapid. We first discuss the mathematical techniques used to describe a complex, multistep fuel oxidation chemical reaction and develop a detailed mechanism for the process. We then show how this mechanism may be reduced and simplified to give an approximate model which adequately predicts heat release rates and a limited number of species composition profiles, but is computationally much faster than the original one. Only such a model can be incorporated into a CFD code without adding significantly to long computation times. Finally, we present some of the recent advances in the development of these simplified chemical mechanisms.

Predicting perceived visual complexity of abstract patterns using computational measures: The influence of mirror symmetry on complexity perception

PubMed Central

Leder, Helmut

2017-01-01

Visual complexity is relevant for many areas ranging from improving usability of technical displays or websites up to understanding aesthetic experiences. Therefore, many attempts have been made to relate objective properties of images to perceived complexity in artworks and other images. It has been argued that visual complexity is a multidimensional construct mainly consisting of two dimensions: A quantitative dimension that increases complexity through number of elements, and a structural dimension representing order negatively related to complexity. The objective of this work is to study human perception of visual complexity utilizing two large independent sets of abstract patterns. A wide range of computational measures of complexity was calculated, further combined using linear models as well as machine learning (random forests), and compared with data from human evaluations. Our results confirm the adequacy of existing two-factor models of perceived visual complexity consisting of a quantitative and a structural factor (in our case mirror symmetry) for both of our stimulus sets. In addition, a non-linear transformation of mirror symmetry giving more influence to small deviations from symmetry greatly increased explained variance. Thus, we again demonstrate the multidimensional nature of human complexity perception and present comprehensive quantitative models of the visual complexity of abstract patterns, which might be useful for future experiments and applications. PMID:29099832

Biocellion: accelerating computer simulation of multicellular biological system models.

PubMed

Kang, Seunghwa; Kahan, Simon; McDermott, Jason; Flann, Nicholas; Shmulevich, Ilya

2014-11-01

Biological system behaviors are often the outcome of complex interactions among a large number of cells and their biotic and abiotic environment. Computational biologists attempt to understand, predict and manipulate biological system behavior through mathematical modeling and computer simulation. Discrete agent-based modeling (in combination with high-resolution grids to model the extracellular environment) is a popular approach for building biological system models. However, the computational complexity of this approach forces computational biologists to resort to coarser resolution approaches to simulate large biological systems. High-performance parallel computers have the potential to address the computing challenge, but writing efficient software for parallel computers is difficult and time-consuming. We have developed Biocellion, a high-performance software framework, to solve this computing challenge using parallel computers. To support a wide range of multicellular biological system models, Biocellion asks users to provide their model specifics by filling the function body of pre-defined model routines. Using Biocellion, modelers without parallel computing expertise can efficiently exploit parallel computers with less effort than writing sequential programs from scratch. We simulate cell sorting, microbial patterning and a bacterial system in soil aggregate as case studies. Biocellion runs on x86 compatible systems with the 64 bit Linux operating system and is freely available for academic use. Visit http://biocellion.com for additional information. © The Author 2014. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Effect of Methyl Substitution on the N-H···O Interaction in Complexes of Pyrrole with Water, Methanol, and Dimethyl Ether: Matrix Isolation Infrared Spectroscopy and ab Initio Computational Studies.

PubMed

Sarkar, Shubhra; Ramanathan, N; Sundararajan, K

2018-03-08

Hydrogen-bonded interactions of pyrrole with water and methanol have been studied using matrix isolation infrared spectroscopy and compared with the calculation performed on dimethyl ether. Computations carried out at MP2/aug-cc-pVDZ level of theory yielded two minima for the pyrrole-water and pyrrole-methanol complexes. The global and local minima correspond to the N-H···O and O-H···π complexes, respectively, where the N-H group of pyrrole interacts with oxygen of water/methanol and O-H of water and methanol interacts with the π cloud of pyrrole. Computations performed on the pyrrole-dimethyl ether gave only N-H···O type complex. From the experimental vibrational wavenumber shifts in the N-H stretching and N-H bending modes of pyrrole, as well as in the O-H stretching modes of water and methanol, the 1:1 N-H···O complexes were discerned. The strength of the N-H···O hydrogen bond and the corresponding shift in the N-H stretching vibrational wavenumbers increases in the order pyrrole-water < pyrrole-methanol < pyrrole-dimethyl ether, where a proton is successively replaced by a methyl group. Apart from the 1:1 complexes, higher clusters of 2:1 and 1:2 pyrrole-water and pyrrole-methanol complexes were also generated in N 2 matrix. Atoms in molecules and natural bond orbital analyses were carried out at the MP2/aug-cc-pVDZ level to understand the nature of interaction in the 1:1 pyrrole-water, pyrrole-methanol and pyrrole-dimethyl ether complexes.

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

Operating a petabyte class archive at ESO

NASA Astrophysics Data System (ADS)

Suchar, Dieter; Lockhart, John S.; Burrows, Andrew

2008-07-01

The challenges of setting up and operating a Petabyte Class Archive will be described in terms of computer systems within a complex Data Centre environment. The computer systems, including the ESO Primary and Secondary Archive and the associated computational environments such as relational databases will be explained. This encompasses the entire system project cycle, including the technical specifications, procurement process, equipment installation and all further operational phases. The ESO Data Centre construction and the complexity of managing the environment will be presented. Many factors had to be considered during the construction phase, such as power consumption, targeted cooling and the accumulated load on the building structure to enable the smooth running of a Petabyte class Archive.

Dynamics and computation in functional shifts

NASA Astrophysics Data System (ADS)

Namikawa, Jun; Hashimoto, Takashi

2004-07-01

We introduce a new type of shift dynamics as an extended model of symbolic dynamics, and investigate the characteristics of shift spaces from the viewpoints of both dynamics and computation. This shift dynamics is called a functional shift, which is defined by a set of bi-infinite sequences of some functions on a set of symbols. To analyse the complexity of functional shifts, we measure them in terms of topological entropy, and locate their languages in the Chomsky hierarchy. Through this study, we argue that considering functional shifts from the viewpoints of both dynamics and computation gives us opposite results about the complexity of systems. We also describe a new class of shift spaces whose languages are not recursively enumerable.

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

An Advanced User Interface Approach for Complex Parameter Study Process Specification in the Information Power Grid

NASA Technical Reports Server (NTRS)

Yarrow, Maurice; McCann, Karen M.; Biswas, Rupak; VanderWijngaart, Rob; Yan, Jerry C. (Technical Monitor)

2000-01-01

The creation of parameter study suites has recently become a more challenging problem as the parameter studies have now become multi-tiered and the computational environment has become a supercomputer grid. The parameter spaces are vast, the individual problem sizes are getting larger, and researchers are now seeking to combine several successive stages of parameterization and computation. Simultaneously, grid-based computing offers great resource opportunity but at the expense of great difficulty of use. We present an approach to this problem which stresses intuitive visual design tools for parameter study creation and complex process specification, and also offers programming-free access to grid-based supercomputer resources and process automation.

12 CFR 502.27 - How does OTS determine the risk/complexity component for a savings and loan holding company?

Code of Federal Regulations, 2010 CFR

2010-01-01

... 12 Banks and Banking 5 2010-01-01 2010-01-01 false How does OTS determine the risk/complexity...-Calculation of Assessments § 502.27 How does OTS determine the risk/complexity component for a savings and loan holding company? (a) OTS computes the risk/complexity component for responsible savings and loan...

Teaching about Complex Systems Is No Simple Matter: Building Effective Professional Development for Computer-Supported Complex Systems Instruction

ERIC Educational Resources Information Center

Yoon, Susan A.; Anderson, Emma; Koehler-Yom, Jessica; Evans, Chad; Park, Miyoung; Sheldon, Josh; Schoenfeld, Ilana; Wendel, Daniel; Scheintaub, Hal; Klopfer, Eric

2017-01-01

The recent next generation science standards in the United States have emphasized learning about complex systems as a core feature of science learning. Over the past 15 years, a number of educational tools and theories have been investigated to help students learn about complex systems; but surprisingly, little research has been devoted to…

SNS programming environment user's guide

NASA Technical Reports Server (NTRS)

Tennille, Geoffrey M.; Howser, Lona M.; Humes, D. Creig; Cronin, Catherine K.; Bowen, John T.; Drozdowski, Joseph M.; Utley, Judith A.; Flynn, Theresa M.; Austin, Brenda A.

1992-01-01

The computing environment is briefly described for the Supercomputing Network Subsystem (SNS) of the Central Scientific Computing Complex of NASA Langley. The major SNS computers are a CRAY-2, a CRAY Y-MP, a CONVEX C-210, and a CONVEX C-220. The software is described that is common to all of these computers, including: the UNIX operating system, computer graphics, networking utilities, mass storage, and mathematical libraries. Also described is file management, validation, SNS configuration, documentation, and customer services.

