Proceedings from the U.S. Army Corps of Engineers (USACE) and the National Oceanic and Atmospheric Administration (NOAA) Engineering With Nature Workshop

DTIC Science & Technology

2017-03-01

opportunities emerged. It will be essential to capture and share lessons learned as the two organizations plan and implement selected EWN projects...their top five or six opportunities and subsequently selected the two highest priorities. Each of the three breakout groups then worked together to...will ensure agency buy-in, establish local reference sites, and promote EWN principles. Site selection will include an iterative process that factors

Design and Development of a User Interface for the Dynamic Model of Software Project Management.

DTIC Science & Technology

1988-03-01

rectory of the user’s choice for future...the last choice selected. Let us assume for the sake of this tour that the user has selected all eight choices . ESTIMATED ACTUAL PROJECT SIZE DEFINITION...manipulation of varaibles in the * •. TJin~ca model "h ... ser Inter ace for the Dynamica model was designed b in iterative process of prototyping

Systematic development of technical textiles

NASA Astrophysics Data System (ADS)

Beer, M.; Schrank, V.; Gloy, Y.-S.; Gries, T.

2016-07-01

Technical textiles are used in various fields of applications, ranging from small scale (e.g. medical applications) to large scale products (e.g. aerospace applications). The development of new products is often complex and time consuming, due to multiple interacting parameters. These interacting parameters are production process related and also a result of the textile structure and used material. A huge number of iteration steps are necessary to adjust the process parameter to finalize the new fabric structure. A design method is developed to support the systematic development of technical textiles and to reduce iteration steps. The design method is subdivided into six steps, starting from the identification of the requirements. The fabric characteristics vary depending on the field of application. If possible, benchmarks are tested. A suitable fabric production technology needs to be selected. The aim of the method is to support a development team within the technology selection without restricting the textile developer. After a suitable technology is selected, the transformation and correlation between input and output parameters follows. This generates the information for the production of the structure. Afterwards, the first prototype can be produced and tested. The resulting characteristics are compared with the initial product requirements.

Comparison of two feature selection methods for the separability analysis of intertidal sediments with spectrometric datasets in the German Wadden Sea

NASA Astrophysics Data System (ADS)

Jung, Richard; Ehlers, Manfred

2016-10-01

The spectral features of intertidal sediments are all influenced by the same biophysical properties, such as water, salinity, grain size or vegetation and therefore they are hard to separate by using only multispectral sensors. This could be shown by a previous study of Jung et al. (2015). A more detailed analysis of their characteristic spectral feature has to be carried out to understand the differences and similarities. Spectrometry data (i.e., hyperspectral sensors), for instance, have the opportunity to measure the reflection of the landscape as a continuous spectral pattern for each pixel of an image built from dozen to hundreds of narrow spectral bands. This reveals a high potential to measure unique spectral responses of different ecological conditions (Hennig et al., 2007). In this context, this study uses spectrometric datasets to distinguish between 14 different sediment classes obtained from a study area in the German Wadden Sea. A new feature selection method is proposed (Jeffries-Matusita distance bases feature selection; JMDFS), which uses the Euclidean distance to eliminate the wavelengths with the most similar reflectance values in an iterative process. Subsequent to each iteration, the separation capability is estimated by the Jeffries-Matusita distance (JMD). Two classes can be separated if the JMD is greater than 1.9 and if less than four wavelengths remain, no separation can be assumed. The results of the JMDFS are compared with a state-of-the-art feature selection method called ReliefF. Both methods showed the ability to improve the separation by achieving overall accuracies greater than 82%. The accuracies are 4%-13% better than the results with all wavelengths applied. The number of remaining wavelengths is very diverse and ranges from 14 to 213 of 703. The advantage of JMDFS compared with ReliefF is clearly the processing time. ReliefF needs 30 min for one temporary result. It is necessary to repeat the process several times and to average all temporary results to achieve a final result. In this study 50 iterations were carried out, which makes four days of processing. In contrast, JMDFS needs only 30 min for a final result.

Conceptual design of data acquisition and control system for two Rf driver based negative ion source for fusion R&D

NASA Astrophysics Data System (ADS)

Soni, Jigensh; Yadav, R. K.; Patel, A.; Gahlaut, A.; Mistry, H.; Parmar, K. G.; Mahesh, V.; Parmar, D.; Prajapati, B.; Singh, M. J.; Bandyopadhyay, M.; Bansal, G.; Pandya, K.; Chakraborty, A.

2013-02-01

Twin Source - An Inductively coupled two RF driver based 180 kW, 1 MHz negative ion source experimental setup is initiated at IPR, Gandhinagar, under Indian program, with the objective of understanding the physics and technology of multi-driver coupling. Twin Source [1] (TS) also provides an intermediate platform between operational ROBIN [2] [5] and eight RF drivers based Indian test facility -INTF [3]. A twin source experiment requires a central system to provide control, data acquisition and communication interface, referred as TS-CODAC, for which a software architecture similar to ITER CODAC core system has been decided for implementation. The Core System is a software suite for ITER plant system manufacturers to use as a template for the development of their interface with CODAC. The ITER approach, in terms of technology, has been adopted for the TS-CODAC so as to develop necessary expertise for developing and operating a control system based on the ITER guidelines as similar configuration needs to be implemented for the INTF. This cost effective approach will provide an opportunity to evaluate and learn ITER CODAC technology, documentation, information technology and control system processes, on an operational machine. Conceptual design of the TS-CODAC system has been completed. For complete control of the system, approximately 200 Nos. control signals and 152 acquisition signals are needed. In TS-CODAC, control loop time required is within the range of 5ms - 10 ms, therefore for the control system, PLC (Siemens S-7 400) has been chosen as suggested in the ITER slow controller catalog. For the data acquisition, the maximum sampling interval required is 100 micro second, and therefore National Instruments (NI) PXIe system and NI 6259 digitizer cards have been selected as suggested in the ITER fast controller catalog. This paper will present conceptual design of TS -CODAC system based on ITER CODAC Core software and applicable plant system integration processes.

Manufacture and mechanical characterisation of high voltage insulation for superconducting busbars - (Part 1) Materials selection and development

NASA Astrophysics Data System (ADS)

Clayton, N.; Crouchen, M.; Devred, A.; Evans, D.; Gung, C.-Y.; Lathwell, I.

2017-04-01

It is planned that the high voltage electrical insulation on the ITER feeder busbars will consist of interleaved layers of epoxy resin pre-impregnated glass tapes ('pre-preg') and polyimide. In addition to its electrical insulation function, the busbar insulation must have adequate mechanical properties to sustain the loads imposed on it during ITER magnet operation. This paper reports an investigation into suitable materials to manufacture the high voltage insulation for the ITER superconducting busbars and pipework. An R&D programme was undertaken in order to identify suitable pre-preg and polyimide materials from a range of suppliers. Pre-preg materials were obtained from 3 suppliers and used with Kapton HN, to make mouldings using the desired insulation architecture. Two main processing routes for pre-pregs have been investigated, namely vacuum bag processing (out of autoclave processing) and processing using a material with a high coefficient of thermal expansion (silicone rubber), to apply the compaction pressure on the insulation. Insulation should have adequate mechanical properties to cope with the stresses induced by the operating environment and a low void content necessary in a high voltage application. The quality of the mouldings was assessed by mechanical testing at 77 K and by the measurement of the void content.

Iterative Refinement of a Binding Pocket Model: Active Computational Steering of Lead Optimization

PubMed Central

2012-01-01

Computational approaches for binding affinity prediction are most frequently demonstrated through cross-validation within a series of molecules or through performance shown on a blinded test set. Here, we show how such a system performs in an iterative, temporal lead optimization exercise. A series of gyrase inhibitors with known synthetic order formed the set of molecules that could be selected for “synthesis.” Beginning with a small number of molecules, based only on structures and activities, a model was constructed. Compound selection was done computationally, each time making five selections based on confident predictions of high activity and five selections based on a quantitative measure of three-dimensional structural novelty. Compound selection was followed by model refinement using the new data. Iterative computational candidate selection produced rapid improvements in selected compound activity, and incorporation of explicitly novel compounds uncovered much more diverse active inhibitors than strategies lacking active novelty selection. PMID:23046104

Natural selection of memory-one strategies for the iterated prisoner's dilemma.

PubMed

Kraines, D P; Kraines, V Y

2000-04-21

In the iterated Prisoner's Dilemma, mutually cooperative behavior can become established through Darwinian natural selection. In simulated interactions of stochastic memory-one strategies for the Iterated Prisoner's Dilemma, Nowak and Sigmund discovered that cooperative agents using a Pavlov (Win-Stay Lose-Switch) type strategy eventually dominate a random population. This emergence follows more directly from a deterministic dynamical system based on differential reproductive success or natural selection. When restricted to an environment of memory-one agents interacting in iterated Prisoner's Dilemma games with a 1% noise level, the Pavlov agent is the only cooperative strategy and one of very few others that cannot be invaded by a similar strategy. Pavlov agents are trusting but no suckers. They will exploit weakness but repent if punished for cheating. Copyright 2000 Academic Press.

Optical-Correlator Neural Network Based On Neocognitron

NASA Technical Reports Server (NTRS)

Chao, Tien-Hsin; Stoner, William W.

1994-01-01

Multichannel optical correlator implements shift-invariant, high-discrimination pattern-recognizing neural network based on paradigm of neocognitron. Selected as basic building block of this neural network because invariance under shifts is inherent advantage of Fourier optics included in optical correlators in general. Neocognitron is conceptual electronic neural-network model for recognition of visual patterns. Multilayer processing achieved by iteratively feeding back output of feature correlator to input spatial light modulator and updating Fourier filters. Neural network trained by use of characteristic features extracted from target images. Multichannel implementation enables parallel processing of large number of selected features.

Selecting an Architecture for a Safety-Critical Distributed Computer System with Power, Weight and Cost Considerations

NASA Technical Reports Server (NTRS)

Torres-Pomales, Wilfredo

2014-01-01

This report presents an example of the application of multi-criteria decision analysis to the selection of an architecture for a safety-critical distributed computer system. The design problem includes constraints on minimum system availability and integrity, and the decision is based on the optimal balance of power, weight and cost. The analysis process includes the generation of alternative architectures, evaluation of individual decision criteria, and the selection of an alternative based on overall value. In this example presented here, iterative application of the quantitative evaluation process made it possible to deliberately generate an alternative architecture that is superior to all others regardless of the relative importance of cost.

Experimental Evaluation of Suitability of Selected Multi-Criteria Decision-Making Methods for Large-Scale Agent-Based Simulations

PubMed Central

2016-01-01

Multi-criteria decision-making (MCDM) can be formally implemented by various methods. This study compares suitability of four selected MCDM methods, namely WPM, TOPSIS, VIKOR, and PROMETHEE, for future applications in agent-based computational economic (ACE) models of larger scale (i.e., over 10 000 agents in one geographical region). These four MCDM methods were selected according to their appropriateness for computational processing in ACE applications. Tests of the selected methods were conducted on four hardware configurations. For each method, 100 tests were performed, which represented one testing iteration. With four testing iterations conducted on each hardware setting and separated testing of all configurations with the–server parameter de/activated, altogether, 12800 data points were collected and consequently analyzed. An illustrational decision-making scenario was used which allows the mutual comparison of all of the selected decision making methods. Our test results suggest that although all methods are convenient and can be used in practice, the VIKOR method accomplished the tests with the best results and thus can be recommended as the most suitable for simulations of large-scale agent-based models. PMID:27806061

A Control Algorithm for Chaotic Physical Systems

DTIC Science & Technology

1991-10-01

revision expands the grid to cover the entire area of any attractor that is present. 5 Map Selection The final choices of the state- space mapping process...interval h?; overrange R0 ; control parameter interval AkO and range [kbro, khigh]; iteration depth. "* State- space mapping : 1. Set up grid by expanding

Comparisons of Observed Process Quality in German and American Infant/Toddler Programs

ERIC Educational Resources Information Center

Tietze, Wolfgang; Cryer, Debby

2004-01-01

Observed process quality in infant/toddler classrooms was compared in Germany (n = 75) and the USA (n = 219). Process quality was assessed with the Infant/Toddler Environment Rating Scale(ITERS) and parent attitudes about ITERS content with the ITERS Parent Questionnaire (ITERSPQ). The ITERS had comparable reliabilities in the two countries and…

Progress on performance assessment of ITER enhanced heat flux first wall technology after neutron irradiation

NASA Astrophysics Data System (ADS)

Hirai, T.; Bao, L.; Barabash, V.; Chappuis, Ph; Eaton, R.; Escourbiac, F.; Giqcuel, S.; Merola, M.; Mitteau, R.; Raffray, R.; Linke, J.; Loewenhoff, Th; Pintsuk, G.; Wirtz, M.; Boomstra, D.; Magielsen, A.; Chen, J.; Wang, P.; Gervash, A.; Safronov, V.

2016-02-01

ITER first wall (FW) panels are irradiated by energetic neutrons during the nuclear phase. Thus, an irradiation and high heat flux testing programme is undertaken by the ITER organization in order to evaluate the effects of neutron irradiation on the performance of enhanced heat flux (EHF) FW components. The test campaign includes neutron irradiation (up to 0.6-0.8 dpa at 200 °C-250 °C) of mock-ups that are representative of the final EHF FW panel design, followed by thermal fatigue tests (up to 4.7 MW m-2). Mock-ups were manufactured by the same manufacturing process as proposed for the series production. After a pre-irradiation thermal screening, eight mock-ups will be selected for the irradiation campaigns. This paper reports the preparatory work of HHF tests and neutron irradiation, assessment results as well as a brief description of mock-up manufacturing and inspection routes.

Iterative non-sequential protein structural alignment.

PubMed

Salem, Saeed; Zaki, Mohammed J; Bystroff, Christopher

2009-06-01

Structural similarity between proteins gives us insights into their evolutionary relationships when there is low sequence similarity. In this paper, we present a novel approach called SNAP for non-sequential pair-wise structural alignment. Starting from an initial alignment, our approach iterates over a two-step process consisting of a superposition step and an alignment step, until convergence. We propose a novel greedy algorithm to construct both sequential and non-sequential alignments. The quality of SNAP alignments were assessed by comparing against the manually curated reference alignments in the challenging SISY and RIPC datasets. Moreover, when applied to a dataset of 4410 protein pairs selected from the CATH database, SNAP produced longer alignments with lower rmsd than several state-of-the-art alignment methods. Classification of folds using SNAP alignments was both highly sensitive and highly selective. The SNAP software along with the datasets are available online at http://www.cs.rpi.edu/~zaki/software/SNAP.

Social Participation of Adolescents with Cerebral Palsy: Trade-Offs and Choices

ERIC Educational Resources Information Center

Stewart, Debra A.; Lawless, John J.; Shimmell, Lorie J.; Palisano, Robert J.; Freeman, Matthew; Rosenbaum, Peter L.; Russell, Dianne J.

2012-01-01

This article reports on the findings of a qualitative study about the experiences and perceptions of adolescents with cerebral palsy (CP) in relation to social participation. A phenomenological approach was used to interview 10 adolescents with CP, 17 to 20 years of age, selected using purposeful sampling. An iterative process of data collection…

Data Integration Tool: Permafrost Data Debugging

NASA Astrophysics Data System (ADS)

Wilcox, H.; Schaefer, K. M.; Jafarov, E. E.; Pulsifer, P. L.; Strawhacker, C.; Yarmey, L.; Basak, R.

2017-12-01

We developed a Data Integration Tool (DIT) to significantly speed up the time of manual processing needed to translate inconsistent, scattered historical permafrost data into files ready to ingest directly into the Global Terrestrial Network-Permafrost (GTN-P). The United States National Science Foundation funded this project through the National Snow and Ice Data Center (NSIDC) with the GTN-P to improve permafrost data access and discovery. We leverage this data to support science research and policy decisions. DIT is a workflow manager that divides data preparation and analysis into a series of steps or operations called widgets (https://github.com/PermaData/DIT). Each widget does a specific operation, such as read, multiply by a constant, sort, plot, and write data. DIT allows the user to select and order the widgets as desired to meet their specific needs, incrementally interact with and evolve the widget workflows, and save those workflows for reproducibility. Taking ideas from visual programming found in the art and design domain, debugging and iterative design principles from software engineering, and the scientific data processing and analysis power of Fortran and Python it was written for interactive, iterative data manipulation, quality control, processing, and analysis of inconsistent data in an easily installable application. DIT was used to completely translate one dataset (133 sites) that was successfully added to GTN-P, nearly translate three datasets (270 sites), and is scheduled to translate 10 more datasets ( 1000 sites) from the legacy inactive site data holdings of the Frozen Ground Data Center (FGDC). Iterative development has provided the permafrost and wider scientific community with an extendable tool designed specifically for the iterative process of translating unruly data.

An open-closed-loop iterative learning control approach for nonlinear switched systems with application to freeway traffic control

NASA Astrophysics Data System (ADS)

Sun, Shu-Ting; Li, Xiao-Dong; Zhong, Ren-Xin

2017-10-01

For nonlinear switched discrete-time systems with input constraints, this paper presents an open-closed-loop iterative learning control (ILC) approach, which includes a feedforward ILC part and a feedback control part. Under a given switching rule, the mathematical induction is used to prove the convergence of ILC tracking error in each subsystem. It is demonstrated that the convergence of ILC tracking error is dependent on the feedforward control gain, but the feedback control can speed up the convergence process of ILC by a suitable selection of feedback control gain. A switched freeway traffic system is used to illustrate the effectiveness of the proposed ILC law.

The Determination of Relevant Goals and Criteria Used to Select an Automated Patient Care Information System

PubMed Central

Chocholik, Joan K.; Bouchard, Susan E.; Tan, Joseph K. H.; Ostrow, David N.

1999-01-01

Objectives: To determine the relevant weighted goals and criteria for use in the selection of an automated patient care information system (PCIS) using a modified Delphi technique to achieve consensus. Design: A three-phase, six-round modified Delphi process was implemented by a ten-member PCIS selection task force. The first phase consisted of an exploratory round. It was followed by the second phase, of two rounds, to determine the selection goals and finally the third phase, of three rounds, to finalize the selection criteria. Results: Consensus on the goals and criteria for selecting a PCIS was measured during the Delphi process by reviewing the mean and standard deviation of the previous round's responses. After the study was completed, the results were analyzed using a limits-of-agreement indicator that showed strong agreement of each individual's responses between each of the goal determination rounds. Further analysis for variability in the group's response showed a significant movement to consensus after the first goal-determination iteration, with consensus reached on all goals by the end of the second iteration. Conclusion: The results indicated that the relevant weighted goals and criteria used to make the final decision for an automated PCIS were developed as a result of strong agreement among members of the PCIS selection task force. It is therefore recognized that the use of the Delphi process was beneficial in achieving consensus among clinical and nonclinical members in a relatively short time while avoiding a decision based on political biases and the “groupthink” of traditional committee meetings. The results suggest that improvements could be made in lessening the number of rounds by having information available through side conversations, by having other statistical indicators besides the mean and standard deviation available between rounds, and by having a content expert address questions between rounds. PMID:10332655

Armour Materials for the ITER Plasma Facing Components

NASA Astrophysics Data System (ADS)

Barabash, V.; Federici, G.; Matera, R.; Raffray, A. R.; ITER Home Teams,

The selection of the armour materials for the Plasma Facing Components (PFCs) of the International Thermonuclear Experimental Reactor (ITER) is a trade-off between multiple requirements derived from the unique features of a burning fusion plasma environment. The factors that affect the selection come primarily from the requirements of plasma performance (e.g., minimise impurity contamination in the confined plasma), engineering integrity, component lifetime (e.g., withstand thermal stresses, acceptable erosion, etc.) and safety (minimise tritium and radioactive dust inventories). The current selection in ITER is to use beryllium on the first-wall, upper baffle and on the port limiter surfaces, carbon fibre composites near the strike points of the divertor vertical target and tungsten elsewhere in the divertor and lower baffle modules. This paper provides the background for this selection vis-à-vis the operating parameters expected during normal and off-normal conditions. The reasons for the selection of the specific grades of armour materials are also described. The effects of the neutron irradiation on the properties of Be, W and carbon fibre composites at the expected ITER conditions are briefly reviewed. Critical issues are discussed together with the necessary future R&D.

Enhancement of the Comb Filtering Selectivity Using Iterative Moving Average for Periodic Waveform and Harmonic Elimination

PubMed Central

Wu, Yan; Aarts, Ronald M.

2018-01-01

A recurring problem regarding the use of conventional comb filter approaches for elimination of periodic waveforms is the degree of selectivity achieved by the filtering process. Some applications, such as the gradient artefact correction in EEG recordings during coregistered EEG-fMRI, require a highly selective comb filtering that provides effective attenuation in the stopbands and gain close to unity in the pass-bands. In this paper, we present a novel comb filtering implementation whereby the iterative filtering application of FIR moving average-based approaches is exploited in order to enhance the comb filtering selectivity. Our results indicate that the proposed approach can be used to effectively approximate the FIR moving average filter characteristics to those of an ideal filter. A cascaded implementation using the proposed approach shows to further increase the attenuation in the filter stopbands. Moreover, broadening of the bandwidth of the comb filtering stopbands around −3 dB according to the fundamental frequency of the stopband can be achieved by the novel method, which constitutes an important characteristic to account for broadening of the harmonic gradient artefact spectral lines. In parallel, the proposed filtering implementation can also be used to design a novel notch filtering approach with enhanced selectivity as well. PMID:29599955

Systems and methods for optimal power flow on a radial network

DOEpatents

Low, Steven H.; Peng, Qiuyu

2018-04-24

Node controllers and power distribution networks in accordance with embodiments of the invention enable distributed power control. One embodiment includes a node controller including a distributed power control application; a plurality of node operating parameters describing the operating parameter of a node and a set of at least one node selected from the group consisting of an ancestor node and at least one child node; wherein send node operating parameters to nodes in the set of at least one node; receive operating parameters from the nodes in the set of at least one node; calculate a plurality of updated node operating parameters using an iterative process to determine the updated node operating parameters using the node operating parameters that describe the operating parameters of the node and the set of at least one node, where the iterative process involves evaluation of a closed form solution; and adjust node operating parameters.

Statistical iterative material image reconstruction for spectral CT using a semi-empirical forward model

NASA Astrophysics Data System (ADS)

Mechlem, Korbinian; Ehn, Sebastian; Sellerer, Thorsten; Pfeiffer, Franz; Noël, Peter B.

2017-03-01

In spectral computed tomography (spectral CT), the additional information about the energy dependence of attenuation coefficients can be exploited to generate material selective images. These images have found applications in various areas such as artifact reduction, quantitative imaging or clinical diagnosis. However, significant noise amplification on material decomposed images remains a fundamental problem of spectral CT. Most spectral CT algorithms separate the process of material decomposition and image reconstruction. Separating these steps is suboptimal because the full statistical information contained in the spectral tomographic measurements cannot be exploited. Statistical iterative reconstruction (SIR) techniques provide an alternative, mathematically elegant approach to obtaining material selective images with improved tradeoffs between noise and resolution. Furthermore, image reconstruction and material decomposition can be performed jointly. This is accomplished by a forward model which directly connects the (expected) spectral projection measurements and the material selective images. To obtain this forward model, detailed knowledge of the different photon energy spectra and the detector response was assumed in previous work. However, accurately determining the spectrum is often difficult in practice. In this work, a new algorithm for statistical iterative material decomposition is presented. It uses a semi-empirical forward model which relies on simple calibration measurements. Furthermore, an efficient optimization algorithm based on separable surrogate functions is employed. This partially negates one of the major shortcomings of SIR, namely high computational cost and long reconstruction times. Numerical simulations and real experiments show strongly improved image quality and reduced statistical bias compared to projection-based material decomposition.

Significance of ITER IWS Material Selection and Qualification

NASA Astrophysics Data System (ADS)

Mehta, Bhoomi K.; Raval, Jigar; Maheshwari, Abha; Laad, Rahul; Singh, Gurlovleen; Pathak, Haresh

2017-04-01

In-Wall Shielding (IWS) is one of the important components of ITER Vacuum Vessel (VV) which fills the space between double walls of VV with cooling water. Procurement Arrangement (PA) for IWS has been signed with Indian Domestic Agency (INDA). Procurement of IWS materials, fabrication of IWS blocks and its delivery to respective Domestic Agency (DA) and ITER Organization (IO) are the main scope of this PA. Hence, INDIA is the only country which is contributing to VV IWS among all seven ITER partners. The main functions of the IWS are to provide Neutron Shielding with blanket, VV shells and water during plasma operations and to reduce ripple of the Toroidal Magnetic Field. To meet these functional requirements IWS blocks are made up of special materials (Borated Steels SS304 B4 & SS304 B7, Ferritic Steels SS 430, Austenitic Steel SS 316 L (N)-IG, XM-19 and Inconel-625) which are qualified, reliable and traceable for the design assessment. The choice of these materials has a significant influence on performance, maintainability, licensing, detailed design parameters and waste disposal. The main reasons for the materials selected for IWS are its high mechanical strength at operating temperatures, water chemistry properties, excellent fabrication characteristics and low cost relative to other similar materials. All the materials are qualified with respect to their respective codes (ASTM/EN standards with additional requirements as described in RCC-MR code 2007) and ITER requirements. Agreed Notified Body (ANB) has control conformity of materials certificates with approved material specification and traceability procedure for Safety Important Component (SIC). The procurement strategy for all the IWS materials has been developed in close collaboration with IO, ANB and Industries as per Product Procurement Specification (PPS). The R&D for sample, bulk material production, testing, inspection and handling as required are carried out by IN DA and IO. At present almost all IWS materials (∼2500 Tons) has been procured by IN DA with spares to manufacture ∼9000 IWS blocks. This paper summarizes IWS material selection, qualification and procurement processes in detail.

Application of an improved maximum correlated kurtosis deconvolution method for fault diagnosis of rolling element bearings

NASA Astrophysics Data System (ADS)

Miao, Yonghao; Zhao, Ming; Lin, Jing; Lei, Yaguo

2017-08-01

The extraction of periodic impulses, which are the important indicators of rolling bearing faults, from vibration signals is considerably significance for fault diagnosis. Maximum correlated kurtosis deconvolution (MCKD) developed from minimum entropy deconvolution (MED) has been proven as an efficient tool for enhancing the periodic impulses in the diagnosis of rolling element bearings and gearboxes. However, challenges still exist when MCKD is applied to the bearings operating under harsh working conditions. The difficulties mainly come from the rigorous requires for the multi-input parameters and the complicated resampling process. To overcome these limitations, an improved MCKD (IMCKD) is presented in this paper. The new method estimates the iterative period by calculating the autocorrelation of the envelope signal rather than relies on the provided prior period. Moreover, the iterative period will gradually approach to the true fault period through updating the iterative period after every iterative step. Since IMCKD is unaffected by the impulse signals with the high kurtosis value, the new method selects the maximum kurtosis filtered signal as the final choice from all candidates in the assigned iterative counts. Compared with MCKD, IMCKD has three advantages. First, without considering prior period and the choice of the order of shift, IMCKD is more efficient and has higher robustness. Second, the resampling process is not necessary for IMCKD, which is greatly convenient for the subsequent frequency spectrum analysis and envelope spectrum analysis without resetting the sampling rate. Third, IMCKD has a significant performance advantage in diagnosing the bearing compound-fault which expands the application range. Finally, the effectiveness and superiority of IMCKD are validated by a number of simulated bearing fault signals and applying to compound faults and single fault diagnosis of a locomotive bearing.

Jini service to reconstruct tomographic data

NASA Astrophysics Data System (ADS)

Knoll, Peter; Mirzaei, S.; Koriska, K.; Koehn, H.

2002-06-01

A number of imaging systems rely on the reconstruction of a 3- dimensional model from its projections through the process of computed tomography (CT). In medical imaging, for example magnetic resonance imaging (MRI), positron emission tomography (PET), and Single Computer Tomography (SPECT) acquire two-dimensional projections of a three dimensional projections of a three dimensional object. In order to calculate the 3-dimensional representation of the object, i.e. its voxel distribution, several reconstruction algorithms have been developed. Currently, mainly two reconstruct use: the filtered back projection(FBP) and iterative methods. Although the quality of iterative reconstructed SPECT slices is better than that of FBP slices, such iterative algorithms are rarely used for clinical routine studies because of their low availability and increased reconstruction time. We used Jini and a self-developed iterative reconstructions algorithm to design and implement a Jini reconstruction service. With this service, the physician selects the patient study from a database and a Jini client automatically discovers the registered Jini reconstruction services in the department's Intranet. After downloading the proxy object the this Jini service, the SPECT acquisition data are reconstructed. The resulting transaxial slices are visualized using a Jini slice viewer, which can be used for various imaging modalities.

Loads specification and embedded plate definition for the ITER cryoline system

NASA Astrophysics Data System (ADS)

Badgujar, S.; Benkheira, L.; Chalifour, M.; Forgeas, A.; Shah, N.; Vaghela, H.; Sarkar, B.

2015-12-01

ITER cryolines (CLs) are complex network of vacuum-insulated multi and single process pipe lines, distributed in three different areas at ITER site. The CLs will support different operating loads during the machine life-time; either considered as nominal, occasional or exceptional. The major loads, which form the design basis are inertial, pressure, temperature, assembly, magnetic, snow, wind, enforced relative displacement and are put together in loads specification. Based on the defined load combinations, conceptual estimation of reaction loads have been carried out for the lines located inside the Tokamak building. Adequate numbers of embedded plates (EPs) per line have been defined and integrated in the building design. The finalization of building EPs to support the lines, before the detailed design, is one of the major design challenges as the usual logic of the design may alter. At the ITER project level, it was important to finalize EPs to allow adequate design and timely availability of the Tokamak building. The paper describes the single loads, load combinations considered in load specification and the approach for conceptual load estimation and selection of EPs for Toroidal Field (TF) Cryoline as an example by converting the load combinations in two main load categories; pressure and seismic.

Gaussian mixed model in support of semiglobal matching leveraged by ground control points

NASA Astrophysics Data System (ADS)

Ma, Hao; Zheng, Shunyi; Li, Chang; Li, Yingsong; Gui, Li

2017-04-01

Semiglobal matching (SGM) has been widely applied in large aerial images because of its good tradeoff between complexity and robustness. The concept of ground control points (GCPs) is adopted to make SGM more robust. We model the effect of GCPs as two data terms for stereo matching between high-resolution aerial epipolar images in an iterative scheme. One term based on GCPs is formulated by Gaussian mixture model, which strengths the relation between GCPs and the pixels to be estimated and encodes some degree of consistency between them with respect to disparity values. Another term depends on pixel-wise confidence, and we further design a confidence updating equation based on three rules. With this confidence-based term, the assignment of disparity can be heuristically selected among disparity search ranges during the iteration process. Several iterations are sufficient to bring out satisfactory results according to our experiments. Experimental results validate that the proposed method outperforms surface reconstruction, which is a representative variant of SGM and behaves excellently on aerial images.

MEGA-CC: computing core of molecular evolutionary genetics analysis program for automated and iterative data analysis.

PubMed

Kumar, Sudhir; Stecher, Glen; Peterson, Daniel; Tamura, Koichiro

2012-10-15

There is a growing need in the research community to apply the molecular evolutionary genetics analysis (MEGA) software tool for batch processing a large number of datasets and to integrate it into analysis workflows. Therefore, we now make available the computing core of the MEGA software as a stand-alone executable (MEGA-CC), along with an analysis prototyper (MEGA-Proto). MEGA-CC provides users with access to all the computational analyses available through MEGA's graphical user interface version. This includes methods for multiple sequence alignment, substitution model selection, evolutionary distance estimation, phylogeny inference, substitution rate and pattern estimation, tests of natural selection and ancestral sequence inference. Additionally, we have upgraded the source code for phylogenetic analysis using the maximum likelihood methods for parallel execution on multiple processors and cores. Here, we describe MEGA-CC and outline the steps for using MEGA-CC in tandem with MEGA-Proto for iterative and automated data analysis. http://www.megasoftware.net/.

The Effect of Iteration on the Design Performance of Primary School Children

ERIC Educational Resources Information Center

Looijenga, Annemarie; Klapwijk, Remke; de Vries, Marc J.

2015-01-01

Iteration during the design process is an essential element. Engineers optimize their design by iteration. Research on iteration in Primary Design Education is however scarce; possibly teachers believe they do not have enough time for iteration in daily classroom practices. Spontaneous playing behavior of children indicates that iteration fits in…

GWASinlps: Nonlocal prior based iterative SNP selection tool for genome-wide association studies.

PubMed

Sanyal, Nilotpal; Lo, Min-Tzu; Kauppi, Karolina; Djurovic, Srdjan; Andreassen, Ole A; Johnson, Valen E; Chen, Chi-Hua

2018-06-19

Multiple marker analysis of the genome-wide association study (GWAS) data has gained ample attention in recent years. However, because of the ultra high-dimensionality of GWAS data, such analysis is challenging. Frequently used penalized regression methods often lead to large number of false positives, whereas Bayesian methods are computationally very expensive. Motivated to ameliorate these issues simultaneously, we consider the novel approach of using nonlocal priors in an iterative variable selection framework. We develop a variable selection method, named, iterative nonlocal prior based selection for GWAS, or GWASinlps, that combines, in an iterative variable selection framework, the computational efficiency of the screen-and-select approach based on some association learning and the parsimonious uncertainty quantification provided by the use of nonlocal priors. The hallmark of our method is the introduction of 'structured screen-and-select' strategy, that considers hierarchical screening, which is not only based on response-predictor associations, but also based on response-response associations, and concatenates variable selection within that hierarchy. Extensive simulation studies with SNPs having realistic linkage disequilibrium structures demonstrate the advantages of our computationally efficient method compared to several frequentist and Bayesian variable selection methods, in terms of true positive rate, false discovery rate, mean squared error, and effect size estimation error. Further, we provide empirical power analysis useful for study design. Finally, a real GWAS data application was considered with human height as phenotype. An R-package for implementing the GWASinlps method is available at https://cran.r-project.org/web/packages/GWASinlps/index.html. Supplementary data are available at Bioinformatics online.

Assay Development Process | Office of Cancer Clinical Proteomics Research

Cancer.gov

Typical steps involved in the development of a  mass spectrometry-based targeted assay include: (1) selection of surrogate or signature peptides corresponding to the targeted protein or modification of interest; (2) iterative optimization of instrument and method parameters for optimal detection of the selected peptide; (3) method development for protein extraction from biological matrices such as tissue, whole cell lysates, or blood plasma/serum and proteolytic digestion of proteins (usually with trypsin); (4) evaluation of the assay in the intended biological matrix to determine if e

Data Integration Tool: From Permafrost Data Translation Research Tool to A Robust Research Application

NASA Astrophysics Data System (ADS)

Wilcox, H.; Schaefer, K. M.; Jafarov, E. E.; Strawhacker, C.; Pulsifer, P. L.; Thurmes, N.

2016-12-01

The United States National Science Foundation funded PermaData project led by the National Snow and Ice Data Center (NSIDC) with a team from the Global Terrestrial Network for Permafrost (GTN-P) aimed to improve permafrost data access and discovery. We developed a Data Integration Tool (DIT) to significantly speed up the time of manual processing needed to translate inconsistent, scattered historical permafrost data into files ready to ingest directly into the GTN-P. We leverage this data to support science research and policy decisions. DIT is a workflow manager that divides data preparation and analysis into a series of steps or operations called widgets. Each widget does a specific operation, such as read, multiply by a constant, sort, plot, and write data. DIT allows the user to select and order the widgets as desired to meet their specific needs. Originally it was written to capture a scientist's personal, iterative, data manipulation and quality control process of visually and programmatically iterating through inconsistent input data, examining it to find problems, adding operations to address the problems, and rerunning until the data could be translated into the GTN-P standard format. Iterative development of this tool led to a Fortran/Python hybrid then, with consideration of users, licensing, version control, packaging, and workflow, to a publically available, robust, usable application. Transitioning to Python allowed the use of open source frameworks for the workflow core and integration with a javascript graphical workflow interface. DIT is targeted to automatically handle 90% of the data processing for field scientists, modelers, and non-discipline scientists. It is available as an open source tool in GitHub packaged for a subset of Mac, Windows, and UNIX systems as a desktop application with a graphical workflow manager. DIT was used to completely translate one dataset (133 sites) that was successfully added to GTN-P, nearly translate three datasets (270 sites), and is scheduled to translate 10 more datasets ( 1000 sites) from the legacy inactive site data holdings of the Frozen Ground Data Center (FGDC). Iterative development has provided the permafrost and wider scientific community with an extendable tool designed specifically for the iterative process of translating unruly data.

ITER Central Solenoid Module Fabrication

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

Smith, John

The fabrication of the modules for the ITER Central Solenoid (CS) has started in a dedicated production facility located in Poway, California, USA. The necessary tools have been designed, built, installed, and tested in the facility to enable the start of production. The current schedule has first module fabrication completed in 2017, followed by testing and subsequent shipment to ITER. The Central Solenoid is a key component of the ITER tokamak providing the inductive voltage to initiate and sustain the plasma current and to position and shape the plasma. The design of the CS has been a collaborative effort betweenmore » the US ITER Project Office (US ITER), the international ITER Organization (IO) and General Atomics (GA). GA’s responsibility includes: completing the fabrication design, developing and qualifying the fabrication processes and tools, and then completing the fabrication of the seven 110 tonne CS modules. The modules will be shipped separately to the ITER site, and then stacked and aligned in the Assembly Hall prior to insertion in the core of the ITER tokamak. A dedicated facility in Poway, California, USA has been established by GA to complete the fabrication of the seven modules. Infrastructure improvements included thick reinforced concrete floors, a diesel generator for backup power, along with, cranes for moving the tooling within the facility. The fabrication process for a single module requires approximately 22 months followed by five months of testing, which includes preliminary electrical testing followed by high current (48.5 kA) tests at 4.7K. The production of the seven modules is completed in a parallel fashion through ten process stations. The process stations have been designed and built with most stations having completed testing and qualification for carrying out the required fabrication processes. The final qualification step for each process station is achieved by the successful production of a prototype coil. Fabrication of the first ITER module is in progress. The seven modules will be individually shipped to Cadarache, France upon their completion. This paper describes the processes and status of the fabrication of the CS Modules for ITER.« less

Using an evidence-based approach for system selection at a large academic medical center: lessons learned in selecting an ambulatory EMR at Mount Sinai Hospital.

PubMed

Kannry, Joseph; Mukani, Sonia; Myers, Kristin

2006-01-01

The experience of Mount Sinai Hospital is representative of the challenges and problems facing large academic medical centers in selecting an ambulatory EMR. The facility successfully revived a stalled process in a challenging financial climate, using a framework of science and rigorous investigation. The process incorporated several innovations: 1) There was a thorough review of medical informatics literature to develop a mission statement, determine practical objectives and guide the demonstration process; 2) The process involved rigorous investigation of vendor statements, industry statements and other institution's views of vendors; 3) The initiative focused on user-centric selection, and the survey instrument was scientifically and specifically designed to assess user feedback; 4) There was scientific analysis of validated findings and survey results at all steering meetings; 5) The process included an assessment of vendors' ability to support research by identifying funded and published research; 6) Selection involved meticulous total cost of ownership analysis to assess and compare real costs of implementing a vendor solution; and finally, 7) There were iterative meetings with stakeholders, executives and users to understand needs, address concerns and communicate the vision.

Global Fleet Station: Station Ship Concept

DTIC Science & Technology

2008-02-01

The basic ISO TEU containers can be designed for any number of configurations and provide many different capabilities. For example there are...Design Design Process The ship was designed using an iterative weight and volume balancing method . This method assigns a weight and volume to each...from existing merchant ships3. Different ship types are modeled in the algorithm though the selection of appropriate non-dimensional factors

SUMMARY REPORT-FY2006 ITER WORK ACCOMPLISHED

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

Martovetsky, N N

2006-04-11

Six parties (EU, Japan, Russia, US, Korea, China) will build ITER. The US proposed to deliver at least 4 out of 7 modules of the Central Solenoid. Phillip Michael (MIT) and I were tasked by DoE to assist ITER in development of the ITER CS and other magnet systems. We work to help Magnets and Structure division headed by Neil Mitchell. During this visit I worked on the selected items of the CS design and carried out other small tasks, like PF temperature margin assessment.

Software for MR image overlay guided needle insertions: the clinical translation process

NASA Astrophysics Data System (ADS)

Ungi, Tamas; U-Thainual, Paweena; Fritz, Jan; Iordachita, Iulian I.; Flammang, Aaron J.; Carrino, John A.; Fichtinger, Gabor

2013-03-01

PURPOSE: Needle guidance software using augmented reality image overlay was translated from the experimental phase to support preclinical and clinical studies. Major functional and structural changes were needed to meet clinical requirements. We present the process applied to fulfill these requirements, and selected features that may be applied in the translational phase of other image-guided surgical navigation systems. METHODS: We used an agile software development process for rapid adaptation to unforeseen clinical requests. The process is based on iterations of operating room test sessions, feedback discussions, and software development sprints. The open-source application framework of 3D Slicer and the NA-MIC kit provided sufficient flexibility and stable software foundations for this work. RESULTS: All requirements were addressed in a process with 19 operating room test iterations. Most features developed in this phase were related to workflow simplification and operator feedback. CONCLUSION: Efficient and affordable modifications were facilitated by an open source application framework and frequent clinical feedback sessions. Results of cadaver experiments show that software requirements were successfully solved after a limited number of operating room tests.

Optimizing the availability of a buffered industrial process

DOEpatents

Martz, Jr., Harry F.; Hamada, Michael S.; Koehler, Arthur J.; Berg, Eric C.

2004-08-24

A computer-implemented process determines optimum configuration parameters for a buffered industrial process. A population size is initialized by randomly selecting a first set of design and operation values associated with subsystems and buffers of the buffered industrial process to form a set of operating parameters for each member of the population. An availability discrete event simulation (ADES) is performed on each member of the population to determine the product-based availability of each member. A new population is formed having members with a second set of design and operation values related to the first set of design and operation values through a genetic algorithm and the product-based availability determined by the ADES. Subsequent population members are then determined by iterating the genetic algorithm with product-based availability determined by ADES to form improved design and operation values from which the configuration parameters are selected for the buffered industrial process.

Dynamic adaptive learning for decision-making supporting systems

NASA Astrophysics Data System (ADS)

He, Haibo; Cao, Yuan; Chen, Sheng; Desai, Sachi; Hohil, Myron E.

2008-03-01

This paper proposes a novel adaptive learning method for data mining in support of decision-making systems. Due to the inherent characteristics of information ambiguity/uncertainty, high dimensionality and noisy in many homeland security and defense applications, such as surveillances, monitoring, net-centric battlefield, and others, it is critical to develop autonomous learning methods to efficiently learn useful information from raw data to help the decision making process. The proposed method is based on a dynamic learning principle in the feature spaces. Generally speaking, conventional approaches of learning from high dimensional data sets include various feature extraction (principal component analysis, wavelet transform, and others) and feature selection (embedded approach, wrapper approach, filter approach, and others) methods. However, very limited understandings of adaptive learning from different feature spaces have been achieved. We propose an integrative approach that takes advantages of feature selection and hypothesis ensemble techniques to achieve our goal. Based on the training data distributions, a feature score function is used to provide a measurement of the importance of different features for learning purpose. Then multiple hypotheses are iteratively developed in different feature spaces according to their learning capabilities. Unlike the pre-set iteration steps in many of the existing ensemble learning approaches, such as adaptive boosting (AdaBoost) method, the iterative learning process will automatically stop when the intelligent system can not provide a better understanding than a random guess in that particular subset of feature spaces. Finally, a voting algorithm is used to combine all the decisions from different hypotheses to provide the final prediction results. Simulation analyses of the proposed method on classification of different US military aircraft databases show the effectiveness of this method.

The Iterative Design Process in Research and Development: A Work Experience Paper

NASA Technical Reports Server (NTRS)

Sullivan, George F. III

2013-01-01

The iterative design process is one of many strategies used in new product development. Top-down development strategies, like waterfall development, place a heavy emphasis on planning and simulation. The iterative process, on the other hand, is better suited to the management of small to medium scale projects. Over the past four months, I have worked with engineers at Johnson Space Center on a multitude of electronics projects. By describing the work I have done these last few months, analyzing the factors that have driven design decisions, and examining the testing and verification process, I will demonstrate that iterative design is the obvious choice for research and development projects.

Selective processing of auditory evoked responses with iterative-randomized stimulation and averaging: A strategy for evaluating the time-invariant assumption.

PubMed

Valderrama, Joaquin T; de la Torre, Angel; Medina, Carlos; Segura, Jose C; Thornton, A Roger D

2016-03-01

The recording of auditory evoked potentials (AEPs) at fast rates allows the study of neural adaptation, improves accuracy in estimating hearing threshold and may help diagnosing certain pathologies. Stimulation sequences used to record AEPs at fast rates require to be designed with a certain jitter, i.e., not periodical. Some authors believe that stimuli from wide-jittered sequences may evoke auditory responses of different morphology, and therefore, the time-invariant assumption would not be accomplished. This paper describes a methodology that can be used to analyze the time-invariant assumption in jittered stimulation sequences. The proposed method [Split-IRSA] is based on an extended version of the iterative randomized stimulation and averaging (IRSA) technique, including selective processing of sweeps according to a predefined criterion. The fundamentals, the mathematical basis and relevant implementation guidelines of this technique are presented in this paper. The results of this study show that Split-IRSA presents an adequate performance and that both fast and slow mechanisms of adaptation influence the evoked-response morphology, thus both mechanisms should be considered when time-invariance is assumed. The significance of these findings is discussed. Crown Copyright © 2016. Published by Elsevier B.V. All rights reserved.

Modern Workflow Full Waveform Inversion Applied to North America and the Northern Atlantic

NASA Astrophysics Data System (ADS)

Krischer, Lion; Fichtner, Andreas; Igel, Heiner

2015-04-01

We present the current state of a new seismic tomography model obtained using full waveform inversion of the crustal and upper mantle structure beneath North America and the Northern Atlantic, including the westernmost part of Europe. Parts of the eastern portion of the initial model consists of previous models by Fichtner et al. (2013) and Rickers et al. (2013). The final results of this study will contribute to the 'Comprehensive Earth Model' being developed by the Computational Seismology group at ETH Zurich. Significant challenges include the size of the domain, the uneven event and station coverage, and the strong east-west alignment of seismic ray paths across the North Atlantic. We use as much data as feasible, resulting in several thousand recordings per event depending on the receivers deployed at the earthquakes' origin times. To manage such projects in a reproducible and collaborative manner, we, as tomographers, should abandon ad-hoc scripts and one-time programs, and adopt sustainable and reusable solutions. Therefore we developed the LArge-scale Seismic Inversion Framework (LASIF - http://lasif.net), an open-source toolbox for managing seismic data in the context of non-linear iterative inversions that greatly reduces the time to research. Information on the applied processing, modelling, iterative model updating, what happened during each iteration, and so on are systematically archived. This results in a provenance record of the final model which in the end significantly enhances the reproducibility of iterative inversions. Additionally, tools for automated data download across different data centers, window selection, misfit measurements, parallel data processing, and input file generation for various forward solvers are provided.

The ATLAS Public Web Pages: Online Management of HEP External Communication Content

NASA Astrophysics Data System (ADS)

Goldfarb, S.; Marcelloni, C.; Eli Phoboo, A.; Shaw, K.

2015-12-01

The ATLAS Education and Outreach Group is in the process of migrating its public online content to a professionally designed set of web pages built on the Drupal [1] content management system. Development of the front-end design passed through several key stages, including audience surveys, stakeholder interviews, usage analytics, and a series of fast design iterations, called sprints. Implementation of the web site involves application of the html design using Drupal templates, refined development iterations, and the overall population of the site with content. We present the design and development processes and share the lessons learned along the way, including the results of the data-driven discovery studies. We also demonstrate the advantages of selecting a back-end supported by content management, with a focus on workflow. Finally, we discuss usage of the new public web pages to implement outreach strategy through implementation of clearly presented themes, consistent audience targeting and messaging, and the enforcement of a well-defined visual identity.

Incorporating prototyping and iteration into intervention development: a case study of a dining hall-based intervention.

PubMed

McClain, Arianna D; Hekler, Eric B; Gardner, Christopher D

2013-01-01

Previous research from the fields of computer science and engineering highlight the importance of an iterative design process (IDP) to create more creative and effective solutions. This study describes IDP as a new method for developing health behavior interventions and evaluates the effectiveness of a dining hall-based intervention developed using IDP on college students' eating behavior and values. participants were 458 students (52.6% female, age = 19.6 ± 1.5 years [M ± SD]). The intervention was developed via an IDP parallel process. A cluster-randomized controlled study compared differences in eating behavior among students in 4 university dining halls (2 intervention, 2 control). The final intervention was a multicomponent, point-of-selection marketing campaign. Students in the intervention dining halls consumed significantly less junk food and high-fat meat and increased their perceived importance of eating a healthful diet relative to the control group. IDP may be valuable for the development of behavior change interventions.

Bounding the Spacecraft Atmosphere Design Space for Future Exploration Missions

NASA Technical Reports Server (NTRS)

Lange, Kevin E.; Perka, Alan T.; Duffield, Bruce E.; Jeng, Frank F.

2005-01-01

The selection of spacecraft and space suit atmospheres for future human space exploration missions will play an important, if not critical, role in the ultimate safety, productivity, and cost of such missions. Internal atmosphere pressure and composition (particularly oxygen concentration) influence many aspects of spacecraft and space suit design, operation, and technology development. Optimal atmosphere solutions must be determined by iterative process involving research, design, development, testing, and systems analysis. A necessary first step in this process is the establishment of working bounds on the atmosphere design space.

DNA capture elements for rapid detection and identification of biological agents

NASA Astrophysics Data System (ADS)

Kiel, Johnathan L.; Parker, Jill E.; Holwitt, Eric A.; Vivekananda, Jeeva

2004-08-01

DNA capture elements (DCEs; aptamers) are artificial DNA sequences, from a random pool of sequences, selected for their specific binding to potential biological warfare agents. These sequences were selected by an affinity method using filters to which the target agent was attached and the DNA isolated and amplified by polymerase chain reaction (PCR) in an iterative, increasingly stringent, process. Reporter molecules were attached to the finished sequences. To date, we have made DCEs to Bacillus anthracis spores, Shiga toxin, Venezuelan Equine Encephalitis (VEE) virus, and Francisella tularensis. These DCEs have demonstrated specificity and sensitivity equal to or better than antibody.

Implementation of an improved adaptive-implicit method in a thermal compositional simulator

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

Tan, T.B.

1988-11-01

A multicomponent thermal simulator with an adaptive-implicit-method (AIM) formulation/inexact-adaptive-Newton (IAN) method is presented. The final coefficient matrix retains the original banded structure so that conventional iterative methods can be used. Various methods for selection of the eliminated unknowns are tested. AIM/IAN method has a lower work count per Newtonian iteration than fully implicit methods, but a wrong choice of unknowns will result in excessive Newtonian iterations. For the problems tested, the residual-error method described in the paper for selecting implicit unknowns, together with the IAN method, had an improvement of up to 28% of the CPU time over the fullymore » implicit method.« less

Development of a laser cleaning method for the first mirror surface of the charge exchange recombination spectroscopy diagnostics on ITER

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

Kuznetsov, A. P., E-mail: APKuznetsov@mephi.ru; Buzinskij, O. I.; Gubsky, K. L.

A set of optical diagnostics is expected for measuring the plasma characteristics in ITER. Optical elements located inside discharge chambers are exposed to an intense radiation load, sputtering due to collisions with energetic atoms formed in the charge transfer processes, and contamination due to recondensation of materials sputtered from different parts of the construction of the chamber. Removing the films of the sputtered materials from the mirrors with the aid of pulsed laser radiation is an efficient cleaning method enabling recovery of the optical properties of the mirrors. In this work, we studied the efficiency of removal of metal oxidemore » films by pulsed radiation of a fiber laser. Optimization of the laser cleaning conditions was carried out on samples representing metal substrates polished with optical quality with deposition of films on them imitating the chemical composition and conditions expected in ITER. It is shown that, by a proper selection of modes of radiation exposure to the surface with a deposited film, it is feasible to restore the original high reflection characteristics of optical elements.« less

Advances in Global Adjoint Tomography - Data Assimilation and Inversion Strategy

NASA Astrophysics Data System (ADS)

Ruan, Y.; Lei, W.; Lefebvre, M. P.; Modrak, R. T.; Smith, J. A.; Bozdag, E.; Tromp, J.

2016-12-01

Seismic tomography provides the most direct way to understand Earth's interior by imaging elastic heterogeneity, anisotropy and anelasticity. Resolving thefine structure of these properties requires accurate simulations of seismic wave propagation in complex 3-D Earth models. On the supercomputer "Titan" at Oak Ridge National Laboratory, we are employing a spectral-element method (Komatitsch & Tromp 1999, 2002) in combination with an adjoint method (Tromp et al., 2005) to accurately calculate theoretical seismograms and Frechet derivatives. Using 253 carefully selected events, Bozdag et al. (2016) iteratively determined a transversely isotropic earth model (GLAD_M15) using 15 preconditioned conjugate-gradient iterations. To obtain higher resolution images of the mantle, we have expanded our database to more than 4,220 Mw5.0-7.0 events occurred between 1995 and 2014. Instead of using the entire database all at once, we choose to draw subsets of about 1,000 events from our database for each iteration to achieve a faster convergence rate with limited computing resources. To provide good coverage of deep structures, we selected approximately 700 deep and intermedia earthquakes and 300 shallow events to start a new iteration. We reinverted the CMT solutions of these events in the latest model, and recalculated synthetic seismograms. Using the synthetics as reference seismograms, we selected time windows that show good agreement with data and make measurements within the windows. From the measurements we further assess the overall quality of each event and station, and exclude bad measurements base upon certain criteria. So far, with very conservative criteria, we have assimilated more than 8.0 million windows from 1,000 earthquakes in three period bands for the new iteration. For subsequent iterations, we will change the period bands and window selecting criteria to include more window. In the inversion, dense array data (e.g., USArray) usually dominate model updates. In order to better handle this issue, we introduced weighting of stations and events based upon their relative distance and showed that the contribution from dense array is better balanced in the Frechet derivatives. We will present a summary of this form of data assimilation and preliminary results of the first few iterations.

Trajectory Optimization for Missions to Small Bodies with a Focus on Scientific Merit.

PubMed

Englander, Jacob A; Vavrina, Matthew A; Lim, Lucy F; McFadden, Lucy A; Rhoden, Alyssa R; Noll, Keith S

2017-01-01

Trajectory design for missions to small bodies is tightly coupled both with the selection of targets for a mission and with the choice of spacecraft power, propulsion, and other hardware. Traditional methods of trajectory optimization have focused on finding the optimal trajectory for an a priori selection of destinations and spacecraft parameters. Recent research has expanded the field of trajectory optimization to multidisciplinary systems optimization that includes spacecraft parameters. The logical next step is to extend the optimization process to include target selection based not only on engineering figures of merit but also scientific value. This paper presents a new technique to solve the multidisciplinary mission optimization problem for small-bodies missions, including classical trajectory design, the choice of spacecraft power and propulsion systems, and also the scientific value of the targets. This technique, when combined with modern parallel computers, enables a holistic view of the small body mission design process that previously required iteration among several different design processes.

Developing and Evaluating an Eighth Grade Curriculum Unit That Links Foundational Chemistry to Biological Growth. Paper #1: Selecting Core Ideas and Practices -- An Iterative Process

ERIC Educational Resources Information Center

Roseman, Jo Ellen; Herrmann-Abell, Cari; Flanagan, Jean; Kruse, Rebecca; Howes, Elaine; Carlson, Janet; Roth, Kathy; Bourdelat-Parks, Brooke

2013-01-01

Researchers at AAAS and BSCS have developed a six-week unit that aims to help middle school students learn important chemistry ideas that can be used to explain growth and repair in animals and plants. By integrating core physical and life science ideas and engaging students in the science practices of modeling and constructing explanations, the…

A Fast, Open EEG Classification Framework Based on Feature Compression and Channel Ranking

PubMed Central

Han, Jiuqi; Zhao, Yuwei; Sun, Hongji; Chen, Jiayun; Ke, Ang; Xu, Gesen; Zhang, Hualiang; Zhou, Jin; Wang, Changyong

2018-01-01

Superior feature extraction, channel selection and classification methods are essential for designing electroencephalography (EEG) classification frameworks. However, the performance of most frameworks is limited by their improper channel selection methods and too specifical design, leading to high computational complexity, non-convergent procedure and narrow expansibility. In this paper, to remedy these drawbacks, we propose a fast, open EEG classification framework centralized by EEG feature compression, low-dimensional representation, and convergent iterative channel ranking. First, to reduce the complexity, we use data clustering to compress the EEG features channel-wise, packing the high-dimensional EEG signal, and endowing them with numerical signatures. Second, to provide easy access to alternative superior methods, we structurally represent each EEG trial in a feature vector with its corresponding numerical signature. Thus, the recorded signals of many trials shrink to a low-dimensional structural matrix compatible with most pattern recognition methods. Third, a series of effective iterative feature selection approaches with theoretical convergence is introduced to rank the EEG channels and remove redundant ones, further accelerating the EEG classification process and ensuring its stability. Finally, a classical linear discriminant analysis (LDA) model is employed to classify a single EEG trial with selected channels. Experimental results on two real world brain-computer interface (BCI) competition datasets demonstrate the promising performance of the proposed framework over state-of-the-art methods. PMID:29713262

High resolution x-ray CMT: Reconstruction methods

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

Brown, J.K.

This paper qualitatively discusses the primary characteristics of methods for reconstructing tomographic images from a set of projections. These reconstruction methods can be categorized as either {open_quotes}analytic{close_quotes} or {open_quotes}iterative{close_quotes} techniques. Analytic algorithms are derived from the formal inversion of equations describing the imaging process, while iterative algorithms incorporate a model of the imaging process and provide a mechanism to iteratively improve image estimates. Analytic reconstruction algorithms are typically computationally more efficient than iterative methods; however, analytic algorithms are available for a relatively limited set of imaging geometries and situations. Thus, the framework of iterative reconstruction methods is better suited formore » high accuracy, tomographic reconstruction codes.« less

Design tool for multiprocessor scheduling and evaluation of iterative dataflow algorithms

NASA Technical Reports Server (NTRS)

Jones, Robert L., III

1995-01-01

A graph-theoretic design process and software tool is defined for selecting a multiprocessing scheduling solution for a class of computational problems. The problems of interest are those that can be described with a dataflow graph and are intended to be executed repetitively on a set of identical processors. Typical applications include signal processing and control law problems. Graph-search algorithms and analysis techniques are introduced and shown to effectively determine performance bounds, scheduling constraints, and resource requirements. The software tool applies the design process to a given problem and includes performance optimization through the inclusion of additional precedence constraints among the schedulable tasks.

Doppler Lidar System Design via Interdisciplinary Design Concept at NASA Langley Research Center - Part I

NASA Technical Reports Server (NTRS)

Boyer, Charles M.; Jackson, Trevor P.; Beyon, Jeffrey Y.; Petway, Larry B.

2013-01-01

Optimized designs of the Navigation Doppler Lidar (NDL) instrument for Autonomous Landing Hazard Avoidance Technology (ALHAT) were accomplished via Interdisciplinary Design Concept (IDEC) at NASA Langley Research Center during the summer of 2013. Three branches in the Engineering Directorate and three students were involved in this joint task through the NASA Langley Aerospace Research Summer Scholars (LARSS) Program. The Laser Remote Sensing Branch (LRSB), Mechanical Systems Branch (MSB), and Structural and Thermal Systems Branch (STSB) were engaged to achieve optimal designs through iterative and interactive collaborative design processes. A preliminary design iteration was able to reduce the power consumption, mass, and footprint by removing redundant components and replacing inefficient components with more efficient ones. A second design iteration reduced volume and mass by replacing bulky components with excessive performance with smaller components custom-designed for the power system. Mechanical placement collaboration reduced potential electromagnetic interference (EMI). Through application of newly selected electrical components and thermal analysis data, a total electronic chassis redesign was accomplished. Use of an innovative forced convection tunnel heat sink was employed to meet and exceed project requirements for cooling, mass reduction, and volume reduction. Functionality was a key concern to make efficient use of airflow, and accessibility was also imperative to allow for servicing of chassis internals. The collaborative process provided for accelerated design maturation with substantiated function.

Applicability of the iterative technique for cardiac resynchronization therapy optimization: full-disclosure, 50-sequential-patient dataset of transmitral Doppler traces, with implications for future research design and guidelines.

PubMed

Jones, Siana; Shun-Shin, Matthew J; Cole, Graham D; Sau, Arunashis; March, Katherine; Williams, Suzanne; Kyriacou, Andreas; Hughes, Alun D; Mayet, Jamil; Frenneaux, Michael; Manisty, Charlotte H; Whinnett, Zachary I; Francis, Darrel P

2014-04-01

Full-disclosure study describing Doppler patterns during iterative atrioventricular delay (AVD) optimization of biventricular pacemakers (cardiac resynchronization therapy, CRT). Doppler traces of the first 50 eligible patients undergoing iterative Doppler AVD optimization in the BRAVO trial were examined. Three experienced observers classified conformity to guideline-described patterns. Each observer then selected the optimum AVD on two separate occasions: blinded and unblinded to AVD. Four Doppler E-A patterns occurred: A (always merged, 18% of patients), B (incrementally less fusion at short AVDs, 12%), C (full separation at short AVDs, as described by the guidelines, 28%), and D (always separated, 42%). In Groups A and D (60%), the iterative guidelines therefore cannot specify one single AVD. On the kappa scale (0 = chance alone; 1 = perfect agreement), observer agreement for the ideal AVD in Classes B and C was poor (0.32) and appeared worse in Groups A and D (0.22). Blinding caused the scattering of the AVD selected as optimal to widen (standard deviation rising from 37 to 49 ms, P < 0.001). By blinding 28% of the selected optimum AVDs were ≤60 or ≥200 ms. All 50 Doppler datasets are presented, to support future methodological testing. In most patients, the iterative method does not clearly specify one AVD. In all the patients, agreement on the ideal AVD between skilled observers viewing identical images is poor. The iterative protocol may successfully exclude some extremely unsuitable AVDs, but so might simply accepting factory default. Irreproducibility of the gold standard also prevents alternative physiological optimization methods from being validated honestly.

Research on material removal accuracy analysis and correction of removal function during ion beam figuring

NASA Astrophysics Data System (ADS)

Wu, Weibin; Dai, Yifan; Zhou, Lin; Xu, Mingjin

2016-09-01

Material removal accuracy has a direct impact on the machining precision and efficiency of ion beam figuring. By analyzing the factors suppressing the improvement of material removal accuracy, we conclude that correcting the removal function deviation and reducing the removal material amount during each iterative process could help to improve material removal accuracy. Removal function correcting principle can effectively compensate removal function deviation between actual figuring and simulated processes, while experiments indicate that material removal accuracy decreases with a long machining time, so a small amount of removal material in each iterative process is suggested. However, more clamping and measuring steps will be introduced in this way, which will also generate machining errors and suppress the improvement of material removal accuracy. On this account, a free-measurement iterative process method is put forward to improve material removal accuracy and figuring efficiency by using less measuring and clamping steps. Finally, an experiment on a φ 100-mm Zerodur planar is preformed, which shows that, in similar figuring time, three free-measurement iterative processes could improve the material removal accuracy and the surface error convergence rate by 62.5% and 17.6%, respectively, compared with a single iterative process.

Selection, periodicity and potential function for Highly Iterative Palindrome-1 (HIP1) in cyanobacterial genomes.

PubMed

Xu, Minli; Lawrence, Jeffrey G; Durand, Dannie

2018-03-16

Highly Iterated Palindrome 1 (HIP1, GCGATCGC) is hyper-abundant in most cyanobacterial genomes. In some cyanobacteria, average HIP1 abundance exceeds one motif per gene. Such high abundance suggests a significant role in cyanobacterial biology. However, 20 years of study have not revealed whether HIP1 has a function, much less what that function might be. We show that HIP1 is 15- to 300-fold over-represented in genomes analyzed. More importantly, HIP1 sites are conserved both within and between open reading frames, suggesting that their overabundance is maintained by selection rather than by continual replenishment by neutral processes, such as biased DNA repair. This evidence for selection suggests a functional role for HIP1. No evidence was found to support a functional role as a peptide or RNA motif or a role in the regulation of gene expression. Rather, we demonstrate that the distribution of HIP1 along cyanobacterial chromosomes is significantly periodic, with periods ranging from 10 to 90 kb, consistent in scale with periodicities reported for co-regulated, co-expressed and evolutionarily correlated genes. The periodicity we observe is also comparable in scale to chromosomal interaction domains previously described in other bacteria. In this context, our findings imply HIP1 functions associated with chromosome and nucleoid structure.

Selection, periodicity and potential function for Highly Iterative Palindrome-1 (HIP1) in cyanobacterial genomes

PubMed Central

Xu, Minli; Lawrence, Jeffrey G; Durand, Dannie

2018-01-01

Abstract Highly Iterated Palindrome 1 (HIP1, GCGATCGC) is hyper-abundant in most cyanobacterial genomes. In some cyanobacteria, average HIP1 abundance exceeds one motif per gene. Such high abundance suggests a significant role in cyanobacterial biology. However, 20 years of study have not revealed whether HIP1 has a function, much less what that function might be. We show that HIP1 is 15- to 300-fold over-represented in genomes analyzed. More importantly, HIP1 sites are conserved both within and between open reading frames, suggesting that their overabundance is maintained by selection rather than by continual replenishment by neutral processes, such as biased DNA repair. This evidence for selection suggests a functional role for HIP1. No evidence was found to support a functional role as a peptide or RNA motif or a role in the regulation of gene expression. Rather, we demonstrate that the distribution of HIP1 along cyanobacterial chromosomes is significantly periodic, with periods ranging from 10 to 90 kb, consistent in scale with periodicities reported for co-regulated, co-expressed and evolutionarily correlated genes. The periodicity we observe is also comparable in scale to chromosomal interaction domains previously described in other bacteria. In this context, our findings imply HIP1 functions associated with chromosome and nucleoid structure. PMID:29432573

Accurate Micro-Tool Manufacturing by Iterative Pulsed-Laser Ablation

NASA Astrophysics Data System (ADS)

Warhanek, Maximilian; Mayr, Josef; Dörig, Christian; Wegener, Konrad

2017-12-01

Iterative processing solutions, including multiple cycles of material removal and measurement, are capable of achieving higher geometric accuracy by compensating for most deviations manifesting directly on the workpiece. Remaining error sources are the measurement uncertainty and the repeatability of the material-removal process including clamping errors. Due to the lack of processing forces, process fluids and wear, pulsed-laser ablation has proven high repeatability and can be realized directly on a measuring machine. This work takes advantage of this possibility by implementing an iterative, laser-based correction process for profile deviations registered directly on an optical measurement machine. This way efficient iterative processing is enabled, which is precise, applicable for all tool materials including diamond and eliminates clamping errors. The concept is proven by a prototypical implementation on an industrial tool measurement machine and a nanosecond fibre laser. A number of measurements are performed on both the machine and the processed workpieces. Results show production deviations within 2 μm diameter tolerance.

Automated IMRT planning with regional optimization using planning scripts

PubMed Central

Wong, Eugene; Bzdusek, Karl; Lock, Michael; Chen, Jeff Z.

2013-01-01

Intensity‐modulated radiation therapy (IMRT) has become a standard technique in radiation therapy for treating different types of cancers. Various class solutions have been developed for simple cases (e.g., localized prostate, whole breast) to generate IMRT plans efficiently. However, for more complex cases (e.g., head and neck, pelvic nodes), it can be time‐consuming for a planner to generate optimized IMRT plans. To generate optimal plans in these more complex cases which generally have multiple target volumes and organs at risk, it is often required to have additional IMRT optimization structures such as dose limiting ring structures, adjust beam geometry, select inverse planning objectives and associated weights, and additional IMRT objectives to reduce cold and hot spots in the dose distribution. These parameters are generally manually adjusted with a repeated trial and error approach during the optimization process. To improve IMRT planning efficiency in these more complex cases, an iterative method that incorporates some of these adjustment processes automatically in a planning script is designed, implemented, and validated. In particular, regional optimization has been implemented in an iterative way to reduce various hot or cold spots during the optimization process that begins with defining and automatic segmentation of hot and cold spots, introducing new objectives and their relative weights into inverse planning, and turn this into an iterative process with termination criteria. The method has been applied to three clinical sites: prostate with pelvic nodes, head and neck, and anal canal cancers, and has shown to reduce IMRT planning time significantly for clinical applications with improved plan quality. The IMRT planning scripts have been used for more than 500 clinical cases. PACS numbers: 87.55.D, 87.55.de PMID:23318393

A Model of Supervisor Decision-Making in the Accommodation of Workers with Low Back Pain.

PubMed

Williams-Whitt, Kelly; Kristman, Vicki; Shaw, William S; Soklaridis, Sophie; Reguly, Paula

2016-09-01

Purpose To explore supervisors' perspectives and decision-making processes in the accommodation of back injured workers. Methods Twenty-three semi-structured, in-depth interviews were conducted with supervisors from eleven Canadian organizations about their role in providing job accommodations. Supervisors were identified through an on-line survey and interviews were recorded, transcribed and entered into NVivo software. The initial analyses identified common units of meaning, which were used to develop a coding guide. Interviews were coded, and a model of supervisor decision-making was developed based on the themes, categories and connecting ideas identified in the data. Results The decision-making model includes a process element that is described as iterative "trial and error" decision-making. Medical restrictions are compared to job demands, employee abilities and available alternatives. A feasible modification is identified through brainstorming and then implemented by the supervisor. Resources used for brainstorming include information, supervisor experience and autonomy, and organizational supports. The model also incorporates the experience of accommodation as a job demand that causes strain for the supervisor. Accommodation demands affect the supervisor's attitude, brainstorming and monitoring effort, and communication with returning employees. Resources and demands have a combined effect on accommodation decision complexity, which in turn affects the quality of the accommodation option selected. If the employee is unable to complete the tasks or is reinjured during the accommodation, the decision cycle repeats. More frequent iteration through the trial and error process reduces the likelihood of return to work success. Conclusion A series of propositions is developed to illustrate the relationships among categories in the model. The model and propositions show: (a) the iterative, problem solving nature of the RTW process; (b) decision resources necessary for accommodation planning, and (c) the impact accommodation demands may have on supervisors and RTW quality.

A new iterative triclass thresholding technique in image segmentation.

PubMed

Cai, Hongmin; Yang, Zhong; Cao, Xinhua; Xia, Weiming; Xu, Xiaoyin

2014-03-01

We present a new method in image segmentation that is based on Otsu's method but iteratively searches for subregions of the image for segmentation, instead of treating the full image as a whole region for processing. The iterative method starts with Otsu's threshold and computes the mean values of the two classes as separated by the threshold. Based on the Otsu's threshold and the two mean values, the method separates the image into three classes instead of two as the standard Otsu's method does. The first two classes are determined as the foreground and background and they will not be processed further. The third class is denoted as a to-be-determined (TBD) region that is processed at next iteration. At the succeeding iteration, Otsu's method is applied on the TBD region to calculate a new threshold and two class means and the TBD region is again separated into three classes, namely, foreground, background, and a new TBD region, which by definition is smaller than the previous TBD regions. Then, the new TBD region is processed in the similar manner. The process stops when the Otsu's thresholds calculated between two iterations is less than a preset threshold. Then, all the intermediate foreground and background regions are, respectively, combined to create the final segmentation result. Tests on synthetic and real images showed that the new iterative method can achieve better performance than the standard Otsu's method in many challenging cases, such as identifying weak objects and revealing fine structures of complex objects while the added computational cost is minimal.

On the unfitness of natural selection to explain sexual reproduction, and the difficulties that remain.

PubMed

van Rossum, Joris

2006-01-01

In its essence, the explanatory potential of the theory of natural selection is based on the iterative process of random production and variation, and subsequent non-random, directive selection. It is shown that within this explanatory framework, there is no place for the explanation of sexual reproduction. Thus in Darwinistic literature, sexual reproduction - one of nature's most salient characteristics - is often either assumed or ignored, but not explained. This fundamental and challenging gap within a complete naturalistic understanding of living beings calls for the need of a cybernetic account for sexual reproduction, meaning an understanding of the dynamic and creative potential of living beings to continuously and autonomously produce new organisms with unique and specific constellations.

Batch, design optimization, and DNA sequencing study for continuous 1,3-propanediol production from waste glycerol by a soil-based inoculum.

PubMed

Kanjilal, Baishali; Noshadi, Iman; Bautista, Eddy J; Srivastava, Ranjan; Parnas, Richard S

2015-03-01

1,3-propanediol (1,3-PD) was produced with a robust fermentation process using waste glycerol feedstock from biodiesel production and a soil-based bacterial inoculum. An iterative inoculation method was developed to achieve independence from soil and selectively breed bacterial populations capable of glycerol metabolism to 1,3-PD. The inoculum showed high resistance to impurities in the feedstock. 1,3-PD selectivity and yield in batch fermentations was optimized by appropriate nutrient compositions and pH control. The batch yield of 1,3-PD was maximized to ~0.7 mol/mol for industrial glycerol which was higher than that for pure glycerin. 16S rDNA sequencing results show a systematic selective enrichment of 1,3-PD producing bacteria with iterative inoculation and subsequent process control. A statistical design of experiments was carried out on industrial glycerol batches to optimize conditions, which were used to run two continuous flow stirred-tank reactor (CSTR) experiments over a period of >500 h each. A detailed analysis of steady states at three dilution rates is presented. Enhanced specific 1,3-PD productivity was observed with faster dilution rates due to lower levels of solvent degeneration. 1,3-PD productivity, specific productivity, and yield of 1.1 g/l hr, 1.5 g/g hr, and 0.6 mol/mol of glycerol were obtained at a dilution rate of 0.1 h(-1)which is bettered only by pure strains in pure glycerin feeds.

Intragranular cellular segregation network structure strengthening 316L stainless steel prepared by selective laser melting

NASA Astrophysics Data System (ADS)

Zhong, Yuan; Liu, Leifeng; Wikman, Stefan; Cui, Daqing; Shen, Zhijian

2016-03-01

A feasibility study was performed to fabricate ITER In-Vessel components by Selective Laser Melting (SLM) supported by Fusion for Energy (F4E). Almost fully dense 316L stainless steel (SS316L) components were prepared from gas-atomized powder and with optimized SLM processing parameters. Tensile tests and Charpy-V tests were carried out at 22 °C and 250 °C and the results showed that SLM SS316L fulfill the RCC-MR code. Microstructure characterization reveals the presence of hierarchical macro-, micro- and nano-structures in as-built samples that were very different from SS316L microstructures prepared by other established methods. The formation of a characteristic intragranular cellular segregation network microstructure appears to contribute to the increase of yield strength without losing ductility. Silicon oxide nano-inclusions were formed during the SLM process that generated a micro-hardness fluctuation in the building direction. The combined influence of a cellular microstructure and the nano-inclusions constraints the size of ductile dimples to nano-scale. The crack propagation is hindered by a pinning effect that improves the defect-tolerance of the SLM SS316L. This work proves that it was possible to manufacture SS316L with properties suitable for ITER First Wall panels. Further studies on irradiation properties of SLM SS316L and manufacturing of larger real-size components are needed.

Progress in Development of the ITER Plasma Control System Simulation Platform

NASA Astrophysics Data System (ADS)

Walker, Michael; Humphreys, David; Sammuli, Brian; Ambrosino, Giuseppe; de Tommasi, Gianmaria; Mattei, Massimiliano; Raupp, Gerhard; Treutterer, Wolfgang; Winter, Axel

2017-10-01

We report on progress made and expected uses of the Plasma Control System Simulation Platform (PCSSP), the primary test environment for development of the ITER Plasma Control System (PCS). PCSSP will be used for verification and validation of the ITER PCS Final Design for First Plasma, to be completed in 2020. We discuss the objectives of PCSSP, its overall structure, selected features, application to existing devices, and expected evolution over the lifetime of the ITER PCS. We describe an archiving solution for simulation results, methods for incorporating physics models of the plasma and physical plant (tokamak, actuator, and diagnostic systems) into PCSSP, and defining characteristics of models suitable for a plasma control development environment such as PCSSP. Applications of PCSSP simulation models including resistive plasma equilibrium evolution are demonstrated. PCSSP development supported by ITER Organization under ITER/CTS/6000000037. Resistive evolution code developed under General Atomics' Internal funding. The views and opinions expressed herein do not necessarily reflect those of the ITER Organization.

Iteration and Prototyping in Creating Technical Specifications.

ERIC Educational Resources Information Center

Flynt, John P.

1994-01-01

Claims that the development process for computer software can be greatly aided by the writers of specifications if they employ basic iteration and prototyping techniques. Asserts that computer software configuration management practices provide ready models for iteration and prototyping. (HB)

DART system analysis.

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

Boggs, Paul T.; Althsuler, Alan; Larzelere, Alex R.

2005-08-01

The Design-through-Analysis Realization Team (DART) is chartered with reducing the time Sandia analysts require to complete the engineering analysis process. The DART system analysis team studied the engineering analysis processes employed by analysts in Centers 9100 and 8700 at Sandia to identify opportunities for reducing overall design-through-analysis process time. The team created and implemented a rigorous analysis methodology based on a generic process flow model parameterized by information obtained from analysts. They also collected data from analysis department managers to quantify the problem type and complexity distribution throughout Sandia's analyst community. They then used this information to develop a communitymore » model, which enables a simple characterization of processes that span the analyst community. The results indicate that equal opportunity for reducing analysis process time is available both by reducing the ''once-through'' time required to complete a process step and by reducing the probability of backward iteration. In addition, reducing the rework fraction (i.e., improving the engineering efficiency of subsequent iterations) offers approximately 40% to 80% of the benefit of reducing the ''once-through'' time or iteration probability, depending upon the process step being considered. Further, the results indicate that geometry manipulation and meshing is the largest portion of an analyst's effort, especially for structural problems, and offers significant opportunity for overall time reduction. Iteration loops initiated late in the process are more costly than others because they increase ''inner loop'' iterations. Identifying and correcting problems as early as possible in the process offers significant opportunity for time savings.« less

PARALLELISATION OF THE MODEL-BASED ITERATIVE RECONSTRUCTION ALGORITHM DIRA.

PubMed

Örtenberg, A; Magnusson, M; Sandborg, M; Alm Carlsson, G; Malusek, A

2016-06-01

New paradigms for parallel programming have been devised to simplify software development on multi-core processors and many-core graphical processing units (GPU). Despite their obvious benefits, the parallelisation of existing computer programs is not an easy task. In this work, the use of the Open Multiprocessing (OpenMP) and Open Computing Language (OpenCL) frameworks is considered for the parallelisation of the model-based iterative reconstruction algorithm DIRA with the aim to significantly shorten the code's execution time. Selected routines were parallelised using OpenMP and OpenCL libraries; some routines were converted from MATLAB to C and optimised. Parallelisation of the code with the OpenMP was easy and resulted in an overall speedup of 15 on a 16-core computer. Parallelisation with OpenCL was more difficult owing to differences between the central processing unit and GPU architectures. The resulting speedup was substantially lower than the theoretical peak performance of the GPU; the cause was explained. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Iterative development of visual control systems in a research vivarium.

PubMed

Bassuk, James A; Washington, Ida M

2014-01-01

The goal of this study was to test the hypothesis that reintroduction of Continuous Performance Improvement (CPI) methodology, a lean approach to management at Seattle Children's (Hospital, Research Institute, Foundation), would facilitate engagement of vivarium employees in the development and sustainment of a daily management system and a work-in-process board. Such engagement was implemented through reintroduction of aspects of the Toyota Production System. Iterations of a Work-In-Process Board were generated using Shewhart's Plan-Do-Check-Act process improvement cycle. Specific attention was given to the importance of detecting and preventing errors through assessment of the following 5 levels of quality: Level 1, customer inspects; Level 2, company inspects; Level 3, work unit inspects; Level 4, self-inspection; Level 5, mistake proofing. A functioning iteration of a Mouse Cage Work-In-Process Board was eventually established using electronic data entry, an improvement that increased the quality level from 1 to 3 while reducing wasteful steps, handoffs and queues. A visual workplace was realized via a daily management system that included a Work-In-Process Board, a problem solving board and two Heijunka boards. One Heijunka board tracked cage changing as a function of a biological kanban, which was validated via ammonia levels. A 17% reduction in cage changing frequency provided vivarium staff with additional time to support Institute researchers in their mutual goal of advancing cures for pediatric diseases. Cage washing metrics demonstrated an improvement in the flow continuum in which a traditional batch and queue push system was replaced with a supermarket-type pull system. Staff engagement during the improvement process was challenging and is discussed. The collective data indicate that the hypothesis was found to be true. The reintroduction of CPI into daily work in the vivarium is consistent with the 4P Model of the Toyota Way and selected Principles that guide implementation of the Toyota Production System.

Iterative Development of Visual Control Systems in a Research Vivarium

PubMed Central

Bassuk, James A.; Washington, Ida M.

2014-01-01

The goal of this study was to test the hypothesis that reintroduction of Continuous Performance Improvement (CPI) methodology, a lean approach to management at Seattle Children’s (Hospital, Research Institute, Foundation), would facilitate engagement of vivarium employees in the development and sustainment of a daily management system and a work-in-process board. Such engagement was implemented through reintroduction of aspects of the Toyota Production System. Iterations of a Work-In-Process Board were generated using Shewhart’s Plan-Do-Check-Act process improvement cycle. Specific attention was given to the importance of detecting and preventing errors through assessment of the following 5 levels of quality: Level 1, customer inspects; Level 2, company inspects; Level 3, work unit inspects; Level 4, self-inspection; Level 5, mistake proofing. A functioning iteration of a Mouse Cage Work-In-Process Board was eventually established using electronic data entry, an improvement that increased the quality level from 1 to 3 while reducing wasteful steps, handoffs and queues. A visual workplace was realized via a daily management system that included a Work-In-Process Board, a problem solving board and two Heijunka boards. One Heijunka board tracked cage changing as a function of a biological kanban, which was validated via ammonia levels. A 17% reduction in cage changing frequency provided vivarium staff with additional time to support Institute researchers in their mutual goal of advancing cures for pediatric diseases. Cage washing metrics demonstrated an improvement in the flow continuum in which a traditional batch and queue push system was replaced with a supermarket-type pull system. Staff engagement during the improvement process was challenging and is discussed. The collective data indicate that the hypothesis was found to be true. The reintroduction of CPI into daily work in the vivarium is consistent with the 4P Model of the Toyota Way and selected Principles that guide implementation of the Toyota Production System. PMID:24736460

Fusion materials: Technical evaluation of the technology of vandium alloys for use as blanket structural materials in fusion power systems

NASA Astrophysics Data System (ADS)

1993-08-01

The Committee's evaluation of vanadium alloys as a structural material for fusion reactors was constrained by limited data and time. The design of the International Thermonuclear Experimental Reactor is still in the concept stage, so meaningful design requirements were not available. The data on the effect of environment and irradiation on vanadium alloys were sparse, and interpolation of these data were made to select the V-5Cr-5Ti alloy. With an aggressive, fully funded program it is possible to qualify a vanadium alloy as the principal structural material for the ITER blanket in the available 5 to 8-year window. However, the data base for V-5Cr-5Ti is limited and will require an extensive development and test program. Because of the chemical reactivity of vanadium the alloy will be less tolerant of system failures, accidents, and off-normal events than most other candidate blanket structural materials and will require more careful handling during fabrication of hardware. Because of the cost of the material more stringent requirements on processes, and minimal historical working experience, it will cost an order of magnitude to qualify a vanadium alloy for ITER blanket structures than other candidate materials. The use of vanadium is difficult and uncertain; therefore, other options should be explored more thoroughly before a final selection of vanadium is confirmed. The Committee views the risk as being too high to rely solely on vanadium alloys. In viewing the state and nature of the design of the ITER blanket as presented to the Committee, it is obvious that there is a need to move toward integrating fabrication, welding, and materials engineers into the ITER design team. If the vanadium alloy option is to be pursued, a large program needs to be started immediately. The commitment of funding and other resources needs to be firm and consistent with a realistic program plan.

Design for disassembly and sustainability assessment to support aircraft end-of-life treatment

NASA Astrophysics Data System (ADS)

Savaria, Christian

Gas turbine engine design is a multidisciplinary and iterative process. Many design iterations are necessary to address the challenges among the disciplines. In the creation of a new engine architecture, the design time is crucial in capturing new business opportunities. At the detail design phase, it was proven very difficult to correct an unsatisfactory design. To overcome this difficulty, the concept of Multi-Disciplinary Optimization (MDO) at the preliminary design phase (Preliminary MDO or PMDO) is used allowing more freedom to perform changes in the design. PMDO also reduces the design time at the preliminary design phase. The concept of PMDO was used was used to create parametric models, and new correlations for high pressure gas turbine housing and shroud segments towards a new design process. First, dedicated parametric models were created because of their reusability and versatility. Their ease of use compared to non-parameterized models allows more design iterations thus reduces set up and design time. Second, geometry correlations were created to minimize the number of parameters used in turbine housing and shroud segment design. Since the turbine housing and the shroud segment geometries are required in tip clearance analyses, care was taken as to not oversimplify the parametric formulation. In addition, a user interface was developed to interact with the parametric models and improve the design time. Third, the cooling flow predictions require many engine parameters (i.e. geometric and performance parameters and air properties) and a reference shroud segments. A second correlation study was conducted to minimize the number of engine parameters required in the cooling flow predictions and to facilitate the selection of a reference shroud segment. Finally, the parametric models, the geometry correlations, and the user interface resulted in a time saving of 50% and an increase in accuracy of 56% in the new design system compared to the existing design system. Also, regarding the cooling flow correlations, the number of engine parameters was reduced by a factor of 6 to create a simplified prediction model and hence a faster shroud segment selection process. None

Use of direct and iterative solvers for estimation of SNP effects in genome-wide selection

PubMed Central

2010-01-01

The aim of this study was to compare iterative and direct solvers for estimation of marker effects in genomic selection. One iterative and two direct methods were used: Gauss-Seidel with Residual Update, Cholesky Decomposition and Gentleman-Givens rotations. For resembling different scenarios with respect to number of markers and of genotyped animals, a simulated data set divided into 25 subsets was used. Number of markers ranged from 1,200 to 5,925 and number of animals ranged from 1,200 to 5,865. Methods were also applied to real data comprising 3081 individuals genotyped for 45181 SNPs. Results from simulated data showed that the iterative solver was substantially faster than direct methods for larger numbers of markers. Use of a direct solver may allow for computing (co)variances of SNP effects. When applied to real data, performance of the iterative method varied substantially, depending on the level of ill-conditioning of the coefficient matrix. From results with real data, Gentleman-Givens rotations would be the method of choice in this particular application as it provided an exact solution within a fairly reasonable time frame (less than two hours). It would indeed be the preferred method whenever computer resources allow its use. PMID:21637627

Airbreathing engine selection criteria for SSTO propulsion system

NASA Astrophysics Data System (ADS)

Ohkami, Yoshiaki; Maita, Masataka

1995-02-01

This paper presents airbreathing engine selection criteria to be applied to the propulsion system of a Single Stage To Orbit (SSTO). To establish the criteria, a relation among three major parameters, i.e., delta-V capability, weight penalty, and effective specific impulse of the engine subsystem, is derived as compared to these parameters of the LH2/LOX rocket engine. The effective specific impulse is a function of the engine I(sub sp) and vehicle thrust-to-drag ratio which is approximated by a function of the vehicle velocity. The weight penalty includes the engine dry weight, cooling subsystem weight. The delta-V capability is defined by the velocity region starting from the minimum operating velocity up to the maximum velocity. The vehicle feasibility is investigated in terms of the structural and propellant weights, which requires an iteration process adjusting the system parameters. The system parameters are computed by iteration based on the Newton-Raphson method. It has been concluded that performance in the higher velocity region is extremely important so that the airbreathing engines are required to operate beyond the velocity equivalent to the rocket engine exhaust velocity (approximately 4500 m/s).

Slaying the Great Green Dragon: Learning and Modelling Iterable Ordered Optional Adjuncts

ERIC Educational Resources Information Center

Fowlie, Meaghan

2017-01-01

Adjuncts and arguments exhibit different syntactic behaviours, but modelling this difference in minimalist syntax is challenging: on the one hand, adjuncts differ from arguments in that they are optional, transparent, and iterable, but on the other hand they are often strictly ordered, reflecting the kind of strict selection seen in argument…

Computed inverse resonance imaging for magnetic susceptibility map reconstruction.

PubMed

Chen, Zikuan; Calhoun, Vince

2012-01-01

This article reports a computed inverse magnetic resonance imaging (CIMRI) model for reconstructing the magnetic susceptibility source from MRI data using a 2-step computational approach. The forward T2*-weighted MRI (T2*MRI) process is broken down into 2 steps: (1) from magnetic susceptibility source to field map establishment via magnetization in the main field and (2) from field map to MR image formation by intravoxel dephasing average. The proposed CIMRI model includes 2 inverse steps to reverse the T2*MRI procedure: field map calculation from MR-phase image and susceptibility source calculation from the field map. The inverse step from field map to susceptibility map is a 3-dimensional ill-posed deconvolution problem, which can be solved with 3 kinds of approaches: the Tikhonov-regularized matrix inverse, inverse filtering with a truncated filter, and total variation (TV) iteration. By numerical simulation, we validate the CIMRI model by comparing the reconstructed susceptibility maps for a predefined susceptibility source. Numerical simulations of CIMRI show that the split Bregman TV iteration solver can reconstruct the susceptibility map from an MR-phase image with high fidelity (spatial correlation ≈ 0.99). The split Bregman TV iteration solver includes noise reduction, edge preservation, and image energy conservation. For applications to brain susceptibility reconstruction, it is important to calibrate the TV iteration program by selecting suitable values of the regularization parameter. The proposed CIMRI model can reconstruct the magnetic susceptibility source of T2*MRI by 2 computational steps: calculating the field map from the phase image and reconstructing the susceptibility map from the field map. The crux of CIMRI lies in an ill-posed 3-dimensional deconvolution problem, which can be effectively solved by the split Bregman TV iteration algorithm.

Computed inverse MRI for magnetic susceptibility map reconstruction

PubMed Central

Chen, Zikuan; Calhoun, Vince

2015-01-01

Objective This paper reports on a computed inverse magnetic resonance imaging (CIMRI) model for reconstructing the magnetic susceptibility source from MRI data using a two-step computational approach. Methods The forward T2*-weighted MRI (T2*MRI) process is decomposed into two steps: 1) from magnetic susceptibility source to fieldmap establishment via magnetization in a main field, and 2) from fieldmap to MR image formation by intravoxel dephasing average. The proposed CIMRI model includes two inverse steps to reverse the T2*MRI procedure: fieldmap calculation from MR phase image and susceptibility source calculation from the fieldmap. The inverse step from fieldmap to susceptibility map is a 3D ill-posed deconvolution problem, which can be solved by three kinds of approaches: Tikhonov-regularized matrix inverse, inverse filtering with a truncated filter, and total variation (TV) iteration. By numerical simulation, we validate the CIMRI model by comparing the reconstructed susceptibility maps for a predefined susceptibility source. Results Numerical simulations of CIMRI show that the split Bregman TV iteration solver can reconstruct the susceptibility map from a MR phase image with high fidelity (spatial correlation≈0.99). The split Bregman TV iteration solver includes noise reduction, edge preservation, and image energy conservation. For applications to brain susceptibility reconstruction, it is important to calibrate the TV iteration program by selecting suitable values of the regularization parameter. Conclusions The proposed CIMRI model can reconstruct the magnetic susceptibility source of T2*MRI by two computational steps: calculating the fieldmap from the phase image and reconstructing the susceptibility map from the fieldmap. The crux of CIMRI lies in an ill-posed 3D deconvolution problem, which can be effectively solved by the split Bregman TV iteration algorithm. PMID:22446372

Analysis of the iteratively regularized Gauss-Newton method under a heuristic rule

NASA Astrophysics Data System (ADS)

Jin, Qinian; Wang, Wei

2018-03-01

The iteratively regularized Gauss-Newton method is one of the most prominent regularization methods for solving nonlinear ill-posed inverse problems when the data is corrupted by noise. In order to produce a useful approximate solution, this iterative method should be terminated properly. The existing a priori and a posteriori stopping rules require accurate information on the noise level, which may not be available or reliable in practical applications. In this paper we propose a heuristic selection rule for this regularization method, which requires no information on the noise level. By imposing certain conditions on the noise, we derive a posteriori error estimates on the approximate solutions under various source conditions. Furthermore, we establish a convergence result without using any source condition. Numerical results are presented to illustrate the performance of our heuristic selection rule.

Rate-Compatible Protograph LDPC Codes

NASA Technical Reports Server (NTRS)

Nguyen, Thuy V. (Inventor); Nosratinia, Aria (Inventor); Divsalar, Dariush (Inventor)

2014-01-01

Digital communication coding methods resulting in rate-compatible low density parity-check (LDPC) codes built from protographs. Described digital coding methods start with a desired code rate and a selection of the numbers of variable nodes and check nodes to be used in the protograph. Constraints are set to satisfy a linear minimum distance growth property for the protograph. All possible edges in the graph are searched for the minimum iterative decoding threshold and the protograph with the lowest iterative decoding threshold is selected. Protographs designed in this manner are used in decode and forward relay channels.

A three-layer model of natural image statistics.

PubMed

Gutmann, Michael U; Hyvärinen, Aapo

2013-11-01

An important property of visual systems is to be simultaneously both selective to specific patterns found in the sensory input and invariant to possible variations. Selectivity and invariance (tolerance) are opposing requirements. It has been suggested that they could be joined by iterating a sequence of elementary selectivity and tolerance computations. It is, however, unknown what should be selected or tolerated at each level of the hierarchy. We approach this issue by learning the computations from natural images. We propose and estimate a probabilistic model of natural images that consists of three processing layers. Two natural image data sets are considered: image patches, and complete visual scenes downsampled to the size of small patches. For both data sets, we find that in the first two layers, simple and complex cell-like computations are performed. In the third layer, we mainly find selectivity to longer contours; for patch data, we further find some selectivity to texture, while for the downsampled complete scenes, some selectivity to curvature is observed. Copyright © 2013 Elsevier Ltd. All rights reserved.

A novel variable selection approach that iteratively optimizes variable space using weighted binary matrix sampling.

PubMed

Deng, Bai-chuan; Yun, Yong-huan; Liang, Yi-zeng; Yi, Lun-zhao

2014-10-07

In this study, a new optimization algorithm called the Variable Iterative Space Shrinkage Approach (VISSA) that is based on the idea of model population analysis (MPA) is proposed for variable selection. Unlike most of the existing optimization methods for variable selection, VISSA statistically evaluates the performance of variable space in each step of optimization. Weighted binary matrix sampling (WBMS) is proposed to generate sub-models that span the variable subspace. Two rules are highlighted during the optimization procedure. First, the variable space shrinks in each step. Second, the new variable space outperforms the previous one. The second rule, which is rarely satisfied in most of the existing methods, is the core of the VISSA strategy. Compared with some promising variable selection methods such as competitive adaptive reweighted sampling (CARS), Monte Carlo uninformative variable elimination (MCUVE) and iteratively retaining informative variables (IRIV), VISSA showed better prediction ability for the calibration of NIR data. In addition, VISSA is user-friendly; only a few insensitive parameters are needed, and the program terminates automatically without any additional conditions. The Matlab codes for implementing VISSA are freely available on the website: https://sourceforge.net/projects/multivariateanalysis/files/VISSA/.

Assessment and selection of materials for ITER in-vessel components

NASA Astrophysics Data System (ADS)

Kalinin, G.; Barabash, V.; Cardella, A.; Dietz, J.; Ioki, K.; Matera, R.; Santoro, R. T.; Tivey, R.; ITER Home Teams

2000-12-01

During the international thermonuclear experimental reactor (ITER) engineering design activities (EDA) significant progress has been made in the selection of materials for the in-vessel components of the reactor. This progress is a result of the worldwide collaboration of material scientists and industries which focused their effort on the optimisation of material and component manufacturing and on the investigation of the most critical material properties. Austenitic stainless steels 316L(N)-IG and 316L, nickel-based alloys Inconel 718 and Inconel 625, Ti-6Al-4V alloy and two copper alloys, CuCrZr-IG and CuAl25-IG, have been proposed as reference structural materials, and ferritic steel 430, and austenitic steel 304B7 with the addition of boron have been selected for some specific parts of the ITER in-vessel components. Beryllium, tungsten and carbon fibre composites are considered as plasma facing armour materials. The data base on the properties of all these materials is critically assessed and briefly reviewed in this paper together with the justification of the material selection (e.g., effect of neutron irradiation on the mechanical properties of materials, effect of manufacturing cycle, etc.).

Strong Convergence of Iteration Processes for Infinite Family of General Extended Mappings

NASA Astrophysics Data System (ADS)

Hussein Maibed, Zena

2018-05-01

The aim of this paper, we introduce a concept of general extended mapping which is independent of nonexpansive mapping and give an iteration process of families of quasi nonexpansive and of general extended mappings. Also, the existence of common fixed point are studied for these process in the Hilbert spaces.

A novel channel selection method for optimal classification in different motor imagery BCI paradigms.

PubMed

Shan, Haijun; Xu, Haojie; Zhu, Shanan; He, Bin

2015-10-21

For sensorimotor rhythms based brain-computer interface (BCI) systems, classification of different motor imageries (MIs) remains a crucial problem. An important aspect is how many scalp electrodes (channels) should be used in order to reach optimal performance classifying motor imaginations. While the previous researches on channel selection mainly focus on MI tasks paradigms without feedback, the present work aims to investigate the optimal channel selection in MI tasks paradigms with real-time feedback (two-class control and four-class control paradigms). In the present study, three datasets respectively recorded from MI tasks experiment, two-class control and four-class control experiments were analyzed offline. Multiple frequency-spatial synthesized features were comprehensively extracted from every channel, and a new enhanced method IterRelCen was proposed to perform channel selection. IterRelCen was constructed based on Relief algorithm, but was enhanced from two aspects: change of target sample selection strategy and adoption of the idea of iterative computation, and thus performed more robust in feature selection. Finally, a multiclass support vector machine was applied as the classifier. The least number of channels that yield the best classification accuracy were considered as the optimal channels. One-way ANOVA was employed to test the significance of performance improvement among using optimal channels, all the channels and three typical MI channels (C3, C4, Cz). The results show that the proposed method outperformed other channel selection methods by achieving average classification accuracies of 85.2, 94.1, and 83.2 % for the three datasets, respectively. Moreover, the channel selection results reveal that the average numbers of optimal channels were significantly different among the three MI paradigms. It is demonstrated that IterRelCen has a strong ability for feature selection. In addition, the results have shown that the numbers of optimal channels in the three different motor imagery BCI paradigms are distinct. From a MI task paradigm, to a two-class control paradigm, and to a four-class control paradigm, the number of required channels for optimizing the classification accuracy increased. These findings may provide useful information to optimize EEG based BCI systems, and further improve the performance of noninvasive BCI.

US NDC Modernization Iteration E2 Prototyping Report: User Interface Framework

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

Lewis, Jennifer E.; Palmer, Melanie A.; Vickers, James Wallace

2014-12-01

During the second iteration of the US NDC Modernization Elaboration phase (E2), the SNL US NDC Modernization project team completed follow-on Rich Client Platform (RCP) exploratory prototyping related to the User Interface Framework (UIF). The team also developed a survey of browser-based User Interface solutions and completed exploratory prototyping for selected solutions. This report presents the results of the browser-based UI survey, summarizes the E2 browser-based UI and RCP prototyping work, and outlines a path forward for the third iteration of the Elaboration phase (E3).

Solving the multiple-set split equality common fixed-point problem of firmly quasi-nonexpansive operators.

PubMed

Zhao, Jing; Zong, Haili

2018-01-01

In this paper, we propose parallel and cyclic iterative algorithms for solving the multiple-set split equality common fixed-point problem of firmly quasi-nonexpansive operators. We also combine the process of cyclic and parallel iterative methods and propose two mixed iterative algorithms. Our several algorithms do not need any prior information about the operator norms. Under mild assumptions, we prove weak convergence of the proposed iterative sequences in Hilbert spaces. As applications, we obtain several iterative algorithms to solve the multiple-set split equality problem.

Language Evolution by Iterated Learning with Bayesian Agents

ERIC Educational Resources Information Center

Griffiths, Thomas L.; Kalish, Michael L.

2007-01-01

Languages are transmitted from person to person and generation to generation via a process of iterated learning: people learn a language from other people who once learned that language themselves. We analyze the consequences of iterated learning for learning algorithms based on the principles of Bayesian inference, assuming that learners compute…

Iterative Neighbour-Information Gathering for Ranking Nodes in Complex Networks

NASA Astrophysics Data System (ADS)

Xu, Shuang; Wang, Pei; Lü, Jinhu

2017-01-01

Designing node influence ranking algorithms can provide insights into network dynamics, functions and structures. Increasingly evidences reveal that node’s spreading ability largely depends on its neighbours. We introduce an iterative neighbourinformation gathering (Ing) process with three parameters, including a transformation matrix, a priori information and an iteration time. The Ing process iteratively combines priori information from neighbours via the transformation matrix, and iteratively assigns an Ing score to each node to evaluate its influence. The algorithm appropriates for any types of networks, and includes some traditional centralities as special cases, such as degree, semi-local, LeaderRank. The Ing process converges in strongly connected networks with speed relying on the first two largest eigenvalues of the transformation matrix. Interestingly, the eigenvector centrality corresponds to a limit case of the algorithm. By comparing with eight renowned centralities, simulations of susceptible-infected-removed (SIR) model on real-world networks reveal that the Ing can offer more exact rankings, even without a priori information. We also observe that an optimal iteration time is always in existence to realize best characterizing of node influence. The proposed algorithms bridge the gaps among some existing measures, and may have potential applications in infectious disease control, designing of optimal information spreading strategies.

Development and Evaluation of an Intuitive Operations Planning Process

DTIC Science & Technology

2006-03-01

designed to be iterative and also prescribes the way in which iterations should occur. On the other hand, participants’ perceived level of trust and...16 4. DESIGN AND METHOD OF THE EXPERIMENTAL EVALUATION OF THE INTUITIVE PLANNING PROCESS...20 4.1.3 Design

A Universal Tare Load Prediction Algorithm for Strain-Gage Balance Calibration Data Analysis

NASA Technical Reports Server (NTRS)

Ulbrich, N.

2011-01-01

An algorithm is discussed that may be used to estimate tare loads of wind tunnel strain-gage balance calibration data. The algorithm was originally developed by R. Galway of IAR/NRC Canada and has been described in the literature for the iterative analysis technique. Basic ideas of Galway's algorithm, however, are universally applicable and work for both the iterative and the non-iterative analysis technique. A recent modification of Galway's algorithm is presented that improves the convergence behavior of the tare load prediction process if it is used in combination with the non-iterative analysis technique. The modified algorithm allows an analyst to use an alternate method for the calculation of intermediate non-linear tare load estimates whenever Galway's original approach does not lead to a convergence of the tare load iterations. It is also shown in detail how Galway's algorithm may be applied to the non-iterative analysis technique. Hand load data from the calibration of a six-component force balance is used to illustrate the application of the original and modified tare load prediction method. During the analysis of the data both the iterative and the non-iterative analysis technique were applied. Overall, predicted tare loads for combinations of the two tare load prediction methods and the two balance data analysis techniques showed excellent agreement as long as the tare load iterations converged. The modified algorithm, however, appears to have an advantage over the original algorithm when absolute voltage measurements of gage outputs are processed using the non-iterative analysis technique. In these situations only the modified algorithm converged because it uses an exact solution of the intermediate non-linear tare load estimate for the tare load iteration.

A methodology for finding the optimal iteration number of the SIRT algorithm for quantitative Electron Tomography.

PubMed

Okariz, Ana; Guraya, Teresa; Iturrondobeitia, Maider; Ibarretxe, Julen

2017-02-01

The SIRT (Simultaneous Iterative Reconstruction Technique) algorithm is commonly used in Electron Tomography to calculate the original volume of the sample from noisy images, but the results provided by this iterative procedure are strongly dependent on the specific implementation of the algorithm, as well as on the number of iterations employed for the reconstruction. In this work, a methodology for selecting the iteration number of the SIRT reconstruction that provides the most accurate segmentation is proposed. The methodology is based on the statistical analysis of the intensity profiles at the edge of the objects in the reconstructed volume. A phantom which resembles a a carbon black aggregate has been created to validate the methodology and the SIRT implementations of two free software packages (TOMOJ and TOMO3D) have been used. Copyright © 2016 Elsevier B.V. All rights reserved.

Regularization Parameter Selection for Nonlinear Iterative Image Restoration and MRI Reconstruction Using GCV and SURE-Based Methods

PubMed Central

Ramani, Sathish; Liu, Zhihao; Rosen, Jeffrey; Nielsen, Jon-Fredrik; Fessler, Jeffrey A.

2012-01-01

Regularized iterative reconstruction algorithms for imaging inverse problems require selection of appropriate regularization parameter values. We focus on the challenging problem of tuning regularization parameters for nonlinear algorithms for the case of additive (possibly complex) Gaussian noise. Generalized cross-validation (GCV) and (weighted) mean-squared error (MSE) approaches (based on Stein's Unbiased Risk Estimate— SURE) need the Jacobian matrix of the nonlinear reconstruction operator (representative of the iterative algorithm) with respect to the data. We derive the desired Jacobian matrix for two types of nonlinear iterative algorithms: a fast variant of the standard iterative reweighted least-squares method and the contemporary split-Bregman algorithm, both of which can accommodate a wide variety of analysis- and synthesis-type regularizers. The proposed approach iteratively computes two weighted SURE-type measures: Predicted-SURE and Projected-SURE (that require knowledge of noise variance σ2), and GCV (that does not need σ2) for these algorithms. We apply the methods to image restoration and to magnetic resonance image (MRI) reconstruction using total variation (TV) and an analysis-type ℓ1-regularization. We demonstrate through simulations and experiments with real data that minimizing Predicted-SURE and Projected-SURE consistently lead to near-MSE-optimal reconstructions. We also observed that minimizing GCV yields reconstruction results that are near-MSE-optimal for image restoration and slightly sub-optimal for MRI. Theoretical derivations in this work related to Jacobian matrix evaluations can be extended, in principle, to other types of regularizers and reconstruction algorithms. PMID:22531764

Calibration and compensation method of three-axis geomagnetic sensor based on pre-processing total least square iteration

NASA Astrophysics Data System (ADS)

Zhou, Y.; Zhang, X.; Xiao, W.

2018-04-01

As the geomagnetic sensor is susceptible to interference, a pre-processing total least square iteration method is proposed for calibration compensation. Firstly, the error model of the geomagnetic sensor is analyzed and the correction model is proposed, then the characteristics of the model are analyzed and converted into nine parameters. The geomagnetic data is processed by Hilbert transform (HHT) to improve the signal-to-noise ratio, and the nine parameters are calculated by using the combination of Newton iteration method and the least squares estimation method. The sifter algorithm is used to filter the initial value of the iteration to ensure that the initial error is as small as possible. The experimental results show that this method does not need additional equipment and devices, can continuously update the calibration parameters, and better than the two-step estimation method, it can compensate geomagnetic sensor error well.

Solving coupled groundwater flow systems using a Jacobian Free Newton Krylov method

NASA Astrophysics Data System (ADS)

Mehl, S.

2012-12-01

Jacobian Free Newton Kyrlov (JFNK) methods can have several advantages for simulating coupled groundwater flow processes versus conventional methods. Conventional methods are defined here as those based on an iterative coupling (rather than a direct coupling) and/or that use Picard iteration rather than Newton iteration. In an iterative coupling, the systems are solved separately, coupling information is updated and exchanged between the systems, and the systems are re-solved, etc., until convergence is achieved. Trusted simulators, such as Modflow, are based on these conventional methods of coupling and work well in many cases. An advantage of the JFNK method is that it only requires calculation of the residual vector of the system of equations and thus can make use of existing simulators regardless of how the equations are formulated. This opens the possibility of coupling different process models via augmentation of a residual vector by each separate process, which often requires substantially fewer changes to the existing source code than if the processes were directly coupled. However, appropriate perturbation sizes need to be determined for accurate approximations of the Frechet derivative, which is not always straightforward. Furthermore, preconditioning is necessary for reasonable convergence of the linear solution required at each Kyrlov iteration. Existing preconditioners can be used and applied separately to each process which maximizes use of existing code and robust preconditioners. In this work, iteratively coupled parent-child local grid refinement models of groundwater flow and groundwater flow models with nonlinear exchanges to streams are used to demonstrate the utility of the JFNK approach for Modflow models. Use of incomplete Cholesky preconditioners with various levels of fill are examined on a suite of nonlinear and linear models to analyze the effect of the preconditioner. Comparisons of convergence and computer simulation time are made using conventional iteratively coupled methods and those based on Picard iteration to those formulated with JFNK to gain insights on the types of nonlinearities and system features that make one approach advantageous. Results indicate that nonlinearities associated with stream/aquifer exchanges are more problematic than those resulting from unconfined flow.

Nested Krylov methods and preserving the orthogonality

NASA Technical Reports Server (NTRS)

Desturler, Eric; Fokkema, Diederik R.

1993-01-01

Recently the GMRESR inner-outer iteraction scheme for the solution of linear systems of equations was proposed by Van der Vorst and Vuik. Similar methods have been proposed by Axelsson and Vassilevski and Saad (FGMRES). The outer iteration is GCR, which minimizes the residual over a given set of direction vectors. The inner iteration is GMRES, which at each step computes a new direction vector by approximately solving the residual equation. However, the optimality of the approximation over the space of outer search directions is ignored in the inner GMRES iteration. This leads to suboptimal corrections to the solution in the outer iteration, as components of the outer iteration directions may reenter in the inner iteration process. Therefore we propose to preserve the orthogonality relations of GCR in the inner GMRES iteration. This gives optimal corrections; however, it involves working with a singular, non-symmetric operator. We will discuss some important properties, and we will show by experiments that, in terms of matrix vector products, this modification (almost) always leads to better convergence. However, because we do more orthogonalizations, it does not always give an improved performance in CPU-time. Furthermore, we will discuss efficient implementations as well as the truncation possibilities of the outer GCR process. The experimental results indicate that for such methods it is advantageous to preserve the orthogonality in the inner iteration. Of course we can also use iteration schemes other than GMRES as the inner method; methods with short recurrences like GICGSTAB are of interest.

A multi-frequency iterative imaging method for discontinuous inverse medium problem

NASA Astrophysics Data System (ADS)

Zhang, Lei; Feng, Lixin

2018-06-01

The inverse medium problem with discontinuous refractive index is a kind of challenging inverse problem. We employ the primal dual theory and fast solution of integral equations, and propose a new iterative imaging method. The selection criteria of regularization parameter is given by the method of generalized cross-validation. Based on multi-frequency measurements of the scattered field, a recursive linearization algorithm has been presented with respect to the frequency from low to high. We also discuss the initial guess selection strategy by semi-analytical approaches. Numerical experiments are presented to show the effectiveness of the proposed method.

Not so Complex: Iteration in the Complex Plane

ERIC Educational Resources Information Center

O'Dell, Robin S.

2014-01-01

The simple process of iteration can produce complex and beautiful figures. In this article, Robin O'Dell presents a set of tasks requiring students to use the geometric interpretation of complex number multiplication to construct linear iteration rules. When the outputs are plotted in the complex plane, the graphs trace pleasing designs…

Developing Conceptual Understanding and Procedural Skill in Mathematics: An Iterative Process.

ERIC Educational Resources Information Center

Rittle-Johnson, Bethany; Siegler, Robert S.; Alibali, Martha Wagner

2001-01-01

Proposes that conceptual and procedural knowledge develop in an iterative fashion and improved problem representation is one mechanism underlying the relations between them. Two experiments were conducted with 5th and 6th grade students learning about decimal fractions. Results indicate conceptual and procedural knowledge do develop, iteratively,…

Finite Volume Element (FVE) discretization and multilevel solution of the axisymmetric heat equation

NASA Astrophysics Data System (ADS)

Litaker, Eric T.

1994-12-01

The axisymmetric heat equation, resulting from a point-source of heat applied to a metal block, is solved numerically; both iterative and multilevel solutions are computed in order to compare the two processes. The continuum problem is discretized in two stages: finite differences are used to discretize the time derivatives, resulting is a fully implicit backward time-stepping scheme, and the Finite Volume Element (FVE) method is used to discretize the spatial derivatives. The application of the FVE method to a problem in cylindrical coordinates is new, and results in stencils which are analyzed extensively. Several iteration schemes are considered, including both Jacobi and Gauss-Seidel; a thorough analysis of these schemes is done, using both the spectral radii of the iteration matrices and local mode analysis. Using this discretization, a Gauss-Seidel relaxation scheme is used to solve the heat equation iteratively. A multilevel solution process is then constructed, including the development of intergrid transfer and coarse grid operators. Local mode analysis is performed on the components of the amplification matrix, resulting in the two-level convergence factors for various combinations of the operators. A multilevel solution process is implemented by using multigrid V-cycles; the iterative and multilevel results are compared and discussed in detail. The computational savings resulting from the multilevel process are then discussed.