Developing Computer Programming Concepts and Skills via Technology-Enriched Language-Art Projects: A Case Study

ERIC Educational Resources Information Center

Lee, Young-Jin

2010-01-01

Teaching computer programming to young children has been considered difficult because of its abstract and complex nature. The objectives of this study are (1) to investigate whether an innovative educational technology tool called Scratch could enable young children to learn abstract knowledge of computer programming while creating multimedia…

Collaborative Strategic Board Games as a Site for Distributed Computational Thinking

ERIC Educational Resources Information Center

Berland, Matthew; Lee, Victor R.

2011-01-01

This paper examines the idea that contemporary strategic board games represent an informal, interactional context in which complex computational thinking takes place. When games are collaborative--that is, a game requires that players work in joint pursuit of a shared goal--the computational thinking is easily observed as distributed across…

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…

Modelling the Influences of Beliefs on Pre-Service Teachers' Attitudes towards Computer Use

ERIC Educational Resources Information Center

Teo, Timothy

2012-01-01

The purpose of this study is to examine the pre-service teachers' attitudes toward computers use. The impact of five variables (perceived usefulness, perceived ease of use, subjective norm, facilitating conditions, and technological complexity) on attitude towards computer was assessed. Data were collected from 230 preservice teachers through…

Loci-STREAM Version 0.9

NASA Technical Reports Server (NTRS)

Wright, Jeffrey; Thakur, Siddharth

2006-01-01

Loci-STREAM is an evolving computational fluid dynamics (CFD) software tool for simulating possibly chemically reacting, possibly unsteady flows in diverse settings, including rocket engines, turbomachines, oil refineries, etc. Loci-STREAM implements a pressure- based flow-solving algorithm that utilizes unstructured grids. (The benefit of low memory usage by pressure-based algorithms is well recognized by experts in the field.) The algorithm is robust for flows at all speeds from zero to hypersonic. The flexibility of arbitrary polyhedral grids enables accurate, efficient simulation of flows in complex geometries, including those of plume-impingement problems. The present version - Loci-STREAM version 0.9 - includes an interface with the Portable, Extensible Toolkit for Scientific Computation (PETSc) library for access to enhanced linear-equation-solving programs therein that accelerate convergence toward a solution. The name "Loci" reflects the creation of this software within the Loci computational framework, which was developed at Mississippi State University for the primary purpose of simplifying the writing of complex multidisciplinary application programs to run in distributed-memory computing environments including clusters of personal computers. Loci has been designed to relieve application programmers of the details of programming for distributed-memory computers.

Sonic and Supersonic Jet Plumes

NASA Technical Reports Server (NTRS)

Venkatapathy, E.; Naughton, J. W.; Flethcher, D. G.; Edwards, Thomas A. (Technical Monitor)

1994-01-01

Study of sonic and supersonic jet plumes are relevant to understanding such phenomenon as jet-noise, plume signatures, and rocket base-heating and radiation. Jet plumes are simple to simulate and yet, have complex flow structures such as Mach disks, triple points, shear-layers, barrel shocks, shock- shear- layer interaction, etc. Experimental and computational simulation of sonic and supersonic jet plumes have been performed for under- and over-expanded, axisymmetric plume conditions. The computational simulation compare very well with the experimental observations of schlieren pictures. Experimental data such as temperature measurements with hot-wire probes are yet to be measured and will be compared with computed values. Extensive analysis of the computational simulations presents a clear picture of how the complex flow structure develops and the conditions under which self-similar flow structures evolve. From the computations, the plume structure can be further classified into many sub-groups. In the proposed paper, detail results from the experimental and computational simulations for single, axisymmetric, under- and over-expanded, sonic and supersonic plumes will be compared and the fluid dynamic aspects of flow structures will be discussed.

Using Commercial-off-the-Shelf Computer Games to Train and Educate Complexity and Complex Decision-Making

DTIC Science & Technology

2008-09-01

Jean Piaget is one of the pioneers of constructivist learning theory , Piaget states that knowledge is constructed and learning occurs through an...the mechanics of each game. For instance, if a training program is developed around the u.S. Army’s America ’ s Army computer games then little funds...gathering and maintaining the data needed. and C04󈧏pIeting and reviewing this collection of information. Send OOIT’II’lents regarding thi s burden

Computer-generated hologram calculation for real scenes using a commercial portable plenoptic camera

NASA Astrophysics Data System (ADS)

Endo, Yutaka; Wakunami, Koki; Shimobaba, Tomoyoshi; Kakue, Takashi; Arai, Daisuke; Ichihashi, Yasuyuki; Yamamoto, Kenji; Ito, Tomoyoshi

2015-12-01

This paper shows the process used to calculate a computer-generated hologram (CGH) for real scenes under natural light using a commercial portable plenoptic camera. In the CGH calculation, a light field captured with the commercial plenoptic camera is converted into a complex amplitude distribution. Then the converted complex amplitude is propagated to a CGH plane. We tested both numerical and optical reconstructions of the CGH and showed that the CGH calculation from captured data with the commercial plenoptic camera was successful.

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

Dress, W.B.

Rosen's modeling relation is embedded in Popper's three worlds to provide an heuristic tool for model building and a guide for thinking about complex systems. The utility of this construct is demonstrated by suggesting a solution to the problem of pseudo science and a resolution of the famous Bohr-Einstein debates. A theory of bizarre systems is presented by an analogy with entangled particles of quantum mechanics. This theory underscores the poverty of present-day computational systems (e.g., computers) for creating complex and bizarre entities by distinguishing between mechanism and organism.

Progress in Computational Electron-Molecule Collisions

NASA Astrophysics Data System (ADS)

Rescigno, Tn

1997-10-01

The past few years have witnessed tremendous progress in the development of sophisticated ab initio methods for treating collisions of slow electrons with isolated small molecules. Researchers in this area have benefited greatly from advances in computer technology; indeed, the advent of parallel computers has made it possible to carry out calculations at a level of sophistication inconceivable a decade ago. But bigger and faster computers are only part of the picture. Even with today's computers, the practical need to study electron collisions with the kinds of complex molecules and fragments encountered in real-world plasma processing environments is taxing present methods beyond their current capabilities. Since extrapolation of existing methods to handle increasingly larger targets will ultimately fail as it would require computational resources beyond any imagined, continued progress must also be linked to new theoretical developments. Some of the techniques recently introduced to address these problems will be discussed and illustrated with examples of electron-molecule collision calculations we have carried out on some fairly complex target gases encountered in processing plasmas. Electron-molecule scattering continues to pose many formidable theoretical and computational challenges. I will touch on some of the outstanding open questions.

Granular computing with multiple granular layers for brain big data processing.

PubMed

Wang, Guoyin; Xu, Ji

2014-12-01

Big data is the term for a collection of datasets so huge and complex that it becomes difficult to be processed using on-hand theoretical models and technique tools. Brain big data is one of the most typical, important big data collected using powerful equipments of functional magnetic resonance imaging, multichannel electroencephalography, magnetoencephalography, Positron emission tomography, near infrared spectroscopic imaging, as well as other various devices. Granular computing with multiple granular layers, referred to as multi-granular computing (MGrC) for short hereafter, is an emerging computing paradigm of information processing, which simulates the multi-granular intelligent thinking model of human brain. It concerns the processing of complex information entities called information granules, which arise in the process of data abstraction and derivation of information and even knowledge from data. This paper analyzes three basic mechanisms of MGrC, namely granularity optimization, granularity conversion, and multi-granularity joint computation, and discusses the potential of introducing MGrC into intelligent processing of brain big data.

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

NASA Astrophysics Data System (ADS)

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

2015-03-01

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

Real-Gas Flow Properties for NASA Langley Research Center Aerothermodynamic Facilities Complex Wind Tunnels

NASA Technical Reports Server (NTRS)

Hollis, Brian R.

1996-01-01

A computational algorithm has been developed which can be employed to determine the flow properties of an arbitrary real (virial) gas in a wind tunnel. A multiple-coefficient virial gas equation of state and the assumption of isentropic flow are used to model the gas and to compute flow properties throughout the wind tunnel. This algorithm has been used to calculate flow properties for the wind tunnels of the Aerothermodynamics Facilities Complex at the NASA Langley Research Center, in which air, CF4. He, and N2 are employed as test gases. The algorithm is detailed in this paper and sample results are presented for each of the Aerothermodynamic Facilities Complex wind tunnels.

The effects of syntactic complexity on the human-computer interaction

NASA Technical Reports Server (NTRS)

Chechile, R. A.; Fleischman, R. N.; Sadoski, D. M.

1986-01-01

Three divided-attention experiments were performed to evaluate the effectiveness of a syntactic analysis of the primary task of editing flight route-way-point information. For all editing conditions, a formal syntactic expression was developed for the operator's interaction with the computer. In terms of the syntactic expression, four measures of syntactic were examined. Increased syntactic complexity did increase the time to train operators, but once the operators were trained, syntactic complexity did not influence the divided-attention performance. However, the number of memory retrievals required of the operator significantly accounted for the variation in the accuracy, workload, and task completion time found on the different editing tasks under attention-sharing conditions.

A new method to real-normalize measured complex modes

NASA Technical Reports Server (NTRS)

Wei, Max L.; Allemang, Randall J.; Zhang, Qiang; Brown, David L.

1987-01-01

A time domain subspace iteration technique is presented to compute a set of normal modes from the measured complex modes. By using the proposed method, a large number of physical coordinates are reduced to a smaller number of model or principal coordinates. Subspace free decay time responses are computed using properly scaled complex modal vectors. Companion matrix for the general case of nonproportional damping is then derived in the selected vector subspace. Subspace normal modes are obtained through eigenvalue solution of the (M sub N) sup -1 (K sub N) matrix and transformed back to the physical coordinates to get a set of normal modes. A numerical example is presented to demonstrate the outlined theory.

Computational modeling of carbohydrate recognition in protein complex

NASA Astrophysics Data System (ADS)

Ishida, Toyokazu

2017-11-01

To understand the mechanistic principle of carbohydrate recognition in proteins, we propose a systematic computational modeling strategy to identify complex carbohydrate chain onto the reduced 2D free energy surface (2D-FES), determined by MD sampling combined with QM/MM energy corrections. In this article, we first report a detailed atomistic simulation study of the norovirus capsid proteins with carbohydrate antigens based on ab initio QM/MM combined with MD-FEP simulations. The present result clearly shows that the binding geometries of complex carbohydrate antigen are determined not by one single, rigid carbohydrate structure, but rather by the sum of averaged conformations mapped onto the minimum free energy region of QM/MM 2D-FES.

Production of graphic symbol sentences by individuals with aphasia: efficacy of a computer-based augmentative and alternative communication intervention.

PubMed

Koul, Rajinder; Corwin, Melinda; Hayes, Summer

2005-01-01

The study employed a single-subject multiple baseline design to examine the ability of 9 individuals with severe Broca's aphasia or global aphasia to produce graphic symbol sentences of varying syntactical complexity using a software program that turns a computer into a speech output communication device. The sentences ranged in complexity from simple two-word phrases to those with morphological inflections, transformations, and relative clauses. Overall, results indicated that individuals with aphasia are able to access, manipulate, and combine graphic symbols to produce phrases and sentences of varying degrees of syntactical complexity. The findings are discussed in terms of the clinical and public policy implications.

Here and now: the intersection of computational science, quantum-mechanical simulations, and materials science

NASA Astrophysics Data System (ADS)

Marzari, Nicola

The last 30 years have seen the steady and exhilarating development of powerful quantum-simulation engines for extended systems, dedicated to the solution of the Kohn-Sham equations of density-functional theory, often augmented by density-functional perturbation theory, many-body perturbation theory, time-dependent density-functional theory, dynamical mean-field theory, and quantum Monte Carlo. Their implementation on massively parallel architectures, now leveraging also GPUs and accelerators, has started a massive effort in the prediction from first principles of many or of complex materials properties, leading the way to the exascale through the combination of HPC (high-performance computing) and HTC (high-throughput computing). Challenges and opportunities abound: complementing hardware and software investments and design; developing the materials' informatics infrastructure needed to encode knowledge into complex protocols and workflows of calculations; managing and curating data; resisting the complacency that we have already reached the predictive accuracy needed for materials design, or a robust level of verification of the different quantum engines. In this talk I will provide an overview of these challenges, with the ultimate prize being the computational understanding, prediction, and design of properties and performance for novel or complex materials and devices.

A novel computational approach "BP-STOCH" to study ligand binding to finite lattice.

PubMed

Beshnova, Daria A; Bereznyak, Ekaterina G; Shestopalova, Anna V; Evstigneev, Maxim P

2011-03-01

We report a novel computational algorithm "BP-STOCH" to be used for studying single-type ligand binding with biopolymers of finite lengths, such as DNA oligonucleotides or oligopeptides. It is based on an idea to represent any type of ligand-biopolymer complex in a form of binary number, where "0" and "1" bits stand for vacant and engaged monomers of the biopolymer, respectively. Cycling over all binary numbers from the lowest 0 up to the highest 2(N) - 1 means a sequential generating of all possible configurations of vacant/engaged monomers, which, after proper filtering, results in a full set of possible types of complexes in solution between the ligand and the N-site lattice. The principal advantage of BP-STOCH algorithm is the possibility to incorporate into this cycle any conditions on computation of the concentrations and observed experimental parameters of the complexes in solution, and programmatic access to each monomer of the biopolymer within each binding site of every binding configuration. The latter is equivalent to unlimited extension of the basic reaction scheme and allows to use BP-STOCH algorithm as an alternative to conventional computational approaches.

Approximate l-fold cross-validation with Least Squares SVM and Kernel Ridge Regression

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

Edwards, Richard E; Zhang, Hao; Parker, Lynne Edwards

2013-01-01

Kernel methods have difficulties scaling to large modern data sets. The scalability issues are based on computational and memory requirements for working with a large matrix. These requirements have been addressed over the years by using low-rank kernel approximations or by improving the solvers scalability. However, Least Squares Support VectorMachines (LS-SVM), a popular SVM variant, and Kernel Ridge Regression still have several scalability issues. In particular, the O(n^3) computational complexity for solving a single model, and the overall computational complexity associated with tuning hyperparameters are still major problems. We address these problems by introducing an O(n log n) approximate l-foldmore » cross-validation method that uses a multi-level circulant matrix to approximate the kernel. In addition, we prove our algorithm s computational complexity and present empirical runtimes on data sets with approximately 1 million data points. We also validate our approximate method s effectiveness at selecting hyperparameters on real world and standard benchmark data sets. Lastly, we provide experimental results on using a multi-level circulant kernel approximation to solve LS-SVM problems with hyperparameters selected using our method.« less

@neurIST: infrastructure for advanced disease management through integration of heterogeneous data, computing, and complex processing services.

PubMed

Benkner, Siegfried; Arbona, Antonio; Berti, Guntram; Chiarini, Alessandro; Dunlop, Robert; Engelbrecht, Gerhard; Frangi, Alejandro F; Friedrich, Christoph M; Hanser, Susanne; Hasselmeyer, Peer; Hose, Rod D; Iavindrasana, Jimison; Köhler, Martin; Iacono, Luigi Lo; Lonsdale, Guy; Meyer, Rodolphe; Moore, Bob; Rajasekaran, Hariharan; Summers, Paul E; Wöhrer, Alexander; Wood, Steven

2010-11-01

The increasing volume of data describing human disease processes and the growing complexity of understanding, managing, and sharing such data presents a huge challenge for clinicians and medical researchers. This paper presents the @neurIST system, which provides an infrastructure for biomedical research while aiding clinical care, by bringing together heterogeneous data and complex processing and computing services. Although @neurIST targets the investigation and treatment of cerebral aneurysms, the system's architecture is generic enough that it could be adapted to the treatment of other diseases. Innovations in @neurIST include confining the patient data pertaining to aneurysms inside a single environment that offers clinicians the tools to analyze and interpret patient data and make use of knowledge-based guidance in planning their treatment. Medical researchers gain access to a critical mass of aneurysm related data due to the system's ability to federate distributed information sources. A semantically mediated grid infrastructure ensures that both clinicians and researchers are able to seamlessly access and work on data that is distributed across multiple sites in a secure way in addition to providing computing resources on demand for performing computationally intensive simulations for treatment planning and research.