A machine learning heuristic to identify biologically relevant and minimal biomarker panels from omics data

PubMed Central

2015-01-01

Background Investigations into novel biomarkers using omics techniques generate large amounts of data. Due to their size and numbers of attributes, these data are suitable for analysis with machine learning methods. A key component of typical machine learning pipelines for omics data is feature selection, which is used to reduce the raw high-dimensional data into a tractable number of features. Feature selection needs to balance the objective of using as few features as possible, while maintaining high predictive power. This balance is crucial when the goal of data analysis is the identification of highly accurate but small panels of biomarkers with potential clinical utility. In this paper we propose a heuristic for the selection of very small feature subsets, via an iterative feature elimination process that is guided by rule-based machine learning, called RGIFE (Rule-guided Iterative Feature Elimination). We use this heuristic to identify putative biomarkers of osteoarthritis (OA), articular cartilage degradation and synovial inflammation, using both proteomic and transcriptomic datasets. Results and discussion Our RGIFE heuristic increased the classification accuracies achieved for all datasets when no feature selection is used, and performed well in a comparison with other feature selection methods. Using this method the datasets were reduced to a smaller number of genes or proteins, including those known to be relevant to OA, cartilage degradation and joint inflammation. The results have shown the RGIFE feature reduction method to be suitable for analysing both proteomic and transcriptomics data. Methods that generate large ‘omics’ datasets are increasingly being used in the area of rheumatology. Conclusions Feature reduction methods are advantageous for the analysis of omics data in the field of rheumatology, as the applications of such techniques are likely to result in improvements in diagnosis, treatment and drug discovery. PMID:25923811

An Atlas of Peroxiredoxins Created Using an Active Site Profile-Based Approach to Functionally Relevant Clustering of Proteins.

PubMed

Harper, Angela F; Leuthaeuser, Janelle B; Babbitt, Patricia C; Morris, John H; Ferrin, Thomas E; Poole, Leslie B; Fetrow, Jacquelyn S

2017-02-01

Peroxiredoxins (Prxs or Prdxs) are a large protein superfamily of antioxidant enzymes that rapidly detoxify damaging peroxides and/or affect signal transduction and, thus, have roles in proliferation, differentiation, and apoptosis. Prx superfamily members are widespread across phylogeny and multiple methods have been developed to classify them. Here we present an updated atlas of the Prx superfamily identified using a novel method called MISST (Multi-level Iterative Sequence Searching Technique). MISST is an iterative search process developed to be both agglomerative, to add sequences containing similar functional site features, and divisive, to split groups when functional site features suggest distinct functionally-relevant clusters. Superfamily members need not be identified initially-MISST begins with a minimal representative set of known structures and searches GenBank iteratively. Further, the method's novelty lies in the manner in which isofunctional groups are selected; rather than use a single or shifting threshold to identify clusters, the groups are deemed isofunctional when they pass a self-identification criterion, such that the group identifies itself and nothing else in a search of GenBank. The method was preliminarily validated on the Prxs, as the Prxs presented challenges of both agglomeration and division. For example, previous sequence analysis clustered the Prx functional families Prx1 and Prx6 into one group. Subsequent expert analysis clearly identified Prx6 as a distinct functionally relevant group. The MISST process distinguishes these two closely related, though functionally distinct, families. Through MISST search iterations, over 38,000 Prx sequences were identified, which the method divided into six isofunctional clusters, consistent with previous expert analysis. The results represent the most complete computational functional analysis of proteins comprising the Prx superfamily. The feasibility of this novel method is demonstrated by the Prx superfamily results, laying the foundation for potential functionally relevant clustering of the universe of protein sequences.

An Atlas of Peroxiredoxins Created Using an Active Site Profile-Based Approach to Functionally Relevant Clustering of Proteins

PubMed Central

Babbitt, Patricia C.; Ferrin, Thomas E.

2017-01-01

Peroxiredoxins (Prxs or Prdxs) are a large protein superfamily of antioxidant enzymes that rapidly detoxify damaging peroxides and/or affect signal transduction and, thus, have roles in proliferation, differentiation, and apoptosis. Prx superfamily members are widespread across phylogeny and multiple methods have been developed to classify them. Here we present an updated atlas of the Prx superfamily identified using a novel method called MISST (Multi-level Iterative Sequence Searching Technique). MISST is an iterative search process developed to be both agglomerative, to add sequences containing similar functional site features, and divisive, to split groups when functional site features suggest distinct functionally-relevant clusters. Superfamily members need not be identified initially—MISST begins with a minimal representative set of known structures and searches GenBank iteratively. Further, the method’s novelty lies in the manner in which isofunctional groups are selected; rather than use a single or shifting threshold to identify clusters, the groups are deemed isofunctional when they pass a self-identification criterion, such that the group identifies itself and nothing else in a search of GenBank. The method was preliminarily validated on the Prxs, as the Prxs presented challenges of both agglomeration and division. For example, previous sequence analysis clustered the Prx functional families Prx1 and Prx6 into one group. Subsequent expert analysis clearly identified Prx6 as a distinct functionally relevant group. The MISST process distinguishes these two closely related, though functionally distinct, families. Through MISST search iterations, over 38,000 Prx sequences were identified, which the method divided into six isofunctional clusters, consistent with previous expert analysis. The results represent the most complete computational functional analysis of proteins comprising the Prx superfamily. The feasibility of this novel method is demonstrated by the Prx superfamily results, laying the foundation for potential functionally relevant clustering of the universe of protein sequences. PMID:28187133

An iterated Laplacian based semi-supervised dimensionality reduction for classification of breast cancer on ultrasound images.

PubMed

Liu, Xiao; Shi, Jun; Zhou, Shichong; Lu, Minhua

2014-01-01

The dimensionality reduction is an important step in ultrasound image based computer-aided diagnosis (CAD) for breast cancer. A newly proposed l2,1 regularized correntropy algorithm for robust feature selection (CRFS) has achieved good performance for noise corrupted data. Therefore, it has the potential to reduce the dimensions of ultrasound image features. However, in clinical practice, the collection of labeled instances is usually expensive and time costing, while it is relatively easy to acquire the unlabeled or undetermined instances. Therefore, the semi-supervised learning is very suitable for clinical CAD. The iterated Laplacian regularization (Iter-LR) is a new regularization method, which has been proved to outperform the traditional graph Laplacian regularization in semi-supervised classification and ranking. In this study, to augment the classification accuracy of the breast ultrasound CAD based on texture feature, we propose an Iter-LR-based semi-supervised CRFS (Iter-LR-CRFS) algorithm, and then apply it to reduce the feature dimensions of ultrasound images for breast CAD. We compared the Iter-LR-CRFS with LR-CRFS, original supervised CRFS, and principal component analysis. The experimental results indicate that the proposed Iter-LR-CRFS significantly outperforms all other algorithms.

Solution of the within-group multidimensional discrete ordinates transport equations on massively parallel architectures

NASA Astrophysics Data System (ADS)

Zerr, Robert Joseph

2011-12-01

The integral transport matrix method (ITMM) has been used as the kernel of new parallel solution methods for the discrete ordinates approximation of the within-group neutron transport equation. The ITMM abandons the repetitive mesh sweeps of the traditional source iterations (SI) scheme in favor of constructing stored operators that account for the direct coupling factors among all the cells and between the cells and boundary surfaces. The main goals of this work were to develop the algorithms that construct these operators and employ them in the solution process, determine the most suitable way to parallelize the entire procedure, and evaluate the behavior and performance of the developed methods for increasing number of processes. This project compares the effectiveness of the ITMM with the SI scheme parallelized with the Koch-Baker-Alcouffe (KBA) method. The primary parallel solution method involves a decomposition of the domain into smaller spatial sub-domains, each with their own transport matrices, and coupled together via interface boundary angular fluxes. Each sub-domain has its own set of ITMM operators and represents an independent transport problem. Multiple iterative parallel solution methods have investigated, including parallel block Jacobi (PBJ), parallel red/black Gauss-Seidel (PGS), and parallel GMRES (PGMRES). The fastest observed parallel solution method, PGS, was used in a weak scaling comparison with the PARTISN code. Compared to the state-of-the-art SI-KBA with diffusion synthetic acceleration (DSA), this new method without acceleration/preconditioning is not competitive for any problem parameters considered. The best comparisons occur for problems that are difficult for SI DSA, namely highly scattering and optically thick. SI DSA execution time curves are generally steeper than the PGS ones. However, until further testing is performed it cannot be concluded that SI DSA does not outperform the ITMM with PGS even on several thousand or tens of thousands of processors. The PGS method does outperform SI DSA for the periodic heterogeneous layers (PHL) configuration problems. Although this demonstrates a relative strength/weakness between the two methods, the practicality of these problems is much less, further limiting instances where it would be beneficial to select ITMM over SI DSA. The results strongly indicate a need for a robust, stable, and efficient acceleration method (or preconditioner for PGMRES). The spatial multigrid (SMG) method is currently incomplete in that it does not work for all cases considered and does not effectively improve the convergence rate for all values of scattering ratio c or cell dimension h. Nevertheless, it does display the desired trend for highly scattering, optically thin problems. That is, it tends to lower the rate of growth of number of iterations with increasing number of processes, P, while not increasing the number of additional operations per iteration to the extent that the total execution time of the rapidly converging accelerated iterations exceeds that of the slower unaccelerated iterations. A predictive parallel performance model has been developed for the PBJ method. Timing tests were performed such that trend lines could be fitted to the data for the different components and used to estimate the execution times. Applied to the weak scaling results, the model notably underestimates construction time, but combined with a slight overestimation in iterative solution time, the model predicts total execution time very well for large P. It also does a decent job with the strong scaling results, closely predicting the construction time and time per iteration, especially as P increases. Although not shown to be competitive up to 1,024 processing elements with the current state of the art, the parallelized ITMM exhibits promising scaling trends. Ultimately, compared to the KBA method, the parallelized ITMM may be found to be a very attractive option for transport calculations spatially decomposed over several tens of thousands of processes. Acceleration/preconditioning of the parallelized ITMM once developed will improve the convergence rate and improve its competitiveness. (Abstract shortened by UMI.)

Transforming paper-based assessment forms to a digital format: Exemplified by the Housing Enabler prototype app.

PubMed

Svarre, Tanja; Lunn, Tine Bieber Kirkegaard; Helle, Tina

2017-11-01

The aim of this paper is to provide the reader with an overall impression of the stepwise user-centred design approach including the specific methods used and lessons learned when transforming paper-based assessment forms into a prototype app, taking the Housing Enabler as an example. Four design iterations were performed, building on a domain study, workshops, expert evaluation and controlled and realistic usability tests. The user-centred design process involved purposefully selected participants with different Housing Enabler knowledge and housing adaptation experience. The design iterations resulted in the development of a Housing Enabler prototype app. The prototype app has several features and options that are new compared with the original paper-based Housing Enabler assessment form. These new features include a user friendly overview of the assessment form; easy navigation by swiping back and forth between items; onsite data analysis; and ranking of the accessibility score, photo documentation and a data export facility. Based on the presented stepwise approach, a high-fidelity Housing Enabler prototype app was successfully developed. The development process has emphasized the importance of combining design participants' knowledge and experiences, and has shown that methods should seem relevant to participants to increase their engagement.

An iterative correction approach used to retrieve the refractive index of squid pigment aerosols

NASA Astrophysics Data System (ADS)

Dinneen, Sean R.; Deravi, Leila F.; Greenslade, Margaret E.

2018-03-01

Pigments localized within cephalopod chromatophores are important for dermal coloration. When isolated and used as materials outside of the animal, the pigments can be processed as aerosols, illustrating a potential application for spray-on-coatings. The optical features of the pigment aerosols are difficult to analyze and require a method to correct for the particle charging and solvent effects accumulated during the aerosolizing process. We describe a method to account for these effects using an innovative iterative approach tied to retrieved refractive index (RI) values. RI retrievals were obtained via the best fit between the corrected, experimentally observed extinction efficiencies compared to those calculated by Mie theory for a specific RI at selected sizes. In addition to these retrievals, the impact of solvent on the particles’ optical properties was also examined via the Maxwell-Garnett mixing rule. Ultimately, we obtained a pigment RI with a real portion (n) of 1.66 (±0.05) representing a lower limit and an imaginary portion (k) of 0.13 (±0.08)i representing an upper limit for the generated aerosols. Combined, this approach advances techniques used to retrieve RI values that benefits both atmospheric chemistry and bio-inspired materials.

3D near-to-surface conductivity reconstruction by inversion of VETEM data using the distorted Born iterative method

USGS Publications Warehouse

Wang, G.L.; Chew, W.C.; Cui, T.J.; Aydiner, A.A.; Wright, D.L.; Smith, D.V.

2004-01-01

Three-dimensional (3D) subsurface imaging by using inversion of data obtained from the very early time electromagnetic system (VETEM) was discussed. The study was carried out by using the distorted Born iterative method to match the internal nonlinear property of the 3D inversion problem. The forward solver was based on the total-current formulation bi-conjugate gradient-fast Fourier transform (BCCG-FFT). It was found that the selection of regularization parameter follow a heuristic rule as used in the Levenberg-Marquardt algorithm so that the iteration is stable.

Pursuing Excellence: The Power of Selection Science to Provide Meaningful Data and Enhance Efficiency in Selecting Surgical Trainees.

PubMed

Gardner, Aimee K; Dunkin, Brian J

2018-05-01

As current screening methods for selecting surgical trainees are receiving increasing scrutiny, development of a more efficient and effective selection system is needed. We describe the process of creating an evidence-based selection system and examine its impact on screening efficiency, faculty perceptions, and improving representation of underrepresented minorities. The program partnered with an expert in organizational science to identify fellowship position requirements and associated competencies. Situational judgment tests, personality profiles, structured interviews, and technical skills assessments were used to measure these competencies. The situational judgment test and personality profiles were administered online and used to identify candidates to invite for on-site structured interviews and skills testing. A final rank list was created based on all data points and their respective importance. All faculty completed follow-up surveys regarding their perceptions of the process. Candidate demographic and experience data were pulled from the application website. Fifty-five of 72 applicants met eligibility requirements and were invited to take the online assessment, with 50 (91%) completing it. Average time to complete was 42 ± 12 minutes. Eighteen applicants (35%) were invited for on-site structured interviews and skills testing-a greater than 50% reduction in number of invites compared to prior years. Time estimates reveal that the process will result in a time savings of 68% for future iterations, compared to traditional methodologies. Fellowship faculty (N = 5) agreed on the value and efficiency of the process. Underrepresented minority candidates increased from an initial 70% to 92% being invited for an interview and ranked using the new screening tools. Applying selection science to the process of choosing surgical trainees is feasible, efficient, and well-received by faculty for making selection decisions.

A model of supervisor decision-making in the accommodation of workers with low back pain

PubMed Central

Williams-Whitt, Kelly; Kristman, Vicki; Shaw, William S.; Soklaridis, Sophie; Reguly, Paula

2016-01-01

PURPOSE To explore supervisors’ perspectives and decision-making processes in the accommodation of back injured workers. METHODS Twenty-three semi-structured, in-depth interviews were conducted with supervisors from eleven Canadian organizations about their role in providing job accommodations. Supervisors were identified through an on-line survey and interviews were recorded, transcribed and entered into NVivo software. The initial analyses identified common units of meaning, which were used to develop a coding guide. Interviews were coded, and a model of supervisor decision-making was developed based on the themes, categories and connecting ideas identified in the data. RESULTS The decision-making model includes a process element that is described as iterative “trial and error” decision-making. Medical restrictions are compared to job demands, employee abilities and available alternatives. A feasible modification is identified through brainstorming and then implemented by the supervisor. Resources used for brainstorming include information, supervisor experience and autonomy, and organizational supports. The model also incorporates the experience of accommodation as a job demand that causes strain for the supervisor. Accommodation demands affect the supervisor’s attitude, brainstorming and monitoring effort and communication with returning employees. Resources and demands have a combined effect on accommodation decision complexity, which in turn affects the quality of the accommodation option selected. If the employee is unable to complete the tasks or is reinjured during the accommodation, the decision cycle repeats. More frequent iteration through the trial and error process reduces the likelihood of return to work success. CONCLUSIONS A series of propositions is developed to illustrate the relationships among categories in the model. The model and propositions show: a) the iterative, problem solving nature of the RTW process; b) decision resources necessary for accommodation planning, and c) the impact accommodation demands may have on supervisors and RTW quality. PMID:26811170

Pulmonary airways tree segmentation from CT examinations using adaptive volume of interest

NASA Astrophysics Data System (ADS)

Park, Sang Cheol; Kim, Won Pil; Zheng, Bin; Leader, Joseph K.; Pu, Jiantao; Tan, Jun; Gur, David

2009-02-01

Airways tree segmentation is an important step in quantitatively assessing the severity of and changes in several lung diseases such as chronic obstructive pulmonary disease (COPD), asthma, and cystic fibrosis. It can also be used in guiding bronchoscopy. The purpose of this study is to develop an automated scheme for segmenting the airways tree structure depicted on chest CT examinations. After lung volume segmentation, the scheme defines the first cylinder-like volume of interest (VOI) using a series of images depicting the trachea. The scheme then iteratively defines and adds subsequent VOIs using a region growing algorithm combined with adaptively determined thresholds in order to trace possible sections of airways located inside the combined VOI in question. The airway tree segmentation process is automatically terminated after the scheme assesses all defined VOIs in the iteratively assembled VOI list. In this preliminary study, ten CT examinations with 1.25mm section thickness and two different CT image reconstruction kernels ("bone" and "standard") were selected and used to test the proposed airways tree segmentation scheme. The experiment results showed that (1) adopting this approach affectively prevented the scheme from infiltrating into the parenchyma, (2) the proposed method reasonably accurately segmented the airways trees with lower false positive identification rate as compared with other previously reported schemes that are based on 2-D image segmentation and data analyses, and (3) the proposed adaptive, iterative threshold selection method for the region growing step in each identified VOI enables the scheme to segment the airways trees reliably to the 4th generation in this limited dataset with successful segmentation up to the 5th generation in a fraction of the airways tree branches.

Master-Leader-Slave Cuckoo Search with Parameter Control for ANN Optimization and Its Real-World Application to Water Quality Prediction

PubMed Central

Jaddi, Najmeh Sadat; Abdullah, Salwani; Abdul Malek, Marlinda

2017-01-01

Artificial neural networks (ANNs) have been employed to solve a broad variety of tasks. The selection of an ANN model with appropriate weights is important in achieving accurate results. This paper presents an optimization strategy for ANN model selection based on the cuckoo search (CS) algorithm, which is rooted in the obligate brood parasitic actions of some cuckoo species. In order to enhance the convergence ability of basic CS, some modifications are proposed. The fraction Pa of the n nests replaced by new nests is a fixed parameter in basic CS. As the selection of Pa is a challenging issue and has a direct effect on exploration and therefore on convergence ability, in this work the Pa is set to a maximum value at initialization to achieve more exploration in early iterations and it is decreased during the search to achieve more exploitation in later iterations until it reaches the minimum value in the final iteration. In addition, a novel master-leader-slave multi-population strategy is used where the slaves employ the best fitness function among all slaves, which is selected by the leader under a certain condition. This fitness function is used for subsequent Lévy flights. In each iteration a copy of the best solution of each slave is migrated to the master and then the best solution is found by the master. The method is tested on benchmark classification and time series prediction problems and the statistical analysis proves the ability of the method. This method is also applied to a real-world water quality prediction problem with promising results. PMID:28125609

Master-Leader-Slave Cuckoo Search with Parameter Control for ANN Optimization and Its Real-World Application to Water Quality Prediction.

PubMed

Jaddi, Najmeh Sadat; Abdullah, Salwani; Abdul Malek, Marlinda

2017-01-01

Artificial neural networks (ANNs) have been employed to solve a broad variety of tasks. The selection of an ANN model with appropriate weights is important in achieving accurate results. This paper presents an optimization strategy for ANN model selection based on the cuckoo search (CS) algorithm, which is rooted in the obligate brood parasitic actions of some cuckoo species. In order to enhance the convergence ability of basic CS, some modifications are proposed. The fraction Pa of the n nests replaced by new nests is a fixed parameter in basic CS. As the selection of Pa is a challenging issue and has a direct effect on exploration and therefore on convergence ability, in this work the Pa is set to a maximum value at initialization to achieve more exploration in early iterations and it is decreased during the search to achieve more exploitation in later iterations until it reaches the minimum value in the final iteration. In addition, a novel master-leader-slave multi-population strategy is used where the slaves employ the best fitness function among all slaves, which is selected by the leader under a certain condition. This fitness function is used for subsequent Lévy flights. In each iteration a copy of the best solution of each slave is migrated to the master and then the best solution is found by the master. The method is tested on benchmark classification and time series prediction problems and the statistical analysis proves the ability of the method. This method is also applied to a real-world water quality prediction problem with promising results.

Status of the ITER Cryodistribution

NASA Astrophysics Data System (ADS)

Chang, H.-S.; Vaghela, H.; Patel, P.; Rizzato, A.; Cursan, M.; Henry, D.; Forgeas, A.; Grillot, D.; Sarkar, B.; Muralidhara, S.; Das, J.; Shukla, V.; Adler, E.

2017-12-01

Since the conceptual design of the ITER Cryodistribution many modifications have been applied due to both system optimization and improved knowledge of the clients’ requirements. Process optimizations in the Cryoplant resulted in component simplifications whereas increased heat load in some of the superconducting magnet systems required more complicated process configuration but also the removal of a cold box was possible due to component arrangement standardization. Another cold box, planned for redundancy, has been removed due to the Tokamak in-Cryostat piping layout modification. In this proceeding we will summarize the present design status and component configuration of the ITER Cryodistribution with all changes implemented which aim at process optimization and simplification as well as operational reliability, stability and flexibility.

Automatic variable selection method and a comparison for quantitative analysis in laser-induced breakdown spectroscopy

NASA Astrophysics Data System (ADS)

Duan, Fajie; Fu, Xiao; Jiang, Jiajia; Huang, Tingting; Ma, Ling; Zhang, Cong

2018-05-01

In this work, an automatic variable selection method for quantitative analysis of soil samples using laser-induced breakdown spectroscopy (LIBS) is proposed, which is based on full spectrum correction (FSC) and modified iterative predictor weighting-partial least squares (mIPW-PLS). The method features automatic selection without artificial processes. To illustrate the feasibility and effectiveness of the method, a comparison with genetic algorithm (GA) and successive projections algorithm (SPA) for different elements (copper, barium and chromium) detection in soil was implemented. The experimental results showed that all the three methods could accomplish variable selection effectively, among which FSC-mIPW-PLS required significantly shorter computation time (12 s approximately for 40,000 initial variables) than the others. Moreover, improved quantification models were got with variable selection approaches. The root mean square errors of prediction (RMSEP) of models utilizing the new method were 27.47 (copper), 37.15 (barium) and 39.70 (chromium) mg/kg, which showed comparable prediction effect with GA and SPA.

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

PubMed

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

2018-02-01

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

An Iterative Approach for the Optimization of Pavement Maintenance Management at the Network Level

PubMed Central

Torres-Machí, Cristina; Chamorro, Alondra; Videla, Carlos; Yepes, Víctor

2014-01-01

Pavement maintenance is one of the major issues of public agencies. Insufficient investment or inefficient maintenance strategies lead to high economic expenses in the long term. Under budgetary restrictions, the optimal allocation of resources becomes a crucial aspect. Two traditional approaches (sequential and holistic) and four classes of optimization methods (selection based on ranking, mathematical optimization, near optimization, and other methods) have been applied to solve this problem. They vary in the number of alternatives considered and how the selection process is performed. Therefore, a previous understanding of the problem is mandatory to identify the most suitable approach and method for a particular network. This study aims to assist highway agencies, researchers, and practitioners on when and how to apply available methods based on a comparative analysis of the current state of the practice. Holistic approach tackles the problem considering the overall network condition, while the sequential approach is easier to implement and understand, but may lead to solutions far from optimal. Scenarios defining the suitability of these approaches are defined. Finally, an iterative approach gathering the advantages of traditional approaches is proposed and applied in a case study. The proposed approach considers the overall network condition in a simpler and more intuitive manner than the holistic approach. PMID:24741352

An iterative approach for the optimization of pavement maintenance management at the network level.

PubMed

Torres-Machí, Cristina; Chamorro, Alondra; Videla, Carlos; Pellicer, Eugenio; Yepes, Víctor

2014-01-01

Pavement maintenance is one of the major issues of public agencies. Insufficient investment or inefficient maintenance strategies lead to high economic expenses in the long term. Under budgetary restrictions, the optimal allocation of resources becomes a crucial aspect. Two traditional approaches (sequential and holistic) and four classes of optimization methods (selection based on ranking, mathematical optimization, near optimization, and other methods) have been applied to solve this problem. They vary in the number of alternatives considered and how the selection process is performed. Therefore, a previous understanding of the problem is mandatory to identify the most suitable approach and method for a particular network. This study aims to assist highway agencies, researchers, and practitioners on when and how to apply available methods based on a comparative analysis of the current state of the practice. Holistic approach tackles the problem considering the overall network condition, while the sequential approach is easier to implement and understand, but may lead to solutions far from optimal. Scenarios defining the suitability of these approaches are defined. Finally, an iterative approach gathering the advantages of traditional approaches is proposed and applied in a case study. The proposed approach considers the overall network condition in a simpler and more intuitive manner than the holistic approach.

Accelerating spirocyclic polyketide synthesis using flow chemistry.

PubMed

Newton, Sean; Carter, Catherine F; Pearson, Colin M; de C Alves, Leandro; Lange, Heiko; Thansandote, Praew; Ley, Steven V

2014-05-05

Over the past decade, the integration of synthetic chemistry with flow processing has resulted in a powerful platform for molecular assembly that is making an impact throughout the chemical community. Herein, we demonstrate the extension of these tools to encompass complex natural product synthesis. We have developed a number of novel flow-through processes for reactions commonly encountered in natural product synthesis programs to achieve the first total synthesis of spirodienal A and the preparation of spirangien A methyl ester. Highlights of the synthetic route include an iridium-catalyzed hydrogenation, iterative Roush crotylations, gold-catalyzed spiroketalization and a late-stage cis-selective reduction. © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Fourier Domain Iterative Approach to Optical Sectioning of 3d Translucent Objects for Ophthalmology Purposes

NASA Astrophysics Data System (ADS)

Razguli, A. V.; Iroshnikov, N. G.; Larichev, A. V.; Romanenko, T. E.; Goncharov, A. S.

2017-05-01

In this paper we deal with the problem of optical sectioning. This is a post processing step while investigating of 3D translucent medical objects based on rapid refocusing of the imaging system by the adaptive optics technique. Each image, captured in focal plane, can be represented as the sum of in-focus true section and out-of-focus images of the neighboring sections of the depth that are undesirable in the subsequent reconstruction of 3D object. The problem of optical sectioning under consideration is to elaborate a robust approach capable of obtaining a stack of cross section images purified from such distortions. For a typical sectioning statement arising in ophthalmology we propose a local iterative method in Fourier spectral plane. Compared to the non-local constant parameter selection for the whole spectral domain, the method demonstrates both improved sectioning results and a good level of scalability when implemented on multi-core CPUs.

Single-snapshot DOA estimation by using Compressed Sensing

NASA Astrophysics Data System (ADS)

Fortunati, Stefano; Grasso, Raffaele; Gini, Fulvio; Greco, Maria S.; LePage, Kevin

2014-12-01

This paper deals with the problem of estimating the directions of arrival (DOA) of multiple source signals from a single observation vector of an array data. In particular, four estimation algorithms based on the theory of compressed sensing (CS), i.e., the classical ℓ 1 minimization (or Least Absolute Shrinkage and Selection Operator, LASSO), the fast smooth ℓ 0 minimization, and the Sparse Iterative Covariance-Based Estimator, SPICE and the Iterative Adaptive Approach for Amplitude and Phase Estimation, IAA-APES algorithms, are analyzed, and their statistical properties are investigated and compared with the classical Fourier beamformer (FB) in different simulated scenarios. We show that unlike the classical FB, a CS-based beamformer (CSB) has some desirable properties typical of the adaptive algorithms (e.g., Capon and MUSIC) even in the single snapshot case. Particular attention is devoted to the super-resolution property. Theoretical arguments and simulation analysis provide evidence that a CS-based beamformer can achieve resolution beyond the classical Rayleigh limit. Finally, the theoretical findings are validated by processing a real sonar dataset.

Exploiting parallel computing with limited program changes using a network of microcomputers

NASA Technical Reports Server (NTRS)

Rogers, J. L., Jr.; Sobieszczanski-Sobieski, J.

1985-01-01

Network computing and multiprocessor computers are two discernible trends in parallel processing. The computational behavior of an iterative distributed process in which some subtasks are completed later than others because of an imbalance in computational requirements is of significant interest. The effects of asynchronus processing was studied. A small existing program was converted to perform finite element analysis by distributing substructure analysis over a network of four Apple IIe microcomputers connected to a shared disk, simulating a parallel computer. The substructure analysis uses an iterative, fully stressed, structural resizing procedure. A framework of beams divided into three substructures is used as the finite element model. The effects of asynchronous processing on the convergence of the design variables are determined by not resizing particular substructures on various iterations.

Metal-induced streak artifact reduction using iterative reconstruction algorithms in x-ray computed tomography image of the dentoalveolar region.

PubMed

Dong, Jian; Hayakawa, Yoshihiko; Kannenberg, Sven; Kober, Cornelia

2013-02-01

The objective of this study was to reduce metal-induced streak artifact on oral and maxillofacial x-ray computed tomography (CT) images by developing the fast statistical image reconstruction system using iterative reconstruction algorithms. Adjacent CT images often depict similar anatomical structures in thin slices. So, first, images were reconstructed using the same projection data of an artifact-free image. Second, images were processed by the successive iterative restoration method where projection data were generated from reconstructed image in sequence. Besides the maximum likelihood-expectation maximization algorithm, the ordered subset-expectation maximization algorithm (OS-EM) was examined. Also, small region of interest (ROI) setting and reverse processing were applied for improving performance. Both algorithms reduced artifacts instead of slightly decreasing gray levels. The OS-EM and small ROI reduced the processing duration without apparent detriments. Sequential and reverse processing did not show apparent effects. Two alternatives in iterative reconstruction methods were effective for artifact reduction. The OS-EM algorithm and small ROI setting improved the performance. Copyright © 2012 Elsevier Inc. All rights reserved.

Modelling the Probability of Landslides Impacting Road Networks

NASA Astrophysics Data System (ADS)

Taylor, F. E.; Malamud, B. D.

2012-04-01

During a landslide triggering event, the threat of landslides blocking roads poses a risk to logistics, rescue efforts and communities dependant on those road networks. Here we present preliminary results of a stochastic model we have developed to evaluate the probability of landslides intersecting a simple road network during a landslide triggering event and apply simple network indices to measure the state of the road network in the affected region. A 4000 x 4000 cell array with a 5 m x 5 m resolution was used, with a pre-defined simple road network laid onto it, and landslides 'randomly' dropped onto it. Landslide areas (AL) were randomly selected from a three-parameter inverse gamma probability density function, consisting of a power-law decay of about -2.4 for medium and large values of AL and an exponential rollover for small values of AL; the rollover (maximum probability) occurs at about AL = 400 m2 This statistical distribution was chosen based on three substantially complete triggered landslide inventories recorded in existing literature. The number of landslide areas (NL) selected for each triggered event iteration was chosen to have an average density of 1 landslide km-2, i.e. NL = 400 landslide areas chosen randomly for each iteration, and was based on several existing triggered landslide event inventories. A simple road network was chosen, in a 'T' shape configuration, with one road 1 x 4000 cells (5 m x 20 km) in a 'T' formation with another road 1 x 2000 cells (5 m x 10 km). The landslide areas were then randomly 'dropped' over the road array and indices such as the location, size (ABL) and number of road blockages (NBL) recorded. This process was performed 500 times (iterations) in a Monte-Carlo type simulation. Initial results show that for a landslide triggering event with 400 landslides over a 400 km2 region, the number of road blocks per iteration, NBL,ranges from 0 to 7. The average blockage area for the 500 iterations (A¯ BL) is about 3000 m2, which closely matches the value of A¯ L for the triggered landslide inventories. We further find that over the 500 iterations, the probability of a given number of road blocks occurring on any given iteration, p(NBL) as a function of NBL, follows reasonably well a three-parameter inverse gamma probability density distribution with an exponential rollover (i.e., the most frequent value) at NBL = 1.3. In this paper we have begun to calculate the probability of the number of landslides blocking roads during a triggering event, and have found that this follows an inverse-gamma distribution, which is similar to that found for the statistics of landslide areas resulting from triggers. As we progress to model more realistic road networks, this work will aid in both long-term and disaster management for road networks by allowing probabilistic assessment of road network potential damage during different magnitude landslide triggering event scenarios.

Drawing dynamical and parameters planes of iterative families and methods.

PubMed

Chicharro, Francisco I; Cordero, Alicia; Torregrosa, Juan R

2013-01-01

The complex dynamical analysis of the parametric fourth-order Kim's iterative family is made on quadratic polynomials, showing the MATLAB codes generated to draw the fractal images necessary to complete the study. The parameter spaces associated with the free critical points have been analyzed, showing the stable (and unstable) regions where the selection of the parameter will provide us the excellent schemes (or dreadful ones).

Strategic Review Process for an Accountable Care Organization and Emerging Accountable Care Best Practices.

PubMed

Conway, Sarah J; Himmelrich, Sarah; Feeser, Scott A; Flynn, John A; Kravet, Steven J; Bailey, Jennifer; Hebert, Lindsay C; Donovan, Susan H; Kachur, Sarah G; Brown, Patricia M C; Baumgartner, William A; Berkowitz, Scott A

2018-02-02

Accountable Care Organizations (ACOs), like other care entities, must be strategic about which initiatives they support in the quest for higher value. This article reviews the current strategic planning process for the Johns Hopkins Medicine Alliance for Patients (JMAP), a Medicare Shared Savings Program Track 1 ACO. It reviews the 3 focus areas for the 2017 strategic review process - (1) optimizing care coordination for complex, at-risk patients, (2) post-acute care, and (3) specialty care integration - reviewing cost savings and quality improvement opportunities, associated best practices from the literature, and opportunities to leverage and advance existing ACO and health system efforts in each area. It then reviews the ultimate selection of priorities for the coming year and early thoughts on implementation. After the robust review process, key stakeholders voted to select interventions targeted at care coordination, post-acute care, and specialty integration including Part B drug and imaging costs. The interventions selected incorporate a mixture of enhancing current ACO initiatives, working collaboratively and synergistically on other health system initiatives, and taking on new projects deemed targeted, cost-effective, and manageable in scope. The annual strategic review has been an essential and iterative process based on performance data and informed by the collective experience of other organizations. The process allows for an evidence-based strategic plan for the ACO in pursuit of the best care for patients.

Activation characteristics of candidate structural materials for a near-term Indian fusion reactor and the impact of their impurities on design considerations

NASA Astrophysics Data System (ADS)

H, L. SWAMI; C, DANANI; A, K. SHAW

2018-06-01

Activation analyses play a vital role in nuclear reactor design. Activation analyses, along with nuclear analyses, provide important information for nuclear safety and maintenance strategies. Activation analyses also help in the selection of materials for a nuclear reactor, by providing the radioactivity and dose rate levels after irradiation. This information is important to help define maintenance activity for different parts of the reactor, and to plan decommissioning and radioactive waste disposal strategies. The study of activation analyses of candidate structural materials for near-term fusion reactors or ITER is equally essential, due to the presence of a high-energy neutron environment which makes decisive demands on material selection. This study comprises two parts; in the first part the activation characteristics, in a fusion radiation environment, of several elements which are widely present in structural materials, are studied. It reveals that the presence of a few specific elements in a material can diminish its feasibility for use in the nuclear environment. The second part of the study concentrates on activation analyses of candidate structural materials for near-term fusion reactors and their comparison in fusion radiation conditions. The structural materials selected for this study, i.e. India-specific Reduced Activation Ferritic‑Martensitic steel (IN-RAFMS), P91-grade steel, stainless steel 316LN ITER-grade (SS-316LN-IG), stainless steel 316L and stainless steel 304, are candidates for use in ITER either in vessel components or test blanket systems. Tungsten is also included in this study because of its use for ITER plasma-facing components. The study is carried out using the reference parameters of the ITER fusion reactor. The activation characteristics of the materials are assessed considering the irradiation at an ITER equatorial port. The presence of elements like Nb, Mo, Co and Ta in a structural material enhance the activity level as well as the dose level, which has an impact on design considerations. IN-RAFMS was shown to be a more effective low-activation material than SS-316LN-IG.

Iterative dataset optimization in automated planning: Implementation for breast and rectal cancer radiotherapy.

PubMed

Fan, Jiawei; Wang, Jiazhou; Zhang, Zhen; Hu, Weigang

2017-06-01

To develop a new automated treatment planning solution for breast and rectal cancer radiotherapy. The automated treatment planning solution developed in this study includes selection of the iterative optimized training dataset, dose volume histogram (DVH) prediction for the organs at risk (OARs), and automatic generation of clinically acceptable treatment plans. The iterative optimized training dataset is selected by an iterative optimization from 40 treatment plans for left-breast and rectal cancer patients who received radiation therapy. A two-dimensional kernel density estimation algorithm (noted as two parameters KDE) which incorporated two predictive features was implemented to produce the predicted DVHs. Finally, 10 additional new left-breast treatment plans are re-planned using the Pinnacle 3 Auto-Planning (AP) module (version 9.10, Philips Medical Systems) with the objective functions derived from the predicted DVH curves. Automatically generated re-optimized treatment plans are compared with the original manually optimized plans. By combining the iterative optimized training dataset methodology and two parameters KDE prediction algorithm, our proposed automated planning strategy improves the accuracy of the DVH prediction. The automatically generated treatment plans using the dose derived from the predicted DVHs can achieve better dose sparing for some OARs without compromising other metrics of plan quality. The proposed new automated treatment planning solution can be used to efficiently evaluate and improve the quality and consistency of the treatment plans for intensity-modulated breast and rectal cancer radiation therapy. © 2017 American Association of Physicists in Medicine.

Simultaneous and iterative weighted regression analysis of toxicity tests using a microplate reader.

PubMed

Galgani, F; Cadiou, Y; Gilbert, F

1992-04-01

A system is described for determination of LC50 or IC50 by an iterative process based on data obtained from a plate reader using a marine unicellular alga as a target species. The esterase activity of Tetraselmis suesica on fluorescein diacetate as a substrate was measured using a fluorescence titerplate. Simultaneous analysis of results was performed using an iterative process adopting the sigmoid function Y = y/1 (dose of toxicant/IC50)slope for dose-response relationships. IC50 (+/- SEM) was estimated (P less than 0.05). An application with phosalone as a toxicant is presented.

Experiments on water detritiation and cryogenic distillation at TLK; Impact on ITER fuel cycle subsystems interfaces

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

Cristescu, I.; Cristescu, I. R.; Doerr, L.

2008-07-15

The ITER Isotope Separation System (ISS) and Water Detritiation System (WDS) should be integrated in order to reduce potential chronic tritium emissions from the ISS. This is achieved by routing the top (protium) product from the ISS to a feed point near the bottom end of the WDS Liquid Phase Catalytic Exchange (LPCE) column. This provides an additional barrier against ISS emissions and should mitigate the memory effects due to process parameter fluctuations in the ISS. To support the research activities needed to characterize the performances of various components for WDS and ISS processes under various working conditions and configurationsmore » as needed for ITER design, an experimental facility called TRENTA representative of the ITER WDS and ISS protium separation column, has been commissioned and is in operation at TLK The experimental program on TRENTA facility is conducted to provide the necessary design data related to the relevant ITER operating modes. The operation availability and performances of ISS-WDS have impact on ITER fuel cycle subsystems with consequences on the design integration. The preliminary experimental data on TRENTA facility are presented. (authors)« less

Fluence map optimization (FMO) with dose-volume constraints in IMRT using the geometric distance sorting method.

PubMed

Lan, Yihua; Li, Cunhua; Ren, Haozheng; Zhang, Yong; Min, Zhifang

2012-10-21

A new heuristic algorithm based on the so-called geometric distance sorting technique is proposed for solving the fluence map optimization with dose-volume constraints which is one of the most essential tasks for inverse planning in IMRT. The framework of the proposed method is basically an iterative process which begins with a simple linear constrained quadratic optimization model without considering any dose-volume constraints, and then the dose constraints for the voxels violating the dose-volume constraints are gradually added into the quadratic optimization model step by step until all the dose-volume constraints are satisfied. In each iteration step, an interior point method is adopted to solve each new linear constrained quadratic programming. For choosing the proper candidate voxels for the current dose constraint adding, a so-called geometric distance defined in the transformed standard quadratic form of the fluence map optimization model was used to guide the selection of the voxels. The new geometric distance sorting technique can mostly reduce the unexpected increase of the objective function value caused inevitably by the constraint adding. It can be regarded as an upgrading to the traditional dose sorting technique. The geometry explanation for the proposed method is also given and a proposition is proved to support our heuristic idea. In addition, a smart constraint adding/deleting strategy is designed to ensure a stable iteration convergence. The new algorithm is tested on four cases including head-neck, a prostate, a lung and an oropharyngeal, and compared with the algorithm based on the traditional dose sorting technique. Experimental results showed that the proposed method is more suitable for guiding the selection of new constraints than the traditional dose sorting method, especially for the cases whose target regions are in non-convex shapes. It is a more efficient optimization technique to some extent for choosing constraints than the dose sorting method. By integrating a smart constraint adding/deleting scheme within the iteration framework, the new technique builds up an improved algorithm for solving the fluence map optimization with dose-volume constraints.

Development of FWIGPR, an open-source package for full-waveform inversion of common-offset GPR data

NASA Astrophysics Data System (ADS)

Jazayeri, S.; Kruse, S.

2017-12-01

We introduce a package for full-waveform inversion (FWI) of Ground Penetrating Radar (GPR) data based on a combination of open-source programs. The FWI requires a good starting model, based on direct knowledge of field conditions or on traditional ray-based inversion methods. With a good starting model, the FWI can improve resolution of selected subsurface features. The package will be made available for general use in educational and research activities. The FWIGPR package consists of four main components: 3D to 2D data conversion, source wavelet estimation, forward modeling, and inversion. (These four components additionally require the development, by the user, of a good starting model.) A major challenge with GPR data is the unknown form of the waveform emitted by the transmitter held close to the ground surface. We apply a blind deconvolution method to estimate the source wavelet, based on a sparsity assumption about the reflectivity series of the subsurface model (Gholami and Sacchi 2012). The estimated wavelet is deconvolved from the data and the sparsest reflectivity series with fewest reflectors. The gprMax code (www.gprmax.com) is used as the forward modeling tool and the PEST parameter estimation package (www.pesthomepage.com) for the inversion. To reduce computation time, the field data are converted to an effective 2D equivalent, and the gprMax code can be run in 2D mode. In the first step, the user must create a good starting model of the data, presumably using ray-based methods. This estimated model will be introduced to the FWI process as an initial model. Next, the 3D data is converted to 2D, then the user estimates the source wavelet that best fits the observed data by sparsity assumption of the earth's response. Last, PEST runs gprMax with the initial model and calculates the misfit between the synthetic and observed data, and using an iterative algorithm calling gprMax several times ineach iteration, finds successive models that better fit the data. To gauge whether the iterative process has arrived at a local or global minima, the process can be repeated with a range of starting models. Tests have shown that this package can successfully improve estimates of selected subsurface model parameters for simple synthetic and real data. Ongoing research will focus on FWI of more complex scenarios.

Iterative-Transform Phase Retrieval Using Adaptive Diversity

NASA Technical Reports Server (NTRS)

Dean, Bruce H.

2007-01-01

A phase-diverse iterative-transform phase-retrieval algorithm enables high spatial-frequency, high-dynamic-range, image-based wavefront sensing. [The terms phase-diverse, phase retrieval, image-based, and wavefront sensing are defined in the first of the two immediately preceding articles, Broadband Phase Retrieval for Image-Based Wavefront Sensing (GSC-14899-1).] As described below, no prior phase-retrieval algorithm has offered both high dynamic range and the capability to recover high spatial-frequency components. Each of the previously developed image-based phase-retrieval techniques can be classified into one of two categories: iterative transform or parametric. Among the modifications of the original iterative-transform approach has been the introduction of a defocus diversity function (also defined in the cited companion article). Modifications of the original parametric approach have included minimizing alternative objective functions as well as implementing a variety of nonlinear optimization methods. The iterative-transform approach offers the advantage of ability to recover low, middle, and high spatial frequencies, but has disadvantage of having a limited dynamic range to one wavelength or less. In contrast, parametric phase retrieval offers the advantage of high dynamic range, but is poorly suited for recovering higher spatial frequency aberrations. The present phase-diverse iterative transform phase-retrieval algorithm offers both the high-spatial-frequency capability of the iterative-transform approach and the high dynamic range of parametric phase-recovery techniques. In implementation, this is a focus-diverse iterative-transform phaseretrieval algorithm that incorporates an adaptive diversity function, which makes it possible to avoid phase unwrapping while preserving high-spatial-frequency recovery. The algorithm includes an inner and an outer loop (see figure). An initial estimate of phase is used to start the algorithm on the inner loop, wherein multiple intensity images are processed, each using a different defocus value. The processing is done by an iterative-transform method, yielding individual phase estimates corresponding to each image of the defocus-diversity data set. These individual phase estimates are combined in a weighted average to form a new phase estimate, which serves as the initial phase estimate for either the next iteration of the iterative-transform method or, if the maximum number of iterations has been reached, for the next several steps, which constitute the outerloop portion of the algorithm. The details of the next several steps must be omitted here for the sake of brevity. The overall effect of these steps is to adaptively update the diversity defocus values according to recovery of global defocus in the phase estimate. Aberration recovery varies with differing amounts as the amount of diversity defocus is updated in each image; thus, feedback is incorporated into the recovery process. This process is iterated until the global defocus error is driven to zero during the recovery process. The amplitude of aberration may far exceed one wavelength after completion of the inner-loop portion of the algorithm, and the classical iterative transform method does not, by itself, enable recovery of multi-wavelength aberrations. Hence, in the absence of a means of off-loading the multi-wavelength portion of the aberration, the algorithm would produce a wrapped phase map. However, a special aberration-fitting procedure can be applied to the wrapped phase data to transfer at least some portion of the multi-wavelength aberration to the diversity function, wherein the data are treated as known phase values. In this way, a multiwavelength aberration can be recovered incrementally by successively applying the aberration-fitting procedure to intermediate wrapped phase maps. During recovery, as more of the aberration is transferred to the diversity function following successive iterations around the ter loop, the estimated phase ceases to wrap in places where the aberration values become incorporated as part of the diversity function. As a result, as the aberration content is transferred to the diversity function, the phase estimate resembles that of a reference flat.

Modeling the dynamics of evaluation: a multilevel neural network implementation of the iterative reprocessing model.

PubMed

Ehret, Phillip J; Monroe, Brian M; Read, Stephen J

2015-05-01

We present a neural network implementation of central components of the iterative reprocessing (IR) model. The IR model argues that the evaluation of social stimuli (attitudes, stereotypes) is the result of the IR of stimuli in a hierarchy of neural systems: The evaluation of social stimuli develops and changes over processing. The network has a multilevel, bidirectional feedback evaluation system that integrates initial perceptual processing and later developing semantic processing. The network processes stimuli (e.g., an individual's appearance) over repeated iterations, with increasingly higher levels of semantic processing over time. As a result, the network's evaluations of stimuli evolve. We discuss the implications of the network for a number of different issues involved in attitudes and social evaluation. The success of the network supports the IR model framework and provides new insights into attitude theory. © 2014 by the Society for Personality and Social Psychology, Inc.

Software Would Largely Automate Design of Kalman Filter

NASA Technical Reports Server (NTRS)

Chuang, Jason C. H.; Negast, William J.

2005-01-01

Embedded Navigation Filter Automatic Designer (ENFAD) is a computer program being developed to automate the most difficult tasks in designing embedded software to implement a Kalman filter in a navigation system. The most difficult tasks are selection of error states of the filter and tuning of filter parameters, which are timeconsuming trial-and-error tasks that require expertise and rarely yield optimum results. An optimum selection of error states and filter parameters depends on navigation-sensor and vehicle characteristics, and on filter processing time. ENFAD would include a simulation module that would incorporate all possible error states with respect to a given set of vehicle and sensor characteristics. The first of two iterative optimization loops would vary the selection of error states until the best filter performance was achieved in Monte Carlo simulations. For a fixed selection of error states, the second loop would vary the filter parameter values until an optimal performance value was obtained. Design constraints would be satisfied in the optimization loops. Users would supply vehicle and sensor test data that would be used to refine digital models in ENFAD. Filter processing time and filter accuracy would be computed by ENFAD.

US NDC Modernization Iteration E1 Prototyping Report: Processing Control Framework

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

Prescott, Ryan; Hamlet, Benjamin R.

2014-12-01

During the first iteration of the US NDC Modernization Elaboration phase (E1), the SNL US NDC modernization project team developed an initial survey of applicable COTS solutions, and established exploratory prototyping related to the processing control framework in support of system architecture definition. This report summarizes these activities and discusses planned follow-on work.

Foucauldian Iterative Learning Conversations--An Example of Organisational Change: Developing Conjoint-Work between EPS and Social Workers

ERIC Educational Resources Information Center

Apter, Brian

2014-01-01

An organisational change-process in a UK local authority (LA) over two years is examined using transcribed excerpts from three meetings. The change-process is analysed using a Foucauldian analytical tool--Iterative Learning Conversations (ILCS). An Educational Psychology Service was changed from being primarily an education-focussed…

Iterative universal state selective correction for the Brillouin-Wigner multireference coupled-cluster theory

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

Banik, Subrata; Ravichandran, Lalitha; Brabec, Jiri

2015-03-21

As a further development of the previously introduced a posteriori Universal State-Selective (USS) corrections [K. Kowalski, J. Chem. Phys. 134, 194107 (2011)] and [Brabec et al., J. Chem. Phys., 136, 124102 (2012)], we suggest an iterative form of the USS correction by means of correcting effective Hamiltonian matrix elements. We also formulate USS corrections via the left Bloch equations. The convergence of the USS corrections with excitation level towards the FCI limit is also investigated. Various forms of the USS and simplified diagonal USSD corrections at the SD and SD(T) levels are numerically assessed on several model systems and onmore » the ozone and tetramethyleneethane molecules. It is shown that the iterative USS correction can successfully replace the previously developed a posteriori BWCC size-extensivity correction, while it is not sensitive to intruder states and performs well also in other cases when the a posteriori one fails, like e.g. for the asymmetric vibration mode of ozone.« less

An iterative reduced field-of-view reconstruction for periodically rotated overlapping parallel lines with enhanced reconstruction (PROPELLER) MRI.

PubMed

Lin, Jyh-Miin; Patterson, Andrew J; Chang, Hing-Chiu; Gillard, Jonathan H; Graves, Martin J

2015-10-01

To propose a new reduced field-of-view (rFOV) strategy for iterative reconstructions in a clinical environment. Iterative reconstructions can incorporate regularization terms to improve the image quality of periodically rotated overlapping parallel lines with enhanced reconstruction (PROPELLER) MRI. However, the large amount of calculations required for full FOV iterative reconstructions has posed a huge computational challenge for clinical usage. By subdividing the entire problem into smaller rFOVs, the iterative reconstruction can be accelerated on a desktop with a single graphic processing unit (GPU). This rFOV strategy divides the iterative reconstruction into blocks, based on the block-diagonal dominant structure. A near real-time reconstruction system was developed for the clinical MR unit, and parallel computing was implemented using the object-oriented model. In addition, the Toeplitz method was implemented on the GPU to reduce the time required for full interpolation. Using the data acquired from the PROPELLER MRI, the reconstructed images were then saved in the digital imaging and communications in medicine format. The proposed rFOV reconstruction reduced the gridding time by 97%, as the total iteration time was 3 s even with multiple processes running. A phantom study showed that the structure similarity index for rFOV reconstruction was statistically superior to conventional density compensation (p < 0.001). In vivo study validated the increased signal-to-noise ratio, which is over four times higher than with density compensation. Image sharpness index was improved using the regularized reconstruction implemented. The rFOV strategy permits near real-time iterative reconstruction to improve the image quality of PROPELLER images. Substantial improvements in image quality metrics were validated in the experiments. The concept of rFOV reconstruction may potentially be applied to other kinds of iterative reconstructions for shortened reconstruction duration.

Exponential Sensitivity and its Cost in Quantum Physics

PubMed Central

Gilyén, András; Kiss, Tamás; Jex, Igor

2016-01-01

State selective protocols, like entanglement purification, lead to an essentially non-linear quantum evolution, unusual in naturally occurring quantum processes. Sensitivity to initial states in quantum systems, stemming from such non-linear dynamics, is a promising perspective for applications. Here we demonstrate that chaotic behaviour is a rather generic feature in state selective protocols: exponential sensitivity can exist for all initial states in an experimentally realisable optical scheme. Moreover, any complex rational polynomial map, including the example of the Mandelbrot set, can be directly realised. In state selective protocols, one needs an ensemble of initial states, the size of which decreases with each iteration. We prove that exponential sensitivity to initial states in any quantum system has to be related to downsizing the initial ensemble also exponentially. Our results show that magnifying initial differences of quantum states (a Schrödinger microscope) is possible; however, there is a strict bound on the number of copies needed. PMID:26861076

Exponential Sensitivity and its Cost in Quantum Physics.

PubMed

Gilyén, András; Kiss, Tamás; Jex, Igor

2016-02-10

State selective protocols, like entanglement purification, lead to an essentially non-linear quantum evolution, unusual in naturally occurring quantum processes. Sensitivity to initial states in quantum systems, stemming from such non-linear dynamics, is a promising perspective for applications. Here we demonstrate that chaotic behaviour is a rather generic feature in state selective protocols: exponential sensitivity can exist for all initial states in an experimentally realisable optical scheme. Moreover, any complex rational polynomial map, including the example of the Mandelbrot set, can be directly realised. In state selective protocols, one needs an ensemble of initial states, the size of which decreases with each iteration. We prove that exponential sensitivity to initial states in any quantum system has to be related to downsizing the initial ensemble also exponentially. Our results show that magnifying initial differences of quantum states (a Schrödinger microscope) is possible; however, there is a strict bound on the number of copies needed.

Cognitive representation of "musical fractals": Processing hierarchy and recursion in the auditory domain.

PubMed

Martins, Mauricio Dias; Gingras, Bruno; Puig-Waldmueller, Estela; Fitch, W Tecumseh

2017-04-01

The human ability to process hierarchical structures has been a longstanding research topic. However, the nature of the cognitive machinery underlying this faculty remains controversial. Recursion, the ability to embed structures within structures of the same kind, has been proposed as a key component of our ability to parse and generate complex hierarchies. Here, we investigated the cognitive representation of both recursive and iterative processes in the auditory domain. The experiment used a two-alternative forced-choice paradigm: participants were exposed to three-step processes in which pure-tone sequences were built either through recursive or iterative processes, and had to choose the correct completion. Foils were constructed according to generative processes that did not match the previous steps. Both musicians and non-musicians were able to represent recursion in the auditory domain, although musicians performed better. We also observed that general 'musical' aptitudes played a role in both recursion and iteration, although the influence of musical training was somehow independent from melodic memory. Moreover, unlike iteration, recursion in audition was well correlated with its non-auditory (recursive) analogues in the visual and action sequencing domains. These results suggest that the cognitive machinery involved in establishing recursive representations is domain-general, even though this machinery requires access to information resulting from domain-specific processes. Copyright © 2017 The Authors. Published by Elsevier B.V. All rights reserved.

Simultaneous gains tuning in boiler/turbine PID-based controller clusters using iterative feedback tuning methodology.

PubMed

Zhang, Shu; Taft, Cyrus W; Bentsman, Joseph; Hussey, Aaron; Petrus, Bryan

2012-09-01

Tuning a complex multi-loop PID based control system requires considerable experience. In today's power industry the number of available qualified tuners is dwindling and there is a great need for better tuning tools to maintain and improve the performance of complex multivariable processes. Multi-loop PID tuning is the procedure for the online tuning of a cluster of PID controllers operating in a closed loop with a multivariable process. This paper presents the first application of the simultaneous tuning technique to the multi-input-multi-output (MIMO) PID based nonlinear controller in the power plant control context, with the closed-loop system consisting of a MIMO nonlinear boiler/turbine model and a nonlinear cluster of six PID-type controllers. Although simplified, the dynamics and cross-coupling of the process and the PID cluster are similar to those used in a real power plant. The particular technique selected, iterative feedback tuning (IFT), utilizes the linearized version of the PID cluster for signal conditioning, but the data collection and tuning is carried out on the full nonlinear closed-loop system. Based on the figure of merit for the control system performance, the IFT is shown to deliver performance favorably comparable to that attained through the empirical tuning carried out by an experienced control engineer. Copyright © 2012 ISA. Published by Elsevier Ltd. All rights reserved.