Grammatical Analysis as a Distributed Neurobiological Function

PubMed Central

Bozic, Mirjana; Fonteneau, Elisabeth; Su, Li; Marslen-Wilson, William D

2015-01-01

Language processing engages large-scale functional networks in both hemispheres. Although it is widely accepted that left perisylvian regions have a key role in supporting complex grammatical computations, patient data suggest that some aspects of grammatical processing could be supported bilaterally. We investigated the distribution and the nature of grammatical computations across language processing networks by comparing two types of combinatorial grammatical sequences—inflectionally complex words and minimal phrases—and contrasting them with grammatically simple words. Novel multivariate analyses revealed that they engage a coalition of separable subsystems: inflected forms triggered left-lateralized activation, dissociable into dorsal processes supporting morphophonological parsing and ventral, lexically driven morphosyntactic processes. In contrast, simple phrases activated a consistently bilateral pattern of temporal regions, overlapping with inflectional activations in L middle temporal gyrus. These data confirm the role of the left-lateralized frontotemporal network in supporting complex grammatical computations. Critically, they also point to the capacity of bilateral temporal regions to support simple, linear grammatical computations. This is consistent with a dual neurobiological framework where phylogenetically older bihemispheric systems form part of the network that supports language function in the modern human, and where significant capacities for language comprehension remain intact even following severe left hemisphere damage. PMID:25421880

Fast algorithm for computing complex number-theoretic transforms

NASA Technical Reports Server (NTRS)

Reed, I. S.; Liu, K. Y.; Truong, T. K.

1977-01-01

A high-radix FFT algorithm for computing transforms over FFT, where q is a Mersenne prime, is developed to implement fast circular convolutions. This new algorithm requires substantially fewer multiplications than the conventional FFT.

Computing Systems | High-Performance Computing | NREL

Science.gov Websites

investigate, build, and test models of complex phenomena or entire integrated systems-that cannot be directly observed or manipulated in the lab, or would be too expensive or time consuming. Models and visualizations

Computational and Organotypic Modeling of Microcephaly (Teratology Society)

EPA Science Inventory

Microcephaly is associated with reduced cortical surface area and ventricular dilations. Many genetic and environmental factors precipitate this malformation, including prenatal alcohol exposure and maternal Zika infection. This complexity motivates the engineering of computation...

92. VIEW OF CHART RECORDERS AND PERSONAL COMPUTER LINING NORTHEAST ...

Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

92. VIEW OF CHART RECORDERS AND PERSONAL COMPUTER LINING NORTHEAST CORNER OF AUTOPILOT ROOM - Vandenberg Air Force Base, Space Launch Complex 3, Launch Operations Building, Napa & Alden Roads, Lompoc, Santa Barbara County, CA

Complex Osteotomies of Tibial Plateau Malunions Using Computer-Assisted Planning and Patient-Specific Surgical Guides.

PubMed

Fürnstahl, Philipp; Vlachopoulos, Lazaros; Schweizer, Andreas; Fucentese, Sandro F; Koch, Peter P

2015-08-01

The accurate reduction of tibial plateau malunions can be challenging without guidance. In this work, we report on a novel technique that combines 3-dimensional computer-assisted planning with patient-specific surgical guides for improving reliability and accuracy of complex intraarticular corrective osteotomies. Preoperative planning based on 3-dimensional bone models was performed to simulate fragment mobilization and reduction in 3 cases. Surgical implementation of the preoperative plan using patient-specific cutting and reduction guides was evaluated; benefits and limitations of the approach were identified and discussed. The preliminary results are encouraging and show that complex, intraarticular corrective osteotomies can be accurately performed with this technique. For selective patients with complex malunions around the tibia plateau, this method might be an attractive option, with the potential to facilitate achieving the most accurate correction possible.

General Quantum Meet-in-the-Middle Search Algorithm Based on Target Solution of Fixed Weight

NASA Astrophysics Data System (ADS)

Fu, Xiang-Qun; Bao, Wan-Su; Wang, Xiang; Shi, Jian-Hong

2016-10-01

Similar to the classical meet-in-the-middle algorithm, the storage and computation complexity are the key factors that decide the efficiency of the quantum meet-in-the-middle algorithm. Aiming at the target vector of fixed weight, based on the quantum meet-in-the-middle algorithm, the algorithm for searching all n-product vectors with the same weight is presented, whose complexity is better than the exhaustive search algorithm. And the algorithm can reduce the storage complexity of the quantum meet-in-the-middle search algorithm. Then based on the algorithm and the knapsack vector of the Chor-Rivest public-key crypto of fixed weight d, we present a general quantum meet-in-the-middle search algorithm based on the target solution of fixed weight, whose computational complexity is \\sumj = 0d {(O(\\sqrt {Cn - k + 1d - j }) + O(C_kj log C_k^j))} with Σd i =0 Ck i memory cost. And the optimal value of k is given. Compared to the quantum meet-in-the-middle search algorithm for knapsack problem and the quantum algorithm for searching a target solution of fixed weight, the computational complexity of the algorithm is lower. And its storage complexity is smaller than the quantum meet-in-the-middle-algorithm. Supported by the National Basic Research Program of China under Grant No. 2013CB338002 and the National Natural Science Foundation of China under Grant No. 61502526

Computer aided reliability, availability, and safety modeling for fault-tolerant computer systems with commentary on the HARP program

NASA Technical Reports Server (NTRS)

Shooman, Martin L.

1991-01-01

Many of the most challenging reliability problems of our present decade involve complex distributed systems such as interconnected telephone switching computers, air traffic control centers, aircraft and space vehicles, and local area and wide area computer networks. In addition to the challenge of complexity, modern fault-tolerant computer systems require very high levels of reliability, e.g., avionic computers with MTTF goals of one billion hours. Most analysts find that it is too difficult to model such complex systems without computer aided design programs. In response to this need, NASA has developed a suite of computer aided reliability modeling programs beginning with CARE 3 and including a group of new programs such as: HARP, HARP-PC, Reliability Analysts Workbench (Combination of model solvers SURE, STEM, PAWS, and common front-end model ASSIST), and the Fault Tree Compiler. The HARP program is studied and how well the user can model systems using this program is investigated. One of the important objectives will be to study how user friendly this program is, e.g., how easy it is to model the system, provide the input information, and interpret the results. The experiences of the author and his graduate students who used HARP in two graduate courses are described. Some brief comparisons were made with the ARIES program which the students also used. Theoretical studies of the modeling techniques used in HARP are also included. Of course no answer can be any more accurate than the fidelity of the model, thus an Appendix is included which discusses modeling accuracy. A broad viewpoint is taken and all problems which occurred in the use of HARP are discussed. Such problems include: computer system problems, installation manual problems, user manual problems, program inconsistencies, program limitations, confusing notation, long run times, accuracy problems, etc.

A conservation and biophysics guided stochastic approach to refining docked multimeric proteins.

PubMed

Akbal-Delibas, Bahar; Haspel, Nurit

2013-01-01

We introduce a protein docking refinement method that accepts complexes consisting of any number of monomeric units. The method uses a scoring function based on a tight coupling between evolutionary conservation, geometry and physico-chemical interactions. Understanding the role of protein complexes in the basic biology of organisms heavily relies on the detection of protein complexes and their structures. Different computational docking methods are developed for this purpose, however, these methods are often not accurate and their results need to be further refined to improve the geometry and the energy of the resulting complexes. Also, despite the fact that complexes in nature often have more than two monomers, most docking methods focus on dimers since the computational complexity increases exponentially due to the addition of monomeric units. Our results show that the refinement scheme can efficiently handle complexes with more than two monomers by biasing the results towards complexes with native interactions, filtering out false positive results. Our refined complexes have better IRMSDs with respect to the known complexes and lower energies than those initial docked structures. Evolutionary conservation information allows us to bias our results towards possible functional interfaces, and the probabilistic selection scheme helps us to escape local energy minima. We aim to incorporate our refinement method in a larger framework which also enables docking of multimeric complexes given only monomeric structures.

Temperature and heat flux datasets of a complex object in a fire plume for the validation of fire and thermal response codes.

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

Jernigan, Dann A.; Blanchat, Thomas K.