Algorithm for ion beam figuring of low-gradient mirrors.

PubMed

Jiao, Changjun; Li, Shengyi; Xie, Xuhui

2009-07-20

Ion beam figuring technology for low-gradient mirrors is discussed. Ion beam figuring is a noncontact machining technique in which a beam of high-energy ions is directed toward a target workpiece to remove material in a predetermined and controlled fashion. Owing to this noncontact mode of material removal, problems associated with tool wear and edge effects, which are common in conventional contact polishing processes, are avoided. Based on the Bayesian principle, an iterative dwell time algorithm for planar mirrors is deduced from the computer-controlled optical surfacing (CCOS) principle. With the properties of the removal function, the shaping process of low-gradient mirrors can be approximated by the linear model for planar mirrors. With these discussions, the error surface figuring technology for low-gradient mirrors with a linear path is set up. With the near-Gaussian property of the removal function, the figuring process with a spiral path can be described by the conventional linear CCOS principle, and a Bayesian-based iterative algorithm can be used to deconvolute the dwell time. Moreover, the selection criterion of the spiral parameter is given. Ion beam figuring technology with a spiral scan path based on these methods can be used to figure mirrors with non-axis-symmetrical errors. Experiments on SiC chemical vapor deposition planar and Zerodur paraboloid samples are made, and the final surface errors are all below 1/100 lambda.

Drawing Dynamical and Parameters Planes of Iterative Families and Methods

PubMed Central

Chicharro, Francisco I.

2013-01-01

The complex dynamical analysis of the parametric fourth-order Kim's iterative family is made on quadratic polynomials, showing the MATLAB codes generated to draw the fractal images necessary to complete the study. The parameter spaces associated with the free critical points have been analyzed, showing the stable (and unstable) regions where the selection of the parameter will provide us the excellent schemes (or dreadful ones). PMID:24376386

RF Pulse Design using Nonlinear Gradient Magnetic Fields

PubMed Central

Kopanoglu, Emre; Constable, R. Todd

2014-01-01

Purpose An iterative k-space trajectory and radio-frequency (RF) pulse design method is proposed for Excitation using Nonlinear Gradient Magnetic fields (ENiGMa). Theory and Methods The spatial encoding functions (SEFs) generated by nonlinear gradient fields (NLGFs) are linearly dependent in Cartesian-coordinates. Left uncorrected, this may lead to flip-angle variations in excitation profiles. In the proposed method, SEFs (k-space samples) are selected using a Matching-Pursuit algorithm, and the RF pulse is designed using a Conjugate-Gradient algorithm. Three variants of the proposed approach are given: the full-algorithm, a computationally-cheaper version, and a third version for designing spoke-based trajectories. The method is demonstrated for various target excitation profiles using simulations and phantom experiments. Results The method is compared to other iterative (Matching-Pursuit and Conjugate Gradient) and non-iterative (coordinate-transformation and Jacobian-based) pulse design methods as well as uniform density spiral and EPI trajectories. The results show that the proposed method can increase excitation fidelity significantly. Conclusion An iterative method for designing k-space trajectories and RF pulses using nonlinear gradient fields is proposed. The method can either be used for selecting the SEFs individually to guide trajectory design, or can be adapted to design and optimize specific trajectories of interest. PMID:25203286

Sensor Selection and Data Validation for Reliable Integrated System Health Management

NASA Technical Reports Server (NTRS)

Garg, Sanjay; Melcher, Kevin J.

2008-01-01

For new access to space systems with challenging mission requirements, effective implementation of integrated system health management (ISHM) must be available early in the program to support the design of systems that are safe, reliable, highly autonomous. Early ISHM availability is also needed to promote design for affordable operations; increased knowledge of functional health provided by ISHM supports construction of more efficient operations infrastructure. Lack of early ISHM inclusion in the system design process could result in retrofitting health management systems to augment and expand operational and safety requirements; thereby increasing program cost and risk due to increased instrumentation and computational complexity. Having the right sensors generating the required data to perform condition assessment, such as fault detection and isolation, with a high degree of confidence is critical to reliable operation of ISHM. Also, the data being generated by the sensors needs to be qualified to ensure that the assessments made by the ISHM is not based on faulty data. NASA Glenn Research Center has been developing technologies for sensor selection and data validation as part of the FDDR (Fault Detection, Diagnosis, and Response) element of the Upper Stage project of the Ares 1 launch vehicle development. This presentation will provide an overview of the GRC approach to sensor selection and data quality validation and will present recent results from applications that are representative of the complexity of propulsion systems for access to space vehicles. A brief overview of the sensor selection and data quality validation approaches is provided below. The NASA GRC developed Systematic Sensor Selection Strategy (S4) is a model-based procedure for systematically and quantitatively selecting an optimal sensor suite to provide overall health assessment of a host system. S4 can be logically partitioned into three major subdivisions: the knowledge base, the down-select iteration, and the final selection analysis. The knowledge base required for productive use of S4 consists of system design information and heritage experience together with a focus on components with health implications. The sensor suite down-selection is an iterative process for identifying a group of sensors that provide good fault detection and isolation for targeted fault scenarios. In the final selection analysis, a statistical evaluation algorithm provides the final robustness test for each down-selected sensor suite. NASA GRC has developed an approach to sensor data qualification that applies empirical relationships, threshold detection techniques, and Bayesian belief theory to a network of sensors related by physics (i.e., analytical redundancy) in order to identify the failure of a given sensor within the network. This data quality validation approach extends the state-of-the-art, from red-lines and reasonableness checks that flag a sensor after it fails, to include analytical redundancy-based methods that can identify a sensor in the process of failing. The focus of this effort is on understanding the proper application of analytical redundancy-based data qualification methods for onboard use in monitoring Upper Stage sensors.

Using In-Training Evaluation Report (ITER) Qualitative Comments to Assess Medical Students and Residents: A Systematic Review.

PubMed

Hatala, Rose; Sawatsky, Adam P; Dudek, Nancy; Ginsburg, Shiphra; Cook, David A

2017-06-01

In-training evaluation reports (ITERs) constitute an integral component of medical student and postgraduate physician trainee (resident) assessment. ITER narrative comments have received less attention than the numeric scores. The authors sought both to determine what validity evidence informs the use of narrative comments from ITERs for assessing medical students and residents and to identify evidence gaps. Reviewers searched for relevant English-language studies in MEDLINE, EMBASE, Scopus, and ERIC (last search June 5, 2015), and in reference lists and author files. They included all original studies that evaluated ITERs for qualitative assessment of medical students and residents. Working in duplicate, they selected articles for inclusion, evaluated quality, and abstracted information on validity evidence using Kane's framework (inferences of scoring, generalization, extrapolation, and implications). Of 777 potential articles, 22 met inclusion criteria. The scoring inference is supported by studies showing that rich narratives are possible, that changing the prompt can stimulate more robust narratives, and that comments vary by context. Generalization is supported by studies showing that narratives reach thematic saturation and that analysts make consistent judgments. Extrapolation is supported by favorable relationships between ITER narratives and numeric scores from ITERs and non-ITER performance measures, and by studies confirming that narratives reflect constructs deemed important in clinical work. Evidence supporting implications is scant. The use of ITER narratives for trainee assessment is generally supported, except that evidence is lacking for implications and decisions. Future research should seek to confirm implicit assumptions and evaluate the impact of decisions.

Novel aspects of plasma control in ITER

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

Humphreys, D.; Jackson, G.; Walker, M.

2015-02-15

ITER plasma control design solutions and performance requirements are strongly driven by its nuclear mission, aggressive commissioning constraints, and limited number of operational discharges. In addition, high plasma energy content, heat fluxes, neutron fluxes, and very long pulse operation place novel demands on control performance in many areas ranging from plasma boundary and divertor regulation to plasma kinetics and stability control. Both commissioning and experimental operations schedules provide limited time for tuning of control algorithms relative to operating devices. Although many aspects of the control solutions required by ITER have been well-demonstrated in present devices and even designed satisfactorily formore » ITER application, many elements unique to ITER including various crucial integration issues are presently under development. We describe selected novel aspects of plasma control in ITER, identifying unique parts of the control problem and highlighting some key areas of research remaining. Novel control areas described include control physics understanding (e.g., current profile regulation, tearing mode (TM) suppression), control mathematics (e.g., algorithmic and simulation approaches to high confidence robust performance), and integration solutions (e.g., methods for management of highly subscribed control resources). We identify unique aspects of the ITER TM suppression scheme, which will pulse gyrotrons to drive current within a magnetic island, and turn the drive off following suppression in order to minimize use of auxiliary power and maximize fusion gain. The potential role of active current profile control and approaches to design in ITER are discussed. Issues and approaches to fault handling algorithms are described, along with novel aspects of actuator sharing in ITER.« less

Novel aspects of plasma control in ITER

DOE PAGES

Humphreys, David; Ambrosino, G.; de Vries, Peter; ...

2015-02-12

ITER plasma control design solutions and performance requirements are strongly driven by its nuclear mission, aggressive commissioning constraints, and limited number of operational discharges. In addition, high plasma energy content, heat fluxes, neutron fluxes, and very long pulse operation place novel demands on control performance in many areas ranging from plasma boundary and divertor regulation to plasma kinetics and stability control. Both commissioning and experimental operations schedules provide limited time for tuning of control algorithms relative to operating devices. Although many aspects of the control solutions required by ITER have been well-demonstrated in present devices and even designed satisfactorily formore » ITER application, many elements unique to ITER including various crucial integration issues are presently under development. We describe selected novel aspects of plasma control in ITER, identifying unique parts of the control problem and highlighting some key areas of research remaining. Novel control areas described include control physics understanding (e.g. current profile regulation, tearing mode suppression (TM)), control mathematics (e.g. algorithmic and simulation approaches to high confidence robust performance), and integration solutions (e.g. methods for management of highly-subscribed control resources). We identify unique aspects of the ITER TM suppression scheme, which will pulse gyrotrons to drive current within a magnetic island, and turn the drive off following suppression in order to minimize use of auxiliary power and maximize fusion gain. The potential role of active current profile control and approaches to design in ITER are discussed. Finally, issues and approaches to fault handling algorithms are described, along with novel aspects of actuator sharing in ITER.« less

Reducing Design Cycle Time and Cost Through Process Resequencing

NASA Technical Reports Server (NTRS)

Rogers, James L.

2004-01-01

In today's competitive environment, companies are under enormous pressure to reduce the time and cost of their design cycle. One method for reducing both time and cost is to develop an understanding of the flow of the design processes and the effects of the iterative subcycles that are found in complex design projects. Once these aspects are understood, the design manager can make decisions that take advantage of decomposition, concurrent engineering, and parallel processing techniques to reduce the total time and the total cost of the design cycle. One software tool that can aid in this decision-making process is the Design Manager's Aid for Intelligent Decomposition (DeMAID). The DeMAID software minimizes the feedback couplings that create iterative subcycles, groups processes into iterative subcycles, and decomposes the subcycles into a hierarchical structure. The real benefits of producing the best design in the least time and at a minimum cost are obtained from sequencing the processes in the subcycles.

From Intent to Action: An Iterative Engineering Process

ERIC Educational Resources Information Center

Mouton, Patrice; Rodet, Jacques; Vacaresse, Sylvain

2015-01-01

Quite by chance, and over the course of a few haphazard meetings, a Master's degree in "E-learning Design" gradually developed in a Faculty of Economics. Its original and evolving design was the result of an iterative process carried out, not by a single Instructional Designer (ID), but by a full ID team. Over the last 10 years it has…

LOSITAN: a workbench to detect molecular adaptation based on a Fst-outlier method.

PubMed

Antao, Tiago; Lopes, Ana; Lopes, Ricardo J; Beja-Pereira, Albano; Luikart, Gordon

2008-07-28

Testing for selection is becoming one of the most important steps in the analysis of multilocus population genetics data sets. Existing applications are difficult to use, leaving many non-trivial, error-prone tasks to the user. Here we present LOSITAN, a selection detection workbench based on a well evaluated Fst-outlier detection method. LOSITAN greatly facilitates correct approximation of model parameters (e.g., genome-wide average, neutral Fst), provides data import and export functions, iterative contour smoothing and generation of graphics in a easy to use graphical user interface. LOSITAN is able to use modern multi-core processor architectures by locally parallelizing fdist, reducing computation time by half in current dual core machines and with almost linear performance gains in machines with more cores. LOSITAN makes selection detection feasible to a much wider range of users, even for large population genomic datasets, by both providing an easy to use interface and essential functionality to complete the whole selection detection process.

Iterated learning and the evolution of language.

PubMed

Kirby, Simon; Griffiths, Tom; Smith, Kenny

2014-10-01

Iterated learning describes the process whereby an individual learns their behaviour by exposure to another individual's behaviour, who themselves learnt it in the same way. It can be seen as a key mechanism of cultural evolution. We review various methods for understanding how behaviour is shaped by the iterated learning process: computational agent-based simulations; mathematical modelling; and laboratory experiments in humans and non-human animals. We show how this framework has been used to explain the origins of structure in language, and argue that cultural evolution must be considered alongside biological evolution in explanations of language origins. Copyright © 2014 Elsevier Ltd. All rights reserved.

Learning Efficient Sparse and Low Rank Models.

PubMed

Sprechmann, P; Bronstein, A M; Sapiro, G

2015-09-01

Parsimony, including sparsity and low rank, has been shown to successfully model data in numerous machine learning and signal processing tasks. Traditionally, such modeling approaches rely on an iterative algorithm that minimizes an objective function with parsimony-promoting terms. The inherently sequential structure and data-dependent complexity and latency of iterative optimization constitute a major limitation in many applications requiring real-time performance or involving large-scale data. Another limitation encountered by these modeling techniques is the difficulty of their inclusion in discriminative learning scenarios. In this work, we propose to move the emphasis from the model to the pursuit algorithm, and develop a process-centric view of parsimonious modeling, in which a learned deterministic fixed-complexity pursuit process is used in lieu of iterative optimization. We show a principled way to construct learnable pursuit process architectures for structured sparse and robust low rank models, derived from the iteration of proximal descent algorithms. These architectures learn to approximate the exact parsimonious representation at a fraction of the complexity of the standard optimization methods. We also show that appropriate training regimes allow to naturally extend parsimonious models to discriminative settings. State-of-the-art results are demonstrated on several challenging problems in image and audio processing with several orders of magnitude speed-up compared to the exact optimization algorithms.

A Multi-Fidelity Surrogate Model for the Equation of State for Mixtures of Real Gases

NASA Astrophysics Data System (ADS)

Ouellet, Frederick; Park, Chanyoung; Koneru, Rahul; Balachandar, S.; Rollin, Bertrand

2017-11-01

The explosive dispersal of particles is a complex multiphase and multi-species fluid flow problem. In these flows, the products of detonated explosives must be treated as real gases while the ideal gas equation of state is used for the ambient air. As the products expand outward, they mix with the air and create a region where both state equations must be satisfied. One of the most accurate, yet expensive, methods to handle this problem is an algorithm that iterates between both state equations until both pressure and thermal equilibrium are achieved inside of each computational cell. This work creates a multi-fidelity surrogate model to replace this process. This is achieved by using a Kriging model to produce a curve fit which interpolates selected data from the iterative algorithm. The surrogate is optimized for computing speed and model accuracy by varying the number of sampling points chosen to construct the model. The performance of the surrogate with respect to the iterative method is tested in simulations using a finite volume code. The model's computational speed and accuracy are analyzed to show the benefits of this novel approach. This work was supported by the U.S. Department of Energy, National Nuclear Security Administration, Advanced Simulation and Computing Program, as a Cooperative Agreement under the Predictive Science Academic Alliance Program, under Contract No. DE-NA00023.

Analysis of a Multi-Fidelity Surrogate for Handling Real Gas Equations of State

NASA Astrophysics Data System (ADS)

Ouellet, Frederick; Park, Chanyoung; Rollin, Bertrand; Balachandar, S.

2017-06-01

The explosive dispersal of particles is a complex multiphase and multi-species fluid flow problem. In these flows, the detonation products of the explosive must be treated as real gas while the ideal gas equation of state is used for the surrounding air. As the products expand outward from the detonation point, they mix with ambient air and create a mixing region where both state equations must be satisfied. One of the most accurate, yet computationally expensive, methods to handle this problem is an algorithm that iterates between both equations of state until pressure and thermal equilibrium are achieved inside of each computational cell. This work aims to use a multi-fidelity surrogate model to replace this process. A Kriging model is used to produce a curve fit which interpolates selected data from the iterative algorithm using Bayesian statistics. We study the model performance with respect to the iterative method in simulations using a finite volume code. The model's (i) computational speed, (ii) memory requirements and (iii) computational accuracy are analyzed to show the benefits of this novel approach. Also, optimizing the combination of model accuracy and computational speed through the choice of sampling points is explained. This work was supported by the U.S. Department of Energy, National Nuclear Security Administration, Advanced Simulation and Computing Program as a Cooperative Agreement under the Predictive Science Academic Alliance Program under Contract No. DE-NA0002378.

Contribution of ASDEX Upgrade to disruption studies for ITER

NASA Astrophysics Data System (ADS)

Pautasso, G.; Zhang, Y.; Reiter, B.; Giannone, L.; Gruber, O.; Herrmann, A.; Kardaun, O.; Khayrutdinov, K. K.; Lukash, V. E.; Maraschek, M.; Mlynek, A.; Nakamura, Y.; Schneider, W.; Sias, G.; Sugihara, M.; ASDEX Upgrade Team

2011-10-01

This paper describes the most recent contributions of ASDEX Upgrade to ITER in the field of disruption studies. (1) The ITER specifications for the halo current magnitude are based on data collected from several tokamaks and summarized in the plot of the toroidal peaking factor versus the maximum halo current fraction. Even if the maximum halo current in ASDEX Upgrade reaches 50% of the plasma current, the duration of this maximum lasts a fraction of a ms. (2) Long-lasting asymmetries of the halo current are rare and do not give rise to a large asymmetric component of the mechanical forces on the machine. Differently from JET, these asymmetries are neither locked nor exhibit a stationary harmonic structure. (3) Recent work on disruption prediction has concentrated on the search for a simple function of the most relevant plasma parameters, which is able to discriminate between the safe and pre-disruption phases of a discharge. For this purpose, the disruptions of the last four years have been classified into groups and then discriminant analysis is used to select the most significant variables and to derive the discriminant function. (4) The attainment of the critical density for the collisional suppression of the runaway electrons seems to be technically and physically possible on our medium size tokamak. The CO2 interferometer and the AXUV diagnostic provide information on the highly 3D impurity transport process during the whole plasma quench.

Twostep-by-twostep PIRK-type PC methods with continuous output formulas

NASA Astrophysics Data System (ADS)

Cong, Nguyen Huu; Xuan, Le Ngoc

2008-11-01

This paper deals with parallel predictor-corrector (PC) iteration methods based on collocation Runge-Kutta (RK) corrector methods with continuous output formulas for solving nonstiff initial-value problems (IVPs) for systems of first-order differential equations. At nth step, the continuous output formulas are used not only for predicting the stage values in the PC iteration methods but also for calculating the step values at (n+2)th step. In this case, the integration processes can be proceeded twostep-by-twostep. The resulting twostep-by-twostep (TBT) parallel-iterated RK-type (PIRK-type) methods with continuous output formulas (twostep-by-twostep PIRKC methods or TBTPIRKC methods) give us a faster integration process. Fixed stepsize applications of these TBTPIRKC methods to a few widely-used test problems reveal that the new PC methods are much more efficient when compared with the well-known parallel-iterated RK methods (PIRK methods), parallel-iterated RK-type PC methods with continuous output formulas (PIRKC methods) and sequential explicit RK codes DOPRI5 and DOP853 available from the literature.

MODFLOW–LGR—Documentation of ghost node local grid refinement (LGR2) for multiple areas and the boundary flow and head (BFH2) package

USGS Publications Warehouse

Mehl, Steffen W.; Hill, Mary C.

2013-01-01

This report documents the addition of ghost node Local Grid Refinement (LGR2) to MODFLOW-2005, the U.S. Geological Survey modular, transient, three-dimensional, finite-difference groundwater flow model. LGR2 provides the capability to simulate groundwater flow using multiple block-shaped higher-resolution local grids (a child model) within a coarser-grid parent model. LGR2 accomplishes this by iteratively coupling separate MODFLOW-2005 models such that heads and fluxes are balanced across the grid-refinement interface boundary. LGR2 can be used in two-and three-dimensional, steady-state and transient simulations and for simulations of confined and unconfined groundwater systems. Traditional one-way coupled telescopic mesh refinement methods can have large, often undetected, inconsistencies in heads and fluxes across the interface between two model grids. The iteratively coupled ghost-node method of LGR2 provides a more rigorous coupling in which the solution accuracy is controlled by convergence criteria defined by the user. In realistic problems, this can result in substantially more accurate solutions and require an increase in computer processing time. The rigorous coupling enables sensitivity analysis, parameter estimation, and uncertainty analysis that reflects conditions in both model grids. This report describes the method used by LGR2, evaluates accuracy and performance for two-and three-dimensional test cases, provides input instructions, and lists selected input and output files for an example problem. It also presents the Boundary Flow and Head (BFH2) Package, which allows the child and parent models to be simulated independently using the boundary conditions obtained through the iterative process of LGR2.

MODFLOW-2005, the U.S. Geological Survey modular ground-water model - documentation of shared node local grid refinement (LGR) and the boundary flow and head (BFH) package

USGS Publications Warehouse

Mehl, Steffen W.; Hill, Mary C.

2006-01-01

This report documents the addition of shared node Local Grid Refinement (LGR) to MODFLOW-2005, the U.S. Geological Survey modular, transient, three-dimensional, finite-difference ground-water flow model. LGR provides the capability to simulate ground-water flow using one block-shaped higher-resolution local grid (a child model) within a coarser-grid parent model. LGR accomplishes this by iteratively coupling two separate MODFLOW-2005 models such that heads and fluxes are balanced across the shared interfacing boundary. LGR can be used in two-and three-dimensional, steady-state and transient simulations and for simulations of confined and unconfined ground-water systems. Traditional one-way coupled telescopic mesh refinement (TMR) methods can have large, often undetected, inconsistencies in heads and fluxes across the interface between two model grids. The iteratively coupled shared-node method of LGR provides a more rigorous coupling in which the solution accuracy is controlled by convergence criteria defined by the user. In realistic problems, this can result in substantially more accurate solutions and require an increase in computer processing time. The rigorous coupling enables sensitivity analysis, parameter estimation, and uncertainty analysis that reflects conditions in both model grids. This report describes the method used by LGR, evaluates LGR accuracy and performance for two- and three-dimensional test cases, provides input instructions, and lists selected input and output files for an example problem. It also presents the Boundary Flow and Head (BFH) Package, which allows the child and parent models to be simulated independently using the boundary conditions obtained through the iterative process of LGR.

Dynamic load simulator

NASA Technical Reports Server (NTRS)

Joncas, K. P.

1972-01-01

Concepts and techniques for identifying and simulating both the steady state and dynamic characteristics of electrical loads for use during integrated system test and evaluation are discussed. The investigations showed that it is feasible to design and develop interrogation and simulation equipment to perform the desired functions. During the evaluation, actual spacecraft loads were interrogated by stimulating the loads with their normal input voltage and measuring the resultant voltage and current time histories. Elements of the circuits were optimized by an iterative process of selecting element values and comparing the time-domain response of the model with those obtained from the real equipment during interrogation.

Learning to improve iterative repair scheduling

NASA Technical Reports Server (NTRS)

Zweben, Monte; Davis, Eugene

1992-01-01

This paper presents a general learning method for dynamically selecting between repair heuristics in an iterative repair scheduling system. The system employs a version of explanation-based learning called Plausible Explanation-Based Learning (PEBL) that uses multiple examples to confirm conjectured explanations. The basic approach is to conjecture contradictions between a heuristic and statistics that measure the quality of the heuristic. When these contradictions are confirmed, a different heuristic is selected. To motivate the utility of this approach we present an empirical evaluation of the performance of a scheduling system with respect to two different repair strategies. We show that the scheduler that learns to choose between the heuristics outperforms the same scheduler with any one of two heuristics alone.

Multidisciplinary systems optimization by linear decomposition

NASA Technical Reports Server (NTRS)

Sobieski, J.

1984-01-01

In a typical design process major decisions are made sequentially. An illustrated example is given for an aircraft design in which the aerodynamic shape is usually decided first, then the airframe is sized for strength and so forth. An analogous sequence could be laid out for any other major industrial product, for instance, a ship. The loops in the discipline boxes symbolize iterative design improvements carried out within the confines of a single engineering discipline, or subsystem. The loops spanning several boxes depict multidisciplinary design improvement iterations. Omitted for graphical simplicity is parallelism of the disciplinary subtasks. The parallelism is important in order to develop a broad workfront necessary to shorten the design time. If all the intradisciplinary and interdisciplinary iterations were carried out to convergence, the process could yield a numerically optimal design. However, it usually stops short of that because of time and money limitations. This is especially true for the interdisciplinary iterations.

Integrating Low-Cost Rapid Usability Testing into Agile System Development of Healthcare IT: A Methodological Perspective.

PubMed

Kushniruk, Andre W; Borycki, Elizabeth M

2015-01-01

The development of more usable and effective healthcare information systems has become a critical issue. In the software industry methodologies such as agile and iterative development processes have emerged to lead to more effective and usable systems. These approaches highlight focusing on user needs and promoting iterative and flexible development practices. Evaluation and testing of iterative agile development cycles is considered an important part of the agile methodology and iterative processes for system design and re-design. However, the issue of how to effectively integrate usability testing methods into rapid and flexible agile design cycles has remained to be fully explored. In this paper we describe our application of an approach known as low-cost rapid usability testing as it has been applied within agile system development in healthcare. The advantages of the integrative approach are described, along with current methodological considerations.

Kernel-based least squares policy iteration for reinforcement learning.

PubMed

Xu, Xin; Hu, Dewen; Lu, Xicheng

2007-07-01

In this paper, we present a kernel-based least squares policy iteration (KLSPI) algorithm for reinforcement learning (RL) in large or continuous state spaces, which can be used to realize adaptive feedback control of uncertain dynamic systems. By using KLSPI, near-optimal control policies can be obtained without much a priori knowledge on dynamic models of control plants. In KLSPI, Mercer kernels are used in the policy evaluation of a policy iteration process, where a new kernel-based least squares temporal-difference algorithm called KLSTD-Q is proposed for efficient policy evaluation. To keep the sparsity and improve the generalization ability of KLSTD-Q solutions, a kernel sparsification procedure based on approximate linear dependency (ALD) is performed. Compared to the previous works on approximate RL methods, KLSPI makes two progresses to eliminate the main difficulties of existing results. One is the better convergence and (near) optimality guarantee by using the KLSTD-Q algorithm for policy evaluation with high precision. The other is the automatic feature selection using the ALD-based kernel sparsification. Therefore, the KLSPI algorithm provides a general RL method with generalization performance and convergence guarantee for large-scale Markov decision problems (MDPs). Experimental results on a typical RL task for a stochastic chain problem demonstrate that KLSPI can consistently achieve better learning efficiency and policy quality than the previous least squares policy iteration (LSPI) algorithm. Furthermore, the KLSPI method was also evaluated on two nonlinear feedback control problems, including a ship heading control problem and the swing up control of a double-link underactuated pendulum called acrobot. Simulation results illustrate that the proposed method can optimize controller performance using little a priori information of uncertain dynamic systems. It is also demonstrated that KLSPI can be applied to online learning control by incorporating an initial controller to ensure online performance.

Aerodynamic Optimization of Rocket Control Surface Geometry Using Cartesian Methods and CAD Geometry

NASA Technical Reports Server (NTRS)

Nelson, Andrea; Aftosmis, Michael J.; Nemec, Marian; Pulliam, Thomas H.

2004-01-01

Aerodynamic design is an iterative process involving geometry manipulation and complex computational analysis subject to physical constraints and aerodynamic objectives. A design cycle consists of first establishing the performance of a baseline design, which is usually created with low-fidelity engineering tools, and then progressively optimizing the design to maximize its performance. Optimization techniques have evolved from relying exclusively on designer intuition and insight in traditional trial and error methods, to sophisticated local and global search methods. Recent attempts at automating the search through a large design space with formal optimization methods include both database driven and direct evaluation schemes. Databases are being used in conjunction with surrogate and neural network models as a basis on which to run optimization algorithms. Optimization algorithms are also being driven by the direct evaluation of objectives and constraints using high-fidelity simulations. Surrogate methods use data points obtained from simulations, and possibly gradients evaluated at the data points, to create mathematical approximations of a database. Neural network models work in a similar fashion, using a number of high-fidelity database calculations as training iterations to create a database model. Optimal designs are obtained by coupling an optimization algorithm to the database model. Evaluation of the current best design then gives either a new local optima and/or increases the fidelity of the approximation model for the next iteration. Surrogate methods have also been developed that iterate on the selection of data points to decrease the uncertainty of the approximation model prior to searching for an optimal design. The database approximation models for each of these cases, however, become computationally expensive with increase in dimensionality. Thus the method of using optimization algorithms to search a database model becomes problematic as the number of design variables is increased.

Multipoint Optimal Minimum Entropy Deconvolution and Convolution Fix: Application to vibration fault detection

NASA Astrophysics Data System (ADS)

McDonald, Geoff L.; Zhao, Qing

2017-01-01

Minimum Entropy Deconvolution (MED) has been applied successfully to rotating machine fault detection from vibration data, however this method has limitations. A convolution adjustment to the MED definition and solution is proposed in this paper to address the discontinuity at the start of the signal - in some cases causing spurious impulses to be erroneously deconvolved. A problem with the MED solution is that it is an iterative selection process, and will not necessarily design an optimal filter for the posed problem. Additionally, the problem goal in MED prefers to deconvolve a single-impulse, while in rotating machine faults we expect one impulse-like vibration source per rotational period of the faulty element. Maximum Correlated Kurtosis Deconvolution was proposed to address some of these problems, and although it solves the target goal of multiple periodic impulses, it is still an iterative non-optimal solution to the posed problem and only solves for a limited set of impulses in a row. Ideally, the problem goal should target an impulse train as the output goal, and should directly solve for the optimal filter in a non-iterative manner. To meet these goals, we propose a non-iterative deconvolution approach called Multipoint Optimal Minimum Entropy Deconvolution Adjusted (MOMEDA). MOMEDA proposes a deconvolution problem with an infinite impulse train as the goal and the optimal filter solution can be solved for directly. From experimental data on a gearbox with and without a gear tooth chip, we show that MOMEDA and its deconvolution spectrums according to the period between the impulses can be used to detect faults and study the health of rotating machine elements effectively.

Towards programmable plant genetic circuits.

PubMed

Medford, June I; Prasad, Ashok

2016-07-01

Synthetic biology enables the construction of genetic circuits with predictable gene functions in plants. Detailed quantitative descriptions of the transfer function or input-output function for genetic parts (promoters, 5' and 3' untranslated regions, etc.) are collected. These data are then used in computational simulations to determine their robustness and desired properties, thereby enabling the best components to be selected for experimental testing in plants. In addition, the process forms an iterative workflow which allows vast improvement to validated elements with sub-optimal function. These processes enable computational functions such as digital logic in living plants and follow the pathway of technological advances which took us from vacuum tubes to cell phones. © 2016 The Authors The Plant Journal © 2016 John Wiley & Sons Ltd.

Carbon fiber composites application in ITER plasma facing components

NASA Astrophysics Data System (ADS)

Barabash, V.; Akiba, M.; Bonal, J. P.; Federici, G.; Matera, R.; Nakamura, K.; Pacher, H. D.; Rödig, M.; Vieider, G.; Wu, C. H.

1998-10-01

Carbon Fiber Composites (CFCs) are one of the candidate armour materials for the plasma facing components of the International Thermonuclear Experimental Reactor (ITER). For the present reference design, CFC has been selected as armour for the divertor target near the plasma strike point mainly because of unique resistance to high normal and off-normal heat loads. It does not melt under disruptions and might have higher erosion lifetime in comparison with other possible armour materials. Issues related to CFC application in ITER are described in this paper. They include erosion lifetime, tritium codeposition with eroded material and possible methods for the removal of the codeposited layers, neutron irradiation effect, development of joining technologies with heat sink materials, and thermomechanical performance. The status of the development of new advanced CFCs for ITER application is also described. Finally, the remaining R&D needs are critically discussed.

Establishing Operational Access: Insights from the Past for the Future

DTIC Science & Technology

2014-06-01

Combined Bomber Offensive, the Yom Kippur War, and Operation Mole Cricket 19 identifies two tenets that must be incorporated into the next iteration of...Mole Cricket 19 identifies two tenets that must be incorporated into the next iteration of the Joint Operational Access Concept. First, the Joint...They are the Battle of Britain, the Combined Bomber Offensive, the Yom Kippur War, and Operation Mole Cricket 19. These examples were selected

Quantized Iterative Learning Consensus Tracking of Digital Networks With Limited Information Communication.

PubMed

Xiong, Wenjun; Yu, Xinghuo; Chen, Yao; Gao, Jie

2017-06-01

This brief investigates the quantized iterative learning problem for digital networks with time-varying topologies. The information is first encoded as symbolic data and then transmitted. After the data are received, a decoder is used by the receiver to get an estimate of the sender's state. Iterative learning quantized communication is considered in the process of encoding and decoding. A sufficient condition is then presented to achieve the consensus tracking problem in a finite interval using the quantized iterative learning controllers. Finally, simulation results are given to illustrate the usefulness of the developed criterion.

Polynomiography and Chaos

NASA Astrophysics Data System (ADS)

Kalantari, Bahman

Polynomiography is the algorithmic visualization of iterative systems for computing roots of a complex polynomial. It is well known that iterations of a rational function in the complex plane result in chaotic behavior near its Julia set. In one scheme of computing polynomiography for a given polynomial p(z), we select an individual member from the Basic Family, an infinite fundamental family of rational iteration functions that in particular include Newton's. Polynomiography is an excellent means for observing, understanding, and comparing chaotic behavior for variety of iterative systems. Other iterative schemes in polynomiography are possible and result in chaotic behavior of different kinds. In another scheme, the Basic Family is collectively applied to p(z) and the iterates for any seed in the Voronoi cell of a root converge to that root. Polynomiography reveals chaotic behavior of another kind near the boundary of the Voronoi diagram of the roots. We also describe a novel Newton-Ellipsoid iterative system with its own chaos and exhibit images demonstrating polynomiographies of chaotic behavior of different kinds. Finally, we consider chaos for the more general case of polynomiography of complex analytic functions. On the one hand polynomiography is a powerful medium capable of demonstrating chaos in different forms, it is educationally instructive to students and researchers, also it gives rise to numerous research problems. On the other hand, it is a medium resulting in images with enormous aesthetic appeal to general audiences.

Alternative sites for LNG facilities in the Cook Inlet/Kenia Peninsula, Alaska area. Final report

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

Not Available

1975-10-02

The purpose of this study was to analyze alternate LNG sites in the Cook Inlet area, Alaska, with primary emphasis on sites not identified by the El Paso-Alaska LNG Company in Docket No. CP-75-96. The evaluation included a systematic gross elimination process of eleven major subregions of Cook Inlet to eight subregions based upon considerations of land use and status, proximity of volcanos and other detrimental geological features, unsafe approaches for maneuvering and docking transport vessels, and adverse meteorological and marine conditions. This initial elimination process was followed by a more detailed iterative process of location and evaluation of 26more » specific sites in terms of local adverse impacts to biotic communities, human populations, and present land use practices. The analysis and elimination process resulted in the eventual selection and ranking of three sites: (1) Nikiski; (2) Cape Starichkof; (3) Resurrection Bay East. (GRA)« less

Automatic reference selection for quantitative EEG interpretation: identification of diffuse/localised activity and the active earlobe reference, iterative detection of the distribution of EEG rhythms.

PubMed

Wang, Bei; Wang, Xingyu; Ikeda, Akio; Nagamine, Takashi; Shibasaki, Hiroshi; Nakamura, Masatoshi

2014-01-01

EEG (Electroencephalograph) interpretation is important for the diagnosis of neurological disorders. The proper adjustment of the montage can highlight the EEG rhythm of interest and avoid false interpretation. The aim of this study was to develop an automatic reference selection method to identify a suitable reference. The results may contribute to the accurate inspection of the distribution of EEG rhythms for quantitative EEG interpretation. The method includes two pre-judgements and one iterative detection module. The diffuse case is initially identified by pre-judgement 1 when intermittent rhythmic waveforms occur over large areas along the scalp. The earlobe reference or averaged reference is adopted for the diffuse case due to the effect of the earlobe reference depending on pre-judgement 2. An iterative detection algorithm is developed for the localised case when the signal is distributed in a small area of the brain. The suitable averaged reference is finally determined based on the detected focal and distributed electrodes. The presented technique was applied to the pathological EEG recordings of nine patients. One example of the diffuse case is introduced by illustrating the results of the pre-judgements. The diffusely intermittent rhythmic slow wave is identified. The effect of active earlobe reference is analysed. Two examples of the localised case are presented, indicating the results of the iterative detection module. The focal and distributed electrodes are detected automatically during the repeating algorithm. The identification of diffuse and localised activity was satisfactory compared with the visual inspection. The EEG rhythm of interest can be highlighted using a suitable selected reference. The implementation of an automatic reference selection method is helpful to detect the distribution of an EEG rhythm, which can improve the accuracy of EEG interpretation during both visual inspection and automatic interpretation. Copyright © 2013 IPEM. Published by Elsevier Ltd. All rights reserved.

Acceleration of image-based resolution modelling reconstruction using an expectation maximization nested algorithm.

PubMed

Angelis, G I; Reader, A J; Markiewicz, P J; Kotasidis, F A; Lionheart, W R; Matthews, J C

2013-08-07

Recent studies have demonstrated the benefits of a resolution model within iterative reconstruction algorithms in an attempt to account for effects that degrade the spatial resolution of the reconstructed images. However, these algorithms suffer from slower convergence rates, compared to algorithms where no resolution model is used, due to the additional need to solve an image deconvolution problem. In this paper, a recently proposed algorithm, which decouples the tomographic and image deconvolution problems within an image-based expectation maximization (EM) framework, was evaluated. This separation is convenient, because more computational effort can be placed on the image deconvolution problem and therefore accelerate convergence. Since the computational cost of solving the image deconvolution problem is relatively small, multiple image-based EM iterations do not significantly increase the overall reconstruction time. The proposed algorithm was evaluated using 2D simulations, as well as measured 3D data acquired on the high-resolution research tomograph. Results showed that bias reduction can be accelerated by interleaving multiple iterations of the image-based EM algorithm solving the resolution model problem, with a single EM iteration solving the tomographic problem. Significant improvements were observed particularly for voxels that were located on the boundaries between regions of high contrast within the object being imaged and for small regions of interest, where resolution recovery is usually more challenging. Minor differences were observed using the proposed nested algorithm, compared to the single iteration normally performed, when an optimal number of iterations are performed for each algorithm. However, using the proposed nested approach convergence is significantly accelerated enabling reconstruction using far fewer tomographic iterations (up to 70% fewer iterations for small regions). Nevertheless, the optimal number of nested image-based EM iterations is hard to be defined and it should be selected according to the given application.

Region of interest processing for iterative reconstruction in x-ray computed tomography

NASA Astrophysics Data System (ADS)

Kopp, Felix K.; Nasirudin, Radin A.; Mei, Kai; Fehringer, Andreas; Pfeiffer, Franz; Rummeny, Ernst J.; Noël, Peter B.

2015-03-01

The recent advancements in the graphics card technology raised the performance of parallel computing and contributed to the introduction of iterative reconstruction methods for x-ray computed tomography in clinical CT scanners. Iterative maximum likelihood (ML) based reconstruction methods are known to reduce image noise and to improve the diagnostic quality of low-dose CT. However, iterative reconstruction of a region of interest (ROI), especially ML based, is challenging. But for some clinical procedures, like cardiac CT, only a ROI is needed for diagnostics. A high-resolution reconstruction of the full field of view (FOV) consumes unnecessary computation effort that results in a slower reconstruction than clinically acceptable. In this work, we present an extension and evaluation of an existing ROI processing algorithm. Especially improvements for the equalization between regions inside and outside of a ROI are proposed. The evaluation was done on data collected from a clinical CT scanner. The performance of the different algorithms is qualitatively and quantitatively assessed. Our solution to the ROI problem provides an increase in signal-to-noise ratio and leads to visually less noise in the final reconstruction. The reconstruction speed of our technique was observed to be comparable with other previous proposed techniques. The development of ROI processing algorithms in combination with iterative reconstruction will provide higher diagnostic quality in the near future.

A 2D systems approach to iterative learning control for discrete linear processes with zero Markov parameters

NASA Astrophysics Data System (ADS)

Hladowski, Lukasz; Galkowski, Krzysztof; Cai, Zhonglun; Rogers, Eric; Freeman, Chris T.; Lewin, Paul L.

2011-07-01

In this article a new approach to iterative learning control for the practically relevant case of deterministic discrete linear plants with uniform rank greater than unity is developed. The analysis is undertaken in a 2D systems setting that, by using a strong form of stability for linear repetitive processes, allows simultaneous consideration of both trial-to-trial error convergence and along the trial performance, resulting in design algorithms that can be computed using linear matrix inequalities (LMIs). Finally, the control laws are experimentally verified on a gantry robot that replicates a pick and place operation commonly found in a number of applications to which iterative learning control is applicable.

A Technique for Transient Thermal Testing of Thick Structures

NASA Technical Reports Server (NTRS)

Horn, Thomas J.; Richards, W. Lance; Gong, Leslie

1997-01-01

A new open-loop heat flux control technique has been developed to conduct transient thermal testing of thick, thermally-conductive aerospace structures. This technique uses calibration of the radiant heater system power level as a function of heat flux, predicted aerodynamic heat flux, and the properties of an instrumented test article. An iterative process was used to generate open-loop heater power profiles prior to each transient thermal test. Differences between the measured and predicted surface temperatures were used to refine the heater power level command profiles through the iteration process. This iteration process has reduced the effects of environmental and test system design factors, which are normally compensated for by closed-loop temperature control, to acceptable levels. The final revised heater power profiles resulted in measured temperature time histories which deviated less than 25 F from the predicted surface temperatures.

Probabilistic-driven oriented Speckle reducing anisotropic diffusion with application to cardiac ultrasonic images.

PubMed

Vegas-Sanchez-Ferrero, G; Aja-Fernandez, S; Martin-Fernandez, M; Frangi, A F; Palencia, C

2010-01-01

A novel anisotropic diffusion filter is proposed in this work with application to cardiac ultrasonic images. It includes probabilistic models which describe the probability density function (PDF) of tissues and adapts the diffusion tensor to the image iteratively. For this purpose, a preliminary study is performed in order to select the probability models that best fit the stastitical behavior of each tissue class in cardiac ultrasonic images. Then, the parameters of the diffusion tensor are defined taking into account the statistical properties of the image at each voxel. When the structure tensor of the probability of belonging to each tissue is included in the diffusion tensor definition, a better boundaries estimates can be obtained instead of calculating directly the boundaries from the image. This is the main contribution of this work. Additionally, the proposed method follows the statistical properties of the image in each iteration. This is considered as a second contribution since state-of-the-art methods suppose that noise or statistical properties of the image do not change during the filter process.

A Fast Reduced Kernel Extreme Learning Machine.

PubMed

Deng, Wan-Yu; Ong, Yew-Soon; Zheng, Qing-Hua

2016-04-01

In this paper, we present a fast and accurate kernel-based supervised algorithm referred to as the Reduced Kernel Extreme Learning Machine (RKELM). In contrast to the work on Support Vector Machine (SVM) or Least Square SVM (LS-SVM), which identifies the support vectors or weight vectors iteratively, the proposed RKELM randomly selects a subset of the available data samples as support vectors (or mapping samples). By avoiding the iterative steps of SVM, significant cost savings in the training process can be readily attained, especially on Big datasets. RKELM is established based on the rigorous proof of universal learning involving reduced kernel-based SLFN. In particular, we prove that RKELM can approximate any nonlinear functions accurately under the condition of support vectors sufficiency. Experimental results on a wide variety of real world small instance size and large instance size applications in the context of binary classification, multi-class problem and regression are then reported to show that RKELM can perform at competitive level of generalized performance as the SVM/LS-SVM at only a fraction of the computational effort incurred. Copyright © 2015 Elsevier Ltd. All rights reserved.

Performance evaluation approach for the supercritical helium cold circulators of ITER

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

Vaghela, H.; Sarkar, B.; Bhattacharya, R.

2014-01-29

The ITER project design foresees Supercritical Helium (SHe) forced flow cooling for the main cryogenic components, namely, the superconducting (SC) magnets and cryopumps (CP). Therefore, cold circulators have been selected to provide the required SHe mass flow rate to cope with specific operating conditions and technical requirements. Considering the availability impacts of such machines, it has been decided to perform evaluation tests of the cold circulators at operating conditions prior to the series production in order to minimize the project technical risks. A proposal has been conceptualized, evaluated and simulated to perform representative tests of the full scale SHe coldmore » circulators. The objectives of the performance tests include the validation of normal operating condition, transient and off-design operating modes as well as the efficiency measurement. A suitable process and instrumentation diagram of the test valve box (TVB) has been developed to implement the tests at the required thermodynamic conditions. The conceptual engineering design of the TVB has been developed along with the required thermal analysis for the normal operating conditions to support the performance evaluation of the SHe cold circulator.« less

Tungsten coating by ATC plasma spraying on CFC for WEST tokamak

NASA Astrophysics Data System (ADS)

Firdaouss, M.; Desgranges, C.; Hernandez, C.; Mateus, C.; Maier, H.; Böswirth, B.; Greuner, H.; Samaille, F.; Bucalossi, J.; Missirlian, M.

2017-12-01

In the field of fusion experiments using a tokamak, the plasma facing components (PFC) are the closest object to the hot plasma. Due to the plasma-wall interaction, the material composing the PFC may enter the plasma and disturb the experiments. In the past, the main material for PFC was carbon (CFC, graphite), while the future reactors like ITER will be fully metallic, in particular tungsten. The Tore Supra tokamak has been transformed in an x-point divertor fusion device within the frame of the WEST (W (tungsten) Environment in Steady-state Tokamak) project in order to have plasma conditions close to those expected in ITER. The PFC other than the divertor has been coated with W to transform Tore Supra into a fully metallic environment. Different coating techniques have been selected for different kind of PFC. This paper gives an overview on the coating process used for the antennae protection limiter, the associated validation programme and concludes on the adequacy of the W coating with the WEST experimental programme requirements and gives perspectives on the development to be pursued.

Simultaneous optimization of micro-heliostat geometry and field layout using a genetic algorithm

NASA Astrophysics Data System (ADS)

Lazardjani, Mani Yousefpour; Kronhardt, Valentina; Dikta, Gerhard; Göttsche, Joachim

2016-05-01

A new optimization tool for micro-heliostat (MH) geometry and field layout is presented. The method intends simultaneous performance improvement and cost reduction through iteration of heliostat geometry and field layout parameters. This tool was developed primarily for the optimization of a novel micro-heliostat concept, which was developed at Solar-Institut Jülich (SIJ). However, the underlying approach for the optimization can be used for any heliostat type. During the optimization the performance is calculated using the ray-tracing tool SolCal. The costs of the heliostats are calculated by use of a detailed cost function. A genetic algorithm is used to change heliostat geometry and field layout in an iterative process. Starting from an initial setup, the optimization tool generates several configurations of heliostat geometries and field layouts. For each configuration a cost-performance ratio is calculated. Based on that, the best geometry and field layout can be selected in each optimization step. In order to find the best configuration, this step is repeated until no significant improvement in the results is observed.

Ion beam figuring of Φ520mm convex hyperbolic secondary mirror

NASA Astrophysics Data System (ADS)

Meng, Xiaohui; Wang, Yonggang; Li, Ang; Li, Wenqing

2016-10-01

The convex hyperbolic secondary mirror is a Φ520-mm Zerodur lightweight hyperbolic convex mirror. Typically conventional methods like CCOS, stressed-lap polishing are used to manufacture this secondary mirror. Nevertheless, the required surface accuracy cannot be achieved through the use of conventional polishing methods because of the unpredictable behavior of the polishing tools, which leads to an unstable removal rate. Ion beam figuring is an optical fabrication method that provides highly controlled error of previously polished surfaces using a directed, inert and neutralized ion beam to physically sputter material from the optic surface. Several iterations with different ion beam size are selected and optimized to fit different stages of surface figure error and spatial frequency components. Before ion beam figuring, surface figure error of the secondary mirror is 2.5λ p-v, 0.23λ rms, and is improved to 0.12λ p-v, 0.014λ rms in several process iterations. The demonstration clearly shows that ion beam figuring can not only be used to the final correction of aspheric, but also be suitable for polishing the coarse surface of large, complex mirror.

A Real-Time Data Acquisition and Processing Framework Based on FlexRIO FPGA and ITER Fast Plant System Controller

NASA Astrophysics Data System (ADS)

Yang, C.; Zheng, W.; Zhang, M.; Yuan, T.; Zhuang, G.; Pan, Y.

2016-06-01

Measurement and control of the plasma in real-time are critical for advanced Tokamak operation. It requires high speed real-time data acquisition and processing. ITER has designed the Fast Plant System Controllers (FPSC) for these purposes. At J-TEXT Tokamak, a real-time data acquisition and processing framework has been designed and implemented using standard ITER FPSC technologies. The main hardware components of this framework are an Industrial Personal Computer (IPC) with a real-time system and FlexRIO devices based on FPGA. With FlexRIO devices, data can be processed by FPGA in real-time before they are passed to the CPU. The software elements are based on a real-time framework which runs under Red Hat Enterprise Linux MRG-R and uses Experimental Physics and Industrial Control System (EPICS) for monitoring and configuring. That makes the framework accord with ITER FPSC standard technology. With this framework, any kind of data acquisition and processing FlexRIO FPGA program can be configured with a FPSC. An application using the framework has been implemented for the polarimeter-interferometer diagnostic system on J-TEXT. The application is able to extract phase-shift information from the intermediate frequency signal produced by the polarimeter-interferometer diagnostic system and calculate plasma density profile in real-time. Different algorithms implementations on the FlexRIO FPGA are compared in the paper.

Rater variables associated with ITER ratings.

PubMed

Paget, Michael; Wu, Caren; McIlwrick, Joann; Woloschuk, Wayne; Wright, Bruce; McLaughlin, Kevin

2013-10-01

Advocates of holistic assessment consider the ITER a more authentic way to assess performance. But this assessment format is subjective and, therefore, susceptible to rater bias. Here our objective was to study the association between rater variables and ITER ratings. In this observational study our participants were clerks at the University of Calgary and preceptors who completed online ITERs between February 2008 and July 2009. Our outcome variable was global rating on the ITER (rated 1-5), and we used a generalized estimating equation model to identify variables associated with this rating. Students were rated "above expected level" or "outstanding" on 66.4 % of 1050 online ITERs completed during the study period. Two rater variables attenuated ITER ratings: the log transformed time taken to complete the ITER [β = -0.06, 95 % confidence interval (-0.10, -0.02), p = 0.002], and the number of ITERs that a preceptor completed over the time period of the study [β = -0.008 (-0.02, -0.001), p = 0.02]. In this study we found evidence of leniency bias that resulted in two thirds of students being rated above expected level of performance. This leniency bias appeared to be attenuated by delay in ITER completion, and was also blunted in preceptors who rated more students. As all biases threaten the internal validity of the assessment process, further research is needed to confirm these and other sources of rater bias in ITER ratings, and to explore ways of limiting their impact.

eNOSHA, a Free, Open and Flexible Learning Object Repository--An Iterative Development Process for Global User-Friendliness

ERIC Educational Resources Information Center

Mozelius, Peter; Hettiarachchi, Enosha

2012-01-01

This paper describes the iterative development process of a Learning Object Repository (LOR), named eNOSHA. Discussions on a project for a LOR started at the e-Learning Centre (eLC) at The University of Colombo, School of Computing (UCSC) in 2007. The eLC has during the last decade been developing learning content for a nationwide e-learning…

Integrating a Genetic Algorithm Into a Knowledge-Based System for Ordering Complex Design Processes

NASA Technical Reports Server (NTRS)

Rogers, James L.; McCulley, Collin M.; Bloebaum, Christina L.

1996-01-01

The design cycle associated with large engineering systems requires an initial decomposition of the complex system into design processes which are coupled through the transference of output data. Some of these design processes may be grouped into iterative subcycles. In analyzing or optimizing such a coupled system, it is essential to be able to determine the best ordering of the processes within these subcycles to reduce design cycle time and cost. Many decomposition approaches assume the capability is available to determine what design processes and couplings exist and what order of execution will be imposed during the design cycle. Unfortunately, this is often a complex problem and beyond the capabilities of a human design manager. A new feature, a genetic algorithm, has been added to DeMAID (Design Manager's Aid for Intelligent Decomposition) to allow the design manager to rapidly examine many different combinations of ordering processes in an iterative subcycle and to optimize the ordering based on cost, time, and iteration requirements. Two sample test cases are presented to show the effects of optimizing the ordering with a genetic algorithm.

Evolutionary Software Development (Developpement Evolutionnaire de Logiciels)

DTIC Science & Technology

2008-08-01

development processes. While this may be true, frequently it is not. MIL-STD-498 was explicitly introduced to encourage iterative development; ISO /IEC... 12207 was carefully worded not to prohibit iterative development. Yet both standards were widely interpreted as requiring waterfall development, as

Evolutionary Software Development (Developpement evolutionnaire de logiciels)

DTIC Science & Technology

2008-08-01

development processes. While this may be true, frequently it is not. MIL-STD-498 was explicitly introduced to encourage iterative development; ISO /IEC... 12207 was carefully worded not to prohibit iterative development. Yet both standards were widely interpreted as requiring waterfall development, as

Quickprop method to speed up learning process of Artificial Neural Network in money's nominal value recognition case

NASA Astrophysics Data System (ADS)

Swastika, Windra

2017-03-01

A money's nominal value recognition system has been developed using Artificial Neural Network (ANN). ANN with Back Propagation has one disadvantage. The learning process is very slow (or never reach the target) in the case of large number of iteration, weight and samples. One way to speed up the learning process is using Quickprop method. Quickprop method is based on Newton's method and able to speed up the learning process by assuming that the weight adjustment (E) is a parabolic function. The goal is to minimize the error gradient (E'). In our system, we use 5 types of money's nominal value, i.e. 1,000 IDR, 2,000 IDR, 5,000 IDR, 10,000 IDR and 50,000 IDR. One of the surface of each nominal were scanned and digitally processed. There are 40 patterns to be used as training set in ANN system. The effectiveness of Quickprop method in the ANN system was validated by 2 factors, (1) number of iterations required to reach error below 0.1; and (2) the accuracy to predict nominal values based on the input. Our results shows that the use of Quickprop method is successfully reduce the learning process compared to Back Propagation method. For 40 input patterns, Quickprop method successfully reached error below 0.1 for only 20 iterations, while Back Propagation method required 2000 iterations. The prediction accuracy for both method is higher than 90%.

Mixed Material Plasma-Surface Interactions in ITER: Recent Results from the PISCES Group

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

Tynan, George R.; Baldwin, Matthew; Doerner, Russell

This paper summarizes recent PISCES studies focused on the effects associated with mixed species plasmas that are similar in composition to what one might expect in ITER. Formation of nanometer scale whiskerlike features occurs in W surfaces exposed to pure He and mixed D/He plasmas and appears to be associated with the formation of He nanometer-scaled bubbles in the W surface. Studies of Be-W alloy formation in Be-seeded D plasmas suggest that this process may be important in ITER all metal wall operational scenarios. Studies also suggest that BeD formation via chemical sputtering of Be walls may be an importantmore » first wall erosion mechanism. D retention in ITER mixed materials has also been studied. The D release behavior from beryllium co-deposits does not appear to be a diffusion dominated process, but instead is consistent with thermal release from a number of variable trapping energy sites. As a result, the amount of tritium remaining in codeposits in ITER after baking will be determined by the maximum temperature achieved, rather than by the duration of the baking cycle.« less

Six sigma: process of understanding the control and capability of ranitidine hydrochloride tablet.

PubMed

Chabukswar, Ar; Jagdale, Sc; Kuchekar, Bs; Joshi, Vd; Deshmukh, Gr; Kothawade, Hs; Kuckekar, Ab; Lokhande, Pd

2011-01-01

The process of understanding the control and capability (PUCC) is an iterative closed loop process for continuous improvement. It covers the DMAIC toolkit in its three phases. PUCC is an iterative approach that rotates between the three pillars of the process of understanding, process control, and process capability, with each iteration resulting in a more capable and robust process. It is rightly said that being at the top is a marathon and not a sprint. The objective of the six sigma study of Ranitidine hydrochloride tablets is to achieve perfection in tablet manufacturing by reviewing the present robust manufacturing process, to find out ways to improve and modify the process, which will yield tablets that are defect-free and will give more customer satisfaction. The application of six sigma led to an improved process capability, due to the improved sigma level of the process from 1.5 to 4, a higher yield, due to reduced variation and reduction of thick tablets, reduction in packing line stoppages, reduction in re-work by 50%, a more standardized process, with smooth flow and change in coating suspension reconstitution level (8%w/w), a huge cost reduction of approximately Rs.90 to 95 lakhs per annum, an improved overall efficiency by 30% approximately, and improved overall quality of the product.

Six Sigma: Process of Understanding the Control and Capability of Ranitidine Hydrochloride Tablet

PubMed Central

Chabukswar, AR; Jagdale, SC; Kuchekar, BS; Joshi, VD; Deshmukh, GR; Kothawade, HS; Kuckekar, AB; Lokhande, PD

2011-01-01

The process of understanding the control and capability (PUCC) is an iterative closed loop process for continuous improvement. It covers the DMAIC toolkit in its three phases. PUCC is an iterative approach that rotates between the three pillars of the process of understanding, process control, and process capability, with each iteration resulting in a more capable and robust process. It is rightly said that being at the top is a marathon and not a sprint. The objective of the six sigma study of Ranitidine hydrochloride tablets is to achieve perfection in tablet manufacturing by reviewing the present robust manufacturing process, to find out ways to improve and modify the process, which will yield tablets that are defect-free and will give more customer satisfaction. The application of six sigma led to an improved process capability, due to the improved sigma level of the process from 1.5 to 4, a higher yield, due to reduced variation and reduction of thick tablets, reduction in packing line stoppages, reduction in re-work by 50%, a more standardized process, with smooth flow and change in coating suspension reconstitution level (8%w/w), a huge cost reduction of approximately Rs.90 to 95 lakhs per annum, an improved overall efficiency by 30% approximately, and improved overall quality of the product. PMID:21607050

Development of EarthCube Governance: An Agile Approach

NASA Astrophysics Data System (ADS)

Pearthree, G.; Allison, M. L.; Patten, K.

2013-12-01

Governance of geosciences cyberinfrastructure is a complex and essential undertaking, critical in enabling distributed knowledge communities to collaborate and communicate across disciplines, distances, and cultures. Advancing science with respect to 'grand challenges," such as global climate change, weather prediction, and core fundamental science, depends not just on technical cyber systems, but also on social systems for strategic planning, decision-making, project management, learning, teaching, and building a community of practice. Simply put, a robust, agile technical system depends on an equally robust and agile social system. Cyberinfrastructure development is wrapped in social, organizational and governance challenges, which may significantly impede progress. An agile development process is underway for governance of transformative investments in geosciences cyberinfrastructure through the NSF EarthCube initiative. Agile development is iterative and incremental, and promotes adaptive planning and rapid and flexible response. Such iterative deployment across a variety of EarthCube stakeholders encourages transparency, consensus, accountability, and inclusiveness. A project Secretariat acts as the coordinating body, carrying out duties for planning, organizing, communicating, and reporting. A broad coalition of stakeholder groups comprises an Assembly (Mainstream Scientists, Cyberinfrastructure Institutions, Information Technology/Computer Sciences, NSF EarthCube Investigators, Science Communities, EarthCube End-User Workshop Organizers, Professional Societies) to serve as a preliminary venue for identifying, evaluating, and testing potential governance models. To offer opportunity for broader end-user input, a crowd-source approach will engage stakeholders not involved otherwise. An Advisory Committee from the Earth, ocean, atmosphere, social, computer and library sciences is guiding the process from a high-level policy point of view. Developmental evaluators from the social sciences embedded in the project provide real-time review and adjustments. While a large number of agencies and organizations have agreed to participate, in order to ensure an open and inclusive process, community selected leaders yet to be identified will play key roles through an Assembly Advisory Council. Once consensus is reached on a governing framework, a community-selected demonstration governance pilot will help facilitate community convergence on system design.

Identifying and Promoting Best Practices in Residency Application and Selection in a Complex Academic Health Network.

PubMed

Bandiera, Glen; Abrahams, Caroline; Ruetalo, Mariela; Hanson, Mark D; Nickell, Leslie; Spadafora, Salvatore

2015-12-01

Medical education institutions have a social mandate to produce a diverse physician workforce that meets the public's needs. Recent reports have framed the admission process outcome of undergraduate and postgraduate medical education (UGME and PGME) programs as a key determinant of the collective contributions graduating cohorts will make to society, creating a sense of urgency around the issue of who gets accepted. The need for evidence-informed residency application and selection processes is growing because of the increasing size and diversity of the applicant pool and the need for equity, fairness, social accountability, and health human resource planning. The selection literature, however, is dominated by a UGME focus and emphasizes determination of desirable qualities of future physicians and selection instrument reliability and validity. Gaps remain regarding PGME selection, particularly the creation of specialty-specific selection criteria, suitable outcome measures, and reliable selection systems.In this Perspective, the authors describe the University of Toronto's centralized approach to defining system-level best practices for residency application and selection. Over the 2012-2013 academic year, the Best Practices in Application and Selection working group reviewed relevant literature and reports, consulted content experts, surveyed local practices, and conducted iterative stakeholder consultations on draft recommendations. Strong agreement arose around the resulting 13 principles and 24 best practices, which had either empirical support or face validity. These recommendations, which are shared in this article, have been adopted by the university's PGME advisory committee and will inform a national initiative to improve trainees' transition from UGME to PGME in Canada.

Instrumentation for Examining Microbial Response to Changes In Environmental Pressures

NASA Technical Reports Server (NTRS)

Blaich, Justin; Storrs, Aaron; Wang, Jonathan; Ouandji, Cynthia; Arismendi, Dillon; Hernandez, Juliana; Sardesh, Nina; Ibanez, Cory; Owyang, Stephanie; Gentry, Diana

2016-01-01

The Automated Adaptive Directed Evolution Chamber (AADEC) is a device that allows operators to generate a micro-scale analog of real world systems that can be used to model the local-scale effects of climate change on microbial ecosystems. The AADEC uses an artificial environment to expose cultures of micro-organisms to environmental pressures, such as UV-C radiation, chemical toxins, and temperature. The AADEC autonomously exposes micro-organisms to selection pressures. This improves upon standard manual laboratory techniques: the process can take place over a longer period of time, involve more stressors, implement real-time adjustments based on the state of the population, and minimize the risk of contamination. We currently use UV-C radiation as the main selection pressure, UV-C is well studied both for its cell and DNA damaging effects as a type of selection pressure and for its related effectiveness as a mutagen; having these functions united makes it a good choice for a proof of concept. The AADEC roadmap includes expansion to different selection pressures, including heavy metal toxicity, temperature, and other forms of radiation.The AADEC uses closed-loop control to feedback the current state of the culture to the AADEC controller that modifies selection pressure intensity during experimentation, in this case culture density and growth rate. Culture density and growth rate are determined by measuring the optical density of the culture using 600 nm light. An array of 600 nm LEDs illuminate the culture and photodiodes are used to measure the shadow on the opposite side of the chamber.Previous experiments showed that we can produce a million fold increase to UV-C radiation over seven iterations. The most recent implements a microfluidic system that can expose cultures to multiple different selection pressures, perform non-survival based selection, and autonomously perform hundreds of exposure cycles. A scalable pump system gives the ability to pump in various different growth media to individual cultures and introduce chemical toxins during experimentation; AADEC can perform freeze and thaw cycles. We improved our baseline characterization by building a custom UV-C exposure hood, a shutter operates on a preset timer allowing the user to set exposure intensity consistently for multiple iterations.

Development of an automated energy audit protocol for office buildings

NASA Astrophysics Data System (ADS)

Deb, Chirag

This study aims to enhance the building energy audit process, and bring about reduction in time and cost requirements in the conduction of a full physical audit. For this, a total of 5 Energy Service Companies in Singapore have collaborated and provided energy audit reports for 62 office buildings. Several statistical techniques are adopted to analyse these reports. These techniques comprise cluster analysis and development of prediction models to predict energy savings for buildings. The cluster analysis shows that there are 3 clusters of buildings experiencing different levels of energy savings. To understand the effect of building variables on the change in EUI, a robust iterative process for selecting the appropriate variables is developed. The results show that the 4 variables of GFA, non-air-conditioning energy consumption, average chiller plant efficiency and installed capacity of chillers should be taken for clustering. This analysis is extended to the development of prediction models using linear regression and artificial neural networks (ANN). An exhaustive variable selection algorithm is developed to select the input variables for the two energy saving prediction models. The results show that the ANN prediction model can predict the energy saving potential of a given building with an accuracy of +/-14.8%.

Geriatric core competencies for family medicine curriculum and enhanced skills: care of elderly.

PubMed

Charles, Lesley; Triscott, Jean A C; Dobbs, Bonnie M; McKay, Rhianne

2014-06-01

There is a growing mandate for Family Medicine residency programs to directly assess residents' clinical competence in Care of the Elderly (COE). The objectives of this paper are to describe the development and implementation of incremental core competencies for Postgraduate Year (PGY)-I Integrated Geriatrics Family Medicine, PGY-II Geriatrics Rotation Family Medicine, and PGY-III Enhanced Skills COE for COE Diploma residents at a Canadian University. Iterative expert panel process for the development of the core competencies, with a pre-defined process for implementation of the core competencies. Eighty-five core competencies were selected overall by the Working Group, with 57 core competencies selected for the PGY-I/II Family Medicine residents and an additional 28 selected for the PGY-III COE residents. The core competencies follow the CanMEDS Family Medicine roles. Both sets of core competencies are based on consensus. Due to demographic changes, it is essential that Family Physicians have the required skills and knowledge to care for the frail elderly. The core competencies described were developed for PGY-I/II Family Medicine residents and PGY-III Enhanced Skills COE, with a focus on the development of geriatric expertise for those patients that would most benefit.

A model for selecting bioindicators to monitor radionuclide concentrations using Amchitka Island in the Aleutians as a case study.

PubMed

Burger, Joanna

2007-11-01

World War II and the Cold War have left the Unites States, and other Nations, with massive cleanup and remediation tasks for radioactive and other legacy hazardous wastes. While some sites can be cleaned up to acceptable residential risk levels, others will continue to hold hazardous wastes, which must be contained and monitored to protect human health and the environment. While media (soil, sediment, groundwater) monitoring is the usual norm at many radiological waste sites, for some situations (both biological and societal), biomonitoring may provide the necessary information to assure greater peace of mind for local and regional residents, and to protect ecologically valuable buffer lands or waters. In most cases, indicators are selected using scientific expertise and a literature review, but not all selected indicators will seem relevant to stakeholders. In this paper, I provide a model for the inclusion of stakeholders in the development of bioindicators for assessing radionuclide levels of biota in the marine environment around Amchitka Island, in the Aleutian Chain of Alaska. Amchitka was the site of three underground nuclear tests from 1965 to 1971. The process was stakeholder-initiated, stakeholder-driven, and included stakeholders during each phase. Phases included conceptualization, initial selection of biota and radionuclides, refinement of biota and radionuclide target lists, collection of biota, selection of biota and radionuclides for analysis, and selection of biota, tissues, and radionuclides for bioindicators. The process produced site-specific information on biota availability and on radionuclide levels that led to selection of site-appropriate bioindicators. I suggest that the lengthy, iterative, stakeholder-driven process described in this paper results in selection of bioindicators that are accepted by biologists, public health personnel, public-policy makers, resource agencies, regulatory agencies, subsistence hunters/fishers, and a wide range of other stakeholders. The process is applicable to other sites with ecologically important buffer lands or waters, or where contamination issues are contentious.

Improved pressure-velocity coupling algorithm based on minimization of global residual norm

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

Chatwani, A.U.; Turan, A.

1991-01-01

In this paper an improved pressure velocity coupling algorithm is proposed based on the minimization of the global residual norm. The procedure is applied to SIMPLE and SIMPLEC algorithms to automatically select the pressure underrelaxation factor to minimize the global residual norm at each iteration level. Test computations for three-dimensional turbulent, isothermal flow is a toroidal vortex combustor indicate that velocity underrelaxation factors as high as 0.7 can be used to obtain a converged solution in 300 iterations.

RAVE: Rapid Visualization Environment

NASA Technical Reports Server (NTRS)

Klumpar, D. M.; Anderson, Kevin; Simoudis, Avangelos

1994-01-01

Visualization is used in the process of analyzing large, multidimensional data sets. However, the selection and creation of visualizations that are appropriate for the characteristics of a particular data set and the satisfaction of the analyst's goals is difficult. The process consists of three tasks that are performed iteratively: generate, test, and refine. The performance of these tasks requires the utilization of several types of domain knowledge that data analysts do not often have. Existing visualization systems and frameworks do not adequately support the performance of these tasks. In this paper we present the RApid Visualization Environment (RAVE), a knowledge-based system that interfaces with commercial visualization frameworks and assists a data analyst in quickly and easily generating, testing, and refining visualizations. RAVE was used for the visualization of in situ measurement data captured by spacecraft.

Improvements in surface singularity analysis and design methods. [applicable to airfoils

NASA Technical Reports Server (NTRS)

Bristow, D. R.

1979-01-01

The coupling of the combined source vortex distribution of Green's potential flow function with contemporary numerical techniques is shown to provide accurate, efficient, and stable solutions to subsonic inviscid analysis and design problems for multi-element airfoils. The analysis problem is solved by direct calculation of the surface singularity distribution required to satisfy the flow tangency boundary condition. The design or inverse problem is solved by an iteration process. In this process, the geometry and the associated pressure distribution are iterated until the pressure distribution most nearly corresponding to the prescribed design distribution is obtained. Typically, five iteration cycles are required for convergence. A description of the analysis and design method is presented, along with supporting examples.

The second iteration of the Systems Prioritization Method: A systems prioritization and decision-aiding tool for the Waste Isolation Pilot Plant: Volume 2, Summary of technical input and model implementation

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

Prindle, N.H.; Mendenhall, F.T.; Trauth, K.

1996-05-01

The Systems Prioritization Method (SPM) is a decision-aiding tool developed by Sandia National Laboratories (SNL). SPM provides an analytical basis for supporting programmatic decisions for the Waste Isolation Pilot Plant (WIPP) to meet selected portions of the applicable US EPA long-term performance regulations. The first iteration of SPM (SPM-1), the prototype for SPM< was completed in 1994. It served as a benchmark and a test bed for developing the tools needed for the second iteration of SPM (SPM-2). SPM-2, completed in 1995, is intended for programmatic decision making. This is Volume II of the three-volume final report of the secondmore » iteration of the SPM. It describes the technical input and model implementation for SPM-2, and presents the SPM-2 technical baseline and the activities, activity outcomes, outcome probabilities, and the input parameters for SPM-2 analysis.« less

Computational aspects of helicopter trim analysis and damping levels from Floquet theory

NASA Technical Reports Server (NTRS)

Gaonkar, Gopal H.; Achar, N. S.

1992-01-01

Helicopter trim settings of periodic initial state and control inputs are investigated for convergence of Newton iteration in computing the settings sequentially and in parallel. The trim analysis uses a shooting method and a weak version of two temporal finite element methods with displacement formulation and with mixed formulation of displacements and momenta. These three methods broadly represent two main approaches of trim analysis: adaptation of initial-value and finite element boundary-value codes to periodic boundary conditions, particularly for unstable and marginally stable systems. In each method, both the sequential and in-parallel schemes are used and the resulting nonlinear algebraic equations are solved by damped Newton iteration with an optimally selected damping parameter. The impact of damped Newton iteration, including earlier-observed divergence problems in trim analysis, is demonstrated by the maximum condition number of the Jacobian matrices of the iterative scheme and by virtual elimination of divergence. The advantages of the in-parallel scheme over the conventional sequential scheme are also demonstrated.

A Fractal Excursion.

ERIC Educational Resources Information Center

Camp, Dane R.

1991-01-01

After introducing the two-dimensional Koch curve, which is generated by simple recursions on an equilateral triangle, the process is extended to three dimensions with simple recursions on a regular tetrahedron. Included, for both fractal sequences, are iterative formulae, illustrations of the first several iterations, and a sample PASCAL program.…

The application of contraction theory to an iterative formulation of electromagnetic scattering

NASA Technical Reports Server (NTRS)

Brand, J. C.; Kauffman, J. F.

1985-01-01

Contraction theory is applied to an iterative formulation of electromagnetic scattering from periodic structures and a computational method for insuring convergence is developed. A short history of spectral (or k-space) formulation is presented with an emphasis on application to periodic surfaces. To insure a convergent solution of the iterative equation, a process called the contraction corrector method is developed. Convergence properties of previously presented iterative solutions to one-dimensional problems are examined utilizing contraction theory and the general conditions for achieving a convergent solution are explored. The contraction corrector method is then applied to several scattering problems including an infinite grating of thin wires with the solution data compared to previous works.

Fast generating Greenberger-Horne-Zeilinger state via iterative interaction pictures

NASA Astrophysics Data System (ADS)

Huang, Bi-Hua; Chen, Ye-Hong; Wu, Qi-Cheng; Song, Jie; Xia, Yan

2016-10-01

We delve a little deeper into the construction of shortcuts to adiabatic passage for three-level systems by iterative interaction picture (multiple Schrödinger dynamics). As an application example, we use the deduced iterative based shortcuts to rapidly generate the Greenberger-Horne-Zeilinger (GHZ) state in a three-atom system with the help of quantum Zeno dynamics. Numerical simulation shows the dynamics designed by the iterative picture method is physically feasible and the shortcut scheme performs much better than that using the conventional adiabatic passage techniques. Also, the influences of various decoherence processes are discussed by numerical simulation and the results prove that the scheme is fast and robust against decoherence and operational imperfection.

A usability evaluation toolkit for In-Vehicle Information Systems (IVISs).

PubMed

Harvey, Catherine; Stanton, Neville A; Pickering, Carl A; McDonald, Mike; Zheng, Pengjun

2011-05-01

Usability must be defined specifically for the context of use of the particular system under investigation. This specific context of use should also be used to guide the definition of specific usability criteria and the selection of appropriate evaluation methods. There are four principles which can guide the selection of evaluation methods, relating to the information required in the evaluation, the stage at which to apply methods, the resources required and the people involved in the evaluation. This paper presents a framework for the evaluation of usability in the context of In-Vehicle Information Systems (IVISs). This framework guides designers through defining usability criteria for an evaluation, selecting appropriate evaluation methods and applying those methods. These stages form an iterative process of design-evaluation-redesign with the overall aim of improving the usability of IVISs and enhancing the driving experience, without compromising the safety of the driver. Copyright © 2010 Elsevier Ltd and The Ergonomics Society. All rights reserved.

Multi-machine analysis of termination scenarios with comparison to simulations of controlled shutdown of ITER discharges

DOE PAGES

de Vries, Peter C.; Luce, Timothy C.; Bae, Young-soon; ...

2017-11-22

To improve our understanding of the dynamics and control of ITER terminations, a study has been carried out on data from existing tokamaks. The aim of this joint analysis is to compare the assumptions for ITER terminations with the present experience basis. The study examined the parameter ranges in which present day devices operated during their terminations, as well as the dynamics of these parameters. The analysis of a database, built using a selected set of experimental termination cases, showed that, the H-mode density decays slower than the plasma current ramp-down. The consequential increase in f_GW limits the duration ofmore » the H-mode phase or result in disruptions. The lower temperatures after the drop out of H-mode will allow the plasma internal inductance to increase. But vertical stability control remains manageable in ITER at high internal inductance when accompanied by a strong elongation reduction. This will result in ITER terminations remaining longer at low q (q₉₅~3) than most present-day devices during the current ramp-down. A fast power ramp-down leads to a larger change in β_p at the H-L transition, but the experimental data showed that these are manageable for the ITER radial position control. The analysis of JET data shows that radiation and impurity levels significantly alter the H-L transition dynamics. Self-consistent calculations of the impurity content and resulting radiation should be taken into account when modelling ITER termination scenarios. Here, the results from this analysis can be used to better prescribe the inputs for the detailed modelling and preparation of ITER termination scenarios.« less

Multi-machine analysis of termination scenarios with comparison to simulations of controlled shutdown of ITER discharges

NASA Astrophysics Data System (ADS)

de Vries, P. C.; Luce, T. C.; Bae, Y. S.; Gerhardt, S.; Gong, X.; Gribov, Y.; Humphreys, D.; Kavin, A.; Khayrutdinov, R. R.; Kessel, C.; Kim, S. H.; Loarte, A.; Lukash, V. E.; de la Luna, E.; Nunes, I.; Poli, F.; Qian, J.; Reinke, M.; Sauter, O.; Sips, A. C. C.; Snipes, J. A.; Stober, J.; Treutterer, W.; Teplukhina, A. A.; Voitsekhovitch, I.; Woo, M. H.; Wolfe, S.; Zabeo, L.; the Alcator C-MOD Team; the ASDEX Upgrade Team; the DIII-D Team; the EAST Team; contributors, JET; the KSTAR Team; the NSTX-U Team; the TCV Team; IOS members, ITPA; experts

2018-02-01

To improve our understanding of the dynamics and control of ITER terminations, a study has been carried out on data from existing tokamaks. The aim of this joint analysis is to compare the assumptions for ITER terminations with the present experience basis. The study examined the parameter ranges in which present day devices operated during their terminations, as well as the dynamics of these parameters. The analysis of a database, built using a selected set of experimental termination cases, showed that, the H-mode density decays slower than the plasma current ramp-down. The consequential increase in f GW limits the duration of the H-mode phase or result in disruptions. The lower temperatures after the drop out of H-mode will allow the plasma internal inductance to increase. But vertical stability control remains manageable in ITER at high internal inductance when accompanied by a strong elongation reduction. This will result in ITER terminations remaining longer at low q (q 95 ~ 3) than most present-day devices during the current ramp-down. A fast power ramp-down leads to a larger change in β p at the H-L transition, but the experimental data showed that these are manageable for the ITER radial position control. The analysis of JET data shows that radiation and impurity levels significantly alter the H-L transition dynamics. Self-consistent calculations of the impurity content and resulting radiation should be taken into account when modelling ITER termination scenarios. The results from this analysis can be used to better prescribe the inputs for the detailed modelling and preparation of ITER termination scenarios.

Equivalent charge source model based iterative maximum neighbor weight for sparse EEG source localization.

PubMed

Xu, Peng; Tian, Yin; Lei, Xu; Hu, Xiao; Yao, Dezhong

2008-12-01

How to localize the neural electric activities within brain effectively and precisely from the scalp electroencephalogram (EEG) recordings is a critical issue for current study in clinical neurology and cognitive neuroscience. In this paper, based on the charge source model and the iterative re-weighted strategy, proposed is a new maximum neighbor weight based iterative sparse source imaging method, termed as CMOSS (Charge source model based Maximum neighbOr weight Sparse Solution). Different from the weight used in focal underdetermined system solver (FOCUSS) where the weight for each point in the discrete solution space is independently updated in iterations, the new designed weight for each point in each iteration is determined by the source solution of the last iteration at both the point and its neighbors. Using such a new weight, the next iteration may have a bigger chance to rectify the local source location bias existed in the previous iteration solution. The simulation studies with comparison to FOCUSS and LORETA for various source configurations were conducted on a realistic 3-shell head model, and the results confirmed the validation of CMOSS for sparse EEG source localization. Finally, CMOSS was applied to localize sources elicited in a visual stimuli experiment, and the result was consistent with those source areas involved in visual processing reported in previous studies.

Iterative Focused Screening with Biological Fingerprints Identifies Selective Asc-1 Inhibitors Distinct from Traditional High Throughput Screening.

PubMed

Kutchukian, Peter S; Warren, Lee; Magliaro, Brian C; Amoss, Adam; Cassaday, Jason A; O'Donnell, Gregory; Squadroni, Brian; Zuck, Paul; Pascarella, Danette; Culberson, J Chris; Cooke, Andrew J; Hurzy, Danielle; Schlegel, Kelly-Ann Sondra; Thomson, Fiona; Johnson, Eric N; Uebele, Victor N; Hermes, Jeffrey D; Parmentier-Batteur, Sophie; Finley, Michael

2017-02-17

N-methyl-d-aspartate receptors (NMDARs) mediate glutamatergic signaling that is critical to cognitive processes in the central nervous system, and NMDAR hypofunction is thought to contribute to cognitive impairment observed in both schizophrenia and Alzheimer's disease. One approach to enhance the function of NMDAR is to increase the concentration of an NMDAR coagonist, such as glycine or d-serine, in the synaptic cleft. Inhibition of alanine-serine-cysteine transporter-1 (Asc-1), the primary transporter of d-serine, is attractive because the transporter is localized to neurons in brain regions critical to cognitive function, including the hippocampus and cortical layers III and IV, and is colocalized with d-serine and NMDARs. To identify novel Asc-1 inhibitors, two different screening approaches were performed with whole-cell amino acid uptake in heterologous cells stably expressing human Asc-1: (1) a high-throughput screen (HTS) of 3 M compounds measuring 35 S l-cysteine uptake into cells attached to scintillation proximity assay beads in a 1536 well format and (2) an iterative focused screen (IFS) of a 45 000 compound diversity set using a 3 H d-serine uptake assay with a liquid scintillation plate reader in a 384 well format. Critically important for both screening approaches was the implementation of counter screens to remove nonspecific inhibitors of radioactive amino acid uptake. Furthermore, a 15 000 compound expansion step incorporating both on- and off-target data into chemical and biological fingerprint-based models for selection of additional hits enabled the identification of novel Asc-1-selective chemical matter from the IFS that was not identified in the full-collection HTS.

Iterative nonlinear joint transform correlation for the detection of objects in cluttered scenes

NASA Astrophysics Data System (ADS)

Haist, Tobias; Tiziani, Hans J.

1999-03-01

An iterative correlation technique with digital image processing in the feedback loop for the detection of small objects in cluttered scenes is proposed. A scanning aperture is combined with the method in order to improve the immunity against noise and clutter. Multiple reference objects or different views of one object are processed in parallel. We demonstrate the method by detecting a noisy and distorted face in a crowd with a nonlinear joint transform correlator.

Improved Savitzky-Golay-method-based fluorescence subtraction algorithm for rapid recovery of Raman spectra.

PubMed

Chen, Kun; Zhang, Hongyuan; Wei, Haoyun; Li, Yan

2014-08-20

In this paper, we propose an improved subtraction algorithm for rapid recovery of Raman spectra that can substantially reduce the computation time. This algorithm is based on an improved Savitzky-Golay (SG) iterative smoothing method, which involves two key novel approaches: (a) the use of the Gauss-Seidel method and (b) the introduction of a relaxation factor into the iterative procedure. By applying a novel successive relaxation (SG-SR) iterative method to the relaxation factor, additional improvement in the convergence speed over the standard Savitzky-Golay procedure is realized. The proposed improved algorithm (the RIA-SG-SR algorithm), which uses SG-SR-based iteration instead of Savitzky-Golay iteration, has been optimized and validated with a mathematically simulated Raman spectrum, as well as experimentally measured Raman spectra from non-biological and biological samples. The method results in a significant reduction in computing cost while yielding consistent rejection of fluorescence and noise for spectra with low signal-to-fluorescence ratios and varied baselines. In the simulation, RIA-SG-SR achieved 1 order of magnitude improvement in iteration number and 2 orders of magnitude improvement in computation time compared with the range-independent background-subtraction algorithm (RIA). Furthermore the computation time of the experimentally measured raw Raman spectrum processing from skin tissue decreased from 6.72 to 0.094 s. In general, the processing of the SG-SR method can be conducted within dozens of milliseconds, which can provide a real-time procedure in practical situations.

Performing Systematic Literature Reviews with Novices: An Iterative Approach

ERIC Educational Resources Information Center

Lavallée, Mathieu; Robillard, Pierre-N.; Mirsalari, Reza

2014-01-01

Reviewers performing systematic literature reviews require understanding of the review process and of the knowledge domain. This paper presents an iterative approach for conducting systematic literature reviews that addresses the problems faced by reviewers who are novices in one or both levels of understanding. This approach is derived from…

Iterative MMSE Detection for MIMO/BLAST DS-CDMA Systems in Frequency Selective Fading Channels - Achieving High Performance in Fully Loaded Systems

NASA Astrophysics Data System (ADS)

Silva, João Carlos; Souto, Nuno; Cercas, Francisco; Dinis, Rui

A MMSE (Minimum Mean Square Error) DS-CDMA (Direct Sequence-Code Division Multiple Access) receiver coupled with a low-complexity iterative interference suppression algorithm was devised for a MIMO/BLAST (Multiple Input, Multiple Output / Bell Laboratories Layered Space Time) system in order to improve system performance, considering frequency selective fading channels. The scheme is compared against the simple MMSE receiver, for both QPSK and 16QAM modulations, under SISO (Single Input, Single Output) and MIMO systems, the latter with 2Tx by 2Rx and 4Tx by 4Rx (MIMO order 2 and 4 respectively) antennas. To assess its performance in an existing system, the uncoded UMTS HSDPA (High Speed Downlink Packet Access) standard was considered.

Mapping raised bogs with an iterative one-class classification approach

NASA Astrophysics Data System (ADS)

Mack, Benjamin; Roscher, Ribana; Stenzel, Stefanie; Feilhauer, Hannes; Schmidtlein, Sebastian; Waske, Björn

2016-10-01

Land use and land cover maps are one of the most commonly used remote sensing products. In many applications the user only requires a map of one particular class of interest, e.g. a specific vegetation type or an invasive species. One-class classifiers are appealing alternatives to common supervised classifiers because they can be trained with labeled training data of the class of interest only. However, training an accurate one-class classification (OCC) model is challenging, particularly when facing a large image, a small class and few training samples. To tackle these problems we propose an iterative OCC approach. The presented approach uses a biased Support Vector Machine as core classifier. In an iterative pre-classification step a large part of the pixels not belonging to the class of interest is classified. The remaining data is classified by a final classifier with a novel model and threshold selection approach. The specific objective of our study is the classification of raised bogs in a study site in southeast Germany, using multi-seasonal RapidEye data and a small number of training sample. Results demonstrate that the iterative OCC outperforms other state of the art one-class classifiers and approaches for model selection. The study highlights the potential of the proposed approach for an efficient and improved mapping of small classes such as raised bogs. Overall the proposed approach constitutes a feasible approach and useful modification of a regular one-class classifier.

Iterative h-minima-based marker-controlled watershed for cell nucleus segmentation.

PubMed

Koyuncu, Can Fahrettin; Akhan, Ece; Ersahin, Tulin; Cetin-Atalay, Rengul; Gunduz-Demir, Cigdem

2016-04-01

Automated microscopy imaging systems facilitate high-throughput screening in molecular cellular biology research. The first step of these systems is cell nucleus segmentation, which has a great impact on the success of the overall system. The marker-controlled watershed is a technique commonly used by the previous studies for nucleus segmentation. These studies define their markers finding regional minima on the intensity/gradient and/or distance transform maps. They typically use the h-minima transform beforehand to suppress noise on these maps. The selection of the h value is critical; unnecessarily small values do not sufficiently suppress the noise, resulting in false and oversegmented markers, and unnecessarily large ones suppress too many pixels, causing missing and undersegmented markers. Because cell nuclei show different characteristics within an image, the same h value may not work to define correct markers for all the nuclei. To address this issue, in this work, we propose a new watershed algorithm that iteratively identifies its markers, considering a set of different h values. In each iteration, the proposed algorithm defines a set of candidates using a particular h value and selects the markers from those candidates provided that they fulfill the size requirement. Working with widefield fluorescence microscopy images, our experiments reveal that the use of multiple h values in our iterative algorithm leads to better segmentation results, compared to its counterparts. © 2016 International Society for Advancement of Cytometry. © 2016 International Society for Advancement of Cytometry.

Designing an over-the-counter consumer decision-making tool for older adults.

PubMed

Martin-Hammond, Aqueasha M; Abegaz, Tamirat; Gilbert, Juan E

2015-10-01

Older adults are at increased risk of adverse drug events due to medication. Older adults tend to take more medication and are at higher risk of chronic illness. Over-the-counter (OTC) medication does not require healthcare provider oversight and understanding OTC information is heavily dependent on a consumer's ability to understand and use the medication appropriately. Coupling health technology with effective communication is one approach to address the challenge of communicating health and improving health related tasks. However, the success of many health technologies also depends on how well the technology is designed and how well it addresses users needs. This is especially true for the older adult population. This paper describes (1) a formative study performed to understand how to design novel health technology to assist older adults with OTC medication information, and (2) how a user-centered design process helped to refine the initial assumptions of user needs and help to conceptualize the technology. An iterative design process was used. The process included two brainstorming and review sessions with human-computer interaction researchers and design sessions with older adults in the form of semi-structured interviews. Methods and principles of user-centered research and design were used to inform the research design. Two researchers with expertise in human-computer interaction performed expert reviews of early system prototypes. After initial prototypes were developed, seven older adults were engaged in semi-structured interviews to understand usability concerns and features and functionality older adults may find useful for selecting appropriate OTC medication. Eight usability concerns were discovered and addressed in the two rounds of expert review, and nine additional usability concerns were discovered in design sessions with older adults. Five themes emerged from the interview transcripts as recommendations for design. These recommendations represent opportunities for technology such as the one described in this paper to support older adults in the OTC decision-making process. This paper illustrates the use of an iterative user-centered process in the formative stages of design and its usefulness for understanding aspects of the technology design that are useful to older adults when making decisions about OTC medication. The technology support mechanisms included in the initial model were revised based on the results from the iterative design sessions and helped to refine and conceptualize the system being designed. Copyright © 2015 Elsevier Inc. All rights reserved.

Curvelet-domain multiple matching method combined with cubic B-spline function

NASA Astrophysics Data System (ADS)

Wang, Tong; Wang, Deli; Tian, Mi; Hu, Bin; Liu, Chengming

2018-05-01

Since the large amount of surface-related multiple existed in the marine data would influence the results of data processing and interpretation seriously, many researchers had attempted to develop effective methods to remove them. The most successful surface-related multiple elimination method was proposed based on data-driven theory. However, the elimination effect was unsatisfactory due to the existence of amplitude and phase errors. Although the subsequent curvelet-domain multiple-primary separation method achieved better results, poor computational efficiency prevented its application. In this paper, we adopt the cubic B-spline function to improve the traditional curvelet multiple matching method. First, select a little number of unknowns as the basis points of the matching coefficient; second, apply the cubic B-spline function on these basis points to reconstruct the matching array; third, build constraint solving equation based on the relationships of predicted multiple, matching coefficients, and actual data; finally, use the BFGS algorithm to iterate and realize the fast-solving sparse constraint of multiple matching algorithm. Moreover, the soft-threshold method is used to make the method perform better. With the cubic B-spline function, the differences between predicted multiple and original data diminish, which results in less processing time to obtain optimal solutions and fewer iterative loops in the solving procedure based on the L1 norm constraint. The applications to synthetic and field-derived data both validate the practicability and validity of the method.

Modifying the Interface Edge to Control the Electrical Transport Properties of Nanocontacts to Nanowires.

PubMed

Lord, Alex M; Ramasse, Quentin M; Kepaptsoglou, Despoina M; Evans, Jonathan E; Davies, Philip R; Ward, Michael B; Wilks, Steve P

2017-02-08

Selecting the electrical properties of nanomaterials is essential if their potential as manufacturable devices is to be reached. Here, we show that the addition or removal of native semiconductor material at the edge of a nanocontact can be used to determine the electrical transport properties of metal-nanowire interfaces. While the transport properties of as-grown Au nanocatalyst contacts to semiconductor nanowires are well-studied, there are few techniques that have been explored to modify the electrical behavior. In this work, we use an iterative analytical process that directly correlates multiprobe transport measurements with subsequent aberration-corrected scanning transmission electron microscopy to study the effects of chemical processes that create structural changes at the contact interface edge. A strong metal-support interaction that encapsulates the Au nanocontacts over time, adding ZnO material to the edge region, gives rise to ohmic transport behavior due to the enhanced quantum-mechanical tunneling path. Removal of the extraneous material at the Au-nanowire interface eliminates the edge-tunneling path, producing a range of transport behavior that is dependent on the final interface quality. These results demonstrate chemically driven processes that can be factored into nanowire-device design to select the final properties.

Shading correction assisted iterative cone-beam CT reconstruction

NASA Astrophysics Data System (ADS)

Yang, Chunlin; Wu, Pengwei; Gong, Shutao; Wang, Jing; Lyu, Qihui; Tang, Xiangyang; Niu, Tianye

2017-11-01

Recent advances in total variation (TV) technology enable accurate CT image reconstruction from highly under-sampled and noisy projection data. The standard iterative reconstruction algorithms, which work well in conventional CT imaging, fail to perform as expected in cone beam CT (CBCT) applications, wherein the non-ideal physics issues, including scatter and beam hardening, are more severe. These physics issues result in large areas of shading artifacts and cause deterioration to the piecewise constant property assumed in reconstructed images. To overcome this obstacle, we incorporate a shading correction scheme into low-dose CBCT reconstruction and propose a clinically acceptable and stable three-dimensional iterative reconstruction method that is referred to as the shading correction assisted iterative reconstruction. In the proposed method, we modify the TV regularization term by adding a shading compensation image to the reconstructed image to compensate for the shading artifacts while leaving the data fidelity term intact. This compensation image is generated empirically, using image segmentation and low-pass filtering, and updated in the iterative process whenever necessary. When the compensation image is determined, the objective function is minimized using the fast iterative shrinkage-thresholding algorithm accelerated on a graphic processing unit. The proposed method is evaluated using CBCT projection data of the Catphan© 600 phantom and two pelvis patients. Compared with the iterative reconstruction without shading correction, the proposed method reduces the overall CT number error from around 200 HU to be around 25 HU and increases the spatial uniformity by a factor of 20 percent, given the same number of sparsely sampled projections. A clinically acceptable and stable iterative reconstruction algorithm for CBCT is proposed in this paper. Differing from the existing algorithms, this algorithm incorporates a shading correction scheme into the low-dose CBCT reconstruction and achieves more stable optimization path and more clinically acceptable reconstructed image. The method proposed by us does not rely on prior information and thus is practically attractive to the applications of low-dose CBCT imaging in the clinic.

Advances in Global Adjoint Tomography -- Massive Data Assimilation

NASA Astrophysics Data System (ADS)

Ruan, Y.; Lei, W.; Bozdag, E.; Lefebvre, M. P.; Smith, J. A.; Krischer, L.; Tromp, J.

2015-12-01

Azimuthal anisotropy and anelasticity are key to understanding a myriad of processes in Earth's interior. Resolving these properties requires accurate simulations of seismic wave propagation in complex 3-D Earth models and an iterative inversion strategy. In the wake of successes in regional studies(e.g., Chen et al., 2007; Tape et al., 2009, 2010; Fichtner et al., 2009, 2010; Chen et al.,2010; Zhu et al., 2012, 2013; Chen et al., 2015), we are employing adjoint tomography based on a spectral-element method (Komatitsch & Tromp 1999, 2002) on a global scale using the supercomputer ''Titan'' at Oak Ridge National Laboratory. After 15 iterations, we have obtained a high-resolution transversely isotropic Earth model (M15) using traveltime data from 253 earthquakes. To obtain higher resolution images of the emerging new features and to prepare the inversion for azimuthal anisotropy and anelasticity, we expanded the original dataset with approximately 4,220 additional global earthquakes (Mw5.5-7.0) --occurring between 1995 and 2014-- and downloaded 300-minute-long time series for all available data archived at the IRIS Data Management Center, ORFEUS, and F-net. Ocean Bottom Seismograph data from the last decade are also included to maximize data coverage. In order to handle the huge dataset and solve the I/O bottleneck in global adjoint tomography, we implemented a python-based parallel data processing workflow based on the newly developed Adaptable Seismic Data Format (ASDF). With the help of the data selection tool MUSTANG developed by IRIS, we cleaned our dataset and assembled event-based ASDF files for parallel processing. We have started Centroid Moment Tensors (CMT) inversions for all 4,220 earthquakes with the latest model M15, and selected high-quality data for measurement. We will statistically investigate each channel using synthetic seismograms calculated in M15 for updated CMTs and identify problematic channels. In addition to data screening, we also modified the conventional multi-taper method to obtain better frequency-dependent measurements of surface-wave phase and amplitude anomalies, and therefore more accurate adjoint sources, which are particularly important for anelastic tomography. We present a summary of these data culling and processing procedures for global adjoint tomography.

ITER Fusion Energy

ScienceCinema

Holtkamp, Norbert

2018-01-09

ITER (in Latin “the way”) is designed to demonstrate the scientific and technological feasibility of fusion energy. Fusion is the process by which two light atomic nuclei combine to form a heavier over one and thus release energy. In the fusion process two isotopes of hydrogen – deuterium and tritium – fuse together to form a helium atom and a neutron. Thus fusion could provide large scale energy production without greenhouse effects; essentially limitless fuel would be available all over the world. The principal goals of ITER are to generate 500 megawatts of fusion power for periods of 300 to 500 seconds with a fusion power multiplication factor, Q, of at least 10. Q ? 10 (input power 50 MW / output power 500 MW). The ITER Organization was officially established in Cadarache, France, on 24 October 2007. The seven members engaged in the project – China, the European Union, India, Japan, Korea, Russia and the United States – represent more than half the world’s population. The costs for ITER are shared by the seven members. The cost for the construction will be approximately 5.5 billion Euros, a similar amount is foreseen for the twenty-year phase of operation and the subsequent decommissioning.

On the safety of ITER accelerators.

PubMed

Li, Ge

2013-01-01

Three 1 MV/40A accelerators in heating neutral beams (HNB) are on track to be implemented in the International Thermonuclear Experimental Reactor (ITER). ITER may produce 500 MWt of power by 2026 and may serve as a green energy roadmap for the world. They will generate -1 MV 1 h long-pulse ion beams to be neutralised for plasma heating. Due to frequently occurring vacuum sparking in the accelerators, the snubbers are used to limit the fault arc current to improve ITER safety. However, recent analyses of its reference design have raised concerns. General nonlinear transformer theory is developed for the snubber to unify the former snubbers' different design models with a clear mechanism. Satisfactory agreement between theory and tests indicates that scaling up to a 1 MV voltage may be possible. These results confirm the nonlinear process behind transformer theory and map out a reliable snubber design for a safer ITER.

On the convergence of an iterative formulation of the electromagnetic scattering from an infinite grating of thin wires

NASA Technical Reports Server (NTRS)

Brand, J. C.

1985-01-01

Contraction theory is applied to an iterative formulation of electromagnetic scattering from periodic structures and a computational method for insuring convergence is developed. A short history of spectral (or k-space) formulation is presented with an emphasis on application to periodic surfaces. The mathematical background for formulating an iterative equation is covered using straightforward single variable examples including an extension to vector spaces. To insure a convergent solution of the iterative equation, a process called the contraction corrector method is developed. Convergence properties of previously presented iterative solutions to one-dimensional problems are examined utilizing contraction theory and the general conditions for achieving a convergent solution are explored. The contraction corrector method is then applied to several scattering problems including an infinite grating of thin wires with the solution data compared to previous works.

On the safety of ITER accelerators

PubMed Central

Li, Ge

2013-01-01

Three 1 MV/40A accelerators in heating neutral beams (HNB) are on track to be implemented in the International Thermonuclear Experimental Reactor (ITER). ITER may produce 500 MWt of power by 2026 and may serve as a green energy roadmap for the world. They will generate −1 MV 1 h long-pulse ion beams to be neutralised for plasma heating. Due to frequently occurring vacuum sparking in the accelerators, the snubbers are used to limit the fault arc current to improve ITER safety. However, recent analyses of its reference design have raised concerns. General nonlinear transformer theory is developed for the snubber to unify the former snubbers' different design models with a clear mechanism. Satisfactory agreement between theory and tests indicates that scaling up to a 1 MV voltage may be possible. These results confirm the nonlinear process behind transformer theory and map out a reliable snubber design for a safer ITER. PMID:24008267

Single-agent parallel window search

NASA Technical Reports Server (NTRS)

Powley, Curt; Korf, Richard E.

1991-01-01

Parallel window search is applied to single-agent problems by having different processes simultaneously perform iterations of Iterative-Deepening-A(asterisk) (IDA-asterisk) on the same problem but with different cost thresholds. This approach is limited by the time to perform the goal iteration. To overcome this disadvantage, the authors consider node ordering. They discuss how global node ordering by minimum h among nodes with equal f = g + h values can reduce the time complexity of serial IDA-asterisk by reducing the time to perform the iterations prior to the goal iteration. Finally, the two ideas of parallel window search and node ordering are combined to eliminate the weaknesses of each approach while retaining the strengths. The resulting approach, called simply parallel window search, can be used to find a near-optimal solution quickly, improve the solution until it is optimal, and then finally guarantee optimality, depending on the amount of time available.

A fast reconstruction algorithm for fluorescence optical diffusion tomography based on preiteration.

PubMed

Song, Xiaolei; Xiong, Xiaoyun; Bai, Jing

2007-01-01

Fluorescence optical diffusion tomography in the near-infrared (NIR) bandwidth is considered to be one of the most promising ways for noninvasive molecular-based imaging. Many reconstructive approaches to it utilize iterative methods for data inversion. However, they are time-consuming and they are far from meeting the real-time imaging demands. In this work, a fast preiteration algorithm based on the generalized inverse matrix is proposed. This method needs only one step of matrix-vector multiplication online, by pushing the iteration process to be executed offline. In the preiteration process, the second-order iterative format is employed to exponentially accelerate the convergence. Simulations based on an analytical diffusion model show that the distribution of fluorescent yield can be well estimated by this algorithm and the reconstructed speed is remarkably increased.

Improvement of tritium accountancy technology for ITER fuel cycle safety enhancement

NASA Astrophysics Data System (ADS)

O'hira, S.; Hayashi, T.; Nakamura, H.; Kobayashi, K.; Tadokoro, T.; Nakamura, H.; Itoh, T.; Yamanishi, T.; Kawamura, Y.; Iwai, Y.; Arita, T.; Maruyama, T.; Kakuta, T.; Konishi, S.; Enoeda, M.; Yamada, M.; Suzuki, T.; Nishi, M.; Nagashima, T.; Ohta, M.

2000-03-01

In order to improve the safe handling and control of tritium for the ITER fuel cycle, effective in situ tritium accounting methods have been developed at the Tritium Process Laboratory in the Japan Atomic Energy Research Institute under one of the ITER-EDA R&D tasks. The remote and multilocation analysis of process gases by an application of laser Raman spectroscopy developed and tested could provide a measurement of hydrogen isotope gases with a detection limit of 0.3 kPa analytical periods of 120 s. An in situ tritium inventory measurement by application of a `self-assaying' storage bed with 25 g tritium capacity could provide a measurement with the required detection limit of less than 1% and a design proof of a bed with 100 g tritium capacity.

Radiofrequency pulse design using nonlinear gradient magnetic fields.

PubMed

Kopanoglu, Emre; Constable, R Todd

2015-09-01

An iterative k-space trajectory and radiofrequency (RF) pulse design method is proposed for excitation using nonlinear gradient magnetic fields. The spatial encoding functions (SEFs) generated by nonlinear gradient fields are linearly dependent in Cartesian coordinates. Left uncorrected, this may lead to flip angle variations in excitation profiles. In the proposed method, SEFs (k-space samples) are selected using a matching pursuit algorithm, and the RF pulse is designed using a conjugate gradient algorithm. Three variants of the proposed approach are given: the full algorithm, a computationally cheaper version, and a third version for designing spoke-based trajectories. The method is demonstrated for various target excitation profiles using simulations and phantom experiments. The method is compared with other iterative (matching pursuit and conjugate gradient) and noniterative (coordinate-transformation and Jacobian-based) pulse design methods as well as uniform density spiral and EPI trajectories. The results show that the proposed method can increase excitation fidelity. An iterative method for designing k-space trajectories and RF pulses using nonlinear gradient fields is proposed. The method can either be used for selecting the SEFs individually to guide trajectory design, or can be adapted to design and optimize specific trajectories of interest. © 2014 Wiley Periodicals, Inc.

Automatic extraction of the mid-sagittal plane using an ICP variant

NASA Astrophysics Data System (ADS)

Fieten, Lorenz; Eschweiler, Jörg; de la Fuente, Matías; Gravius, Sascha; Radermacher, Klaus

2008-03-01

Precise knowledge of the mid-sagittal plane is important for the assessment and correction of several deformities. Furthermore, the mid-sagittal plane can be used for the definition of standardized coordinate systems such as pelvis or skull coordinate systems. A popular approach for mid-sagittal plane computation is based on the selection of anatomical landmarks located either directly on the plane or symmetrically to it. However, the manual selection of landmarks is a tedious, time-consuming and error-prone task, which requires great care. In order to overcome this drawback, previously it was suggested to use the iterative closest point (ICP) algorithm: After an initial mirroring of the data points on a default mirror plane, the mirrored data points should be registered iteratively to the model points using rigid transforms. Finally, a reflection transform approximating the cumulative transform could be extracted. In this work, we present an ICP variant for the iterative optimization of the reflection parameters. It is based on a closed-form solution to the least-squares problem of matching data points to model points using a reflection. In experiments on CT pelvis and skull datasets our method showed a better ability to match homologous areas.

Working set selection using functional gain for LS-SVM.

PubMed

Bo, Liefeng; Jiao, Licheng; Wang, Ling

2007-09-01

The efficiency of sequential minimal optimization (SMO) depends strongly on the working set selection. This letter shows how the improvement of SMO in each iteration, named the functional gain (FG), is used to select the working set for least squares support vector machine (LS-SVM). We prove the convergence of the proposed method and give some theoretical support for its performance. Empirical comparisons demonstrate that our method is superior to the maximum violating pair (MVP) working set selection.

Iterative Authoring Using Story Generation Feedback: Debugging or Co-creation?

NASA Astrophysics Data System (ADS)

Swartjes, Ivo; Theune, Mariët

We explore the role that story generation feedback may play within the creative process of interactive story authoring. While such feedback is often used as 'debugging' information, we explore here a 'co-creation' view, in which the outcome of the story generator influences authorial intent. We illustrate an iterative authoring approach in which each iteration consists of idea generation, implementation and simulation. We find that the tension between authorial intent and the partially uncontrollable story generation outcome may be relieved by taking such a co-creation approach.

Rescheduling with iterative repair

NASA Technical Reports Server (NTRS)

Zweben, Monte; Davis, Eugene; Daun, Brian; Deale, Michael

1992-01-01

This paper presents a new approach to rescheduling called constraint-based iterative repair. This approach gives our system the ability to satisfy domain constraints, address optimization concerns, minimize perturbation to the original schedule, and produce modified schedules quickly. The system begins with an initial, flawed schedule and then iteratively repairs constraint violations until a conflict-free schedule is produced. In an empirical demonstration, we vary the importance of minimizing perturbation and report how fast the system is able to resolve conflicts in a given time bound. These experiments were performed within the domain of Space Shuttle ground processing.

Implementation of Competency-Based Pharmacy Education (CBPE)

PubMed Central

Koster, Andries; Schalekamp, Tom; Meijerman, Irma

2017-01-01

Implementation of competency-based pharmacy education (CBPE) is a time-consuming, complicated process, which requires agreement on the tasks of a pharmacist, commitment, institutional stability, and a goal-directed developmental perspective of all stakeholders involved. In this article the main steps in the development of a fully-developed competency-based pharmacy curriculum (bachelor, master) are described and tips are given for a successful implementation. After the choice for entering into CBPE is made and a competency framework is adopted (step 1), intended learning outcomes are defined (step 2), followed by analyzing the required developmental trajectory (step 3) and the selection of appropriate assessment methods (step 4). Designing the teaching-learning environment involves the selection of learning activities, student experiences, and instructional methods (step 5). Finally, an iterative process of evaluation and adjustment of individual courses, and the curriculum as a whole, is entered (step 6). Successful implementation of CBPE requires a system of effective quality management and continuous professional development as a teacher. In this article suggestions for the organization of CBPE and references to more detailed literature are given, hoping to facilitate the implementation of CBPE. PMID:28970422

Nanoparticle-labeled DNA capture elements for detection and identification of biological agents

NASA Astrophysics Data System (ADS)

Kiel, Johnathan L.; Holwitt, Eric A.; Parker, Jill E.; Vivekananda, Jeevalatha; Franz, Veronica

2004-12-01

Aptamers, synthetic DNA capture elements (DCEs), can be made chemically or in genetically engineered bacteria. DNA capture elements are artificial DNA sequences, from a random pool of sequences, selected for their specific binding to potential biological warfare or terrorism agents. These sequences were selected by an affinity method using filters to which the target agent was attached and the DNA isolated and amplified by polymerase chain reaction (PCR) in an iterative, increasingly stringent, process. The probes can then be conjugated to Quantum Dots and super paramagnetic nanoparticles. The former provide intense, bleach-resistant fluorescent detection of bioagent and the latter provide a means to collect the bioagents with a magnet. The fluorescence can be detected in a flow cytometer, in a fluorescence plate reader, or with a fluorescence microscope. To date, we have made DCEs to Bacillus anthracis spores, Shiga toxin, Venezuelan Equine Encephalitis (VEE) virus, and Francisella tularensis. DCEs can easily distinguish Bacillus anthracis from its nearest relatives, Bacillus cereus and Bacillus thuringiensis. Development of a high through-put process is currently being investigated.

Studies on the behaviour of tritium in components and structure materials of tritium confinement and detritiation systems of ITER

NASA Astrophysics Data System (ADS)

Kobayashi, K.; Isobe, K.; Iwai, Y.; Hayashi, T.; Shu, W.; Nakamura, H.; Kawamura, Y.; Yamada, M.; Suzuki, T.; Miura, H.; Uzawa, M.; Nishikawa, M.; Yamanishi, T.

2007-12-01

Confinement and the removal of tritium are key subjects for the safety of ITER. The ITER buildings are confinement barriers of tritium. In a hot cell, tritium is often released as vapour and is in contact with the inner walls. The inner walls of the ITER tritium plant building will also be exposed to tritium in an accident. The tritium released in the buildings is removed by the atmosphere detritiation systems (ADS), where the tritium is oxidized by catalysts and is removed as water. A special gas of SF6 is used in ITER and is expected to be released in an accident such as a fire. Although the SF6 gas has potential as a catalyst poison, the performance of ADS with the existence of SF6 has not been confirmed as yet. Tritiated water is produced in the regeneration process of ADS and is subsequently processed by the ITER water detritiation system (WDS). One of the key components of the WDS is an electrolysis cell. To overcome the issues in a global tritium confinement, a series of experimental studies have been carried out as an ITER R&D task: (1) tritium behaviour in concrete; (2) the effect of SF6 on the performance of ADS and (3) tritium durability of the electrolysis cell of the ITER-WDS. (1) The tritiated water vapour penetrated up to 50 mm into the concrete from the surface in six months' exposure. The penetration rate of tritium in the concrete was thus appreciably first, the isotope exchange capacity of the cement paste plays an important role in tritium trapping and penetration into concrete materials when concrete is exposed to tritiated water vapour. It is required to evaluate the effect of coating on the penetration rate quantitatively from the actual tritium tests. (2) SF6 gas decreased the detritiation factor of ADS. Since the effect of SF6 depends closely on its concentration, the amount of SF6 released into the tritium handling area in an accident should be reduced by some ideas of arrangement of components in the buildings. (3) It was expected that the electrolysis cell of the ITER-WDS could endure 3 years' operation under the ITER design conditions. Measuring the concentration of the fluorine ions could be a promising technique for monitoring the damage to the electrolysis cell.

Improving Drive Files for Vehicle Road Simulations

NASA Astrophysics Data System (ADS)

Cherng, John G.; Goktan, Ali; French, Mark; Gu, Yi; Jacob, Anil

2001-09-01

Shaker tables are commonly used in laboratories for automotive vehicle component testing to study durability and acoustics performance. An example is development testing of car seats. However, it is difficult to repeat the measured road data perfectly with the response of a shaker table as there are basic differences in dynamic characteristics between a flexible vehicle and substantially rigid shaker table. In addition, there are performance limits in the shaker table drive systems that can limit correlation. In practice, an optimal drive signal for the actuators is created iteratively. During each iteration, the error between the road data and the response data is minimised by an optimising algorithm which is generally a part of the feed back loop of the shake table controller. This study presents a systematic investigation to the errors in time and frequency domains as well as joint time-frequency domain and an evaluation of different digital signal processing techniques that have been used in previous work. In addition, we present an innovative approach that integrates the dynamic characteristics of car seats and the human body into the error-minimising iteration process. We found that the iteration process can be shortened and the error reduced by using a weighting function created by normalising the frequency response function of the car seat. Two road data test sets were used in the study.

A practical guide for nurses in diluent selection for subcutaneous infusion using a syringe driver.