It is necessary to improve understanding and develop temporally- and spatially-resolved integral scale validation data of the heat flux incident to a complex object in addition to measuring the thermal response of said object located within the fire plume for the validation of the SIERRA/FUEGO/SYRINX fire and SIERRA/CALORE codes. To meet this objective, a complex calorimeter with sufficient instrumentation to allow validation of the coupling between FUEGO/SYRINX/CALORE has been designed, fabricated, and tested in the Fire Laboratory for Accreditation of Models and Experiments (FLAME) facility. Validation experiments are specifically designed for direct comparison with the computational predictions. Making meaningful comparisonmore » between the computational and experimental results requires careful characterization and control of the experimental features or parameters used as inputs into the computational model. Validation experiments must be designed to capture the essential physical phenomena, including all relevant initial and boundary conditions. This report presents the data validation steps and processes, the results of the penlight radiant heat experiments (for the purpose of validating the CALORE heat transfer modeling of the complex calorimeter), and the results of the fire tests in FLAME.« less

Photofragmentation of Gas-Phase Lanthanide Cyclopentadienyl Complexes: Experimental and Time-Dependent Excited-State Molecular Dynamics

PubMed Central

2015-01-01

Unimolecular gas-phase laser-photodissociation reaction mechanisms of open-shell lanthanide cyclopentadienyl complexes, Ln(Cp)3 and Ln(TMCp)3, are analyzed from experimental and computational perspectives. The most probable pathways for the photoreactions are inferred from photoionization time-of-flight mass spectrometry (PI-TOF-MS), which provides the sequence of reaction intermediates and the distribution of final products. Time-dependent excited-state molecular dynamics (TDESMD) calculations provide insight into the electronic mechanisms for the individual steps of the laser-driven photoreactions for Ln(Cp)3. Computational analysis correctly predicts several key reaction products as well as the observed branching between two reaction pathways: (1) ligand ejection and (2) ligand cracking. Simulations support our previous assertion that both reaction pathways are initiated via a ligand-to-metal charge-transfer (LMCT) process. For the more complex chemistry of the tetramethylcyclopentadienyl complexes Ln(TMCp)3, TMESMD is less tractable, but computational geometry optimization reveals the structures of intermediates deduced from PI-TOF-MS, including several classic “tuck-in” structures and products of Cp ring expansion. The results have important implications for metal–organic catalysis and laser-assisted metal–organic chemical vapor deposition (LCVD) of insulators with high dielectric constants. PMID:24910492

Training Knowledge Bots for Physics-Based Simulations Using Artificial Neural Networks

NASA Technical Reports Server (NTRS)

Samareh, Jamshid A.; Wong, Jay Ming

2014-01-01

Millions of complex physics-based simulations are required for design of an aerospace vehicle. These simulations are usually performed by highly trained and skilled analysts, who execute, monitor, and steer each simulation. Analysts rely heavily on their broad experience that may have taken 20-30 years to accumulate. In addition, the simulation software is complex in nature, requiring significant computational resources. Simulations of system of systems become even more complex and are beyond human capacity to effectively learn their behavior. IBM has developed machines that can learn and compete successfully with a chess grandmaster and most successful jeopardy contestants. These machines are capable of learning some complex problems much faster than humans can learn. In this paper, we propose using artificial neural network to train knowledge bots to identify the idiosyncrasies of simulation software and recognize patterns that can lead to successful simulations. We examine the use of knowledge bots for applications of computational fluid dynamics (CFD), trajectory analysis, commercial finite-element analysis software, and slosh propellant dynamics. We will show that machine learning algorithms can be used to learn the idiosyncrasies of computational simulations and identify regions of instability without including any additional information about their mathematical form or applied discretization approaches.

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.

Sensitivity analysis of dynamic biological systems with time-delays.

PubMed

Wu, Wu Hsiung; Wang, Feng Sheng; Chang, Maw Shang

2010-10-15

Mathematical modeling has been applied to the study and analysis of complex biological systems for a long time. Some processes in biological systems, such as the gene expression and feedback control in signal transduction networks, involve a time delay. These systems are represented as delay differential equation (DDE) models. Numerical sensitivity analysis of a DDE model by the direct method requires the solutions of model and sensitivity equations with time-delays. The major effort is the computation of Jacobian matrix when computing the solution of sensitivity equations. The computation of partial derivatives of complex equations either by the analytic method or by symbolic manipulation is time consuming, inconvenient, and prone to introduce human errors. To address this problem, an automatic approach to obtain the derivatives of complex functions efficiently and accurately is necessary. We have proposed an efficient algorithm with an adaptive step size control to compute the solution and dynamic sensitivities of biological systems described by ordinal differential equations (ODEs). The adaptive direct-decoupled algorithm is extended to solve the solution and dynamic sensitivities of time-delay systems describing by DDEs. To save the human effort and avoid the human errors in the computation of partial derivatives, an automatic differentiation technique is embedded in the extended algorithm to evaluate the Jacobian matrix. The extended algorithm is implemented and applied to two realistic models with time-delays: the cardiovascular control system and the TNF-α signal transduction network. The results show that the extended algorithm is a good tool for dynamic sensitivity analysis on DDE models with less user intervention. By comparing with direct-coupled methods in theory, the extended algorithm is efficient, accurate, and easy to use for end users without programming background to do dynamic sensitivity analysis on complex biological systems with time-delays.

Synthetic biology: insights into biological computation.

PubMed

Manzoni, Romilde; Urrios, Arturo; Velazquez-Garcia, Silvia; de Nadal, Eulàlia; Posas, Francesc

2016-04-18

Organisms have evolved a broad array of complex signaling mechanisms that allow them to survive in a wide range of environmental conditions. They are able to sense external inputs and produce an output response by computing the information. Synthetic biology attempts to rationally engineer biological systems in order to perform desired functions. Our increasing understanding of biological systems guides this rational design, while the huge background in electronics for building circuits defines the methodology. In this context, biocomputation is the branch of synthetic biology aimed at implementing artificial computational devices using engineered biological motifs as building blocks. Biocomputational devices are defined as biological systems that are able to integrate inputs and return outputs following pre-determined rules. Over the last decade the number of available synthetic engineered devices has increased exponentially; simple and complex circuits have been built in bacteria, yeast and mammalian cells. These devices can manage and store information, take decisions based on past and present inputs, and even convert a transient signal into a sustained response. The field is experiencing a fast growth and every day it is easier to implement more complex biological functions. This is mainly due to advances in in vitro DNA synthesis, new genome editing tools, novel molecular cloning techniques, continuously growing part libraries as well as other technological advances. This allows that digital computation can now be engineered and implemented in biological systems. Simple logic gates can be implemented and connected to perform novel desired functions or to better understand and redesign biological processes. Synthetic biological digital circuits could lead to new therapeutic approaches, as well as new and efficient ways to produce complex molecules such as antibiotics, bioplastics or biofuels. Biological computation not only provides possible biomedical and biotechnological applications, but also affords a greater understanding of biological systems.

Ventral-stream-like shape representation: from pixel intensity values to trainable object-selective COSFIRE models

PubMed Central

Azzopardi, George; Petkov, Nicolai

2014-01-01

The remarkable abilities of the primate visual system have inspired the construction of computational models of some visual neurons. We propose a trainable hierarchical object recognition model, which we call S-COSFIRE (S stands for Shape and COSFIRE stands for Combination Of Shifted FIlter REsponses) and use it to localize and recognize objects of interests embedded in complex scenes. It is inspired by the visual processing in the ventral stream (V1/V2 → V4 → TEO). Recognition and localization of objects embedded in complex scenes is important for many computer vision applications. Most existing methods require prior segmentation of the objects from the background which on its turn requires recognition. An S-COSFIRE filter is automatically configured to be selective for an arrangement of contour-based features that belong to a prototype shape specified by an example. The configuration comprises selecting relevant vertex detectors and determining certain blur and shift parameters. The response is computed as the weighted geometric mean of the blurred and shifted responses of the selected vertex detectors. S-COSFIRE filters share similar properties with some neurons in inferotemporal cortex, which provided inspiration for this work. We demonstrate the effectiveness of S-COSFIRE filters in two applications: letter and keyword spotting in handwritten manuscripts and object spotting in complex scenes for the computer vision system of a domestic robot. S-COSFIRE filters are effective to recognize and localize (deformable) objects in images of complex scenes without requiring prior segmentation. They are versatile trainable shape detectors, conceptually simple and easy to implement. The presented hierarchical shape representation contributes to a better understanding of the brain and to more robust computer vision algorithms. PMID:25126068

Management of health care expenditure by soft computing methodology

NASA Astrophysics Data System (ADS)

Maksimović, Goran; Jović, Srđan; Jovanović, Radomir; Aničić, Obrad

2017-01-01

In this study was managed the health care expenditure by soft computing methodology. The main goal was to predict the gross domestic product (GDP) according to several factors of health care expenditure. Soft computing methodologies were applied since GDP prediction is very complex task. The performances of the proposed predictors were confirmed with the simulation results. According to the results, support vector regression (SVR) has better prediction accuracy compared to other soft computing methodologies. The soft computing methods benefit from the soft computing capabilities of global optimization in order to avoid local minimum issues.

Role of optical computers in aeronautical control applications

NASA Technical Reports Server (NTRS)

Baumbick, R. J.

1981-01-01

The role that optical computers play in aircraft control is determined. The optical computer has the potential high speed capability required, especially for matrix/matrix operations. The optical computer also has the potential for handling nonlinear simulations in real time. They are also more compatible with fiber optic signal transmission. Optics also permit the use of passive sensors to measure process variables. No electrical energy need be supplied to the sensor. Complex interfacing between optical sensors and the optical computer is avoided if the optical sensor outputs can be directly processed by the optical computer.