PubMed

McLeod, Fiona; Flowers, Charne

2006-12-01

Appropriate diluent selection in continuous subcutaneous infusion optimises symptom management and client well-being. The responsibility of diluent selection is commonly one of the attending nurse. This paper was developed with the intention of providing nurses with practical instruction for diluent selection when preparing medications for administration subcutaneously using a syringe driver. A literature review was undertaken of published journal databases and published guidelines sites. Recommendations regarding diluent choice were reviewed in two iterations by an expert panel of palliative care nurse clinicians. The principles for diluent selection are presented. They are based primarily on expert opinion level of evidence given a lack of primary research evidence in the area of diluent selection. There is a pressing need for manufacturers' guidance on diluent selection and independent research to establish the impact of diluents on drug and drug combinations when using syringe drivers. Until such time that this evidence is available to guide practice, clinicians need to be trained to inspect solutions and assess the effectiveness of the medication in controlling symptoms. The capacity of this paper to provide practical instruction has been limited by the lack of rigorous evidence available, and indeed, the process of developing this guide identified perhaps more questions than answers available at the present time.

Adaptive Greedy Dictionary Selection for Web Media Summarization.

PubMed

Cong, Yang; Liu, Ji; Sun, Gan; You, Quanzeng; Li, Yuncheng; Luo, Jiebo

2017-01-01

Initializing an effective dictionary is an indispensable step for sparse representation. In this paper, we focus on the dictionary selection problem with the objective to select a compact subset of basis from original training data instead of learning a new dictionary matrix as dictionary learning models do. We first design a new dictionary selection model via l 2,0 norm. For model optimization, we propose two methods: one is the standard forward-backward greedy algorithm, which is not suitable for large-scale problems; the other is based on the gradient cues at each forward iteration and speeds up the process dramatically. In comparison with the state-of-the-art dictionary selection models, our model is not only more effective and efficient, but also can control the sparsity. To evaluate the performance of our new model, we select two practical web media summarization problems: 1) we build a new data set consisting of around 500 users, 3000 albums, and 1 million images, and achieve effective assisted albuming based on our model and 2) by formulating the video summarization problem as a dictionary selection issue, we employ our model to extract keyframes from a video sequence in a more flexible way. Generally, our model outperforms the state-of-the-art methods in both these two tasks.

Optimal Binarization of Gray-Scaled Digital Images via Fuzzy Reasoning

NASA Technical Reports Server (NTRS)

Dominguez, Jesus A. (Inventor); Klinko, Steven J. (Inventor)

2007-01-01

A technique for finding an optimal threshold for binarization of a gray scale image employs fuzzy reasoning. A triangular membership function is employed which is dependent on the degree to which the pixels in the image belong to either the foreground class or the background class. Use of a simplified linear fuzzy entropy factor function facilitates short execution times and use of membership values between 0.0 and 1.0 for improved accuracy. To improve accuracy further, the membership function employs lower and upper bound gray level limits that can vary from image to image and are selected to be equal to the minimum and the maximum gray levels, respectively, that are present in the image to be converted. To identify the optimal binarization threshold, an iterative process is employed in which different possible thresholds are tested and the one providing the minimum fuzzy entropy measure is selected.

Decoding and optimized implementation of SECDED codes over GF(q)

DOEpatents

Ward, H. Lee; Ganti, Anand; Resnick, David R

2013-10-22

A plurality of columns for a check matrix that implements a distance d linear error correcting code are populated by providing a set of vectors from which to populate the columns, and applying to the set of vectors a filter operation that reduces the set by eliminating therefrom all vectors that would, if used to populate the columns, prevent the check matrix from satisfying a column-wise linear independence requirement associated with check matrices of distance d linear codes. One of the vectors from the reduced set may then be selected to populate one of the columns. The filtering and selecting repeats iteratively until either all of the columns are populated or the number of currently unpopulated columns exceeds the number of vectors in the reduced set. Columns for the check matrix may be processed to reduce the amount of logic needed to implement the check matrix in circuit logic.

A conceptual study of the rotor systems research aircraft

NASA Technical Reports Server (NTRS)

1972-01-01

The analytical comparison of the two candidate Rotor Systems Research Aircraft (RSRA) configurations selected by the Government at the completion of Part 1 of the RSRA Conceptual Predesign Study is presented. The purpose of the comparison was to determine the relative suitability of both vehicles for the RSRA missions described in the Government Statement of Work, and to assess their versatility in the testing of new rotor concepts. The analytical comparison was performed primarily with regard to performance and stability and control. A weights, center-of-gravity, and inertia computation was performed for each iteration in the analysis process. The dynamics investigation was not concerned so much with a comparison of the two vehicles, but explored the dynamic problems attending operation of any RSRA operating with large rotor RPM and diameter ranges over large forward speed ranges. Several means of isolating in- and out-of-plane rotor vibrations were analyzed. An optimum isolation scheme was selected.

Design, decoding and optimized implementation of SECDED codes over GF(q)

DOEpatents

Ward, H Lee; Ganti, Anand; Resnick, David R

2014-06-17

A plurality of columns for a check matrix that implements a distance d linear error correcting code are populated by providing a set of vectors from which to populate the columns, and applying to the set of vectors a filter operation that reduces the set by eliminating therefrom all vectors that would, if used to populate the columns, prevent the check matrix from satisfying a column-wise linear independence requirement associated with check matrices of distance d linear codes. One of the vectors from the reduced set may then be selected to populate one of the columns. The filtering and selecting repeats iteratively until either all of the columns are populated or the number of currently unpopulated columns exceeds the number of vectors in the reduced set. Columns for the check matrix may be processed to reduce the amount of logic needed to implement the check matrix in circuit logic.

Decoding and optimized implementation of SECDED codes over GF(q)

DOEpatents

Ward, H Lee; Ganti, Anand; Resnick, David R

2014-11-18

A plurality of columns for a check matrix that implements a distance d linear error correcting code are populated by providing a set of vectors from which to populate the columns, and applying to the set of vectors a filter operation that reduces the set by eliminating therefrom all vectors that would, if used to populate the columns, prevent the check matrix from satisfying a column-wise linear independence requirement associated with check matrices of distance d linear codes. One of the vectors from the reduced set may then be selected to populate one of the columns. The filtering and selecting repeats iteratively until either all of the columns are populated or the number of currently unpopulated columns exceeds the number of vectors in the reduced set. Columns for the check matrix may be processed to reduce the amount of logic needed to implement the check matrix in circuit logic.

Orthogonal Luciferase-Luciferin Pairs for Bioluminescence Imaging.

PubMed

Jones, Krysten A; Porterfield, William B; Rathbun, Colin M; McCutcheon, David C; Paley, Miranda A; Prescher, Jennifer A

2017-02-15

Bioluminescence imaging with luciferase-luciferin pairs is widely used in biomedical research. Several luciferases have been identified in nature, and many have been adapted for tracking cells in whole animals. Unfortunately, the optimal luciferases for imaging in vivo utilize the same substrate and therefore cannot easily differentiate multiple cell types in a single subject. To develop a broader set of distinguishable probes, we crafted custom luciferins that can be selectively processed by engineered luciferases. Libraries of mutant enzymes were iteratively screened with sterically modified luciferins, and orthogonal enzyme-substrate "hits" were identified. These tools produced light when complementary enzyme-substrate partners interacted both in vitro and in cultured cell models. Based on their selectivity, these designer pairs will bolster multicomponent imaging and enable the direct interrogation of cell networks not currently possible with existing tools. Our screening platform is also general and will expedite the identification of more unique luciferases and luciferins, further expanding the bioluminescence toolkit.

A review of active learning approaches to experimental design for uncovering biological networks

PubMed Central

2017-01-01

Various types of biological knowledge describe networks of interactions among elementary entities. For example, transcriptional regulatory networks consist of interactions among proteins and genes. Current knowledge about the exact structure of such networks is highly incomplete, and laboratory experiments that manipulate the entities involved are conducted to test hypotheses about these networks. In recent years, various automated approaches to experiment selection have been proposed. Many of these approaches can be characterized as active machine learning algorithms. Active learning is an iterative process in which a model is learned from data, hypotheses are generated from the model to propose informative experiments, and the experiments yield new data that is used to update the model. This review describes the various models, experiment selection strategies, validation techniques, and successful applications described in the literature; highlights common themes and notable distinctions among methods; and identifies likely directions of future research and open problems in the area. PMID:28570593

Restoration of multichannel microwave radiometric images

NASA Technical Reports Server (NTRS)

Chin, R. T.; Yeh, C. L.; Olson, W. S.

1983-01-01

A constrained iterative image restoration method is applied to multichannel diffraction-limited imagery. This method is based on the Gerchberg-Papoulis algorithm utilizing incomplete information and partial constraints. The procedure is described using the orthogonal projection operators which project onto two prescribed subspaces iteratively. Some of its properties and limitations are also presented. The selection of appropriate constraints was emphasized in a practical application. Multichannel microwave images, each having different spatial resolution, were restored to a common highest resolution to demonstrate the effectiveness of the method. Both noise-free and noisy images were used in this investigation.

Conjecture Mapping to Optimize the Educational Design Research Process

ERIC Educational Resources Information Center

Wozniak, Helen

2015-01-01

While educational design research promotes closer links between practice and theory, reporting its outcomes from iterations across multiple contexts is often constrained by the volumes of data generated, and the context bound nature of the research outcomes. Reports tend to focus on a single iteration of implementation without further research to…

Iterated reaction graphs: simulating complex Maillard reaction pathways.

PubMed

Patel, S; Rabone, J; Russell, S; Tissen, J; Klaffke, W

2001-01-01

This study investigates a new method of simulating a complex chemical system including feedback loops and parallel reactions. The practical purpose of this approach is to model the actual reactions that take place in the Maillard process, a set of food browning reactions, in sufficient detail to be able to predict the volatile composition of the Maillard products. The developed framework, called iterated reaction graphs, consists of two main elements: a soup of molecules and a reaction base of Maillard reactions. An iterative process loops through the reaction base, taking reactants from and feeding products back to the soup. This produces a reaction graph, with molecules as nodes and reactions as arcs. The iterated reaction graph is updated and validated by comparing output with the main products found by classical gas-chromatographic/mass spectrometric analysis. To ensure a realistic output and convergence to desired volatiles only, the approach contains a number of novel elements: rate kinetics are treated as reaction probabilities; only a subset of the true chemistry is modeled; and the reactions are blocked into groups.

Overhead longwave infrared hyperspectral material identification using radiometric models

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

Zelinski, M. E.

Material detection algorithms used in hyperspectral data processing are computationally efficient but can produce relatively high numbers of false positives. Material identification performed as a secondary processing step on detected pixels can help separate true and false positives. This paper presents a material identification processing chain for longwave infrared hyperspectral data of solid materials collected from airborne platforms. The algorithms utilize unwhitened radiance data and an iterative algorithm that determines the temperature, humidity, and ozone of the atmospheric profile. Pixel unmixing is done using constrained linear regression and Bayesian Information Criteria for model selection. The resulting product includes an optimalmore » atmospheric profile and full radiance material model that includes material temperature, abundance values, and several fit statistics. A logistic regression method utilizing all model parameters to improve identification is also presented. This paper details the processing chain and provides justification for the algorithms used. Several examples are provided using modeled data at different noise levels.« less

A fast method to emulate an iterative POCS image reconstruction algorithm.

PubMed

Zeng, Gengsheng L

2017-10-01

Iterative image reconstruction algorithms are commonly used to optimize an objective function, especially when the objective function is nonquadratic. Generally speaking, the iterative algorithms are computationally inefficient. This paper presents a fast algorithm that has one backprojection and no forward projection. This paper derives a new method to solve an optimization problem. The nonquadratic constraint, for example, an edge-preserving denoising constraint is implemented as a nonlinear filter. The algorithm is derived based on the POCS (projections onto projections onto convex sets) approach. A windowed FBP (filtered backprojection) algorithm enforces the data fidelity. An iterative procedure, divided into segments, enforces edge-enhancement denoising. Each segment performs nonlinear filtering. The derived iterative algorithm is computationally efficient. It contains only one backprojection and no forward projection. Low-dose CT data are used for algorithm feasibility studies. The nonlinearity is implemented as an edge-enhancing noise-smoothing filter. The patient studies results demonstrate its effectiveness in processing low-dose x ray CT data. This fast algorithm can be used to replace many iterative algorithms. © 2017 American Association of Physicists in Medicine.

Robust iterative learning control for multi-phase batch processes: an average dwell-time method with 2D convergence indexes

NASA Astrophysics Data System (ADS)

Wang, Limin; Shen, Yiteng; Yu, Jingxian; Li, Ping; Zhang, Ridong; Gao, Furong

2018-01-01

In order to cope with system disturbances in multi-phase batch processes with different dimensions, a hybrid robust control scheme of iterative learning control combined with feedback control is proposed in this paper. First, with a hybrid iterative learning control law designed by introducing the state error, the tracking error and the extended information, the multi-phase batch process is converted into a two-dimensional Fornasini-Marchesini (2D-FM) switched system with different dimensions. Second, a switching signal is designed using the average dwell-time method integrated with the related switching conditions to give sufficient conditions ensuring stable running for the system. Finally, the minimum running time of the subsystems and the control law gains are calculated by solving the linear matrix inequalities. Meanwhile, a compound 2D controller with robust performance is obtained, which includes a robust extended feedback control for ensuring the steady-state tracking error to converge rapidly. The application on an injection molding process displays the effectiveness and superiority of the proposed strategy.

Developing measures of educational change for academic health care teams implementing the chronic care model in teaching practices.

PubMed

Bowen, Judith L; Stevens, David P; Sixta, Connie S; Provost, Lloyd; Johnson, Julie K; Woods, Donna M; Wagner, Edward H

2010-09-01

The Chronic Care Model (CCM) is a multidimensional framework designed to improve care for patients with chronic health conditions. The model strives for productive interactions between informed, activated patients and proactive practice teams, resulting in better clinical outcomes and greater satisfaction. While measures for improving care may be clear, measures of residents' competency to provide chronic care do not exist. This report describes the process used to develop educational measures and results from CCM settings that used them to monitor curricular innovations. Twenty-six academic health care teams participating in the national and California Academic Chronic Care Collaboratives. Using successive discussion groups and surveys, participants engaged in an iterative process to identify desirable and feasible educational measures for curricula that addressed educational objectives linked to the CCM. The measures were designed to facilitate residency programs' abilities to address new accreditation requirements and tested with teams actively engaged in redesigning educational programs. Field notes from each discussion and lists from work groups were synthesized using the CCM framework. Descriptive statistics were used to report survey results and measurement performance. Work groups generated educational objectives and 17 associated measurements. Seventeen (65%) teams provided feasibility and desirability ratings for the 17 measures. Two process measures were selected for use by all teams. Teams reported variable success using the measures. Several teams reported use of additional measures, suggesting more extensive curricular change. Using an iterative process in collaboration with program participants, we successfully defined a set of feasible and desirable education measures for academic health care teams using the CCM. These were used variably to measure the results of curricular changes, while simultaneously addressing requirements for residency accreditation.

Psychosocial work characteristics of personal care and service occupations: a process for developing meaningful measures for a multiethnic workforce.

PubMed

Hoppe, Annekatrin; Heaney, Catherine A; Fujishiro, Kaori; Gong, Fang; Baron, Sherry

2015-01-01

Despite their rapid increase in number, workers in personal care and service occupations are underrepresented in research on psychosocial work characteristics and occupational health. Some of the research challenges stem from the high proportion of immigrants in these occupations. Language barriers, low literacy, and cultural differences as well as their nontraditional work setting (i.e., providing service for one person in his/her home) make generic questionnaire measures inadequate for capturing salient aspects of personal care and service work. This study presents strategies for (1) identifying psychosocial work characteristics of home care workers that may affect their occupational safety and health and (2) creating survey measures that overcome barriers posed by language, low literacy, and cultural differences. We pursued these aims in four phases: (Phase 1) Six focus groups to identify the psychosocial work characteristics affecting the home care workers' occupational safety and health; (Phase 2) Selection of questionnaire items (i.e., questions or statements to assess the target construct) and first round of cognitive interviews (n = 30) to refine the items in an iterative process; (Phase 3) Item revision and second round of cognitive interviews (n = 11); (Phase 4) Quantitative pilot test to ensure the scales' reliability and validity across three language groups (English, Spanish, and Chinese; total n = 404). Analysis of the data from each phase informed the nature of subsequent phases. This iterative process ensured that survey measures not only met the reliability and validity criteria across groups, but were also meaningful to home care workers. This complex process is necessary when conducting research with nontraditional and multilingual worker populations.

Using Negotiated Joining to Construct and Fill Open-ended Roles in Elite Culinary Groups.

PubMed

Tan, Vaughn

2015-03-01

This qualitative study examines membership processes in groups operating in an uncertain environment that prevents them from fully predefining new members' roles. I describe how nine elite high-end, cutting-edge culinary groups in the U.S. and Europe, ranging from innovative restaurants to culinary R&D groups, use negotiated joining-a previously undocumented process-to systematically construct and fill these emergent, open-ended roles. I show that negotiated joining is a consistently patterned, iterative process that begins with a role that both aspirant and target group explicitly understand to be provisional. This provisional role is then jointly modified and constructed by the aspirant and target group through repeated iterations of proposition, validation through trial and evaluation, and selective integration of validated role components. The initially provisional role stabilizes and the aspirant achieves membership if enough role components are validated; otherwise the negotiated joining process is abandoned. Negotiated joining allows the aspirant and target group to learn if a mutually desirable role is likely and, if so, to construct such a role. In addition, the provisional roles in negotiated joining can support absorptive capacity by allowing novel role components to enter target groups through aspirants' efforts to construct stable roles for themselves, while the internal adjustment involved in integrating newly validated role components can have the unintended side effect of supporting adaptation by providing opportunities for the groups to use these novel role components to modify their role structure and goals to suit a changing and uncertain environment. Negotiated joining thus reveals role ambiguity's hitherto unexamined beneficial consequences and provides a foundation for a contingency theory of new-member acquisition.

SU-D-17A-02: Four-Dimensional CBCT Using Conventional CBCT Dataset and Iterative Subtraction Algorithm of a Lung Patient

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

Hu, E; Lasio, G; Yi, B

2014-06-01

Purpose: The Iterative Subtraction Algorithm (ISA) method generates retrospectively a pre-selected motion phase cone-beam CT image from the full motion cone-beam CT acquired at standard rotation speed. This work evaluates ISA method with real lung patient data. Methods: The goal of the ISA algorithm is to extract motion and no- motion components form the full reconstruction CBCT. The workflow consists of subtracting from the full CBCT all of the undesired motion phases and obtain a motion de-blurred single-phase CBCT image, followed by iteration of this subtraction process. ISA is realized as follows: 1) The projections are sorted to various phases,more » and from all phases, a full reconstruction is performed to generate an image CTM. 2) Generate forward projections of CTM at the desired phase projection angles, the subtraction of projection and the forward projection will reconstruct a CTSub1, which diminishes the desired phase component. 3) By adding back the CTSub1 to CTm, no motion CBCT, CTS1, can be computed. 4) CTS1 still contains residual motion component. 5) This residual motion component can be further reduced by iteration.The ISA 4DCBCT technique was implemented using Varian Trilogy accelerator OBI system. To evaluate the method, a lung patient CBCT dataset was used. The reconstruction algorithm is FDK. Results: The single phase CBCT reconstruction generated via ISA successfully isolates the desired motion phase from the full motion CBCT, effectively reducing motion blur. It also shows improved image quality, with reduced streak artifacts with respect to the reconstructions from unprocessed phase-sorted projections only. Conclusion: A CBCT motion de-blurring algorithm, ISA, has been developed and evaluated with lung patient data. The algorithm allows improved visualization of a single phase motion extracted from a standard CBCT dataset. This study has been supported by National Institute of Health through R01CA133539.« less

Formation and termination of runaway beams in ITER disruptions

NASA Astrophysics Data System (ADS)

Martín-Solís, J. R.; Loarte, A.; Lehnen, M.

2017-06-01

A self-consistent analysis of the relevant physics regarding the formation and termination of runaway beams during mitigated disruptions by Ar and Ne injection is presented for selected ITER scenarios with the aim of improving our understanding of the physics underlying the runaway heat loads onto the plasma facing components (PFCs) and identifying open issues for developing and accessing disruption mitigation schemes for ITER. This is carried out by means of simplified models, but still retaining sufficient details of the key physical processes, including: (a) the expected dominant runaway generation mechanisms (avalanche and primary runaway seeds: Dreicer and hot tail runaway generation, tritium decay and Compton scattering of γ rays emitted by the activated wall), (b) effects associated with the plasma and runaway current density profile shape, and (c) corrections to the runaway dynamics to account for the collisions of the runaways with the partially stripped impurity ions, which are found to have strong effects leading to low runaway current generation and low energy conversion during current termination for mitigated disruptions by noble gas injection (particularly for Ne injection) for the shortest current quench times compatible with acceptable forces on the ITER vessel and in-vessel components ({τ\\text{res}}∼ 22~\\text{ms} ). For the case of long current quench times ({τ\\text{res}}∼ 66~\\text{ms} ), runaway beams up to  ∼10 MA can be generated during the disruption current quench and, if the termination of the runaway current is slow enough, the generation of runaways by the avalanche mechanism can play an important role, increasing substantially the energy deposited by the runaways onto the PFCs up to a few hundreds of MJs. Mixed impurity (Ar or Ne) plus deuterium injection proves to be effective in controlling the formation of the runaway current during the current quench, even for the longest current quench times, as well as in decreasing the energy deposited on the runaway electrons during current termination.

Clinical application and validation of an iterative forward projection matching algorithm for permanent brachytherapy seed localization from conebeam-CT x-ray projections.

PubMed

Pokhrel, Damodar; Murphy, Martin J; Todor, Dorin A; Weiss, Elisabeth; Williamson, Jeffrey F

2010-09-01

To experimentally validate a new algorithm for reconstructing the 3D positions of implanted brachytherapy seeds from postoperatively acquired 2D conebeam-CT (CBCT) projection images. The iterative forward projection matching (IFPM) algorithm finds the 3D seed geometry that minimizes the sum of the squared intensity differences between computed projections of an initial estimate of the seed configuration and radiographic projections of the implant. In-house machined phantoms, containing arrays of 12 and 72 seeds, respectively, are used to validate this method. Also, four 103Pd postimplant patients are scanned using an ACUITY digital simulator. Three to ten x-ray images are selected from the CBCT projection set and processed to create binary seed-only images. To quantify IFPM accuracy, the reconstructed seed positions are forward projected and overlaid on the measured seed images to find the nearest-neighbor distance between measured and computed seed positions for each image pair. Also, the estimated 3D seed coordinates are compared to known seed positions in the phantom and clinically obtained VariSeed planning coordinates for the patient data. For the phantom study, seed localization error is (0.58 +/- 0.33) mm. For all four patient cases, the mean registration error is better than 1 mm while compared against the measured seed projections. IFPM converges in 20-28 iterations, with a computation time of about 1.9-2.8 min/ iteration on a 1 GHz processor. The IFPM algorithm avoids the need to match corresponding seeds in each projection as required by standard back-projection methods. The authors' results demonstrate approximately 1 mm accuracy in reconstructing the 3D positions of brachytherapy seeds from the measured 2D projections. This algorithm also successfully localizes overlapping clustered and highly migrated seeds in the implant.

Fast Image Restoration for Spatially Varying Defocus Blur of Imaging Sensor

PubMed Central

Cheong, Hejin; Chae, Eunjung; Lee, Eunsung; Jo, Gwanghyun; Paik, Joonki

2015-01-01

This paper presents a fast adaptive image restoration method for removing spatially varying out-of-focus blur of a general imaging sensor. After estimating the parameters of space-variant point-spread-function (PSF) using the derivative in each uniformly blurred region, the proposed method performs spatially adaptive image restoration by selecting the optimal restoration filter according to the estimated blur parameters. Each restoration filter is implemented in the form of a combination of multiple FIR filters, which guarantees the fast image restoration without the need of iterative or recursive processing. Experimental results show that the proposed method outperforms existing space-invariant restoration methods in the sense of both objective and subjective performance measures. The proposed algorithm can be employed to a wide area of image restoration applications, such as mobile imaging devices, robot vision, and satellite image processing. PMID:25569760

Cooperation and heterogeneity of the autistic mind.

PubMed

Yoshida, Wako; Dziobek, Isabel; Kliemann, Dorit; Heekeren, Hauke R; Friston, Karl J; Dolan, Ray J

2010-06-30

Individuals with autism spectrum conditions (ASCs) have a core difficulty in recursively inferring the intentions of others. The precise cognitive dysfunctions that determine the heterogeneity at the heart of this spectrum, however, remains unclear. Furthermore, it remains possible that impairment in social interaction is not a fundamental deficit but a reflection of deficits in distinct cognitive processes. To better understand heterogeneity within ASCs, we employed a game-theoretic approach to characterize unobservable computational processes implicit in social interactions. Using a social hunting game with autistic adults, we found that a selective difficulty representing the level of strategic sophistication of others, namely inferring others' mindreading strategy, specifically predicts symptom severity. In contrast, a reduced ability in iterative planning was predicted by overall intellectual level. Our findings provide the first quantitative approach that can reveal the underlying computational dysfunctions that generate the autistic "spectrum."

Interactive iterative relative fuzzy connectedness lung segmentation on thoracic 4D dynamic MR images

NASA Astrophysics Data System (ADS)

Tong, Yubing; Udupa, Jayaram K.; Odhner, Dewey; Wu, Caiyun; Zhao, Yue; McDonough, Joseph M.; Capraro, Anthony; Torigian, Drew A.; Campbell, Robert M.

2017-03-01

Lung delineation via dynamic 4D thoracic magnetic resonance imaging (MRI) is necessary for quantitative image analysis for studying pediatric respiratory diseases such as thoracic insufficiency syndrome (TIS). This task is very challenging because of the often-extreme malformations of the thorax in TIS, lack of signal from bone and connective tissues resulting in inadequate image quality, abnormal thoracic dynamics, and the inability of the patients to cooperate with the protocol needed to get good quality images. We propose an interactive fuzzy connectedness approach as a potential practical solution to this difficult problem. Manual segmentation is too labor intensive especially due to the 4D nature of the data and can lead to low repeatability of the segmentation results. Registration-based approaches are somewhat inefficient and may produce inaccurate results due to accumulated registration errors and inadequate boundary information. The proposed approach works in a manner resembling the Iterative Livewire tool but uses iterative relative fuzzy connectedness (IRFC) as the delineation engine. Seeds needed by IRFC are set manually and are propagated from slice-to-slice, decreasing the needed human labor, and then a fuzzy connectedness map is automatically calculated almost instantaneously. If the segmentation is acceptable, the user selects "next" slice. Otherwise, the seeds are refined and the process continues. Although human interaction is needed, an advantage of the method is the high level of efficient user-control on the process and non-necessity to refine the results. Dynamic MRI sequences from 5 pediatric TIS patients involving 39 3D spatial volumes are used to evaluate the proposed approach. The method is compared to two other IRFC strategies with a higher level of automation. The proposed method yields an overall true positive and false positive volume fraction of 0.91 and 0.03, respectively, and Hausdorff boundary distance of 2 mm.

CRISM Hyperspectral Data Filtering with Application to MSL Landing Site Selection

NASA Astrophysics Data System (ADS)

Seelos, F. P.; Parente, M.; Clark, T.; Morgan, F.; Barnouin-Jha, O. S.; McGovern, A.; Murchie, S. L.; Taylor, H.

2009-12-01

We report on the development and implementation of a custom filtering procedure for Compact Reconnaissance Imaging Spectrometer for Mars (CRISM) IR hyperspectral data that is suitable for incorporation into the CRISM Reduced Data Record (RDR) calibration pipeline. Over the course of the Mars Reconnaissance Orbiter (MRO) Primary Science Phase (PSP) and the ongoing Extended Science Phase (ESP) CRISM has operated with an IR detector temperature between ~107 K and ~127 K. This ~20 K range in operational temperature has resulted in variable data quality, with observations acquired at higher detector temperatures exhibiting a marked increase in both systematic and stochastic noise. The CRISM filtering procedure consists of two main data processing capabilities. The primary systematic noise component in CRISM IR data appears as along track or column oriented striping. This is addressed by the robust derivation and application of an inter-column ratio correction frame. The correction frame is developed through the serial evaluation of band specific column ratio statistics and so does not compromise the spectral fidelity of the image cube. The dominant CRISM IR stochastic noise components appear as isolated data spikes or column oriented segments of variable length with erroneous data values. The non-systematic noise is identified and corrected through the application of an iterative-recursive kernel modeling procedure which employs a formal statistical outlier test as the iteration control and recursion termination criterion. This allows the filtering procedure to make a statistically supported determination between high frequency (spatial/spectral) signal and high frequency noise based on the information content of a given multidimensional data kernel. The governing statistical test also allows the kernel filtering procedure to be self regulating and adaptive to the intrinsic noise level in the data. The CRISM IR filtering procedure is scheduled to be incorporated into the next augmentation of the CRISM IR calibration (version 3). The filtering algorithm will be applied to the I/F data (IF) delivered to the Planetary Data System (PDS), but the radiance on sensor data (RA) will remain unfiltered. The development of CRISM hyperspectral analysis products in support of the Mars Science Laboratory (MSL) landing site selection process has motivated the advance of CRISM-specific data processing techniques. The quantitative results of the CRISM IR filtering procedure as applied to CRISM observations acquired in support of MSL landing site selection will be presented.

ACT Payload Shroud Structural Concept Analysis and Optimization

NASA Technical Reports Server (NTRS)

Zalewski, Bart B.; Bednarcyk, Brett A.

2010-01-01

Aerospace structural applications demand a weight efficient design to perform in a cost effective manner. This is particularly true for launch vehicle structures, where weight is the dominant design driver. The design process typically requires many iterations to ensure that a satisfactory minimum weight has been obtained. Although metallic structures can be weight efficient, composite structures can provide additional weight savings due to their lower density and additional design flexibility. This work presents structural analysis and weight optimization of a composite payload shroud for NASA s Ares V heavy lift vehicle. Two concepts, which were previously determined to be efficient for such a structure are evaluated: a hat stiffened/corrugated panel and a fiber reinforced foam sandwich panel. A composite structural optimization code, HyperSizer, is used to optimize the panel geometry, composite material ply orientations, and sandwich core material. HyperSizer enables an efficient evaluation of thousands of potential designs versus multiple strength and stability-based failure criteria across multiple load cases. HyperSizer sizing process uses a global finite element model to obtain element forces, which are statistically processed to arrive at panel-level design-to loads. These loads are then used to analyze each candidate panel design. A near optimum design is selected as the one with the lowest weight that also provides all positive margins of safety. The stiffness of each newly sized panel or beam component is taken into account in the subsequent finite element analysis. Iteration of analysis/optimization is performed to ensure a converged design. Sizing results for the hat stiffened panel concept and the fiber reinforced foam sandwich concept are presented.

Effects of error covariance structure on estimation of model averaging weights and predictive performance

USGS Publications Warehouse

Lu, Dan; Ye, Ming; Meyer, Philip D.; Curtis, Gary P.; Shi, Xiaoqing; Niu, Xu-Feng; Yabusaki, Steve B.

2013-01-01

When conducting model averaging for assessing groundwater conceptual model uncertainty, the averaging weights are often evaluated using model selection criteria such as AIC, AICc, BIC, and KIC (Akaike Information Criterion, Corrected Akaike Information Criterion, Bayesian Information Criterion, and Kashyap Information Criterion, respectively). However, this method often leads to an unrealistic situation in which the best model receives overwhelmingly large averaging weight (close to 100%), which cannot be justified by available data and knowledge. It was found in this study that this problem was caused by using the covariance matrix, CE, of measurement errors for estimating the negative log likelihood function common to all the model selection criteria. This problem can be resolved by using the covariance matrix, Cek, of total errors (including model errors and measurement errors) to account for the correlation between the total errors. An iterative two-stage method was developed in the context of maximum likelihood inverse modeling to iteratively infer the unknown Cek from the residuals during model calibration. The inferred Cek was then used in the evaluation of model selection criteria and model averaging weights. While this method was limited to serial data using time series techniques in this study, it can be extended to spatial data using geostatistical techniques. The method was first evaluated in a synthetic study and then applied to an experimental study, in which alternative surface complexation models were developed to simulate column experiments of uranium reactive transport. It was found that the total errors of the alternative models were temporally correlated due to the model errors. The iterative two-stage method using Cekresolved the problem that the best model receives 100% model averaging weight, and the resulting model averaging weights were supported by the calibration results and physical understanding of the alternative models. Using Cek obtained from the iterative two-stage method also improved predictive performance of the individual models and model averaging in both synthetic and experimental studies.

Adaptively Tuned Iterative Low Dose CT Image Denoising

PubMed Central

Hashemi, SayedMasoud; Paul, Narinder S.; Beheshti, Soosan; Cobbold, Richard S. C.

2015-01-01

Improving image quality is a critical objective in low dose computed tomography (CT) imaging and is the primary focus of CT image denoising. State-of-the-art CT denoising algorithms are mainly based on iterative minimization of an objective function, in which the performance is controlled by regularization parameters. To achieve the best results, these should be chosen carefully. However, the parameter selection is typically performed in an ad hoc manner, which can cause the algorithms to converge slowly or become trapped in a local minimum. To overcome these issues a noise confidence region evaluation (NCRE) method is used, which evaluates the denoising residuals iteratively and compares their statistics with those produced by additive noise. It then updates the parameters at the end of each iteration to achieve a better match to the noise statistics. By combining NCRE with the fundamentals of block matching and 3D filtering (BM3D) approach, a new iterative CT image denoising method is proposed. It is shown that this new denoising method improves the BM3D performance in terms of both the mean square error and a structural similarity index. Moreover, simulations and patient results show that this method preserves the clinically important details of low dose CT images together with a substantial noise reduction. PMID:26089972

Collapse of cooperation in evolving games.

PubMed

Stewart, Alexander J; Plotkin, Joshua B

2014-12-09

Game theory provides a quantitative framework for analyzing the behavior of rational agents. The Iterated Prisoner's Dilemma in particular has become a standard model for studying cooperation and cheating, with cooperation often emerging as a robust outcome in evolving populations. Here we extend evolutionary game theory by allowing players' payoffs as well as their strategies to evolve in response to selection on heritable mutations. In nature, many organisms engage in mutually beneficial interactions and individuals may seek to change the ratio of risk to reward for cooperation by altering the resources they commit to cooperative interactions. To study this, we construct a general framework for the coevolution of strategies and payoffs in arbitrary iterated games. We show that, when there is a tradeoff between the benefits and costs of cooperation, coevolution often leads to a dramatic loss of cooperation in the Iterated Prisoner's Dilemma. The collapse of cooperation is so extreme that the average payoff in a population can decline even as the potential reward for mutual cooperation increases. Depending upon the form of tradeoffs, evolution may even move away from the Iterated Prisoner's Dilemma game altogether. Our work offers a new perspective on the Prisoner's Dilemma and its predictions for cooperation in natural populations; and it provides a general framework to understand the coevolution of strategies and payoffs in iterated interactions.

Applying matching pursuit decomposition time-frequency processing to UGS footstep classification

NASA Astrophysics Data System (ADS)

Larsen, Brett W.; Chung, Hugh; Dominguez, Alfonso; Sciacca, Jacob; Kovvali, Narayan; Papandreou-Suppappola, Antonia; Allee, David R.

2013-06-01

The challenge of rapid footstep detection and classification in remote locations has long been an important area of study for defense technology and national security. Also, as the military seeks to create effective and disposable unattended ground sensors (UGS), computational complexity and power consumption have become essential considerations in the development of classification techniques. In response to these issues, a research project at the Flexible Display Center at Arizona State University (ASU) has experimented with footstep classification using the matching pursuit decomposition (MPD) time-frequency analysis method. The MPD provides a parsimonious signal representation by iteratively selecting matched signal components from a pre-determined dictionary. The resulting time-frequency representation of the decomposed signal provides distinctive features for different types of footsteps, including footsteps during walking or running activities. The MPD features were used in a Bayesian classification method to successfully distinguish between the different activities. The computational cost of the iterative MPD algorithm was reduced, without significant loss in performance, using a modified MPD with a dictionary consisting of signals matched to cadence temporal gait patterns obtained from real seismic measurements. The classification results were demonstrated with real data from footsteps under various conditions recorded using a low-cost seismic sensor.

The impact of initialization procedures on unsupervised unmixing of hyperspectral imagery using the constrained positive matrix factorization

NASA Astrophysics Data System (ADS)

Masalmah, Yahya M.; Vélez-Reyes, Miguel

2007-04-01

The authors proposed in previous papers the use of the constrained Positive Matrix Factorization (cPMF) to perform unsupervised unmixing of hyperspectral imagery. Two iterative algorithms were proposed to compute the cPMF based on the Gauss-Seidel and penalty approaches to solve optimization problems. Results presented in previous papers have shown the potential of the proposed method to perform unsupervised unmixing in HYPERION and AVIRIS imagery. The performance of iterative methods is highly dependent on the initialization scheme. Good initialization schemes can improve convergence speed, whether or not a global minimum is found, and whether or not spectra with physical relevance are retrieved as endmembers. In this paper, different initializations using random selection, longest norm pixels, and standard endmembers selection routines are studied and compared using simulated and real data.

Development of an efficient multigrid method for the NEM form of the multigroup neutron diffusion equation

NASA Astrophysics Data System (ADS)

Al-Chalabi, Rifat M. Khalil

1997-09-01

Development of an improvement to the computational efficiency of the existing nested iterative solution strategy of the Nodal Exapansion Method (NEM) nodal based neutron diffusion code NESTLE is presented. The improvement in the solution strategy is the result of developing a multilevel acceleration scheme that does not suffer from the numerical stalling associated with a number of iterative solution methods. The acceleration scheme is based on the multigrid method, which is specifically adapted for incorporation into the NEM nonlinear iterative strategy. This scheme optimizes the computational interplay between the spatial discretization and the NEM nonlinear iterative solution process through the use of the multigrid method. The combination of the NEM nodal method, calculation of the homogenized, neutron nodal balance coefficients (i.e. restriction operator), efficient underlying smoothing algorithm (power method of NESTLE), and the finer mesh reconstruction algorithm (i.e. prolongation operator), all operating on a sequence of coarser spatial nodes, constitutes the multilevel acceleration scheme employed in this research. Two implementations of the multigrid method into the NESTLE code were examined; the Imbedded NEM Strategy and the Imbedded CMFD Strategy. The main difference in implementation between the two methods is that in the Imbedded NEM Strategy, the NEM solution is required at every MG level. Numerical tests have shown that the Imbedded NEM Strategy suffers from divergence at coarse- grid levels, hence all the results for the different benchmarks presented here were obtained using the Imbedded CMFD Strategy. The novelties in the developed MG method are as follows: the formulation of the restriction and prolongation operators, and the selection of the relaxation method. The restriction operator utilizes a variation of the reactor physics, consistent homogenization technique. The prolongation operator is based upon a variant of the pin power reconstruction methodology. The relaxation method, which is the power method, utilizes a constant coefficient matrix within the NEM non-linear iterative strategy. The choice of the MG nesting within the nested iterative strategy enables the incorporation of other non-linear effects with no additional coding effort. In addition, if an eigenvalue problem is being solved, it remains an eigenvalue problem at all grid levels, simplifying coding implementation. The merit of the developed MG method was tested by incorporating it into the NESTLE iterative solver, and employing it to solve four different benchmark problems. In addition to the base cases, three different sensitivity studies are performed, examining the effects of number of MG levels, homogenized coupling coefficients correction (i.e. restriction operator), and fine-mesh reconstruction algorithm (i.e. prolongation operator). The multilevel acceleration scheme developed in this research provides the foundation for developing adaptive multilevel acceleration methods for steady-state and transient NEM nodal neutron diffusion equations. (Abstract shortened by UMI.)

A novel Iterative algorithm to text segmentation for web born-digital images

NASA Astrophysics Data System (ADS)

Xu, Zhigang; Zhu, Yuesheng; Sun, Ziqiang; Liu, Zhen

2015-07-01

Since web born-digital images have low resolution and dense text atoms, text region over-merging and miss detection are still two open issues to be addressed. In this paper a novel iterative algorithm is proposed to locate and segment text regions. In each iteration, the candidate text regions are generated by detecting Maximally Stable Extremal Region (MSER) with diminishing thresholds, and categorized into different groups based on a new similarity graph, and the texted region groups are identified by applying several features and rules. With our proposed overlap checking method the final well-segmented text regions are selected from these groups in all iterations. Experiments have been carried out on the web born-digital image datasets used for robust reading competition in ICDAR 2011 and 2013, and the results demonstrate that our proposed scheme can significantly reduce both the number of over-merge regions and the lost rate of target atoms, and the overall performance outperforms the best compared with the methods shown in the two competitions in term of recall rate and f-score at the cost of slightly higher computational complexity.

Iterative optimization method for design of quantitative magnetization transfer imaging experiments.

PubMed

Levesque, Ives R; Sled, John G; Pike, G Bruce

2011-09-01

Quantitative magnetization transfer imaging (QMTI) using spoiled gradient echo sequences with pulsed off-resonance saturation can be a time-consuming technique. A method is presented for selection of an optimum experimental design for quantitative magnetization transfer imaging based on the iterative reduction of a discrete sampling of the Z-spectrum. The applicability of the technique is demonstrated for human brain white matter imaging at 1.5 T and 3 T, and optimal designs are produced to target specific model parameters. The optimal number of measurements and the signal-to-noise ratio required for stable parameter estimation are also investigated. In vivo imaging results demonstrate that this optimal design approach substantially improves parameter map quality. The iterative method presented here provides an advantage over free form optimal design methods, in that pragmatic design constraints are readily incorporated. In particular, the presented method avoids clustering and repeated measures in the final experimental design, an attractive feature for the purpose of magnetization transfer model validation. The iterative optimal design technique is general and can be applied to any method of quantitative magnetization transfer imaging. Copyright © 2011 Wiley-Liss, Inc.

SCOUSE: Semi-automated multi-COmponent Universal Spectral-line fitting Engine

NASA Astrophysics Data System (ADS)

Henshaw, J. D.; Longmore, S. N.; Kruijssen, J. M. D.; Davies, B.; Bally, J.; Barnes, A.; Battersby, C.; Burton, M.; Cunningham, M. R.; Dale, J. E.; Ginsburg, A.; Immer, K.; Jones, P. A.; Kendrew, S.; Mills, E. A. C.; Molinari, S.; Moore, T. J. T.; Ott, J.; Pillai, T.; Rathborne, J.; Schilke, P.; Schmiedeke, A.; Testi, L.; Walker, D.; Walsh, A.; Zhang, Q.

2016-01-01

The Semi-automated multi-COmponent Universal Spectral-line fitting Engine (SCOUSE) is a spectral line fitting algorithm that fits Gaussian files to spectral line emission. It identifies the spatial area over which to fit the data and generates a grid of spectral averaging areas (SAAs). The spatially averaged spectra are fitted according to user-provided tolerance levels, and the best fit is selected using the Akaike Information Criterion, which weights the chisq of a best-fitting solution according to the number of free-parameters. A more detailed inspection of the spectra can be performed to improve the fit through an iterative process, after which SCOUSE integrates the new solutions into the solution file.

Geriatric Core Competencies for Family Medicine Curriculum and Enhanced Skills: Care of Elderly

PubMed Central

Charles, Lesley; Triscott, Jean A.C.; Dobbs, Bonnie M.; McKay, Rhianne

2014-01-01

Background There is a growing mandate for Family Medicine residency programs to directly assess residents’ clinical competence in Care of the Elderly (COE). The objectives of this paper are to describe the development and implementation of incremental core competencies for Postgraduate Year (PGY)-I Integrated Geriatrics Family Medicine, PGY-II Geriatrics Rotation Family Medicine, and PGY-III Enhanced Skills COE for COE Diploma residents at a Canadian University. Methods Iterative expert panel process for the development of the core competencies, with a pre-defined process for implementation of the core competencies. Results Eighty-five core competencies were selected overall by the Working Group, with 57 core competencies selected for the PGY-I/II Family Medicine residents and an additional 28 selected for the PGY-III COE residents. The core competencies follow the CanMEDS Family Medicine roles. Both sets of core competencies are based on consensus. Conclusions Due to demographic changes, it is essential that Family Physicians have the required skills and knowledge to care for the frail elderly. The core competencies described were developed for PGY-I/II Family Medicine residents and PGY-III Enhanced Skills COE, with a focus on the development of geriatric expertise for those patients that would most benefit. PMID:24883163

Lung nodule detection from CT scans using 3D convolutional neural networks without candidate selection

NASA Astrophysics Data System (ADS)

Jenuwine, Natalia M.; Mahesh, Sunny N.; Furst, Jacob D.; Raicu, Daniela S.

2018-02-01

Early detection of lung nodules from CT scans is key to improving lung cancer treatment, but poses a significant challenge for radiologists due to the high throughput required of them. Computer-Aided Detection (CADe) systems aim to automatically detect these nodules with computer algorithms, thus improving diagnosis. These systems typically use a candidate selection step, which identifies all objects that resemble nodules, followed by a machine learning classifier which separates true nodules from false positives. We create a CADe system that uses a 3D convolutional neural network (CNN) to detect nodules in CT scans without a candidate selection step. Using data from the LIDC database, we train a 3D CNN to analyze subvolumes from anywhere within a CT scan and output the probability that each subvolume contains a nodule. Once trained, we apply our CNN to detect nodules from entire scans, by systematically dividing the scan into overlapping subvolumes which we input into the CNN to obtain the corresponding probabilities. By enabling our network to process an entire scan, we expect to streamline the detection process while maintaining its effectiveness. Our results imply that with continued training using an iterative training scheme, the one-step approach has the potential to be highly effective.

An iterative analytical technique for the design of interplanetary direct transfer trajectories including perturbations

NASA Astrophysics Data System (ADS)

Parvathi, S. P.; Ramanan, R. V.

2018-06-01

An iterative analytical trajectory design technique that includes perturbations in the departure phase of the interplanetary orbiter missions is proposed. The perturbations such as non-spherical gravity of Earth and the third body perturbations due to Sun and Moon are included in the analytical design process. In the design process, first the design is obtained using the iterative patched conic technique without including the perturbations and then modified to include the perturbations. The modification is based on, (i) backward analytical propagation of the state vector obtained from the iterative patched conic technique at the sphere of influence by including the perturbations, and (ii) quantification of deviations in the orbital elements at periapsis of the departure hyperbolic orbit. The orbital elements at the sphere of influence are changed to nullify the deviations at the periapsis. The analytical backward propagation is carried out using the linear approximation technique. The new analytical design technique, named as biased iterative patched conic technique, does not depend upon numerical integration and all computations are carried out using closed form expressions. The improved design is very close to the numerical design. The design analysis using the proposed technique provides a realistic insight into the mission aspects. Also, the proposed design is an excellent initial guess for numerical refinement and helps arrive at the four distinct design options for a given opportunity.

SACFIR: SDN-Based Application-Aware Centralized Adaptive Flow Iterative Reconfiguring Routing Protocol for WSNs.

PubMed

Aslam, Muhammad; Hu, Xiaopeng; Wang, Fan

2017-12-13

Smart reconfiguration of a dynamic networking environment is offered by the central control of Software-Defined Networking (SDN). Centralized SDN-based management architectures are capable of retrieving global topology intelligence and decoupling the forwarding plane from the control plane. Routing protocols developed for conventional Wireless Sensor Networks (WSNs) utilize limited iterative reconfiguration methods to optimize environmental reporting. However, the challenging networking scenarios of WSNs involve a performance overhead due to constant periodic iterative reconfigurations. In this paper, we propose the SDN-based Application-aware Centralized adaptive Flow Iterative Reconfiguring (SACFIR) routing protocol with the centralized SDN iterative solver controller to maintain the load-balancing between flow reconfigurations and flow allocation cost. The proposed SACFIR's routing protocol offers a unique iterative path-selection algorithm, which initially computes suitable clustering based on residual resources at the control layer and then implements application-aware threshold-based multi-hop report transmissions on the forwarding plane. The operation of the SACFIR algorithm is centrally supervised by the SDN controller residing at the Base Station (BS). This paper extends SACFIR to SDN-based Application-aware Main-value Centralized adaptive Flow Iterative Reconfiguring (SAMCFIR) to establish both proactive and reactive reporting. The SAMCFIR transmission phase enables sensor nodes to trigger direct transmissions for main-value reports, while in the case of SACFIR, all reports follow computed routes. Our SDN-enabled proposed models adjust the reconfiguration period according to the traffic burden on sensor nodes, which results in heterogeneity awareness, load-balancing and application-specific reconfigurations of WSNs. Extensive experimental simulation-based results show that SACFIR and SAMCFIR yield the maximum scalability, network lifetime and stability period when compared to existing routing protocols.

Evaluation of integration methods for hybrid simulation of complex structural systems through collapse

NASA Astrophysics Data System (ADS)

Del Carpio R., Maikol; Hashemi, M. Javad; Mosqueda, Gilberto

2017-10-01

This study examines the performance of integration methods for hybrid simulation of large and complex structural systems in the context of structural collapse due to seismic excitations. The target application is not necessarily for real-time testing, but rather for models that involve large-scale physical sub-structures and highly nonlinear numerical models. Four case studies are presented and discussed. In the first case study, the accuracy of integration schemes including two widely used methods, namely, modified version of the implicit Newmark with fixed-number of iteration (iterative) and the operator-splitting (non-iterative) is examined through pure numerical simulations. The second case study presents the results of 10 hybrid simulations repeated with the two aforementioned integration methods considering various time steps and fixed-number of iterations for the iterative integration method. The physical sub-structure in these tests consists of a single-degree-of-freedom (SDOF) cantilever column with replaceable steel coupons that provides repeatable highlynonlinear behavior including fracture-type strength and stiffness degradations. In case study three, the implicit Newmark with fixed-number of iterations is applied for hybrid simulations of a 1:2 scale steel moment frame that includes a relatively complex nonlinear numerical substructure. Lastly, a more complex numerical substructure is considered by constructing a nonlinear computational model of a moment frame coupled to a hybrid model of a 1:2 scale steel gravity frame. The last two case studies are conducted on the same porotype structure and the selection of time steps and fixed number of iterations are closely examined in pre-test simulations. The generated unbalance forces is used as an index to track the equilibrium error and predict the accuracy and stability of the simulations.

SACFIR: SDN-Based Application-Aware Centralized Adaptive Flow Iterative Reconfiguring Routing Protocol for WSNs

PubMed Central

Hu, Xiaopeng; Wang, Fan

2017-01-01

Smart reconfiguration of a dynamic networking environment is offered by the central control of Software-Defined Networking (SDN). Centralized SDN-based management architectures are capable of retrieving global topology intelligence and decoupling the forwarding plane from the control plane. Routing protocols developed for conventional Wireless Sensor Networks (WSNs) utilize limited iterative reconfiguration methods to optimize environmental reporting. However, the challenging networking scenarios of WSNs involve a performance overhead due to constant periodic iterative reconfigurations. In this paper, we propose the SDN-based Application-aware Centralized adaptive Flow Iterative Reconfiguring (SACFIR) routing protocol with the centralized SDN iterative solver controller to maintain the load-balancing between flow reconfigurations and flow allocation cost. The proposed SACFIR’s routing protocol offers a unique iterative path-selection algorithm, which initially computes suitable clustering based on residual resources at the control layer and then implements application-aware threshold-based multi-hop report transmissions on the forwarding plane. The operation of the SACFIR algorithm is centrally supervised by the SDN controller residing at the Base Station (BS). This paper extends SACFIR to SDN-based Application-aware Main-value Centralized adaptive Flow Iterative Reconfiguring (SAMCFIR) to establish both proactive and reactive reporting. The SAMCFIR transmission phase enables sensor nodes to trigger direct transmissions for main-value reports, while in the case of SACFIR, all reports follow computed routes. Our SDN-enabled proposed models adjust the reconfiguration period according to the traffic burden on sensor nodes, which results in heterogeneity awareness, load-balancing and application-specific reconfigurations of WSNs. Extensive experimental simulation-based results show that SACFIR and SAMCFIR yield the maximum scalability, network lifetime and stability period when compared to existing routing protocols. PMID:29236031

Incorporating Prototyping and Iteration into Intervention Development: A Case Study of a Dining Hall-Based Intervention

ERIC Educational Resources Information Center

McClain, Arianna D.; Hekler, Eric B.; Gardner, Christopher D.

2013-01-01

Background: Previous research from the fields of computer science and engineering highlight the importance of an iterative design process (IDP) to create more creative and effective solutions. Objective: This study describes IDP as a new method for developing health behavior interventions and evaluates the effectiveness of a dining hall--based…

Not All Wizards Are from Oz: Iterative Design of Intelligent Learning Environments by Communication Capacity Tapering

ERIC Educational Resources Information Center

Mavrikis, Manolis; Gutierrez-Santos, Sergio

2010-01-01

This paper presents a methodology for the design of intelligent learning environments. We recognise that in the educational technology field, theory development and system-design should be integrated and rely on an iterative process that addresses: (a) the difficulty to elicit precise, concise, and operationalized knowledge from "experts" and (b)…

Item Purification Does Not Always Improve DIF Detection: A Counterexample with Angoff's Delta Plot

ERIC Educational Resources Information Center

Magis, David; Facon, Bruno

2013-01-01

Item purification is an iterative process that is often advocated as improving the identification of items affected by differential item functioning (DIF). With test-score-based DIF detection methods, item purification iteratively removes the items currently flagged as DIF from the test scores to get purified sets of items, unaffected by DIF. The…

The use of process mapping in healthcare quality improvement projects.

PubMed

Antonacci, Grazia; Reed, Julie E; Lennox, Laura; Barlow, James

2018-05-01

Introduction Process mapping provides insight into systems and processes in which improvement interventions are introduced and is seen as useful in healthcare quality improvement projects. There is little empirical evidence on the use of process mapping in healthcare practice. This study advances understanding of the benefits and success factors of process mapping within quality improvement projects. Methods Eight quality improvement projects were purposively selected from different healthcare settings within the UK's National Health Service. Data were gathered from multiple data-sources, including interviews exploring participants' experience of using process mapping in their projects and perceptions of benefits and challenges related to its use. These were analysed using inductive analysis. Results Eight key benefits related to process mapping use were reported by participants (gathering a shared understanding of the reality; identifying improvement opportunities; engaging stakeholders in the project; defining project's objectives; monitoring project progress; learning; increased empathy; simplicity of the method) and five factors related to successful process mapping exercises (simple and appropriate visual representation, information gathered from multiple stakeholders, facilitator's experience and soft skills, basic training, iterative use of process mapping throughout the project). Conclusions Findings highlight benefits and versatility of process mapping and provide practical suggestions to improve its use in practice.

The role of simulation in the design of a neural network chip

NASA Technical Reports Server (NTRS)

Desai, Utpal; Roppel, Thaddeus A.; Padgett, Mary L.

1993-01-01

An iterative, simulation-based design procedure for a neural network chip is introduced. For this design procedure, the goal is to produce a chip layout for a neural network in which the weights are determined by transistor gate width-to-length ratios. In a given iteration, the current layout is simulated using the circuit simulator SPICE, and layout adjustments are made based on conventional gradient-decent methods. After the iteration converges, the chip is fabricated. Monte Carlo analysis is used to predict the effect of statistical fabrication process variations on the overall performance of the neural network chip.

Modeling design iteration in product design and development and its solution by a novel artificial bee colony algorithm.

PubMed

Chen, Tinggui; Xiao, Renbin

2014-01-01

Due to fierce market competition, how to improve product quality and reduce development cost determines the core competitiveness of enterprises. However, design iteration generally causes increases of product cost and delays of development time as well, so how to identify and model couplings among tasks in product design and development has become an important issue for enterprises to settle. In this paper, the shortcomings existing in WTM model are discussed and tearing approach as well as inner iteration method is used to complement the classic WTM model. In addition, the ABC algorithm is also introduced to find out the optimal decoupling schemes. In this paper, firstly, tearing approach and inner iteration method are analyzed for solving coupled sets. Secondly, a hybrid iteration model combining these two technologies is set up. Thirdly, a high-performance swarm intelligence algorithm, artificial bee colony, is adopted to realize problem-solving. Finally, an engineering design of a chemical processing system is given in order to verify its reasonability and effectiveness.

Usability Evaluation of a Clinical Decision Support System for Geriatric ED Pain Treatment.