Moving alcohol prevention research forward-Part I: introducing a complex systems paradigm.

PubMed

Apostolopoulos, Yorghos; Lemke, Michael K; Barry, Adam E; Lich, Kristen Hassmiller

2018-02-01

The drinking environment is a complex system consisting of a number of heterogeneous, evolving and interacting components, which exhibit circular causality and emergent properties. These characteristics reduce the efficacy of commonly used research approaches, which typically do not account for the underlying dynamic complexity of alcohol consumption and the interdependent nature of diverse factors influencing misuse over time. We use alcohol misuse among college students in the United States as an example for framing our argument for a complex systems paradigm. A complex systems paradigm, grounded in socio-ecological and complex systems theories and computational modeling and simulation, is introduced. Theoretical, conceptual, methodological and analytical underpinnings of this paradigm are described in the context of college drinking prevention research. The proposed complex systems paradigm can transcend limitations of traditional approaches, thereby fostering new directions in alcohol prevention research. By conceptualizing student alcohol misuse as a complex adaptive system, computational modeling and simulation methodologies and analytical techniques can be used. Moreover, use of participatory model-building approaches to generate simulation models can further increase stakeholder buy-in, understanding and policymaking. A complex systems paradigm for research into alcohol misuse can provide a holistic understanding of the underlying drinking environment and its long-term trajectory, which can elucidate high-leverage preventive interventions. © 2017 Society for the Study of Addiction.

Neural network-based brain tissue segmentation in MR images using extracted features from intraframe coding in H.264

NASA Astrophysics Data System (ADS)

Jafari, Mehdi; Kasaei, Shohreh

2012-01-01

Automatic brain tissue segmentation is a crucial task in diagnosis and treatment of medical images. This paper presents a new algorithm to segment different brain tissues, such as white matter (WM), gray matter (GM), cerebral spinal fluid (CSF), background (BKG), and tumor tissues. The proposed technique uses the modified intraframe coding yielded from H.264/(AVC), for feature extraction. Extracted features are then imposed to an artificial back propagation neural network (BPN) classifier to assign each block to its appropriate class. Since the newest coding standard, H.264/AVC, has the highest compression ratio, it decreases the dimension of extracted features and thus yields to a more accurate classifier with low computational complexity. The performance of the BPN classifier is evaluated using the classification accuracy and computational complexity terms. The results show that the proposed technique is more robust and effective with low computational complexity compared to other recent works.

Neural network-based brain tissue segmentation in MR images using extracted features from intraframe coding in H.264

NASA Astrophysics Data System (ADS)

Jafari, Mehdi; Kasaei, Shohreh

2011-12-01

Automatic brain tissue segmentation is a crucial task in diagnosis and treatment of medical images. This paper presents a new algorithm to segment different brain tissues, such as white matter (WM), gray matter (GM), cerebral spinal fluid (CSF), background (BKG), and tumor tissues. The proposed technique uses the modified intraframe coding yielded from H.264/(AVC), for feature extraction. Extracted features are then imposed to an artificial back propagation neural network (BPN) classifier to assign each block to its appropriate class. Since the newest coding standard, H.264/AVC, has the highest compression ratio, it decreases the dimension of extracted features and thus yields to a more accurate classifier with low computational complexity. The performance of the BPN classifier is evaluated using the classification accuracy and computational complexity terms. The results show that the proposed technique is more robust and effective with low computational complexity compared to other recent works.

Applications of Phase-Based Motion Processing

NASA Technical Reports Server (NTRS)

Branch, Nicholas A.; Stewart, Eric C.

2018-01-01

Image pyramids provide useful information in determining structural response at low cost using commercially available cameras. The current effort applies previous work on the complex steerable pyramid to analyze and identify imperceptible linear motions in video. Instead of implicitly computing motion spectra through phase analysis of the complex steerable pyramid and magnifying the associated motions, instead present a visual technique and the necessary software to display the phase changes of high frequency signals within video. The present technique quickly identifies regions of largest motion within a video with a single phase visualization and without the artifacts of motion magnification, but requires use of the computationally intensive Fourier transform. While Riesz pyramids present an alternative to the computationally intensive complex steerable pyramid for motion magnification, the Riesz formulation contains significant noise, and motion magnification still presents large amounts of data that cannot be quickly assessed by the human eye. Thus, user-friendly software is presented for quickly identifying structural response through optical flow and phase visualization in both Python and MATLAB.

Fast and Epsilon-Optimal Discretized Pursuit Learning Automata.

PubMed

Zhang, JunQi; Wang, Cheng; Zhou, MengChu

2015-10-01

Learning automata (LA) are powerful tools for reinforcement learning. A discretized pursuit LA is the most popular one among them. During an iteration its operation consists of three basic phases: 1) selecting the next action; 2) finding the optimal estimated action; and 3) updating the state probability. However, when the number of actions is large, the learning becomes extremely slow because there are too many updates to be made at each iteration. The increased updates are mostly from phases 1 and 3. A new fast discretized pursuit LA with assured ε -optimality is proposed to perform both phases 1 and 3 with the computational complexity independent of the number of actions. Apart from its low computational complexity, it achieves faster convergence speed than the classical one when operating in stationary environments. This paper can promote the applications of LA toward the large-scale-action oriented area that requires efficient reinforcement learning tools with assured ε -optimality, fast convergence speed, and low computational complexity for each iteration.

Fast and Accurate Circuit Design Automation through Hierarchical Model Switching.

PubMed

Huynh, Linh; Tagkopoulos, Ilias

2015-08-21

In computer-aided biological design, the trifecta of characterized part libraries, accurate models and optimal design parameters is crucial for producing reliable designs. As the number of parts and model complexity increase, however, it becomes exponentially more difficult for any optimization method to search the solution space, hence creating a trade-off that hampers efficient design. To address this issue, we present a hierarchical computer-aided design architecture that uses a two-step approach for biological design. First, a simple model of low computational complexity is used to predict circuit behavior and assess candidate circuit branches through branch-and-bound methods. Then, a complex, nonlinear circuit model is used for a fine-grained search of the reduced solution space, thus achieving more accurate results. Evaluation with a benchmark of 11 circuits and a library of 102 experimental designs with known characterization parameters demonstrates a speed-up of 3 orders of magnitude when compared to other design methods that provide optimality guarantees.

Computing Tutte polynomials of contact networks in classrooms

NASA Astrophysics Data System (ADS)

Hincapié, Doracelly; Ospina, Juan

2013-05-01

Objective: The topological complexity of contact networks in classrooms and the potential transmission of an infectious disease were analyzed by sex and age. Methods: The Tutte polynomials, some topological properties and the number of spanning trees were used to algebraically compute the topological complexity. Computations were made with the Maple package GraphTheory. Published data of mutually reported social contacts within a classroom taken from primary school, consisting of children in the age ranges of 4-5, 7-8 and 10-11, were used. Results: The algebraic complexity of the Tutte polynomial and the probability of disease transmission increases with age. The contact networks are not bipartite graphs, gender segregation was observed especially in younger children. Conclusion: Tutte polynomials are tools to understand the topology of the contact networks and to derive numerical indexes of such topologies. It is possible to establish relationships between the Tutte polynomial of a given contact network and the potential transmission of an infectious disease within such network

Computer models of complex multiloop branched pipeline systems

NASA Astrophysics Data System (ADS)

Kudinov, I. V.; Kolesnikov, S. V.; Eremin, A. V.; Branfileva, A. N.

2013-11-01

This paper describes the principal theoretical concepts of the method used for constructing computer models of complex multiloop branched pipeline networks, and this method is based on the theory of graphs and two Kirchhoff's laws applied to electrical circuits. The models make it possible to calculate velocities, flow rates, and pressures of a fluid medium in any section of pipeline networks, when the latter are considered as single hydraulic systems. On the basis of multivariant calculations the reasons for existing problems can be identified, the least costly methods of their elimination can be proposed, and recommendations for planning the modernization of pipeline systems and construction of their new sections can be made. The results obtained can be applied to complex pipeline systems intended for various purposes (water pipelines, petroleum pipelines, etc.). The operability of the model has been verified on an example of designing a unified computer model of the heat network for centralized heat supply of the city of Samara.

"Let's get physical": advantages of a physical model over 3D computer models and textbooks in learning imaging anatomy.

PubMed

Preece, Daniel; Williams, Sarah B; Lam, Richard; Weller, Renate

2013-01-01

Three-dimensional (3D) information plays an important part in medical and veterinary education. Appreciating complex 3D spatial relationships requires a strong foundational understanding of anatomy and mental 3D visualization skills. Novel learning resources have been introduced to anatomy training to achieve this. Objective evaluation of their comparative efficacies remains scarce in the literature. This study developed and evaluated the use of a physical model in demonstrating the complex spatial relationships of the equine foot. It was hypothesized that the newly developed physical model would be more effective for students to learn magnetic resonance imaging (MRI) anatomy of the foot than textbooks or computer-based 3D models. Third year veterinary medicine students were randomly assigned to one of three teaching aid groups (physical model; textbooks; 3D computer model). The comparative efficacies of the three teaching aids were assessed through students' abilities to identify anatomical structures on MR images. Overall mean MRI assessment scores were significantly higher in students utilizing the physical model (86.39%) compared with students using textbooks (62.61%) and the 3D computer model (63.68%) (P < 0.001), with no significant difference between the textbook and 3D computer model groups (P = 0.685). Student feedback was also more positive in the physical model group compared with both the textbook and 3D computer model groups. Our results suggest that physical models may hold a significant advantage over alternative learning resources in enhancing visuospatial and 3D understanding of complex anatomical architecture, and that 3D computer models have significant limitations with regards to 3D learning. © 2013 American Association of Anatomists.

WE-D-303-01: Development and Application of Digital Human Phantoms

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

Segars, P.

2015-06-15

Modern medical physics deals with complex problems such as 4D radiation therapy and imaging quality optimization. Such problems involve a large number of radiological parameters, and anatomical and physiological breathing patterns. A major challenge is how to develop, test, evaluate and compare various new imaging and treatment techniques, which often involves testing over a large range of radiological parameters as well as varying patient anatomies and motions. It would be extremely challenging, if not impossible, both ethically and practically, to test every combination of parameters and every task on every type of patient under clinical conditions. Computer-based simulation using computationalmore » phantoms offers a practical technique with which to evaluate, optimize, and compare imaging technologies and methods. Within simulation, the computerized phantom provides a virtual model of the patient’s anatomy and physiology. Imaging data can be generated from it as if it was a live patient using accurate models of the physics of the imaging and treatment process. With sophisticated simulation algorithms, it is possible to perform virtual experiments entirely on the computer. By serving as virtual patients, computational phantoms hold great promise in solving some of the most complex problems in modern medical physics. In this proposed symposium, we will present the history and recent developments of computational phantom models, share experiences in their application to advanced imaging and radiation applications, and discuss their promises and limitations. Learning Objectives: Understand the need and requirements of computational phantoms in medical physics research Discuss the developments and applications of computational phantoms Know the promises and limitations of computational phantoms in solving complex problems.« less

Mind the Noise When Identifying Computational Models of Cognition from Brain Activity.

PubMed

Kolossa, Antonio; Kopp, Bruno

2016-01-01

The aim of this study was to analyze how measurement error affects the validity of modeling studies in computational neuroscience. A synthetic validity test was created using simulated P300 event-related potentials as an example. The model space comprised four computational models of single-trial P300 amplitude fluctuations which differed in terms of complexity and dependency. The single-trial fluctuation of simulated P300 amplitudes was computed on the basis of one of the models, at various levels of measurement error and at various numbers of data points. Bayesian model selection was performed based on exceedance probabilities. At very low numbers of data points, the least complex model generally outperformed the data-generating model. Invalid model identification also occurred at low levels of data quality and under low numbers of data points if the winning model's predictors were closely correlated with the predictors from the data-generating model. Given sufficient data quality and numbers of data points, the data-generating model could be correctly identified, even against models which were very similar to the data-generating model. Thus, a number of variables affects the validity of computational modeling studies, and data quality and numbers of data points are among the main factors relevant to the issue. Further, the nature of the model space (i.e., model complexity, model dependency) should not be neglected. This study provided quantitative results which show the importance of ensuring the validity of computational modeling via adequately prepared studies. The accomplishment of synthetic validity tests is recommended for future applications. Beyond that, we propose to render the demonstration of sufficient validity via adequate simulations mandatory to computational modeling studies.

Performance evaluation of GPU parallelization, space-time adaptive algorithms, and their combination for simulating cardiac electrophysiology.

PubMed

Sachetto Oliveira, Rafael; Martins Rocha, Bernardo; Burgarelli, Denise; Meira, Wagner; Constantinides, Christakis; Weber Dos Santos, Rodrigo

2018-02-01

The use of computer models as a tool for the study and understanding of the complex phenomena of cardiac electrophysiology has attained increased importance nowadays. At the same time, the increased complexity of the biophysical processes translates into complex computational and mathematical models. To speed up cardiac simulations and to allow more precise and realistic uses, 2 different techniques have been traditionally exploited: parallel computing and sophisticated numerical methods. In this work, we combine a modern parallel computing technique based on multicore and graphics processing units (GPUs) and a sophisticated numerical method based on a new space-time adaptive algorithm. We evaluate each technique alone and in different combinations: multicore and GPU, multicore and GPU and space adaptivity, multicore and GPU and space adaptivity and time adaptivity. All the techniques and combinations were evaluated under different scenarios: 3D simulations on slabs, 3D simulations on a ventricular mouse mesh, ie, complex geometry, sinus-rhythm, and arrhythmic conditions. Our results suggest that multicore and GPU accelerate the simulations by an approximate factor of 33×, whereas the speedups attained by the space-time adaptive algorithms were approximately 48. Nevertheless, by combining all the techniques, we obtained speedups that ranged between 165 and 498. The tested methods were able to reduce the execution time of a simulation by more than 498× for a complex cellular model in a slab geometry and by 165× in a realistic heart geometry simulating spiral waves. The proposed methods will allow faster and more realistic simulations in a feasible time with no significant loss of accuracy. Copyright © 2017 John Wiley & Sons, Ltd.

Role of HPC in Advancing Computational Aeroelasticity

NASA Technical Reports Server (NTRS)

Guruswamy, Guru P.

2004-01-01

On behalf of the High Performance Computing and Modernization Program (HPCMP) and NASA Advanced Supercomputing Division (NAS) a study is conducted to assess the role of supercomputers on computational aeroelasticity of aerospace vehicles. The study is mostly based on the responses to a web based questionnaire that was designed to capture the nuances of high performance computational aeroelasticity, particularly on parallel computers. A procedure is presented to assign a fidelity-complexity index to each application. Case studies based on major applications using HPCMP resources are presented.

Parallel Computing:. Some Activities in High Energy Physics

NASA Astrophysics Data System (ADS)

Willers, Ian

This paper examines some activities in High Energy Physics that utilise parallel computing. The topic includes all computing from the proposed SIMD front end detectors, the farming applications, high-powered RISC processors and the large machines in the computer centers. We start by looking at the motivation behind using parallelism for general purpose computing. The developments around farming are then described from its simplest form to the more complex system in Fermilab. Finally, there is a list of some developments that are happening close to the experiments.

Computation of Symmetric Discrete Cosine Transform Using Bakhvalov's Algorithm

NASA Technical Reports Server (NTRS)

Aburdene, Maurice F.; Strojny, Brian C.; Dorband, John E.

2005-01-01

A number of algorithms for recursive computation of the discrete cosine transform (DCT) have been developed recently. This paper presents a new method for computing the discrete cosine transform and its inverse using Bakhvalov's algorithm, a method developed for evaluation of a polynomial at a point. In this paper, we will focus on both the application of the algorithm to the computation of the DCT-I and its complexity. In addition, Bakhvalov s algorithm is compared with Clenshaw s algorithm for the computation of the DCT.

Computer-Aided Reliability Estimation

NASA Technical Reports Server (NTRS)

Bavuso, S. J.; Stiffler, J. J.; Bryant, L. A.; Petersen, P. L.

1986-01-01

CARE III (Computer-Aided Reliability Estimation, Third Generation) helps estimate reliability of complex, redundant, fault-tolerant systems. Program specifically designed for evaluation of fault-tolerant avionics systems. However, CARE III general enough for use in evaluation of other systems as well.

Cloud Computing Techniques for Space Mission Design

NASA Technical Reports Server (NTRS)

Arrieta, Juan; Senent, Juan

2014-01-01

The overarching objective of space mission design is to tackle complex problems producing better results, and faster. In developing the methods and tools to fulfill this objective, the user interacts with the different layers of a computing system.

Research in Parallel Algorithms and Software for Computational Aerosciences

DOT National Transportation Integrated Search

1996-04-01

Phase I is complete for the development of a Computational Fluid Dynamics : with automatic grid generation and adaptation for the Euler : analysis of flow over complex geometries. SPLITFLOW, an unstructured Cartesian : grid code developed at Lockheed...