PubMed

Genes, Nicholas; Kim, Min Soon; Thum, Frederick L; Rivera, Laura; Beato, Rosemary; Song, Carolyn; Soriano, Jared; Kannry, Joseph; Baumlin, Kevin; Hwang, Ula

2016-01-01

Older adults are at risk for inadequate emergency department (ED) pain care. Unrelieved acute pain is associated with poor outcomes. Clinical decision support systems (CDSS) hold promise to improve patient care, but CDSS quality varies widely, particularly when usability evaluation is not employed. To conduct an iterative usability and redesign process of a novel geriatric abdominal pain care CDSS. We hypothesized this process would result in the creation of more usable and favorable pain care interventions. Thirteen emergency physicians familiar with the Electronic Health Record (EHR) in use at the study site were recruited. Over a 10-week period, 17 1-hour usability test sessions were conducted across 3 rounds of testing. Participants were given 3 patient scenarios and provided simulated clinical care using the EHR, while interacting with the CDSS interventions. Quantitative System Usability Scores (SUS), favorability scores and qualitative narrative feedback were collected for each session. Using a multi-step review process by an interdisciplinary team, positive and negative usability issues in effectiveness, efficiency, and satisfaction were considered, prioritized and incorporated in the iterative redesign process of the CDSS. Video analysis was used to determine the appropriateness of the CDS appearances during simulated clinical care. Over the 3 rounds of usability evaluations and subsequent redesign processes, mean SUS progressively improved from 74.8 to 81.2 to 88.9; mean favorability scores improved from 3.23 to 4.29 (1 worst, 5 best). Video analysis revealed that, in the course of the iterative redesign processes, rates of physicians' acknowledgment of CDS interventions increased, however most rates of desired actions by physicians (such as more frequent pain score updates) decreased. The iterative usability redesign process was instrumental in improving the usability of the CDSS; if implemented in practice, it could improve geriatric pain care. The usability evaluation process led to improved acknowledgement and favorability. Incorporating usability testing when designing CDSS interventions for studies may be effective to enhance clinician use.

Optimal spiral phase modulation in Gerchberg-Saxton algorithm for wavefront reconstruction and correction

NASA Astrophysics Data System (ADS)

Baránek, M.; Běhal, J.; Bouchal, Z.

2018-01-01

In the phase retrieval applications, the Gerchberg-Saxton (GS) algorithm is widely used for the simplicity of implementation. This iterative process can advantageously be deployed in the combination with a spatial light modulator (SLM) enabling simultaneous correction of optical aberrations. As recently demonstrated, the accuracy and efficiency of the aberration correction using the GS algorithm can be significantly enhanced by a vortex image spot used as the target intensity pattern in the iterative process. Here we present an optimization of the spiral phase modulation incorporated into the GS algorithm.

Combined iterative reconstruction and image-domain decomposition for dual energy CT using total-variation regularization

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

Dong, Xue; Niu, Tianye; Zhu, Lei, E-mail: leizhu@gatech.edu

2014-05-15

Purpose: Dual-energy CT (DECT) is being increasingly used for its capability of material decomposition and energy-selective imaging. A generic problem of DECT, however, is that the decomposition process is unstable in the sense that the relative magnitude of decomposed signals is reduced due to signal cancellation while the image noise is accumulating from the two CT images of independent scans. Direct image decomposition, therefore, leads to severe degradation of signal-to-noise ratio on the resultant images. Existing noise suppression techniques are typically implemented in DECT with the procedures of reconstruction and decomposition performed independently, which do not explore the statistical propertiesmore » of decomposed images during the reconstruction for noise reduction. In this work, the authors propose an iterative approach that combines the reconstruction and the signal decomposition procedures to minimize the DECT image noise without noticeable loss of resolution. Methods: The proposed algorithm is formulated as an optimization problem, which balances the data fidelity and total variation of decomposed images in one framework, and the decomposition step is carried out iteratively together with reconstruction. The noise in the CT images from the proposed algorithm becomes well correlated even though the noise of the raw projections is independent on the two CT scans. Due to this feature, the proposed algorithm avoids noise accumulation during the decomposition process. The authors evaluate the method performance on noise suppression and spatial resolution using phantom studies and compare the algorithm with conventional denoising approaches as well as combined iterative reconstruction methods with different forms of regularization. Results: On the Catphan©600 phantom, the proposed method outperforms the existing denoising methods on preserving spatial resolution at the same level of noise suppression, i.e., a reduction of noise standard deviation by one order of magnitude. This improvement is mainly attributed to the high noise correlation in the CT images reconstructed by the proposed algorithm. Iterative reconstruction using different regularization, including quadratic orq-generalized Gaussian Markov random field regularization, achieves similar noise suppression from high noise correlation. However, the proposed TV regularization obtains a better edge preserving performance. Studies of electron density measurement also show that our method reduces the average estimation error from 9.5% to 7.1%. On the anthropomorphic head phantom, the proposed method suppresses the noise standard deviation of the decomposed images by a factor of ∼14 without blurring the fine structures in the sinus area. Conclusions: The authors propose a practical method for DECT imaging reconstruction, which combines the image reconstruction and material decomposition into one optimization framework. Compared to the existing approaches, our method achieves a superior performance on DECT imaging with respect to decomposition accuracy, noise reduction, and spatial resolution.« less

Individualized statistical learning from medical image databases: application to identification of brain lesions.

PubMed

Erus, Guray; Zacharaki, Evangelia I; Davatzikos, Christos

2014-04-01

This paper presents a method for capturing statistical variation of normal imaging phenotypes, with emphasis on brain structure. The method aims to estimate the statistical variation of a normative set of images from healthy individuals, and identify abnormalities as deviations from normality. A direct estimation of the statistical variation of the entire volumetric image is challenged by the high-dimensionality of images relative to smaller sample sizes. To overcome this limitation, we iteratively sample a large number of lower dimensional subspaces that capture image characteristics ranging from fine and localized to coarser and more global. Within each subspace, a "target-specific" feature selection strategy is applied to further reduce the dimensionality, by considering only imaging characteristics present in a test subject's images. Marginal probability density functions of selected features are estimated through PCA models, in conjunction with an "estimability" criterion that limits the dimensionality of estimated probability densities according to available sample size and underlying anatomy variation. A test sample is iteratively projected to the subspaces of these marginals as determined by PCA models, and its trajectory delineates potential abnormalities. The method is applied to segmentation of various brain lesion types, and to simulated data on which superiority of the iterative method over straight PCA is demonstrated. Copyright © 2014 Elsevier B.V. All rights reserved.

Individualized Statistical Learning from Medical Image Databases: Application to Identification of Brain Lesions

PubMed Central

Erus, Guray; Zacharaki, Evangelia I.; Davatzikos, Christos

2014-01-01

This paper presents a method for capturing statistical variation of normal imaging phenotypes, with emphasis on brain structure. The method aims to estimate the statistical variation of a normative set of images from healthy individuals, and identify abnormalities as deviations from normality. A direct estimation of the statistical variation of the entire volumetric image is challenged by the high-dimensionality of images relative to smaller sample sizes. To overcome this limitation, we iteratively sample a large number of lower dimensional subspaces that capture image characteristics ranging from fine and localized to coarser and more global. Within each subspace, a “target-specific” feature selection strategy is applied to further reduce the dimensionality, by considering only imaging characteristics present in a test subject’s images. Marginal probability density functions of selected features are estimated through PCA models, in conjunction with an “estimability” criterion that limits the dimensionality of estimated probability densities according to available sample size and underlying anatomy variation. A test sample is iteratively projected to the subspaces of these marginals as determined by PCA models, and its trajectory delineates potential abnormalities. The method is applied to segmentation of various brain lesion types, and to simulated data on which superiority of the iterative method over straight PCA is demonstrated. PMID:24607564

Simultaneous imaging/reflectivity measurements to assess diagnostic mirror cleaning.

PubMed

Skinner, C H; Gentile, C A; Doerner, R

2012-10-01

Practical methods to clean ITER's diagnostic mirrors and restore reflectivity will be critical to ITER's plasma operations. We describe a technique to assess the efficacy of mirror cleaning techniques and detect any damage to the mirror surface. The method combines microscopic imaging and reflectivity measurements in the red, green, and blue spectral regions and at selected wavelengths. The method has been applied to laser cleaning of single crystal molybdenum mirrors coated with either carbon or beryllium films 150-420 nm thick. It is suitable for hazardous materials such as beryllium as the mirrors remain sealed in a vacuum chamber.

Precise and fast spatial-frequency analysis using the iterative local Fourier transform.

PubMed

Lee, Sukmock; Choi, Heejoo; Kim, Dae Wook

2016-09-19

The use of the discrete Fourier transform has decreased since the introduction of the fast Fourier transform (fFT), which is a numerically efficient computing process. This paper presents the iterative local Fourier transform (ilFT), a set of new processing algorithms that iteratively apply the discrete Fourier transform within a local and optimal frequency domain. The new technique achieves 2¹⁰ times higher frequency resolution than the fFT within a comparable computation time. The method's superb computing efficiency, high resolution, spectrum zoom-in capability, and overall performance are evaluated and compared to other advanced high-resolution Fourier transform techniques, such as the fFT combined with several fitting methods. The effectiveness of the ilFT is demonstrated through the data analysis of a set of Talbot self-images (1280 × 1024 pixels) obtained with an experimental setup using grating in a diverging beam produced by a coherent point source.

On iterative processes in the Krylov-Sonneveld subspaces

NASA Astrophysics Data System (ADS)

Ilin, Valery P.

2016-10-01

The iterative Induced Dimension Reduction (IDR) methods are considered for solving large systems of linear algebraic equations (SLAEs) with nonsingular nonsymmetric matrices. These approaches are investigated by many authors and are charachterized sometimes as the alternative to the classical processes of Krylov type. The key moments of the IDR algorithms consist in the construction of the embedded Sonneveld subspaces, which have the decreasing dimensions and use the orthogonalization to some fixed subspace. Other independent approaches for research and optimization of the iterations are based on the augmented and modified Krylov subspaces by using the aggregation and deflation procedures with present various low rank approximations of the original matrices. The goal of this paper is to show, that IDR method in Sonneveld subspaces present an original interpretation of the modified algorithms in the Krylov subspaces. In particular, such description is given for the multi-preconditioned semi-conjugate direction methods which are actual for the parallel algebraic domain decomposition approaches.

The effects of iterative reconstruction in CT on low-contrast liver lesion volumetry: a phantom study

NASA Astrophysics Data System (ADS)

Li, Qin; Berman, Benjamin P.; Schumacher, Justin; Liang, Yongguang; Gavrielides, Marios A.; Yang, Hao; Zhao, Binsheng; Petrick, Nicholas

2017-03-01

Tumor volume measured from computed tomography images is considered a biomarker for disease progression or treatment response. The estimation of the tumor volume depends on the imaging system parameters selected, as well as lesion characteristics. In this study, we examined how different image reconstruction methods affect the measurement of lesions in an anthropomorphic liver phantom with a non-uniform background. Iterative statistics-based and model-based reconstructions, as well as filtered back-projection, were evaluated and compared in this study. Statistics-based and filtered back-projection yielded similar estimation performance, while model-based yielded higher precision but lower accuracy in the case of small lesions. Iterative reconstructions exhibited higher signal-to-noise ratio but slightly lower contrast of the lesion relative to the background. A better understanding of lesion volumetry performance as a function of acquisition parameters and lesion characteristics can lead to its incorporation as a routine sizing tool.

A Mixed Methods Bounded Case Study: Data-Driven Decision Making within Professional Learning Communities for Response to Intervention

ERIC Educational Resources Information Center

Rodriguez, Gabriel R.

2017-01-01

A growing number of schools are implementing PLCs to address school improvement, staff engage with data to identify student needs and determine instructional interventions. This is a starting point for engaging in the iterative process of learning for the teach in order to increase student learning (Hord & Sommers, 2008). The iterative process…

Evaluating the iterative development of VR/AR human factors tools for manual work.

PubMed

Liston, Paul M; Kay, Alison; Cromie, Sam; Leva, Chiara; D'Cruz, Mirabelle; Patel, Harshada; Langley, Alyson; Sharples, Sarah; Aromaa, Susanna

2012-01-01

This paper outlines the approach taken to iteratively evaluate a set of VR/AR (virtual reality / augmented reality) applications for five different manual-work applications - terrestrial spacecraft assembly, assembly-line design, remote maintenance of trains, maintenance of nuclear reactors, and large-machine assembly process design - and examines the evaluation data for evidence of the effectiveness of the evaluation framework as well as the benefits to the development process of feedback from iterative evaluation. ManuVAR is an EU-funded research project that is working to develop an innovative technology platform and a framework to support high-value, high-knowledge manual work throughout the product lifecycle. The results of this study demonstrate the iterative improvements reached throughout the design cycles, observable through the trending of the quantitative results from three successive trials of the applications and the investigation of the qualitative interview findings. The paper discusses the limitations of evaluation in complex, multi-disciplinary development projects and finds evidence of the effectiveness of the use of the particular set of complementary evaluation methods incorporating a common inquiry structure used for the evaluation - particularly in facilitating triangulation of the data.

An adaptive Gaussian process-based iterative ensemble smoother for data assimilation

NASA Astrophysics Data System (ADS)

Ju, Lei; Zhang, Jiangjiang; Meng, Long; Wu, Laosheng; Zeng, Lingzao

2018-05-01

Accurate characterization of subsurface hydraulic conductivity is vital for modeling of subsurface flow and transport. The iterative ensemble smoother (IES) has been proposed to estimate the heterogeneous parameter field. As a Monte Carlo-based method, IES requires a relatively large ensemble size to guarantee its performance. To improve the computational efficiency, we propose an adaptive Gaussian process (GP)-based iterative ensemble smoother (GPIES) in this study. At each iteration, the GP surrogate is adaptively refined by adding a few new base points chosen from the updated parameter realizations. Then the sensitivity information between model parameters and measurements is calculated from a large number of realizations generated by the GP surrogate with virtually no computational cost. Since the original model evaluations are only required for base points, whose number is much smaller than the ensemble size, the computational cost is significantly reduced. The applicability of GPIES in estimating heterogeneous conductivity is evaluated by the saturated and unsaturated flow problems, respectively. Without sacrificing estimation accuracy, GPIES achieves about an order of magnitude of speed-up compared with the standard IES. Although subsurface flow problems are considered in this study, the proposed method can be equally applied to other hydrological models.

Iteration of ultrasound aberration correction methods

NASA Astrophysics Data System (ADS)

Maasoey, Svein-Erik; Angelsen, Bjoern; Varslot, Trond

2004-05-01

Aberration in ultrasound medical imaging is usually modeled by time-delay and amplitude variations concentrated on the transmitting/receiving array. This filter process is here denoted a TDA filter. The TDA filter is an approximation to the physical aberration process, which occurs over an extended part of the human body wall. Estimation of the TDA filter, and performing correction on transmit and receive, has proven difficult. It has yet to be shown that this method works adequately for severe aberration. Estimation of the TDA filter can be iterated by retransmitting a corrected signal and re-estimate until a convergence criterion is fulfilled (adaptive imaging). Two methods for estimating time-delay and amplitude variations in receive signals from random scatterers have been developed. One method correlates each element signal with a reference signal. The other method use eigenvalue decomposition of the receive cross-spectrum matrix, based upon a receive energy-maximizing criterion. Simulations of iterating aberration correction with a TDA filter have been investigated to study its convergence properties. A weak and strong human-body wall model generated aberration. Both emulated the human abdominal wall. Results after iteration improve aberration correction substantially, and both estimation methods converge, even for the case of strong aberration.

Iterative load-balancing method with multigrid level relaxation for particle simulation with short-range interactions

NASA Astrophysics Data System (ADS)

Furuichi, Mikito; Nishiura, Daisuke

2017-10-01

We developed dynamic load-balancing algorithms for Particle Simulation Methods (PSM) involving short-range interactions, such as Smoothed Particle Hydrodynamics (SPH), Moving Particle Semi-implicit method (MPS), and Discrete Element method (DEM). These are needed to handle billions of particles modeled in large distributed-memory computer systems. Our method utilizes flexible orthogonal domain decomposition, allowing the sub-domain boundaries in the column to be different for each row. The imbalances in the execution time between parallel logical processes are treated as a nonlinear residual. Load-balancing is achieved by minimizing the residual within the framework of an iterative nonlinear solver, combined with a multigrid technique in the local smoother. Our iterative method is suitable for adjusting the sub-domain frequently by monitoring the performance of each computational process because it is computationally cheaper in terms of communication and memory costs than non-iterative methods. Numerical tests demonstrated the ability of our approach to handle workload imbalances arising from a non-uniform particle distribution, differences in particle types, or heterogeneous computer architecture which was difficult with previously proposed methods. We analyzed the parallel efficiency and scalability of our method using Earth simulator and K-computer supercomputer systems.

TU-AB-303-12: Towards Inter and Intra Fraction Plan Adaptation for the MR-Linac

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

Kontaxis, C; Bol, G; Lagendijk, J

Purpose: To develop a new sequencer for IMRT that during treatment can account for anatomy changes provided by online and real-time MRI. This sequencer employs a novel inter and intra fraction scheme that converges to the prescribed dose without a final segment weight optimization (SWO) and enables immediate optimization and delivery of radiation adapted to the deformed anatomy. Methods: The sequencer is initially supplied with a voxel-based dose prescription and during the optimization iteratively generates segments that provide this prescribed dose. Every iteration selects the best segment for the current anatomy state, calculates the dose it will deliver, warps itmore » back to the reference prescription grid and subtracts it from the remaining prescribed dose. This process continues until a certain percentage of dose or a number of segments has been delivered. The anatomy changes that occur during treatment require that convergence is achieved without a final SWO. This is resolved by adding the difference between the prescribed and delivered dose up to this fraction to the prescription of the subsequent fraction. This process is repeated for all fractions of the treatment. Results: Two breast cases were selected to stress test the pipeline by producing artificial inter and intra fraction anatomy deformations using a combination of incrementally applied rigid transformations. The dose convergence of the adaptive scheme over the entire treatment, relative to the prescribed dose, was on average 8.6% higher than the static plans delivered to the respective deformed anatomies and only 1.6% less than the static segment weighted plans on the static anatomy. Conclusion: This new adaptive sequencing strategy enables dose convergence without the need of SWO while adapting the plan to intermediate anatomies, which is a prerequisite for online plan adaptation. We are now testing our pipeline on prostate cases using clinical anatomy deformation data from our department. This work is financially supported by Elekta AB, Stockholm, Sweden.« less

Seeking consensus for cyberinfrastructure governance in the USA

NASA Astrophysics Data System (ADS)

Allison, M. Lee; Zanzkerkia, Eva

2014-05-01

Governance of geosciences cyberinfrastructure is a complex and essential undertaking, critical in enabling distributed knowledge communities to collaborate and communicate across disciplines, distances, and cultures. Advancing science with respect to "grand challenges," such as global change, Earth system observation, modeling, and prediction, and core fundamental science, depends not just on technical cyber systems, but also on social systems for strategic planning, decision-making, project management, learning, teaching, and building a community of practice. Simply put, a robust, agile technical system depends on an equally robust and adaptable social system. Cyberinfrastructure development is wrapped in social, organizational and governance challenges which may significantly impede technical progress and result in inefficiencies, duplication of effort, incompatibilities, wasted resources or user frustration. These issues are also the most time consuming to resolve due to significant institutional and social inertia: hence the urgency for developing a governance blueprint. An agile development process is underway for governance of transformative investments in geosciences cyberinfrastructure through the US National Science Foundation's EarthCube Program. Agile development is iterative and incremental, and promotes adaptive planning and rapid and flexible response. Such iterative deployment across a variety of EarthCube stakeholders encourages transparency, consensus, accountability, and inclusiveness. A broad coalition of stakeholder groups comprises an Assembly to serve as a preliminary venue for identifying, evaluating, and testing potential governance models. To offer opportunity for ensure broader end-user input and buy-in, a crowd-source approach engages stakeholders not involved otherwise in the Assembly. Developmental evaluators from the social sciences embedded in the project will provide real-time review and adjustments. In order to ensure an open and inclusive process, community-selected leaders play key roles through an Assembly Advisory Council. If consensus is reached on a governing framework, a community-selected demonstration governance demonstration pilot will help facilitate community convergence on system design.

Improved bioluminescence and fluorescence reconstruction algorithms using diffuse optical tomography, normalized data, and optimized selection of the permissible source region

PubMed Central

Naser, Mohamed A.; Patterson, Michael S.

2011-01-01

Reconstruction algorithms are presented for two-step solutions of the bioluminescence tomography (BLT) and the fluorescence tomography (FT) problems. In the first step, a continuous wave (cw) diffuse optical tomography (DOT) algorithm is used to reconstruct the tissue optical properties assuming known anatomical information provided by x-ray computed tomography or other methods. Minimization problems are formed based on L1 norm objective functions, where normalized values for the light fluence rates and the corresponding Green’s functions are used. Then an iterative minimization solution shrinks the permissible regions where the sources are allowed by selecting points with higher probability to contribute to the source distribution. Throughout this process the permissible region shrinks from the entire object to just a few points. The optimum reconstructed bioluminescence and fluorescence distributions are chosen to be the results of the iteration corresponding to the permissible region where the objective function has its global minimum This provides efficient BLT and FT reconstruction algorithms without the need for a priori information about the bioluminescence sources or the fluorophore concentration. Multiple small sources and large distributed sources can be reconstructed with good accuracy for the location and the total source power for BLT and the total number of fluorophore molecules for the FT. For non-uniform distributed sources, the size and magnitude become degenerate due to the degrees of freedom available for possible solutions. However, increasing the number of data points by increasing the number of excitation sources can improve the accuracy of reconstruction for non-uniform fluorophore distributions. PMID:21326647

Chaotic Dynamics of Linguistic-Like Processes at the Syntactical and Semantic Levels: in the Pursuit of a Multifractal Attractor

NASA Astrophysics Data System (ADS)

Nicolis, John S.; Katsikas, Anastassis A.

Collective parameters such as the Zipf's law-like statistics, the Transinformation, the Block Entropy and the Markovian character are compared for natural, genetic, musical and artificially generated long texts from generating partitions (alphabets) on homogeneous as well as on multifractal chaotic maps. It appears that minimal requirements for a language at the syntactical level such as memory, selectivity of few keywords and broken symmetry in one dimension (polarity) are more or less met by dynamically iterating simple maps or flows e.g. very simple chaotic hardware. The same selectivity is observed at the semantic level where the aim refers to partitioning a set of enviromental impinging stimuli onto coexisting attractors-categories. Under the regime of pattern recognition and classification, few key features of a pattern or few categories claim the lion's share of the information stored in this pattern and practically, only these key features are persistently scanned by the cognitive processor. A multifractal attractor model can in principle explain this high selectivity, both at the syntactical and the semantic levels.

A multiresolution approach to iterative reconstruction algorithms in X-ray computed tomography.

PubMed

De Witte, Yoni; Vlassenbroeck, Jelle; Van Hoorebeke, Luc

2010-09-01

In computed tomography, the application of iterative reconstruction methods in practical situations is impeded by their high computational demands. Especially in high resolution X-ray computed tomography, where reconstruction volumes contain a high number of volume elements (several giga voxels), this computational burden prevents their actual breakthrough. Besides the large amount of calculations, iterative algorithms require the entire volume to be kept in memory during reconstruction, which quickly becomes cumbersome for large data sets. To overcome this obstacle, we present a novel multiresolution reconstruction, which greatly reduces the required amount of memory without significantly affecting the reconstructed image quality. It is shown that, combined with an efficient implementation on a graphical processing unit, the multiresolution approach enables the application of iterative algorithms in the reconstruction of large volumes at an acceptable speed using only limited resources.

The child's perspective as a guiding principle: Young children as co-designers in the design of an interactive application meant to facilitate participation in healthcare situations.

PubMed

Stålberg, Anna; Sandberg, Anette; Söderbäck, Maja; Larsson, Thomas

2016-06-01

During the last decade, interactive technology has entered mainstream society. Its many users also include children, even the youngest ones, who use the technology in different situations for both fun and learning. When designing technology for children, it is crucial to involve children in the process in order to arrive at an age-appropriate end product. In this study we describe the specific iterative process by which an interactive application was developed. This application is intended to facilitate young children's, three-to five years old, participation in healthcare situations. We also describe the specific contributions of the children, who tested the prototypes in a preschool, a primary health care clinic and an outpatient unit at a hospital, during the development process. The iterative phases enabled the children to be involved at different stages of the process and to evaluate modifications and improvements made after each prior iteration. The children contributed their own perspectives (the child's perspective) on the usability, content and graphic design of the application, substantially improving the software and resulting in an age-appropriate product. Copyright © 2016 Elsevier Inc. All rights reserved.

Iterative dip-steering median filter

NASA Astrophysics Data System (ADS)

Huo, Shoudong; Zhu, Weihong; Shi, Taikun

2017-09-01

Seismic data are always contaminated with high noise components, which present processing challenges especially for signal preservation and its true amplitude response. This paper deals with an extension of the conventional median filter, which is widely used in random noise attenuation. It is known that the standard median filter works well with laterally aligned coherent events but cannot handle steep events, especially events with conflicting dips. In this paper, an iterative dip-steering median filter is proposed for the attenuation of random noise in the presence of multiple dips. The filter first identifies the dominant dips inside an optimized processing window by a Fourier-radial transform in the frequency-wavenumber domain. The optimum size of the processing window depends on the intensity of random noise that needs to be attenuated and the amount of signal to be preserved. It then applies median filter along the dominant dip and retains the signals. Iterations are adopted to process the residual signals along the remaining dominant dips in a descending sequence, until all signals have been retained. The method is tested by both synthetic and field data gathers and also compared with the commonly used f-k least squares de-noising and f-x deconvolution.

Enantioselective functionalization of allylic C-H bonds following a strategy of functionalization and diversification.

PubMed

Sharma, Ankit; Hartwig, John F

2013-11-27

We report the enantioselective functionalization of allylic C-H bonds in terminal alkenes by a strategy involving the installation of a temporary functional group at the terminal carbon atom by C-H bond functionalization, followed by the catalytic diversification of this intermediate with a broad scope of reagents. The method consists of a one-pot sequence of palladium-catalyzed allylic C-H bond oxidation under neutral conditions to form linear allyl benzoates, followed by iridium-catalyzed allylic substitution. This overall transformation forms a variety of chiral products containing a new C-N, C-O, C-S, or C-C bond at the allylic position in good yield with a high branched-to-linear selectivity and excellent enantioselectivity (ee ≤97%). The broad scope of the overall process results from separating the oxidation and functionalization steps; by doing so, the scope of nucleophile encompasses those sensitive to direct oxidative functionalization. The high enantioselectivity of the overall process is achieved by developing an allylic oxidation that occurs without acid to form the linear isomer with high selectivity. These allylic functionalization processes are amenable to an iterative sequence leading to (1,n)-functionalized products with catalyst-controlled diastereo- and enantioselectivity. The utility of the method in the synthesis of biologically active molecules has been demonstrated.

How does culture affect experiential training feedback in exported Canadian health professional curricula?

PubMed Central

Mousa Bacha, Rasha; Abdelaziz, Somaia

2017-01-01

Objectives To explore feedback processes of Western-based health professional student training curricula conducted in an Arab clinical teaching setting. Methods This qualitative study employed document analysis of in-training evaluation reports (ITERs) used by Canadian nursing, pharmacy, respiratory therapy, paramedic, dental hygiene, and pharmacy technician programs established in Qatar. Six experiential training program coordinators were interviewed between February and May 2016 to explore how national cultural differences are perceived to affect feedback processes between students and clinical supervisors. Interviews were recorded, transcribed, and coded according to a priori cultural themes. Results Document analysis found all programs’ ITERs outlined competency items for students to achieve. Clinical supervisors choose a response option corresponding to their judgment of student performance and may provide additional written feedback in spaces provided. Only one program required formal face-to-face feedback exchange between students and clinical supervisors. Experiential training program coordinators identified that no ITER was expressly culturally adapted, although in some instances, modifications were made for differences in scopes of practice between Canada and Qatar.  Power distance was recognized by all coordinators who also identified both student and supervisor reluctance to document potentially negative feedback in ITERs. Instances of collectivism were described as more lenient student assessment by clinical supervisors of the same cultural background. Uncertainty avoidance did not appear to impact feedback processes. Conclusions Our findings suggest that differences in specific cultural dimensions between Qatar and Canada have implications on the feedback process in experiential training which may be addressed through simple measures to accommodate communication preferences. PMID:28315858

How does culture affect experiential training feedback in exported Canadian health professional curricula?

PubMed

Wilbur, Kerry; Mousa Bacha, Rasha; Abdelaziz, Somaia

2017-03-17

To explore feedback processes of Western-based health professional student training curricula conducted in an Arab clinical teaching setting. This qualitative study employed document analysis of in-training evaluation reports (ITERs) used by Canadian nursing, pharmacy, respiratory therapy, paramedic, dental hygiene, and pharmacy technician programs established in Qatar. Six experiential training program coordinators were interviewed between February and May 2016 to explore how national cultural differences are perceived to affect feedback processes between students and clinical supervisors. Interviews were recorded, transcribed, and coded according to a priori cultural themes. Document analysis found all programs' ITERs outlined competency items for students to achieve. Clinical supervisors choose a response option corresponding to their judgment of student performance and may provide additional written feedback in spaces provided. Only one program required formal face-to-face feedback exchange between students and clinical supervisors. Experiential training program coordinators identified that no ITER was expressly culturally adapted, although in some instances, modifications were made for differences in scopes of practice between Canada and Qatar.  Power distance was recognized by all coordinators who also identified both student and supervisor reluctance to document potentially negative feedback in ITERs. Instances of collectivism were described as more lenient student assessment by clinical supervisors of the same cultural background. Uncertainty avoidance did not appear to impact feedback processes. Our findings suggest that differences in specific cultural dimensions between Qatar and Canada have implications on the feedback process in experiential training which may be addressed through simple measures to accommodate communication preferences.

Beryllium processing technology review for applications in plasma-facing components

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

Castro, R.G.; Jacobson, L.A.; Stanek, P.W.

1993-07-01

Materials research and development activities for the International Thermonuclear Experimental Reactor (ITER), i.e., the next generation fusion reactor, are investigating beryllium as the first-wall containment material for the reactor. Important in the selection of beryllium is the ability to process, fabricate and repair beryllium first-wall components using existing technologies. Two issues that will need to be addressed during the engineering design activity will be the bonding of beryllium tiles in high-heat-flux areas of the reactor, and the in situ repair of damaged beryllium tiles. The following review summarizes the current technology associated with welding and joining of beryllium to itselfmore » and other materials, and the state-of-the-art in plasma-spray technology as an in situ repair technique for damaged beryllium tiles. In addition, a review of the current status of beryllium technology in the former Soviet Union is also included.« less

The Multidimensional Assessment of Interoceptive Awareness (MAIA)

PubMed Central

Mehling, Wolf E.; Price, Cynthia; Daubenmier, Jennifer J.; Acree, Mike; Bartmess, Elizabeth; Stewart, Anita

2012-01-01

This paper describes the development of a multidimensional self-report measure of interoceptive body awareness. The systematic mixed-methods process involved reviewing the current literature, specifying a multidimensional conceptual framework, evaluating prior instruments, developing items, and analyzing focus group responses to scale items by instructors and patients of body awareness-enhancing therapies. Following refinement by cognitive testing, items were field-tested in students and instructors of mind-body approaches. Final item selection was achieved by submitting the field test data to an iterative process using multiple validation methods, including exploratory cluster and confirmatory factor analyses, comparison between known groups, and correlations with established measures of related constructs. The resulting 32-item multidimensional instrument assesses eight concepts. The psychometric properties of these final scales suggest that the Multidimensional Assessment of Interoceptive Awareness (MAIA) may serve as a starting point for research and further collaborative refinement. PMID:23133619

Fractional watt Vuillemier cryogenic refrigerator program engineering notebook. Volume 1: Thermal analysis

NASA Technical Reports Server (NTRS)

Miller, W. S.

1974-01-01

The cryogenic refrigerator thermal design calculations establish design approach and basic sizing of the machine's elements. After the basic design is defined, effort concentrates on matching the thermodynamic design with that of the heat transfer devices (heat exchangers and regenerators). Typically, the heat transfer device configurations and volumes are adjusted to improve their heat transfer and pressure drop characteristics. These adjustments imply that changes be made to the active displaced volumes, compensating for the influence of the heat transfer devices on the thermodynamic processes of the working fluid. Then, once the active volumes are changed, the heat transfer devices require adjustment to account for the variations in flows, pressure levels, and heat loads. This iterative process is continued until the thermodynamic cycle parameters match the design of the heat transfer devices. By examing several matched designs, a near-optimum refrigerator is selected.

Reducing neural network training time with parallel processing

NASA Technical Reports Server (NTRS)

Rogers, James L., Jr.; Lamarsh, William J., II

1995-01-01

Obtaining optimal solutions for engineering design problems is often expensive because the process typically requires numerous iterations involving analysis and optimization programs. Previous research has shown that a near optimum solution can be obtained in less time by simulating a slow, expensive analysis with a fast, inexpensive neural network. A new approach has been developed to further reduce this time. This approach decomposes a large neural network into many smaller neural networks that can be trained in parallel. Guidelines are developed to avoid some of the pitfalls when training smaller neural networks in parallel. These guidelines allow the engineer: to determine the number of nodes on the hidden layer of the smaller neural networks; to choose the initial training weights; and to select a network configuration that will capture the interactions among the smaller neural networks. This paper presents results describing how these guidelines are developed.

Model for Simulating a Spiral Software-Development Process

NASA Technical Reports Server (NTRS)

Mizell, Carolyn; Curley, Charles; Nayak, Umanath

2010-01-01

A discrete-event simulation model, and a computer program that implements the model, have been developed as means of analyzing a spiral software-development process. This model can be tailored to specific development environments for use by software project managers in making quantitative cases for deciding among different software-development processes, courses of action, and cost estimates. A spiral process can be contrasted with a waterfall process, which is a traditional process that consists of a sequence of activities that include analysis of requirements, design, coding, testing, and support. A spiral process is an iterative process that can be regarded as a repeating modified waterfall process. Each iteration includes assessment of risk, analysis of requirements, design, coding, testing, delivery, and evaluation. A key difference between a spiral and a waterfall process is that a spiral process can accommodate changes in requirements at each iteration, whereas in a waterfall process, requirements are considered to be fixed from the beginning and, therefore, a waterfall process is not flexible enough for some projects, especially those in which requirements are not known at the beginning or may change during development. For a given project, a spiral process may cost more and take more time than does a waterfall process, but may better satisfy a customer's expectations and needs. Models for simulating various waterfall processes have been developed previously, but until now, there have been no models for simulating spiral processes. The present spiral-process-simulating model and the software that implements it were developed by extending a discrete-event simulation process model of the IEEE 12207 Software Development Process, which was built using commercially available software known as the Process Analysis Tradeoff Tool (PATT). Typical inputs to PATT models include industry-average values of product size (expressed as number of lines of code), productivity (number of lines of code per hour), and number of defects per source line of code. The user provides the number of resources, the overall percent of effort that should be allocated to each process step, and the number of desired staff members for each step. The output of PATT includes the size of the product, a measure of effort, a measure of rework effort, the duration of the entire process, and the numbers of injected, detected, and corrected defects as well as a number of other interesting features. In the development of the present model, steps were added to the IEEE 12207 waterfall process, and this model and its implementing software were made to run repeatedly through the sequence of steps, each repetition representing an iteration in a spiral process. Because the IEEE 12207 model is founded on a waterfall paradigm, it enables direct comparison of spiral and waterfall processes. The model can be used throughout a software-development project to analyze the project as more information becomes available. For instance, data from early iterations can be used as inputs to the model, and the model can be used to estimate the time and cost of carrying the project to completion.

Collapse of cooperation in evolving games

PubMed Central

Stewart, Alexander J.; Plotkin, Joshua B.

2014-01-01

Game theory provides a quantitative framework for analyzing the behavior of rational agents. The Iterated Prisoner’s Dilemma in particular has become a standard model for studying cooperation and cheating, with cooperation often emerging as a robust outcome in evolving populations. Here we extend evolutionary game theory by allowing players’ payoffs as well as their strategies to evolve in response to selection on heritable mutations. In nature, many organisms engage in mutually beneficial interactions and individuals may seek to change the ratio of risk to reward for cooperation by altering the resources they commit to cooperative interactions. To study this, we construct a general framework for the coevolution of strategies and payoffs in arbitrary iterated games. We show that, when there is a tradeoff between the benefits and costs of cooperation, coevolution often leads to a dramatic loss of cooperation in the Iterated Prisoner’s Dilemma. The collapse of cooperation is so extreme that the average payoff in a population can decline even as the potential reward for mutual cooperation increases. Depending upon the form of tradeoffs, evolution may even move away from the Iterated Prisoner’s Dilemma game altogether. Our work offers a new perspective on the Prisoner’s Dilemma and its predictions for cooperation in natural populations; and it provides a general framework to understand the coevolution of strategies and payoffs in iterated interactions. PMID:25422421

Selective Iterative Waterfilling for Digital Subscriber Lines

NASA Astrophysics Data System (ADS)

Xu, Yang; Le-Ngoc, Tho; Panigrahi, Saswat

2007-12-01

This paper presents a high-performance, low-complexity, quasi-distributed dynamic spectrum management (DSM) algorithm suitable for DSL systems. We analytically demonstrate that the rate degradation of the distributed iterative waterfilling (IW) algorithm in near-far scenarios is caused by the insufficient utilization of all available frequency and power resources due to its nature of noncooperative game theoretic formulation. Inspired by this observation, we propose the selective IW (SIW) algorithm that can considerably alleviate the performance degradation of IW by applying IW selectively to different groups of users over different frequency bands so that all the available resources can be fully utilized. For [InlineEquation not available: see fulltext.] users, the proposed SIW algorithm needs at most [InlineEquation not available: see fulltext.] times the complexity of the IW algorithm, and is much simpler than the centralized optimal spectrum balancing (OSB), while it can offer a rate performance much better than that of the IW and close to the maximum possible rate region computed by the OSB in realistic near-far DSL scenarios. Furthermore, its predominantly distributed structure makes it suitable for DSL implementation.

Regression Model Term Selection for the Analysis of Strain-Gage Balance Calibration Data

NASA Technical Reports Server (NTRS)

Ulbrich, Norbert Manfred; Volden, Thomas R.

2010-01-01

The paper discusses the selection of regression model terms for the analysis of wind tunnel strain-gage balance calibration data. Different function class combinations are presented that may be used to analyze calibration data using either a non-iterative or an iterative method. The role of the intercept term in a regression model of calibration data is reviewed. In addition, useful algorithms and metrics originating from linear algebra and statistics are recommended that will help an analyst (i) to identify and avoid both linear and near-linear dependencies between regression model terms and (ii) to make sure that the selected regression model of the calibration data uses only statistically significant terms. Three different tests are suggested that may be used to objectively assess the predictive capability of the final regression model of the calibration data. These tests use both the original data points and regression model independent confirmation points. Finally, data from a simplified manual calibration of the Ames MK40 balance is used to illustrate the application of some of the metrics and tests to a realistic calibration data set.

Varying face occlusion detection and iterative recovery for face recognition

NASA Astrophysics Data System (ADS)

Wang, Meng; Hu, Zhengping; Sun, Zhe; Zhao, Shuhuan; Sun, Mei

2017-05-01

In most sparse representation methods for face recognition (FR), occlusion problems were usually solved via removing the occlusion part of both query samples and training samples to perform the recognition process. This practice ignores the global feature of facial image and may lead to unsatisfactory results due to the limitation of local features. Considering the aforementioned drawback, we propose a method called varying occlusion detection and iterative recovery for FR. The main contributions of our method are as follows: (1) to detect an accurate occlusion area of facial images, an image processing and intersection-based clustering combination method is used for occlusion FR; (2) according to an accurate occlusion map, the new integrated facial images are recovered iteratively and put into a recognition process; and (3) the effectiveness on recognition accuracy of our method is verified by comparing it with three typical occlusion map detection methods. Experiments show that the proposed method has a highly accurate detection and recovery performance and that it outperforms several similar state-of-the-art methods against partial contiguous occlusion.

Iterative near-term ecological forecasting: Needs, opportunities, and challenges

USGS Publications Warehouse

Dietze, Michael C.; Fox, Andrew; Beck-Johnson, Lindsay; Betancourt, Julio L.; Hooten, Mevin B.; Jarnevich, Catherine S.; Keitt, Timothy H.; Kenney, Melissa A.; Laney, Christine M.; Larsen, Laurel G.; Loescher, Henry W.; Lunch, Claire K.; Pijanowski, Bryan; Randerson, James T.; Read, Emily; Tredennick, Andrew T.; Vargas, Rodrigo; Weathers, Kathleen C.; White, Ethan P.

2018-01-01

Two foundational questions about sustainability are “How are ecosystems and the services they provide going to change in the future?” and “How do human decisions affect these trajectories?” Answering these questions requires an ability to forecast ecological processes. Unfortunately, most ecological forecasts focus on centennial-scale climate responses, therefore neither meeting the needs of near-term (daily to decadal) environmental decision-making nor allowing comparison of specific, quantitative predictions to new observational data, one of the strongest tests of scientific theory. Near-term forecasts provide the opportunity to iteratively cycle between performing analyses and updating predictions in light of new evidence. This iterative process of gaining feedback, building experience, and correcting models and methods is critical for improving forecasts. Iterative, near-term forecasting will accelerate ecological research, make it more relevant to society, and inform sustainable decision-making under high uncertainty and adaptive management. Here, we identify the immediate scientific and societal needs, opportunities, and challenges for iterative near-term ecological forecasting. Over the past decade, data volume, variety, and accessibility have greatly increased, but challenges remain in interoperability, latency, and uncertainty quantification. Similarly, ecologists have made considerable advances in applying computational, informatic, and statistical methods, but opportunities exist for improving forecast-specific theory, methods, and cyberinfrastructure. Effective forecasting will also require changes in scientific training, culture, and institutions. The need to start forecasting is now; the time for making ecology more predictive is here, and learning by doing is the fastest route to drive the science forward.

Iterative near-term ecological forecasting: Needs, opportunities, and challenges.

PubMed

Dietze, Michael C; Fox, Andrew; Beck-Johnson, Lindsay M; Betancourt, Julio L; Hooten, Mevin B; Jarnevich, Catherine S; Keitt, Timothy H; Kenney, Melissa A; Laney, Christine M; Larsen, Laurel G; Loescher, Henry W; Lunch, Claire K; Pijanowski, Bryan C; Randerson, James T; Read, Emily K; Tredennick, Andrew T; Vargas, Rodrigo; Weathers, Kathleen C; White, Ethan P

2018-02-13

Two foundational questions about sustainability are "How are ecosystems and the services they provide going to change in the future?" and "How do human decisions affect these trajectories?" Answering these questions requires an ability to forecast ecological processes. Unfortunately, most ecological forecasts focus on centennial-scale climate responses, therefore neither meeting the needs of near-term (daily to decadal) environmental decision-making nor allowing comparison of specific, quantitative predictions to new observational data, one of the strongest tests of scientific theory. Near-term forecasts provide the opportunity to iteratively cycle between performing analyses and updating predictions in light of new evidence. This iterative process of gaining feedback, building experience, and correcting models and methods is critical for improving forecasts. Iterative, near-term forecasting will accelerate ecological research, make it more relevant to society, and inform sustainable decision-making under high uncertainty and adaptive management. Here, we identify the immediate scientific and societal needs, opportunities, and challenges for iterative near-term ecological forecasting. Over the past decade, data volume, variety, and accessibility have greatly increased, but challenges remain in interoperability, latency, and uncertainty quantification. Similarly, ecologists have made considerable advances in applying computational, informatic, and statistical methods, but opportunities exist for improving forecast-specific theory, methods, and cyberinfrastructure. Effective forecasting will also require changes in scientific training, culture, and institutions. The need to start forecasting is now; the time for making ecology more predictive is here, and learning by doing is the fastest route to drive the science forward.

A novel decoding algorithm based on the hierarchical reliable strategy for SCG-LDPC codes in optical communications

NASA Astrophysics Data System (ADS)

Yuan, Jian-guo; Tong, Qing-zhen; Huang, Sheng; Wang, Yong

2013-11-01

An effective hierarchical reliable belief propagation (HRBP) decoding algorithm is proposed according to the structural characteristics of systematically constructed Gallager low-density parity-check (SCG-LDPC) codes. The novel decoding algorithm combines the layered iteration with the reliability judgment, and can greatly reduce the number of the variable nodes involved in the subsequent iteration process and accelerate the convergence rate. The result of simulation for SCG-LDPC(3969,3720) code shows that the novel HRBP decoding algorithm can greatly reduce the computing amount at the condition of ensuring the performance compared with the traditional belief propagation (BP) algorithm. The bit error rate (BER) of the HRBP algorithm is considerable at the threshold value of 15, but in the subsequent iteration process, the number of the variable nodes for the HRBP algorithm can be reduced by about 70% at the high signal-to-noise ratio (SNR) compared with the BP algorithm. When the threshold value is further increased, the HRBP algorithm will gradually degenerate into the layered-BP algorithm, but at the BER of 10-7 and the maximal iteration number of 30, the net coding gain (NCG) of the HRBP algorithm is 0.2 dB more than that of the BP algorithm, and the average iteration times can be reduced by about 40% at the high SNR. Therefore, the novel HRBP decoding algorithm is more suitable for optical communication systems.

Rescheduling with iterative repair

NASA Technical Reports Server (NTRS)

Zweben, Monte; Davis, Eugene; Daun, Brian; Deale, Michael

1992-01-01

This paper presents a new approach to rescheduling called constraint-based iterative repair. This approach gives our system the ability to satisfy domain constraints, address optimization concerns, minimize perturbation to the original schedule, produce modified schedules, quickly, and exhibits 'anytime' behavior. The system begins with an initial, flawed schedule and then iteratively repairs constraint violations until a conflict-free schedule is produced. In an empirical demonstration, we vary the importance of minimizing perturbation and report how fast the system is able to resolve conflicts in a given time bound. We also show the anytime characteristics of the system. These experiments were performed within the domain of Space Shuttle ground processing.

Scheduling and rescheduling with iterative repair

NASA Technical Reports Server (NTRS)

Zweben, Monte; Davis, Eugene; Daun, Brian; Deale, Michael

1992-01-01

This paper describes the GERRY scheduling and rescheduling system being applied to coordinate Space Shuttle Ground Processing. The system uses constraint-based iterative repair, a technique that starts with a complete but possibly flawed schedule and iteratively improves it by using constraint knowledge within repair heuristics. In this paper we explore the tradeoff between the informedness and the computational cost of several repair heuristics. We show empirically that some knowledge can greatly improve the convergence speed of a repair-based system, but that too much knowledge, such as the knowledge embodied within the MIN-CONFLICTS lookahead heuristic, can overwhelm a system and result in degraded performance.

Effect of automated tube voltage selection, integrated circuit detector and advanced iterative reconstruction on radiation dose and image quality of 3rd generation dual-source aortic CT angiography: An intra-individual comparison.

PubMed

Mangold, Stefanie; De Cecco, Carlo N; Wichmann, Julian L; Canstein, Christian; Varga-Szemes, Akos; Caruso, Damiano; Fuller, Stephen R; Bamberg, Fabian; Nikolaou, Konstantin; Schoepf, U Joseph

2016-05-01

To compare, on an intra-individual basis, the effect of automated tube voltage selection (ATVS), integrated circuit detector and advanced iterative reconstruction on radiation dose and image quality of aortic CTA studies using 2nd and 3rd generation dual-source CT (DSCT). We retrospectively evaluated 32 patients who had undergone CTA of the entire aorta with both 2nd generation DSCT at 120kV using filtered back projection (FBP) (protocol 1) and 3rd generation DSCT using ATVS, an integrated circuit detector and advanced iterative reconstruction (protocol 2). Contrast-to-noise ratio (CNR) was calculated. Image quality was subjectively evaluated using a five-point scale. Radiation dose parameters were recorded. All studies were considered of diagnostic image quality. CNR was significantly higher with protocol 2 (15.0±5.2 vs 11.0±4.2; p<.0001). Subjective image quality analysis revealed no significant differences for evaluation of attenuation (p=0.08501) but image noise was rated significantly lower with protocol 2 (p=0.0005). Mean tube voltage and effective dose were 94.7±14.1kV and 6.7±3.9mSv with protocol 2; 120±0kV and 11.5±5.2mSv with protocol 1 (p<0.0001, respectively). Aortic CTA performed with 3rd generation DSCT, ATVS, integrated circuit detector, and advanced iterative reconstruction allow a substantial reduction of radiation exposure while improving image quality in comparison to 120kV imaging with FBP. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Entropy-Based Search Algorithm for Experimental Design

NASA Astrophysics Data System (ADS)

Malakar, N. K.; Knuth, K. H.

2011-03-01

The scientific method relies on the iterated processes of inference and inquiry. The inference phase consists of selecting the most probable models based on the available data; whereas the inquiry phase consists of using what is known about the models to select the most relevant experiment. Optimizing inquiry involves searching the parameterized space of experiments to select the experiment that promises, on average, to be maximally informative. In the case where it is important to learn about each of the model parameters, the relevance of an experiment is quantified by Shannon entropy of the distribution of experimental outcomes predicted by a probable set of models. If the set of potential experiments is described by many parameters, we must search this high-dimensional entropy space. Brute force search methods will be slow and computationally expensive. We present an entropy-based search algorithm, called nested entropy sampling, to select the most informative experiment for efficient experimental design. This algorithm is inspired by Skilling's nested sampling algorithm used in inference and borrows the concept of a rising threshold while a set of experiment samples are maintained. We demonstrate that this algorithm not only selects highly relevant experiments, but also is more efficient than brute force search. Such entropic search techniques promise to greatly benefit autonomous experimental design.

Using Negotiated Joining to Construct and Fill Open-ended Roles in Elite Culinary Groups

PubMed Central

Tan, Vaughn

2015-01-01

This qualitative study examines membership processes in groups operating in an uncertain environment that prevents them from fully predefining new members’ roles. I describe how nine elite high-end, cutting-edge culinary groups in the U.S. and Europe, ranging from innovative restaurants to culinary R&D groups, use negotiated joining—a previously undocumented process—to systematically construct and fill these emergent, open-ended roles. I show that negotiated joining is a consistently patterned, iterative process that begins with a role that both aspirant and target group explicitly understand to be provisional. This provisional role is then jointly modified and constructed by the aspirant and target group through repeated iterations of proposition, validation through trial and evaluation, and selective integration of validated role components. The initially provisional role stabilizes and the aspirant achieves membership if enough role components are validated; otherwise the negotiated joining process is abandoned. Negotiated joining allows the aspirant and target group to learn if a mutually desirable role is likely and, if so, to construct such a role. In addition, the provisional roles in negotiated joining can support absorptive capacity by allowing novel role components to enter target groups through aspirants’ efforts to construct stable roles for themselves, while the internal adjustment involved in integrating newly validated role components can have the unintended side effect of supporting adaptation by providing opportunities for the groups to use these novel role components to modify their role structure and goals to suit a changing and uncertain environment. Negotiated joining thus reveals role ambiguity’s hitherto unexamined beneficial consequences and provides a foundation for a contingency theory of new-member acquisition. PMID:26273105

Defense Advanced Research Projects Agency (DARPA) Network Archive (DNA)

DTIC Science & Technology

2008-12-01

therefore decided for an iterative development process even within such a small project. The first iteration consisted of conducting specific...Public reporting burden for this collection of information is estimated to average 1 hour per response, including the time for reviewing instructions...regarding this burden estimate or any other aspect of this collection of information, including suggestions for reducing this burden to Washington

Development of the Nuclear-Electronic Orbital Approach and Applications to Ionic Liquids and Tunneling Processes

DTIC Science & Technology

2010-02-24

electronic Schrodinger equation . In previous grant cycles, we implemented the NEO approach at the Hartree-Fock (NEO-HF),13 configuration interaction...electronic and nuclear molecular orbitals. The resulting electronic and nuclear Hartree-Fock-Roothaan equations are solved iteratively until self...directly into the standard Hartree- Fock-Roothaan equations , which are solved iteratively to self-consistency. The density matrix representation

A decision support model for investment on P2P lending platform.

PubMed

Zeng, Xiangxiang; Liu, Li; Leung, Stephen; Du, Jiangze; Wang, Xun; Li, Tao

2017-01-01

Peer-to-peer (P2P) lending, as a novel economic lending model, has triggered new challenges on making effective investment decisions. In a P2P lending platform, one lender can invest N loans and a loan may be accepted by M investors, thus forming a bipartite graph. Basing on the bipartite graph model, we built an iteration computation model to evaluate the unknown loans. To validate the proposed model, we perform extensive experiments on real-world data from the largest American P2P lending marketplace-Prosper. By comparing our experimental results with those obtained by Bayes and Logistic Regression, we show that our computation model can help borrowers select good loans and help lenders make good investment decisions. Experimental results also show that the Logistic classification model is a good complement to our iterative computation model, which motivates us to integrate the two classification models. The experimental results of the hybrid classification model demonstrate that the logistic classification model and our iteration computation model are complementary to each other. We conclude that the hybrid model (i.e., the integration of iterative computation model and Logistic classification model) is more efficient and stable than the individual model alone.

A decision support model for investment on P2P lending platform

PubMed Central

Liu, Li; Leung, Stephen; Du, Jiangze; Wang, Xun; Li, Tao

2017-01-01

Peer-to-peer (P2P) lending, as a novel economic lending model, has triggered new challenges on making effective investment decisions. In a P2P lending platform, one lender can invest N loans and a loan may be accepted by M investors, thus forming a bipartite graph. Basing on the bipartite graph model, we built an iteration computation model to evaluate the unknown loans. To validate the proposed model, we perform extensive experiments on real-world data from the largest American P2P lending marketplace—Prosper. By comparing our experimental results with those obtained by Bayes and Logistic Regression, we show that our computation model can help borrowers select good loans and help lenders make good investment decisions. Experimental results also show that the Logistic classification model is a good complement to our iterative computation model, which motivates us to integrate the two classification models. The experimental results of the hybrid classification model demonstrate that the logistic classification model and our iteration computation model are complementary to each other. We conclude that the hybrid model (i.e., the integration of iterative computation model and Logistic classification model) is more efficient and stable than the individual model alone. PMID:28877234

Evaluation of power transfer efficiency for a high power inductively coupled radio-frequency hydrogen ion source

NASA Astrophysics Data System (ADS)

Jain, P.; Recchia, M.; Cavenago, M.; Fantz, U.; Gaio, E.; Kraus, W.; Maistrello, A.; Veltri, P.

2018-04-01

Neutral beam injection (NBI) for plasma heating and current drive is necessary for International Thermonuclear Experimental reactor (ITER) tokamak. Due to its various advantages, a radio frequency (RF) driven plasma source type was selected as a reference ion source for the ITER heating NBI. The ITER relevant RF negative ion sources are inductively coupled (IC) devices whose operational working frequency has been chosen to be 1 MHz and are characterized by high RF power density (˜9.4 W cm-3) and low operational pressure (around 0.3 Pa). The RF field is produced by a coil in a cylindrical chamber leading to a plasma generation followed by its expansion inside the chamber. This paper recalls different concepts based on which a methodology is developed to evaluate the efficiency of the RF power transfer to hydrogen plasma. This efficiency is then analyzed as a function of the working frequency and in dependence of other operating source and plasma parameters. The study is applied to a high power IC RF hydrogen ion source which is similar to one simplified driver of the ELISE source (half the size of the ITER NBI source).

Operator models for delivering municipal solid waste management services in developing countries: Part B: Decision support.

PubMed

Soós, Reka; Whiteman, Andrew D; Wilson, David C; Briciu, Cosmin; Nürnberger, Sofia; Oelz, Barbara; Gunsilius, Ellen; Schwehn, Ekkehard

2017-08-01

This is the second of two papers reporting the results of a major study considering 'operator models' for municipal solid waste management (MSWM) in emerging and developing countries. Part A documents the evidence base, while Part B presents a four-step decision support system for selecting an appropriate operator model in a particular local situation. Step 1 focuses on understanding local problems and framework conditions; Step 2 on formulating and prioritising local objectives; and Step 3 on assessing capacities and conditions, and thus identifying strengths and weaknesses, which underpin selection of the operator model. Step 4A addresses three generic questions, including public versus private operation, inter-municipal co-operation and integration of services. For steps 1-4A, checklists have been developed as decision support tools. Step 4B helps choose locally appropriate models from an evidence-based set of 42 common operator models ( coms); decision support tools here are a detailed catalogue of the coms, setting out advantages and disadvantages of each, and a decision-making flowchart. The decision-making process is iterative, repeating steps 2-4 as required. The advantages of a more formal process include avoiding pre-selection of a particular com known to and favoured by one decision maker, and also its assistance in identifying the possible weaknesses and aspects to consider in the selection and design of operator models. To make the best of whichever operator models are selected, key issues which need to be addressed include the capacity of the public authority as 'client', management in general and financial management in particular.

Application of a repetitive process setting to design of monotonically convergent iterative learning control

NASA Astrophysics Data System (ADS)

Boski, Marcin; Paszke, Wojciech

2015-11-01

This paper deals with the problem of designing an iterative learning control algorithm for discrete linear systems using repetitive process stability theory. The resulting design produces a stabilizing output feedback controller in the time domain and a feedforward controller that guarantees monotonic convergence in the trial-to-trial domain. The results are also extended to limited frequency range design specification. New design procedure is introduced in terms of linear matrix inequality (LMI) representations, which guarantee the prescribed performances of ILC scheme. A simulation example is given to illustrate the theoretical developments.