Reproducible research in vadose zone sciences

USDA-ARS?s Scientific Manuscript database

A significant portion of present-day soil and Earth science research is computational, involving complex data analysis pipelines, advanced mathematical and statistical models, and sophisticated computer codes. Opportunities for scientific progress are greatly diminished if reproducing and building o...

A novel single neuron perceptron with universal approximation and XOR computation properties.

PubMed

Lotfi, Ehsan; Akbarzadeh-T, M-R

2014-01-01

We propose a biologically motivated brain-inspired single neuron perceptron (SNP) with universal approximation and XOR computation properties. This computational model extends the input pattern and is based on the excitatory and inhibitory learning rules inspired from neural connections in the human brain's nervous system. The resulting architecture of SNP can be trained by supervised excitatory and inhibitory online learning rules. The main features of proposed single layer perceptron are universal approximation property and low computational complexity. The method is tested on 6 UCI (University of California, Irvine) pattern recognition and classification datasets. Various comparisons with multilayer perceptron (MLP) with gradient decent backpropagation (GDBP) learning algorithm indicate the superiority of the approach in terms of higher accuracy, lower time, and spatial complexity, as well as faster training. Hence, we believe the proposed approach can be generally applicable to various problems such as in pattern recognition and classification.

Modeling And Simulation Of Bar Code Scanners Using Computer Aided Design Software

NASA Astrophysics Data System (ADS)

Hellekson, Ron; Campbell, Scott

1988-06-01

Many optical systems have demanding requirements to package the system in a small 3 dimensional space. The use of computer graphic tools can be a tremendous aid to the designer in analyzing the optical problems created by smaller and less costly systems. The Spectra Physics grocery store bar code scanner employs an especially complex 3 dimensional scan pattern to read bar code labels. By using a specially written program which interfaces with a computer aided design system, we have simulated many of the functions of this complex optical system. In this paper we will illustrate how a recent version of the scanner has been designed. We will discuss the use of computer graphics in the design process including interactive tweaking of the scan pattern, analysis of collected light, analysis of the scan pattern density, and analysis of the manufacturing tolerances used to build the scanner.

STARS: An integrated general-purpose finite element structural, aeroelastic, and aeroservoelastic analysis computer program

NASA Technical Reports Server (NTRS)

Gupta, Kajal K.

1991-01-01

The details of an integrated general-purpose finite element structural analysis computer program which is also capable of solving complex multidisciplinary problems is presented. Thus, the SOLIDS module of the program possesses an extensive finite element library suitable for modeling most practical problems and is capable of solving statics, vibration, buckling, and dynamic response problems of complex structures, including spinning ones. The aerodynamic module, AERO, enables computation of unsteady aerodynamic forces for both subsonic and supersonic flow for subsequent flutter and divergence analysis of the structure. The associated aeroservoelastic analysis module, ASE, effects aero-structural-control stability analysis yielding frequency responses as well as damping characteristics of the structure. The program is written in standard FORTRAN to run on a wide variety of computers. Extensive graphics, preprocessing, and postprocessing routines are also available pertaining to a number of terminals.

A computer program to trace seismic ray distribution in complex two-dimensional geological models

USGS Publications Warehouse

Yacoub, Nazieh K.; Scott, James H.

1970-01-01

A computer program has been developed to trace seismic rays and their amplitudes and energies through complex two-dimensional geological models, for which boundaries between elastic units are defined by a series of digitized X-, Y-coordinate values. Input data for the program includes problem identification, control parameters, model coordinates and elastic parameter for the elastic units. The program evaluates the partitioning of ray amplitude and energy at elastic boundaries, computes the total travel time, total travel distance and other parameters for rays arising at the earth's surface. Instructions are given for punching program control cards and data cards, and for arranging input card decks. An example of printer output for a simple problem is presented. The program is written in FORTRAN IV language. The listing of the program is shown in the Appendix, with an example output from a CDC-6600 computer.

The computational challenges of Earth-system science.

PubMed

O'Neill, Alan; Steenman-Clark, Lois

2002-06-15

The Earth system--comprising atmosphere, ocean, land, cryosphere and biosphere--is an immensely complex system, involving processes and interactions on a wide range of space- and time-scales. To understand and predict the evolution of the Earth system is one of the greatest challenges of modern science, with success likely to bring enormous societal benefits. High-performance computing, along with the wealth of new observational data, is revolutionizing our ability to simulate the Earth system with computer models that link the different components of the system together. There are, however, considerable scientific and technical challenges to be overcome. This paper will consider four of them: complexity, spatial resolution, inherent uncertainty and time-scales. Meeting these challenges requires a significant increase in the power of high-performance computers. The benefits of being able to make reliable predictions about the evolution of the Earth system should, on their own, amply repay this investment.

Efficient quantum walk on a quantum processor

PubMed Central

Qiang, Xiaogang; Loke, Thomas; Montanaro, Ashley; Aungskunsiri, Kanin; Zhou, Xiaoqi; O'Brien, Jeremy L.; Wang, Jingbo B.; Matthews, Jonathan C. F.

2016-01-01

The random walk formalism is used across a wide range of applications, from modelling share prices to predicting population genetics. Likewise, quantum walks have shown much potential as a framework for developing new quantum algorithms. Here we present explicit efficient quantum circuits for implementing continuous-time quantum walks on the circulant class of graphs. These circuits allow us to sample from the output probability distributions of quantum walks on circulant graphs efficiently. We also show that solving the same sampling problem for arbitrary circulant quantum circuits is intractable for a classical computer, assuming conjectures from computational complexity theory. This is a new link between continuous-time quantum walks and computational complexity theory and it indicates a family of tasks that could ultimately demonstrate quantum supremacy over classical computers. As a proof of principle, we experimentally implement the proposed quantum circuit on an example circulant graph using a two-qubit photonics quantum processor. PMID:27146471

CFD for hypersonic propulsion

NASA Technical Reports Server (NTRS)

Povinelli, Louis A.

1991-01-01

An overview is given of research activity on the application of computational fluid dynamics (CDF) for hypersonic propulsion systems. After the initial consideration of the highly integrated nature of air-breathing hypersonic engines and airframe, attention is directed toward computations carried out for the components of the engine. A generic inlet configuration is considered in order to demonstrate the highly three dimensional viscous flow behavior occurring within rectangular inlets. Reacting flow computations for simple jet injection as well as for more complex combustion chambers are then discussed in order to show the capability of viscous finite rate chemical reaction computer simulations. Finally, the nozzle flow fields are demonstrated, showing the existence of complex shear layers and shock structure in the exhaust plume. The general issues associated with code validation as well as the specific issue associated with the use of CFD for design are discussed. A prognosis for the success of CFD in the design of future propulsion systems is offered.

CFD for hypersonic propulsion

NASA Technical Reports Server (NTRS)

Povinelli, Louis A.

1990-01-01

An overview is given of research activity on the application of computational fluid dynamics (CDF) for hypersonic propulsion systems. After the initial consideration of the highly integrated nature of air-breathing hypersonic engines and airframe, attention is directed toward computations carried out for the components of the engine. A generic inlet configuration is considered in order to demonstrate the highly three dimensional viscous flow behavior occurring within rectangular inlets. Reacting flow computations for simple jet injection as well as for more complex combustion chambers are then discussed in order to show the capability of viscous finite rate chemical reaction computer simulations. Finally, the nozzle flow fields are demonstrated, showing the existence of complex shear layers and shock structure in the exhaust plume. The general issues associated with code validation as well as the specific issue associated with the use of CFD for design are discussed. A prognosis for the success of CFD in the design of future propulsion systems is offered.

Conference on Complex Turbulent Flows: Comparison of Computation and Experiment, Stanford University, Stanford, CA, September 14-18, 1981, Proceedings. Volume 2 - Taxonomies, reporters' summaries, evaluation, and conclusions

NASA Technical Reports Server (NTRS)

Kline, S. J. (Editor); Cantwell, B. J. (Editor); Lilley, G. M.

1982-01-01

Computational techniques for simulating turbulent flows were explored, together with the results of experimental investigations. Particular attention was devoted to the possibility of defining a universal closure model, applicable for all turbulence situations; however, conclusions were drawn that zonal models, describing localized structures, were the most promising techniques to date. The taxonomy of turbulent flows was summarized, as were algebraic, differential, integral, and partial differential methods for numerical depiction of turbulent flows. Numerous comparisons of theoretically predicted and experimentally obtained data for wall pressure distributions, velocity profiles, turbulent kinetic energy profiles, Reynolds shear stress profiles, and flows around transonic airfoils were presented. Simplifying techniques for reducing the necessary computational time for modeling complex flowfields were surveyed, together with the industrial requirements and applications of computational fluid dynamics techniques.