Dual genetic selection of synthetic riboswitches in Escherichia coli.

PubMed

Nomura, Yoko; Yokobayashi, Yohei

2014-01-01

This chapter describes a genetic selection strategy to engineer synthetic riboswitches that can chemically regulate gene expression in Escherichia coli. Riboswitch libraries are constructed by randomizing the nucleotides that potentially comprise an expression platform and fused to the hybrid selection/screening marker tetA-gfpuv. Iterative ON and OFF selections are performed under appropriate conditions that favor the survival or the growth of the cells harboring the desired riboswitches. After the selection, rapid screening of individual riboswitch clones is performed by measuring GFPuv fluorescence without subcloning. This optimized dual genetic selection strategy can be used to rapidly develop synthetic riboswitches without detailed computational design or structural knowledge.

Process control strategy for ITER central solenoid operation

NASA Astrophysics Data System (ADS)

Maekawa, R.; Takami, S.; Iwamoto, A.; Chang, H.-S.; Forgeas, A.; Chalifour, M.

2016-12-01

ITER Central Solenoid (CS) pulse operation induces significant flow disturbance in the forced-flow Supercritical Helium (SHe) cooling circuit, which could impact primarily on the operation of cold circulator (SHe centrifugal pump) in Auxiliary Cold Box (ACB). Numerical studies using Venecia®, SUPERMAGNET and 4C have identified reverse flow at the CS module inlet due to the substantial thermal energy deposition at the inner-most winding. To assess the reliable operation of ACB-CS (dedicated ACB for CS), the process analyses have been conducted with a dynamic process simulation model developed by Cryogenic Process REal-time SimulaTor (C-PREST). As implementing process control of hydrodynamic instability, several strategies have been applied to evaluate their feasibility. The paper discusses control strategy to protect the centrifugal type cold circulator/compressor operations and its impact on the CS cooling.

Automated Synthesis of Architecture of Avionic Systems

NASA Technical Reports Server (NTRS)

Chau, Savio; Xu, Joseph; Dang, Van; Lu, James F.

2006-01-01

The Architecture Synthesis Tool (AST) is software that automatically synthesizes software and hardware architectures of avionic systems. The AST is expected to be most helpful during initial formulation of an avionic-system design, when system requirements change frequently and manual modification of architecture is time-consuming and susceptible to error. The AST comprises two parts: (1) an architecture generator, which utilizes a genetic algorithm to create a multitude of architectures; and (2) a functionality evaluator, which analyzes the architectures for viability, rejecting most of the non-viable ones. The functionality evaluator generates and uses a viability tree a hierarchy representing functions and components that perform the functions such that the system as a whole performs system-level functions representing the requirements for the system as specified by a user. Architectures that survive the functionality evaluator are further evaluated by the selection process of the genetic algorithm. Architectures found to be most promising to satisfy the user s requirements and to perform optimally are selected as parents to the next generation of architectures. The foregoing process is iterated as many times as the user desires. The final output is one or a few viable architectures that satisfy the user s requirements.

Optimizing longwall mine layouts

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

Minkel, M.J.

1996-12-31

Before spending the time to design an underground mine in detail, the mining engineer should be assured of the economic viability of the location of the layout. This has historically been a trial-and-error, iterative process. Traditional underground mine planning usually bases the layout on the geological characteristics of a deposit such as minimum seam height, quality, and the absence of faults. Whether one attempts to make a decision manually. or use traditional mine planning software, the process works something like this: First you build geological model. Then you impose a {open_quotes}best guess{close_quotes} as to which geological layers will become partmore » of the mined product, or will influence mining. Next you place your design where you believe is the best location to make a mine. Then you select equipment which you believe will cost-effectively mine the area. Finally, you schedule your equipment selection through the design over the mine life, run financial analyses and see if the rate of return is acceptable. If the NPV is acceptable, the design is accepted. If the NPV is not acceptable, the engineer has to restart the cycle of redesigning the layout, rescheduling the equipment, and restudying the economics again.« less

Development of microtitre plates for electrokinetic assays

NASA Astrophysics Data System (ADS)

Burt, J. P. H.; Goater, A. D.; Menachery, A.; Pethig, R.; Rizvi, N. H.

2007-02-01

Electrokinetic processes have wide ranging applications in microsystems technology. Their optimum performance at micro and nano dimensions allows their use both as characterization and diagnostic tools and as a means of general particle manipulation. Within analytical studies, measurement of the electrokinesis of biological cells has the sensitivity and selectivity to distinguish subtle differences between cell types and cells undergoing changes and is gaining acceptance as a diagnostic tool in high throughput screening for drug discovery applications. In this work the development and manufacture of an electrokinetic-based microtitre plate is described. The plate is intended to be compatible with automated sample loading and handling systems. Manufacturing of the microtitre plate, which employs indium tin oxide microelectrodes, has been entirely undertaken using excimer and ultra-fast pulsed laser micromachining due to its flexibility in materials processing and accuracy in microstructuring. Laser micromachining has the ability to rapidly realize iterations in device prototype design while also having the capability to be scaled up for large scale manufacture. Device verification is achieved by the measurement of the electrorotation and dielectrophoretic properties of yeast cells while the flexibility of the developed microtitre plate is demonstrated by the selective separation of live yeast from polystyrene microbeads.

Improving performances of suboptimal greedy iterative biclustering heuristics via localization.

PubMed

Erten, Cesim; Sözdinler, Melih

2010-10-15

Biclustering gene expression data is the problem of extracting submatrices of genes and conditions exhibiting significant correlation across both the rows and the columns of a data matrix of expression values. Even the simplest versions of the problem are computationally hard. Most of the proposed solutions therefore employ greedy iterative heuristics that locally optimize a suitably assigned scoring function. We provide a fast and simple pre-processing algorithm called localization that reorders the rows and columns of the input data matrix in such a way as to group correlated entries in small local neighborhoods within the matrix. The proposed localization algorithm takes its roots from effective use of graph-theoretical methods applied to problems exhibiting a similar structure to that of biclustering. In order to evaluate the effectivenesss of the localization pre-processing algorithm, we focus on three representative greedy iterative heuristic methods. We show how the localization pre-processing can be incorporated into each representative algorithm to improve biclustering performance. Furthermore, we propose a simple biclustering algorithm, Random Extraction After Localization (REAL) that randomly extracts submatrices from the localization pre-processed data matrix, eliminates those with low similarity scores, and provides the rest as correlated structures representing biclusters. We compare the proposed localization pre-processing with another pre-processing alternative, non-negative matrix factorization. We show that our fast and simple localization procedure provides similar or even better results than the computationally heavy matrix factorization pre-processing with regards to H-value tests. We next demonstrate that the performances of the three representative greedy iterative heuristic methods improve with localization pre-processing when biological correlations in the form of functional enrichment and PPI verification constitute the main performance criteria. The fact that the random extraction method based on localization REAL performs better than the representative greedy heuristic methods under same criteria also confirms the effectiveness of the suggested pre-processing method. Supplementary material including code implementations in LEDA C++ library, experimental data, and the results are available at http://code.google.com/p/biclustering/ cesim@khas.edu.tr; melihsozdinler@boun.edu.tr Supplementary data are available at Bioinformatics online.

Instrumentation

for Examining

Microbial Response

to Changes In Environmental Pressures

NASA Astrophysics Data System (ADS)

Blaich, J.; Storrs, A.; Wang, J.; Ouandji, C.; Arismendi, D.; Hernandez, J.; Sardesh, N.; Ibanez, C. R.; Owyang, S.; Gentry, D.

2016-12-01

The Automated Adaptive Directed Evolution Chamber (AADEC) is a device that allows operators to generate a micro-scale analog of real world systems that can be used to model the local-scale effects of climate change on microbial ecosystems. The AADEC uses an artificial environment to expose cultures of micro-organisms to environmental pressures, such as UV-C radiation, chemical toxins, and temperature. The AADEC autonomously exposes micro-organisms to slection pressures. This improves upon standard manual laboratory techniques: the process can take place over a longer period of time, involve more stressors, implement real-time adjustments based on the state of the population, and minimize the risk of contamination. We currently use UV-C radiation as the main selection pressure, UV-C is well studied both for its cell and DNA damaging effects as a type of selection pressure and for its related effectiveness as a mutagen; having these functions united makes it a good choice for a proof of concept. The AADEC roadmap includes expansion to different selection pressures, including heavy metal toxicity, temperature, and other forms of radiation. The AADEC uses closed-loop control to feedback the current state of the culture to the AADEC controller that modifies selection pressure intensity during experimentation, in this case culture density and growth rate. Culture density and growth rate are determined by measuring the optical density of the culture using 600 nm light. An array of 600 nm LEDs illuminate the culture and photodiodes are used to measure the shadow on the opposite side of the chamber. Previous experiments showed that we can produce a million fold increase to UV-C radiation over seven iterations. The most recent implements a microfluidic system that can expose cultures to multiple different selection pressures, perform non-survival based selection, and autonomously perform hundreds of exposure cycles. A scalable pump system gives the ability to pump in various different growth media to individual cultures and introduce chemical toxins during experimentation; AADEC can perform freeze and thaw cycles. We improved our baseline characterization by building a custom UV-C exposure hood, a shutter operates on a preset timer allowing the user to set exposure intensity consistently for multiple iterations.

Low-temperature tensile strength of the ITER-TF model coil insulation system after reactor irradiation

NASA Astrophysics Data System (ADS)

Bittner-Rohrhofer, K.; Humer, K.; Weber, H. W.

The windings of the superconducting magnet coils for the ITER-FEAT fusion device are affected by high mechanical stresses at cryogenic temperatures and by a radiation environment, which impose certain constraints especially on the insulating materials. A glass fiber reinforced plastic (GFRP) laminate, which consists of Kapton/R-glass-fiber reinforcement tapes, vacuum-impregnated in a DGEBA epoxy system, was used for the European toroidal field model coil turn insulation of ITER. In order to assess its mechanical properties under the actual operating conditions of ITER-FEAT, cryogenic (77 K) static tensile tests and tension-tension fatigue measurements were done before and after irradiation to a fast neutron fluence of 1×10 22 m -2 ( E>0.1 MeV), i.e. the ITER-FEAT design fluence level. We find that the mechanical strength and the fracture behavior of this GFRP are strongly influenced by the winding direction of the tape and by the radiation induced delamination process. In addition, the composite swells by 3%, forming bubbles inside the laminate, and loses weight (1.4%) at the design fluence.

A stopping criterion to halt iterations at the Richardson-Lucy deconvolution of radiographic images

NASA Astrophysics Data System (ADS)

Almeida, G. L.; Silvani, M. I.; Souza, E. S.; Lopes, R. T.

2015-07-01

Radiographic images, as any experimentally acquired ones, are affected by spoiling agents which degrade their final quality. The degradation caused by agents of systematic character, can be reduced by some kind of treatment such as an iterative deconvolution. This approach requires two parameters, namely the system resolution and the best number of iterations in order to achieve the best final image. This work proposes a novel procedure to estimate the best number of iterations, which replaces the cumbersome visual inspection by a comparison of numbers. These numbers are deduced from the image histograms, taking into account the global difference G between them for two subsequent iterations. The developed algorithm, including a Richardson-Lucy deconvolution procedure has been embodied into a Fortran program capable to plot the 1st derivative of G as the processing progresses and to stop it automatically when this derivative - within the data dispersion - reaches zero. The radiograph of a specially chosen object acquired with thermal neutrons from the Argonauta research reactor at Institutode Engenharia Nuclear - CNEN, Rio de Janeiro, Brazil, have undergone this treatment with fair results.

A heuristic statistical stopping rule for iterative reconstruction in emission tomography.

PubMed

Ben Bouallègue, F; Crouzet, J F; Mariano-Goulart, D

2013-01-01

We propose a statistical stopping criterion for iterative reconstruction in emission tomography based on a heuristic statistical description of the reconstruction process. The method was assessed for MLEM reconstruction. Based on Monte-Carlo numerical simulations and using a perfectly modeled system matrix, our method was compared with classical iterative reconstruction followed by low-pass filtering in terms of Euclidian distance to the exact object, noise, and resolution. The stopping criterion was then evaluated with realistic PET data of a Hoffman brain phantom produced using the GATE platform for different count levels. The numerical experiments showed that compared with the classical method, our technique yielded significant improvement of the noise-resolution tradeoff for a wide range of counting statistics compatible with routine clinical settings. When working with realistic data, the stopping rule allowed a qualitatively and quantitatively efficient determination of the optimal image. Our method appears to give a reliable estimation of the optimal stopping point for iterative reconstruction. It should thus be of practical interest as it produces images with similar or better quality than classical post-filtered iterative reconstruction with a mastered computation time.

Modeling Design Iteration in Product Design and Development and Its Solution by a Novel Artificial Bee Colony Algorithm

PubMed Central

2014-01-01

Due to fierce market competition, how to improve product quality and reduce development cost determines the core competitiveness of enterprises. However, design iteration generally causes increases of product cost and delays of development time as well, so how to identify and model couplings among tasks in product design and development has become an important issue for enterprises to settle. In this paper, the shortcomings existing in WTM model are discussed and tearing approach as well as inner iteration method is used to complement the classic WTM model. In addition, the ABC algorithm is also introduced to find out the optimal decoupling schemes. In this paper, firstly, tearing approach and inner iteration method are analyzed for solving coupled sets. Secondly, a hybrid iteration model combining these two technologies is set up. Thirdly, a high-performance swarm intelligence algorithm, artificial bee colony, is adopted to realize problem-solving. Finally, an engineering design of a chemical processing system is given in order to verify its reasonability and effectiveness. PMID:25431584

Differential Characteristics Based Iterative Multiuser Detection for Wireless Sensor Networks

PubMed Central

Chen, Xiaoguang; Jiang, Xu; Wu, Zhilu; Zhuang, Shufeng

2017-01-01

High throughput, low latency and reliable communication has always been a hot topic for wireless sensor networks (WSNs) in various applications. Multiuser detection is widely used to suppress the bad effect of multiple access interference in WSNs. In this paper, a novel multiuser detection method based on differential characteristics is proposed to suppress multiple access interference. The proposed iterative receive method consists of three stages. Firstly, a differential characteristics function is presented based on the optimal multiuser detection decision function; then on the basis of differential characteristics, a preliminary threshold detection is utilized to find the potential wrongly received bits; after that an error bit corrector is employed to correct the wrong bits. In order to further lower the bit error ratio (BER), the differential characteristics calculation, threshold detection and error bit correction process described above are iteratively executed. Simulation results show that after only a few iterations the proposed multiuser detection method can achieve satisfactory BER performance. Besides, BER and near far resistance performance are much better than traditional suboptimal multiuser detection methods. Furthermore, the proposed iterative multiuser detection method also has a large system capacity. PMID:28212328

Self-consistent hybrid functionals for solids: a fully-automated implementation

NASA Astrophysics Data System (ADS)

Erba, A.

2017-08-01

A fully-automated algorithm for the determination of the system-specific optimal fraction of exact exchange in self-consistent hybrid functionals of the density-functional-theory is illustrated, as implemented into the public Crystal program. The exchange fraction of this new class of functionals is self-consistently updated proportionally to the inverse of the dielectric response of the system within an iterative procedure (Skone et al 2014 Phys. Rev. B 89, 195112). Each iteration of the present scheme, in turn, implies convergence of a self-consistent-field (SCF) and a coupled-perturbed-Hartree-Fock/Kohn-Sham (CPHF/KS) procedure. The present implementation, beside improving the user-friendliness of self-consistent hybrids, exploits the unperturbed and electric-field perturbed density matrices from previous iterations as guesses for subsequent SCF and CPHF/KS iterations, which is documented to reduce the overall computational cost of the whole process by a factor of 2.

Magnet Design Considerations for Fusion Nuclear Science Facility

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

Zhai, Y.; Kessel, C.; El-Guebaly, L.

2016-06-01

The Fusion Nuclear Science Facility (FNSF) is a nuclear confinement facility that provides a fusion environment with components of the reactor integrated together to bridge the technical gaps of burning plasma and nuclear science between the International Thermonuclear Experimental Reactor (ITER) and the demonstration power plant (DEMO). Compared with ITER, the FNSF is smaller in size but generates much higher magnetic field, i.e., 30 times higher neutron fluence with three orders of magnitude longer plasma operation at higher operating temperatures for structures surrounding the plasma. Input parameters to the magnet design from system code analysis include magnetic field of 7.5more » T at the plasma center with a plasma major radius of 4.8 m and a minor radius of 1.2 m and a peak field of 15.5 T on the toroidal field (TF) coils for the FNSF. Both low-temperature superconductors (LTS) and high-temperature superconductors (HTS) are considered for the FNSF magnet design based on the state-of-the-art fusion magnet technology. The higher magnetic field can be achieved by using the high-performance ternary restacked-rod process Nb3Sn strands for TF magnets. The circular cable-in-conduit conductor (CICC) design similar to ITER magnets and a high-aspect-ratio rectangular CICC design are evaluated for FNSF magnets, but low-activation-jacket materials may need to be selected. The conductor design concept and TF coil winding pack composition and dimension based on the horizontal maintenance schemes are discussed. Neutron radiation limits for the LTS and HTS superconductors and electrical insulation materials are also reviewed based on the available materials previously tested. The material radiation limits for FNSF magnets are defined as part of the conceptual design studies for FNSF magnets.« less

RELAP5 Model of the First Wall/Blanket Primary Heat Transfer System

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

Popov, Emilian L; Yoder Jr, Graydon L; Kim, Seokho H

2010-06-01

ITER inductive power operation is modeled and simulated using a system level computer code to evaluate the behavior of the Primary Heat Transfer System (PHTS) and predict parameter operational ranges. The control algorithm strategy and derivation are summarized in this report as well. A major feature of ITER is pulsed operation. The plasma does not burn continuously, but the power is pulsed with large periods of zero power between pulses. This feature requires active temperature control to maintain a constant blanket inlet temperature and requires accommodation of coolant thermal expansion during the pulse. In view of the transient nature ofmore » the power (plasma) operation state a transient system thermal-hydraulics code was selected: RELAP5. The code has a well-documented history for nuclear reactor transient analyses, it has been benchmarked against numerous experiments, and a large user database of commonly accepted modeling practices exists. The process of heat deposition and transfer in the blanket modules is multi-dimensional and cannot be accurately captured by a one-dimensional code such as RELAP5. To resolve this, a separate CFD calculation of blanket thermal power evolution was performed using the 3-D SC/Tetra thermofluid code. A 1D-3D co-simulation more realistically models FW/blanket internal time-dependent thermal inertia while eliminating uncertainties in the time constant assumed in a 1-D system code. Blanket water outlet temperature and heat release histories for any given ITER pulse operation scenario are calculated. These results provide the basis for developing time dependent power forcing functions which are used as input in the RELAP5 calculations.« less

The neural correlates of theory of mind and their role during empathy and the game of chess: A functional magnetic resonance imaging study.

PubMed

Powell, Joanne L; Grossi, Davide; Corcoran, Rhiannon; Gobet, Fernand; García-Fiñana, Marta

2017-07-04

Chess involves the capacity to reason iteratively about potential intentional choices of an opponent and therefore involves high levels of explicit theory of mind [ToM] (i.e. ability to infer mental states of others) alongside clear, strategic rule-based decision-making. Functional magnetic resonance imaging was used on 12 healthy male novice chess players to identify cortical regions associated with chess, ToM and empathizing. The blood-oxygenation-level-dependent (BOLD) response for chess and empathizing tasks was extracted from each ToM region. Results showed neural overlap between ToM, chess and empathizing tasks in right-hemisphere temporo-parietal junction (TPJ) [BA40], left-hemisphere superior temporal gyrus [BA22] and posterior cingulate gyrus [BA23/31]. TPJ is suggested to underlie the capacity to reason iteratively about another's internal state in a range of tasks. Areas activated by ToM and empathy included right-hemisphere orbitofrontal cortex and bilateral middle temporal gyrus: areas that become active when there is need to inhibit one's own experience when considering the internal state of another and for visual evaluation of action rationality. Results support previous findings, that ToM recruits a neural network with each region sub-serving a supporting role depending on the nature of the task itself. In contrast, a network of cortical regions primarily located within right- and left-hemisphere medial-frontal and parietal cortex, outside the internal representational network, was selectively recruited during the chess task. We hypothesize that in our cohort of novice chess players the strategy was to employ an iterative thinking pattern which in part involved mentalizing processes and recruited core ToM-related regions. Copyright © 2017. Published by Elsevier Ltd.

Magnet design considerations for Fusion Nuclear Science Facility

DOE PAGES

Zhai, Yuhu; Kessel, Chuck; El-guebaly, Laila; ...

2016-02-25

The Fusion Nuclear Science Facility (FNSF) is a nuclear confinement facility to provide a fusion environment with components of the reactor integrated together to bridge the technical gaps of burning plasma and nuclear science between ITER and the demonstration power plant (DEMO). Compared to ITER, the FNSF is smaller in size but generates much higher magnetic field, 30 times higher neutron fluence with 3 orders of magnitude longer plasma operation at higher operating temperatures for structures surrounding the plasma. Input parameters to the magnet design from system code analysis include magnetic field of 7.5 T at the plasma center withmore » plasma major radius of 4.8 m and minor radius of 1.2 m, and a peak field of 15.5 T on the TF coils for FNSF. Both low temperature superconductor (LTS) and high temperature superconductor (HTS) are considered for the FNSF magnet design based on the state-of-the-art fusion magnet technology. The higher magnetic field can be achieved by using the high performance ternary Restack Rod Process (RRP) Nb3Sn strands for toroidal field (TF) magnets. The circular cable-in-conduit conductor (CICC) design similar to ITER magnets and a high aspect ratio rectangular CICC design are evaluated for FNSF magnets but low activation jacket materials may need to be selected. The conductor design concept and TF coil winding pack composition and dimension based on the horizontal maintenance schemes are discussed. Neutron radiation limits for the LTS and HTS superconductors and electrical insulation materials are also reviewed based on the available materials previously tested. As a result, the material radiation limits for FNSF magnets are defined as part of the conceptual design studies for FNSF magnets.« less

Sensor-Based Vibration Signal Feature Extraction Using an Improved Composite Dictionary Matching Pursuit Algorithm

PubMed Central

Cui, Lingli; Wu, Na; Wang, Wenjing; Kang, Chenhui

2014-01-01

This paper presents a new method for a composite dictionary matching pursuit algorithm, which is applied to vibration sensor signal feature extraction and fault diagnosis of a gearbox. Three advantages are highlighted in the new method. First, the composite dictionary in the algorithm has been changed from multi-atom matching to single-atom matching. Compared to non-composite dictionary single-atom matching, the original composite dictionary multi-atom matching pursuit (CD-MaMP) algorithm can achieve noise reduction in the reconstruction stage, but it cannot dramatically reduce the computational cost and improve the efficiency in the decomposition stage. Therefore, the optimized composite dictionary single-atom matching algorithm (CD-SaMP) is proposed. Second, the termination condition of iteration based on the attenuation coefficient is put forward to improve the sparsity and efficiency of the algorithm, which adjusts the parameters of the termination condition constantly in the process of decomposition to avoid noise. Third, composite dictionaries are enriched with the modulation dictionary, which is one of the important structural characteristics of gear fault signals. Meanwhile, the termination condition of iteration settings, sub-feature dictionary selections and operation efficiency between CD-MaMP and CD-SaMP are discussed, aiming at gear simulation vibration signals with noise. The simulation sensor-based vibration signal results show that the termination condition of iteration based on the attenuation coefficient enhances decomposition sparsity greatly and achieves a good effect of noise reduction. Furthermore, the modulation dictionary achieves a better matching effect compared to the Fourier dictionary, and CD-SaMP has a great advantage of sparsity and efficiency compared with the CD-MaMP. The sensor-based vibration signals measured from practical engineering gearbox analyses have further shown that the CD-SaMP decomposition and reconstruction algorithm is feasible and effective. PMID:25207870

Sensor-based vibration signal feature extraction using an improved composite dictionary matching pursuit algorithm.

PubMed

Cui, Lingli; Wu, Na; Wang, Wenjing; Kang, Chenhui

2014-09-09

This paper presents a new method for a composite dictionary matching pursuit algorithm, which is applied to vibration sensor signal feature extraction and fault diagnosis of a gearbox. Three advantages are highlighted in the new method. First, the composite dictionary in the algorithm has been changed from multi-atom matching to single-atom matching. Compared to non-composite dictionary single-atom matching, the original composite dictionary multi-atom matching pursuit (CD-MaMP) algorithm can achieve noise reduction in the reconstruction stage, but it cannot dramatically reduce the computational cost and improve the efficiency in the decomposition stage. Therefore, the optimized composite dictionary single-atom matching algorithm (CD-SaMP) is proposed. Second, the termination condition of iteration based on the attenuation coefficient is put forward to improve the sparsity and efficiency of the algorithm, which adjusts the parameters of the termination condition constantly in the process of decomposition to avoid noise. Third, composite dictionaries are enriched with the modulation dictionary, which is one of the important structural characteristics of gear fault signals. Meanwhile, the termination condition of iteration settings, sub-feature dictionary selections and operation efficiency between CD-MaMP and CD-SaMP are discussed, aiming at gear simulation vibration signals with noise. The simulation sensor-based vibration signal results show that the termination condition of iteration based on the attenuation coefficient enhances decomposition sparsity greatly and achieves a good effect of noise reduction. Furthermore, the modulation dictionary achieves a better matching effect compared to the Fourier dictionary, and CD-SaMP has a great advantage of sparsity and efficiency compared with the CD-MaMP. The sensor-based vibration signals measured from practical engineering gearbox analyses have further shown that the CD-SaMP decomposition and reconstruction algorithm is feasible and effective.

Choosing order of operations to accelerate strip structure analysis in parameter range

NASA Astrophysics Data System (ADS)

Kuksenko, S. P.; Akhunov, R. R.; Gazizov, T. R.

2018-05-01

The paper considers the issue of using iteration methods in solving the sequence of linear algebraic systems obtained in quasistatic analysis of strip structures with the method of moments. Using the analysis of 4 strip structures, the authors have proved that additional acceleration (up to 2.21 times) of the iterative process can be obtained during the process of solving linear systems repeatedly by means of choosing a proper order of operations and a preconditioner. The obtained results can be used to accelerate the process of computer-aided design of various strip structures. The choice of the order of operations to accelerate the process is quite simple, universal and could be used not only for strip structure analysis but also for a wide range of computational problems.

Evaluation of noise limits to improve image processing in soft X-ray projection microscopy.

PubMed

Jamsranjav, Erdenetogtokh; Kuge, Kenichi; Ito, Atsushi; Kinjo, Yasuhito; Shiina, Tatsuo

2017-03-03

Soft X-ray microscopy has been developed for high resolution imaging of hydrated biological specimens due to the availability of water window region. In particular, a projection type microscopy has advantages in wide viewing area, easy zooming function and easy extensibility to computed tomography (CT). The blur of projection image due to the Fresnel diffraction of X-rays, which eventually reduces spatial resolution, could be corrected by an iteration procedure, i.e., repetition of Fresnel and inverse Fresnel transformations. However, it was found that the correction is not enough to be effective for all images, especially for images with low contrast. In order to improve the effectiveness of image correction by computer processing, we in this study evaluated the influence of background noise in the iteration procedure through a simulation study. In the study, images of model specimen with known morphology were used as a substitute for the chromosome images, one of the targets of our microscope. Under the condition that artificial noise was distributed on the images randomly, we introduced two different parameters to evaluate noise effects according to each situation where the iteration procedure was not successful, and proposed an upper limit of the noise within which the effective iteration procedure for the chromosome images was possible. The study indicated that applying the new simulation and noise evaluation method was useful for image processing where background noises cannot be ignored compared with specimen images.

Nonequal iteration directional filters permit selective clearance of ripples in passband circuits

NASA Technical Reports Server (NTRS)

Kurpis, G. P.

1970-01-01

Modified directional filter is comprised of alternate pairs of dielectric and air gap filter sections with unequal electrical lengths. Filter provides more flexibility in choosing dielectric material thickness and permits switching from specially ground to standard thicknesses.

Numerical Simulation of Molten Flow in Directed Energy Deposition Using an Iterative Geometry Technique

NASA Astrophysics Data System (ADS)

Vincent, Timothy J.; Rumpfkeil, Markus P.; Chaudhary, Anil

2018-03-01

The complex, multi-faceted physics of laser-based additive metals processing tends to demand high-fidelity models and costly simulation tools to provide predictions accurate enough to aid in selecting process parameters. Of particular difficulty is the accurate determination of melt pool shape and size, which are useful for predicting lack-of-fusion, as this typically requires an adequate treatment of thermal and fluid flow. In this article we describe a novel numerical simulation tool which aims to achieve a balance between accuracy and cost. This is accomplished by making simplifying assumptions regarding the behavior of the gas-liquid interface for processes with a moderate energy density, such as Laser Engineered Net Shaping (LENS). The details of the implementation, which is based on the solver simpleFoam of the well-known software suite OpenFOAM, are given here and the tool is verified and validated for a LENS process involving Ti-6Al-4V. The results indicate that the new tool predicts width and height of a deposited track to engineering accuracy levels.

Numerical Simulation of Molten Flow in Directed Energy Deposition Using an Iterative Geometry Technique

NASA Astrophysics Data System (ADS)

Vincent, Timothy J.; Rumpfkeil, Markus P.; Chaudhary, Anil

2018-06-01

The complex, multi-faceted physics of laser-based additive metals processing tends to demand high-fidelity models and costly simulation tools to provide predictions accurate enough to aid in selecting process parameters. Of particular difficulty is the accurate determination of melt pool shape and size, which are useful for predicting lack-of-fusion, as this typically requires an adequate treatment of thermal and fluid flow. In this article we describe a novel numerical simulation tool which aims to achieve a balance between accuracy and cost. This is accomplished by making simplifying assumptions regarding the behavior of the gas-liquid interface for processes with a moderate energy density, such as Laser Engineered Net Shaping (LENS). The details of the implementation, which is based on the solver simpleFoam of the well-known software suite OpenFOAM, are given here and the tool is verified and validated for a LENS process involving Ti-6Al-4V. The results indicate that the new tool predicts width and height of a deposited track to engineering accuracy levels.

Evolution of catalytic RNA in the laboratory

NASA Technical Reports Server (NTRS)

Joyce, Gerald F.

1992-01-01

We are interested in the biochemistry of existing RNA enzymes and in the development of RNA enzymes with novel catalytic function. The focal point of our research program has been the design and operation of a laboratory system for the controlled evolution of catalytic RNA. This system serves as working model of RNA-based life and can be used to explore the catalytic potential of RNA. Evolution requires the integration of three chemical processes: amplification, mutation, and selection. Amplification results in additional copies of the genetic material. Mutation operates at the level of genotype to introduce variability, this variability in turn being expressed as a range of phenotypes. Selection operates at the level of phenotype to reduce variability by excluding those individuals that do not conform to the prevailing fitness criteria. These three processes must be linked so that only the selected individuals are amplified, subject to mutational error, to produce a progeny distribution of mutant individuals. We devised techniques for the amplification, mutation, and selection of catalytic RNA, all of which can be performed rapidly in vitro within a single reaction vessel. We integrated these techniques in such a way that they can be performed iteratively and routinely. This allowed us to conduct evolution experiments in response to artificially-imposed selection constraints. Our objective was to develop novel RNA enzymes by altering the selection constraints in a controlled manner. In this way we were able to expand the catalytic repertoire of RNA. Our long-range objective is to develop an RNA enzyme with RNA replicase activity. If such an enzyme had the ability to produce additional copies of itself, then RNA evolution would operate autonomously and the origin of life will have been realized in the laboratory.

SU-E-T-446: Group-Sparsity Based Angle Generation Method for Beam Angle Optimization

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

Gao, H

2015-06-15

Purpose: This work is to develop the effective algorithm for beam angle optimization (BAO), with the emphasis on enabling further improvement from existing treatment-dependent templates based on clinical knowledge and experience. Methods: The proposed BAO algorithm utilizes a priori beam angle templates as the initial guess, and iteratively generates angular updates for this initial set, namely angle generation method, with improved dose conformality that is quantitatively measured by the objective function. That is, during each iteration, we select “the test angle” in the initial set, and use group-sparsity based fluence map optimization to identify “the candidate angle” for updating “themore » test angle”, for which all the angles in the initial set except “the test angle”, namely “the fixed set”, are set free, i.e., with no group-sparsity penalty, and the rest of angles including “the test angle” during this iteration are in “the working set”. And then “the candidate angle” is selected with the smallest objective function value from the angles in “the working set” with locally maximal group sparsity, and replaces “the test angle” if “the fixed set” with “the candidate angle” has a smaller objective function value by solving the standard fluence map optimization (with no group-sparsity regularization). Similarly other angles in the initial set are in turn selected as “the test angle” for angular updates and this chain of updates is iterated until no further new angular update is identified for a full loop. Results: The tests using the MGH public prostate dataset demonstrated the effectiveness of the proposed BAO algorithm. For example, the optimized angular set from the proposed BAO algorithm was better the MGH template. Conclusion: A new BAO algorithm is proposed based on the angle generation method via group sparsity, with improved dose conformality from the given template. Hao Gao was partially supported by the NSFC (#11405105), the 973 Program (#2015CB856000) and the Shanghai Pujiang Talent Program (#14PJ1404500)« less

Salient Point Detection in Protrusion Parts of 3D Object Robust to Isometric Variations

NASA Astrophysics Data System (ADS)

Mirloo, Mahsa; Ebrahimnezhad, Hosein

2018-03-01

In this paper, a novel method is proposed to detect 3D object salient points robust to isometric variations and stable against scaling and noise. Salient points can be used as the representative points from object protrusion parts in order to improve the object matching and retrieval algorithms. The proposed algorithm is started by determining the first salient point of the model based on the average geodesic distance of several random points. Then, according to the previous salient point, a new point is added to this set of points in each iteration. By adding every salient point, decision function is updated. Hence, a condition is created for selecting the next point in which the iterative point is not extracted from the same protrusion part so that drawing out of a representative point from every protrusion part is guaranteed. This method is stable against model variations with isometric transformations, scaling, and noise with different levels of strength due to using a feature robust to isometric variations and considering the relation between the salient points. In addition, the number of points used in averaging process is decreased in this method, which leads to lower computational complexity in comparison with the other salient point detection algorithms.

Manufacturing and assembly of IWS support rib and lower bracket for ITER vacuum vessel

NASA Astrophysics Data System (ADS)

Laad, R.; Sarvaiya, Y.; Pathak, H. A.; Raval, J. R.; Choi, C. H.

2017-04-01

ITER Vacuum Vessel (VV) is made of double walls connected by ribs structure and flexible housings. Space between these walls is filled up with In Wall Shielding (IWS) blocks to (1) shield neutrons streaming out of plasma and (2) reduce toroidal magnetic field ripple. These blocks will be connected to the VV through a supporting structure of Support Rib (SR) and Lower Bracket (LB) assembly. SR and LB are two independent components manufactured from SS 316L(N)-IG, Total 1584 support ribs and 3168 lower bracket of different sizes and shapes will be manufactured for the IWS. Two lower brackets will be welded with one support rib to make an assembly. The welding between SR and LB is a full penetration welding. Total 1584 assemblies of different sizes and shapes will be manufactured. Sufficient experience gained from manufacturing and testing of mock ups, final manufacturing of IWS support rib and lower bracket has been started at the site of IWS manufacturer M/s. Avasarala Technologies Limited (ATL). This paper will describe, optimization of water jet cutting speed on IWS material, selection criteria for K type weld joint, unique features of fixture of assembly, manufacturing of Mock ups, and welding processes with NDTs.

Feature selection with harmony search.

PubMed

Diao, Ren; Shen, Qiang

2012-12-01

Many search strategies have been exploited for the task of feature selection (FS), in an effort to identify more compact and better quality subsets. Such work typically involves the use of greedy hill climbing (HC), or nature-inspired heuristics, in order to discover the optimal solution without going through exhaustive search. In this paper, a novel FS approach based on harmony search (HS) is presented. It is a general approach that can be used in conjunction with many subset evaluation techniques. The simplicity of HS is exploited to reduce the overall complexity of the search process. The proposed approach is able to escape from local solutions and identify multiple solutions owing to the stochastic nature of HS. Additional parameter control schemes are introduced to reduce the effort and impact of parameter configuration. These can be further combined with the iterative refinement strategy, tailored to enforce the discovery of quality subsets. The resulting approach is compared with those that rely on HC, genetic algorithms, and particle swarm optimization, accompanied by in-depth studies of the suggested improvements.

An evaluation of the NQF Quality Data Model for representing Electronic Health Record driven phenotyping algorithms.

PubMed

Thompson, William K; Rasmussen, Luke V; Pacheco, Jennifer A; Peissig, Peggy L; Denny, Joshua C; Kho, Abel N; Miller, Aaron; Pathak, Jyotishman

2012-01-01

The development of Electronic Health Record (EHR)-based phenotype selection algorithms is a non-trivial and highly iterative process involving domain experts and informaticians. To make it easier to port algorithms across institutions, it is desirable to represent them using an unambiguous formal specification language. For this purpose we evaluated the recently developed National Quality Forum (NQF) information model designed for EHR-based quality measures: the Quality Data Model (QDM). We selected 9 phenotyping algorithms that had been previously developed as part of the eMERGE consortium and translated them into QDM format. Our study concluded that the QDM contains several core elements that make it a promising format for EHR-driven phenotyping algorithms for clinical research. However, we also found areas in which the QDM could be usefully extended, such as representing information extracted from clinical text, and the ability to handle algorithms that do not consist of Boolean combinations of criteria.

Memetic Algorithm-Based Multi-Objective Coverage Optimization for Wireless Sensor Networks

PubMed Central

Chen, Zhi; Li, Shuai; Yue, Wenjing

2014-01-01

Maintaining effective coverage and extending the network lifetime as much as possible has become one of the most critical issues in the coverage of WSNs. In this paper, we propose a multi-objective coverage optimization algorithm for WSNs, namely MOCADMA, which models the coverage control of WSNs as the multi-objective optimization problem. MOCADMA uses a memetic algorithm with a dynamic local search strategy to optimize the coverage of WSNs and achieve the objectives such as high network coverage, effective node utilization and more residual energy. In MOCADMA, the alternative solutions are represented as the chromosomes in matrix form, and the optimal solutions are selected through numerous iterations of the evolution process, including selection, crossover, mutation, local enhancement, and fitness evaluation. The experiment and evaluation results show MOCADMA can have good capabilities in maintaining the sensing coverage, achieve higher network coverage while improving the energy efficiency and effectively prolonging the network lifetime, and have a significant improvement over some existing algorithms. PMID:25360579

Memetic algorithm-based multi-objective coverage optimization for wireless sensor networks.

PubMed

Chen, Zhi; Li, Shuai; Yue, Wenjing

2014-10-30

Maintaining effective coverage and extending the network lifetime as much as possible has become one of the most critical issues in the coverage of WSNs. In this paper, we propose a multi-objective coverage optimization algorithm for WSNs, namely MOCADMA, which models the coverage control of WSNs as the multi-objective optimization problem. MOCADMA uses a memetic algorithm with a dynamic local search strategy to optimize the coverage of WSNs and achieve the objectives such as high network coverage, effective node utilization and more residual energy. In MOCADMA, the alternative solutions are represented as the chromosomes in matrix form, and the optimal solutions are selected through numerous iterations of the evolution process, including selection, crossover, mutation, local enhancement, and fitness evaluation. The experiment and evaluation results show MOCADMA can have good capabilities in maintaining the sensing coverage, achieve higher network coverage while improving the energy efficiency and effectively prolonging the network lifetime, and have a significant improvement over some existing algorithms.

Assessing the accuracy and stability of variable selection ...

EPA Pesticide Factsheets

Random forest (RF) modeling has emerged as an important statistical learning method in ecology due to its exceptional predictive performance. However, for large and complex ecological datasets there is limited guidance on variable selection methods for RF modeling. Typically, either a preselected set of predictor variables are used, or stepwise procedures are employed which iteratively add/remove variables according to their importance measures. This paper investigates the application of variable selection methods to RF models for predicting probable biological stream condition. Our motivating dataset consists of the good/poor condition of n=1365 stream survey sites from the 2008/2009 National Rivers and Stream Assessment, and a large set (p=212) of landscape features from the StreamCat dataset. Two types of RF models are compared: a full variable set model with all 212 predictors, and a reduced variable set model selected using a backwards elimination approach. We assess model accuracy using RF's internal out-of-bag estimate, and a cross-validation procedure with validation folds external to the variable selection process. We also assess the stability of the spatial predictions generated by the RF models to changes in the number of predictors, and argue that model selection needs to consider both accuracy and stability. The results suggest that RF modeling is robust to the inclusion of many variables of moderate to low importance. We found no substanti

Solving large mixed linear models using preconditioned conjugate gradient iteration.

PubMed

Strandén, I; Lidauer, M

1999-12-01

Continuous evaluation of dairy cattle with a random regression test-day model requires a fast solving method and algorithm. A new computing technique feasible in Jacobi and conjugate gradient based iterative methods using iteration on data is presented. In the new computing technique, the calculations in multiplication of a vector by a matrix were recorded to three steps instead of the commonly used two steps. The three-step method was implemented in a general mixed linear model program that used preconditioned conjugate gradient iteration. Performance of this program in comparison to other general solving programs was assessed via estimation of breeding values using univariate, multivariate, and random regression test-day models. Central processing unit time per iteration with the new three-step technique was, at best, one-third that needed with the old technique. Performance was best with the test-day model, which was the largest and most complex model used. The new program did well in comparison to other general software. Programs keeping the mixed model equations in random access memory required at least 20 and 435% more time to solve the univariate and multivariate animal models, respectively. Computations of the second best iteration on data took approximately three and five times longer for the animal and test-day models, respectively, than did the new program. Good performance was due to fast computing time per iteration and quick convergence to the final solutions. Use of preconditioned conjugate gradient based methods in solving large breeding value problems is supported by our findings.

Role of Outgassing of ITER Vacuum Vessel In-Wall Shielding Materials in Leak Detection of ITER Vacuum Vessel

NASA Astrophysics Data System (ADS)

Maheshwari, A.; Pathak, H. A.; Mehta, B. K.; Phull, G. S.; Laad, R.; Shaikh, M. S.; George, S.; Joshi, K.; Khan, Z.

2017-04-01

ITER Vacuum Vessel is a torus-shaped, double wall structure. The space between the double walls of the VV is filled with In-Wall Shielding Blocks (IWS) and Water. The main purpose of IWS is to provide neutron shielding during ITER plasma operation and to reduce ripple of Toroidal Magnetic Field (TF). Although In-Wall Shield Blocks (IWS) will be submerged in water in between the walls of the ITER Vacuum Vessel (VV), Outgassing Rate (OGR) of IWS materials plays a significant role in leak detection of Vacuum Vessel of ITER. Thermal Outgassing Rate of a material critically depends on the Surface Roughness of material. During leak detection process using RGA equipped Leak detector and tracer gas Helium, there will be a spill over of mass 3 and mass 2 to mass 4 which creates a background reading. Helium background will have contribution of Hydrogen too. So it is necessary to ensure the low OGR of Hydrogen. To achieve an effective leak test it is required to obtain a background below 1 × 10-8 mbar 1 s-1 and hence the maximum Outgassing rate of IWS Materials should comply with the maximum Outgassing rate required for hydrogen i.e. 1 x 10-10 mbar 1 s-1 cm-2 at room temperature. As IWS Materials are special materials developed for ITER project, it is necessary to ensure the compliance of Outgassing rate with the requirement. There is a possibility of diffusing the gasses in material at the time of production. So, to validate the production process of materials as well as manufacturing of final product from this material, three coupons of each IWS material have been manufactured with the same technique which is being used in manufacturing of IWS blocks. Manufacturing records of these coupons have been approved by ITER-IO (International Organization). Outgassing rates of these coupons have been measured at room temperature and found in acceptable limit to obtain the required Helium Background. On the basis of these measurements, test reports have been generated and got approved by IO. This paper will describe the preparation, characteristics and cleaning procedure of samples, description of the system, Outgassing rate Measurement of these samples to ensure the accurate leak detection.

Demons deformable registration of CT and cone-beam CT using an iterative intensity matching approach.

PubMed

Nithiananthan, Sajendra; Schafer, Sebastian; Uneri, Ali; Mirota, Daniel J; Stayman, J Webster; Zbijewski, Wojciech; Brock, Kristy K; Daly, Michael J; Chan, Harley; Irish, Jonathan C; Siewerdsen, Jeffrey H

2011-04-01

A method of intensity-based deformable registration of CT and cone-beam CT (CBCT) images is described, in which intensity correction occurs simultaneously within the iterative registration process. The method preserves the speed and simplicity of the popular Demons algorithm while providing robustness and accuracy in the presence of large mismatch between CT and CBCT voxel values ("intensity"). A variant of the Demons algorithm was developed in which an estimate of the relationship between CT and CBCT intensity values for specific materials in the image is computed at each iteration based on the set of currently overlapping voxels. This tissue-specific intensity correction is then used to estimate the registration output for that iteration and the process is repeated. The robustness of the method was tested in CBCT images of a cadaveric head exhibiting a broad range of simulated intensity variations associated with x-ray scatter, object truncation, and/or errors in the reconstruction algorithm. The accuracy of CT-CBCT registration was also measured in six real cases, exhibiting deformations ranging from simple to complex during surgery or radiotherapy guided by a CBCT-capable C-arm or linear accelerator, respectively. The iterative intensity matching approach was robust against all levels of intensity variation examined, including spatially varying errors in voxel value of a factor of 2 or more, as can be encountered in cases of high x-ray scatter. Registration accuracy without intensity matching degraded severely with increasing magnitude of intensity error and introduced image distortion. A single histogram match performed prior to registration alleviated some of these effects but was also prone to image distortion and was quantifiably less robust and accurate than the iterative approach. Within the six case registration accuracy study, iterative intensity matching Demons reduced mean TRE to (2.5 +/- 2.8) mm compared to (3.5 +/- 3.0) mm with rigid registration. A method was developed to iteratively correct CT-CBCT intensity disparity during Demons registration, enabling fast, intensity-based registration in CBCT-guided procedures such as surgery and radiotherapy, in which CBCT voxel values may be inaccurate. Accurate CT-CBCT registration in turn facilitates registration of multimodality preoperative image and planning data to intraoperative CBCT by way of the preoperative CT, thereby linking the intraoperative frame of reference to a wealth of preoperative information that could improve interventional guidance.

ECOMAT INC. BIOLOGICAL DENITRIFICATION PROCESS, ITER

EPA Science Inventory

EcoMat, Inc. of Hayward, California (EcoMat) has developed an ex situ anoxic biofilter biodenitrification (BDN) process. The process uses specific biocarriers and bacteria to treat nitrate-contaminated water and employs a patented reactor that retains biocarrier within the syste...

Progress on the application of ELM control schemes to ITER scenarios from the non-active phase to DT operation

NASA Astrophysics Data System (ADS)

Loarte, A.; Huijsmans, G.; Futatani, S.; Baylor, L. R.; Evans, T. E.; Orlov, D. M.; Schmitz, O.; Becoulet, M.; Cahyna, P.; Gribov, Y.; Kavin, A.; Sashala Naik, A.; Campbell, D. J.; Casper, T.; Daly, E.; Frerichs, H.; Kischner, A.; Laengner, R.; Lisgo, S.; Pitts, R. A.; Saibene, G.; Wingen, A.

2014-03-01

Progress in the definition of the requirements for edge localized mode (ELM) control and the application of ELM control methods both for high fusion performance DT operation and non-active low-current operation in ITER is described. Evaluation of the power fluxes for low plasma current H-modes in ITER shows that uncontrolled ELMs will not lead to damage to the tungsten (W) divertor target, unlike for high-current H-modes in which divertor damage by uncontrolled ELMs is expected. Despite the lack of divertor damage at lower currents, ELM control is found to be required in ITER under these conditions to prevent an excessive contamination of the plasma by W, which could eventually lead to an increased disruptivity. Modelling with the non-linear MHD code JOREK of the physics processes determining the flow of energy from the confined plasma onto the plasma-facing components during ELMs at the ITER scale shows that the relative contribution of conductive and convective losses is intrinsically linked to the magnitude of the ELM energy loss. Modelling of the triggering of ELMs by pellet injection for DIII-D and ITER has identified the minimum pellet size required to trigger ELMs and, from this, the required fuel throughput for the application of this technique to ITER is evaluated and shown to be compatible with the installed fuelling and tritium re-processing capabilities in ITER. The evaluation of the capabilities of the ELM control coil system in ITER for ELM suppression is carried out (in the vacuum approximation) and found to have a factor of ˜2 margin in terms of coil current to achieve its design criterion, although such a margin could be substantially reduced when plasma shielding effects are taken into account. The consequences for the spatial distribution of the power fluxes at the divertor of ELM control by three-dimensional (3D) fields are evaluated and found to lead to substantial toroidal asymmetries in zones of the divertor target away from the separatrix. Therefore, specifications for the rotation of the 3D perturbation applied for ELM control in order to avoid excessive localized erosion of the ITER divertor target are derived. It is shown that a rotation frequency in excess of 1 Hz for the whole toroidally asymmetric divertor power flux pattern is required (corresponding to n Hz frequency in the variation of currents in the coils, where n is the toroidal symmetry of the perturbation applied) in order to avoid unacceptable thermal cycling of the divertor target for the highest power fluxes and worst toroidal power flux asymmetries expected. The possible use of the in-vessel vertical stability coils for ELM control as a back-up to the main ELM control systems in ITER is described and the feasibility of its application to control ELMs in low plasma current H-modes, foreseen for initial ITER operation, is evaluated and found to be viable for plasma currents up to 5-10 MA depending on modelling assumptions.

Flexible Method for Developing Tactics, Techniques, and Procedures for Future Capabilities

DTIC Science & Technology

2009-02-01

levels of ability, military experience, and motivation, (b) number and type of significant events, and (c) other sources of natural variability...research has developed a number of specific instruments designed to aid in this process. Second, the iterative, feed-forward nature of the method allows...FLEX method), but still lack the structured KE approach and iterative, feed-forward nature of the FLEX method. To facilitate decision making

Cold Test and Performance Evaluation of Prototype Cryoline-X

NASA Astrophysics Data System (ADS)

Shah, N.; Choukekar, K.; Kapoor, H.; Muralidhara, S.; Garg, A.; Kumar, U.; Jadon, M.; Dash, B.; Bhattachrya, R.; Badgujar, S.; Billot, V.; Bravais, P.; Cadeau, P.

2017-12-01

The multi-process pipe vacuum jacketed cryolines for the ITER project are probably world’s most complex cryolines in terms of layout, load cases, quality, safety and regulatory requirements. As a risk mitigation plan, design, manufacturing and testing of prototype cryoline (PTCL) was planned before the approval of final design of ITER cryolines. The 29 meter long PTCL consist of 6 process pipes encased by thermal shield inside Outer Vacuum Jacket of DN 600 size and carries cold helium at 4.5 K and 80 K. The global heat load limit was defined as 1.2 W/m at 4.5 K and 4.5 W/m at 80 K. The PTCL-X (PTCL for Group-X cryolines) was specified in detail by ITER-India and designed as well as manufactured by Air Liquide. PTCL-X was installed and tested at cryogenic temperature at ITER-India Cryogenic Laboratory in 2016. The heat load at 4.5 K and 80 K, estimated using enthalpy difference method, was found to be approximately 0.8 W/m at 4.5 K, 4.2 W/m at 80 K, which is well within the defined limits. Thermal shield temperature profile was also found to be satisfactory. Paper summarizes the cold test results of PTCL-X

Integrative Analysis of High-throughput Cancer Studies with Contrasted Penalization

PubMed Central

Shi, Xingjie; Liu, Jin; Huang, Jian; Zhou, Yong; Shia, BenChang; Ma, Shuangge

2015-01-01

In cancer studies with high-throughput genetic and genomic measurements, integrative analysis provides a way to effectively pool and analyze heterogeneous raw data from multiple independent studies and outperforms “classic” meta-analysis and single-dataset analysis. When marker selection is of interest, the genetic basis of multiple datasets can be described using the homogeneity model or the heterogeneity model. In this study, we consider marker selection under the heterogeneity model, which includes the homogeneity model as a special case and can be more flexible. Penalization methods have been developed in the literature for marker selection. This study advances from the published ones by introducing the contrast penalties, which can accommodate the within- and across-dataset structures of covariates/regression coefficients and, by doing so, further improve marker selection performance. Specifically, we develop a penalization method that accommodates the across-dataset structures by smoothing over regression coefficients. An effective iterative algorithm, which calls an inner coordinate descent iteration, is developed. Simulation shows that the proposed method outperforms the benchmark with more accurate marker identification. The analysis of breast cancer and lung cancer prognosis studies with gene expression measurements shows that the proposed method identifies genes different from those using the benchmark and has better prediction performance. PMID:24395534

Automating Microbial Directed Evolution For Bioengineering Applications

NASA Astrophysics Data System (ADS)

Lee, A.; Demachkie, I. S.; Sardesh, N.; Arismendi, D.; Ouandji, C.; Wang, J.; Blaich, J.; Gentry, D.

2016-12-01

From a micro-biology perspective, directed evolution is a technique that uses controlled environmental pressures to select for a desired phenotype. Directed evolution has the distinct advantage over rational design of not needing extensive knowledge of the genome or pathways associated with a microorganism to induce phenotypes. However, there are currently limitations to the applicability of this technique including being time-consuming, error-prone, and dependent on existing assays that may lack selectivity for the given phenotype. The AADEC (Autonomous Adaptive Directed Evolution Chamber) system is a proof-of-concept instrument to automate and improve the technique such that directed evolution can be used more effectively as a general bioengineering tool. A series of tests using the automated system and comparable by-hand survival assay measurements have been carried out using UV-C radiation and Escherichia coli cultures in order to demonstrate the advantages of the AADEC versus traditional implementations of directed evolution such as random mutagenesis. AADEC uses UV-C exposure as both a source of environmental stress and mutagenesis, so in order to evaluate the UV-C tolerance obtained from the cultures, a manual UV-C exposure survival assay was developed alongside the device to compare the survival fractions at a fixed dosage. This survival assay involves exposing E.coli to UV-C radiation using a custom-designed exposure hood to control the flux and dose. Surviving cells are counted then transferred to the next iteration and so on for several iterations to calculate the survival fractions for each exposure iteration. This survival assay primarily serves as a baseline for the AADEC device, allowing quantification of the differences between the AADEC system over the manual approach. The primary data of comparison is survival fractions; this is obtained by optical density and plate counts in the manual assay and by optical density growth curve fits pre- and post-exposure in the automated case. This data can then be compiled to calculate trends over the iterations to characterize increasing UV-C resistance of the E.coli strains. The observed trends are statistically indistinguishable through several iterations from both sources.

Iterative pixelwise approach applied to computer-generated holograms and diffractive optical elements.

PubMed

Hsu, Wei-Feng; Lin, Shih-Chih

2018-01-01

This paper presents a novel approach to optimizing the design of phase-only computer-generated holograms (CGH) for the creation of binary images in an optical Fourier transform system. Optimization begins by selecting an image pixel with a temporal change in amplitude. The modulated image function undergoes an inverse Fourier transform followed by the imposition of a CGH constraint and the Fourier transform to yield an image function associated with the change in amplitude of the selected pixel. In iterations where the quality of the image is improved, that image function is adopted as the input for the next iteration. In cases where the image quality is not improved, the image function before the pixel changed is used as the input. Thus, the proposed approach is referred to as the pixelwise hybrid input-output (PHIO) algorithm. The PHIO algorithm was shown to achieve image quality far exceeding that of the Gerchberg-Saxton (GS) algorithm. The benefits were particularly evident when the PHIO algorithm was equipped with a dynamic range of image intensities equivalent to the amplitude freedom of the image signal. The signal variation of images reconstructed from the GS algorithm was 1.0223, but only 0.2537 when using PHIO, i.e., a 75% improvement. Nonetheless, the proposed scheme resulted in a 10% degradation in diffraction efficiency and signal-to-noise ratio.

How good are the Garvey-Kelson predictions of nuclear masses?

NASA Astrophysics Data System (ADS)

Morales, Irving O.; López Vieyra, J. C.; Hirsch, J. G.; Frank, A.

2009-09-01

The Garvey-Kelson relations are used in an iterative process to predict nuclear masses in the neighborhood of nuclei with measured masses. Average errors in the predicted masses for the first three iteration shells are smaller than those obtained with the best nuclear mass models. Their quality is comparable with the Audi-Wapstra extrapolations, offering a simple and reproducible procedure for short range mass predictions. A systematic study of the way the error grows as a function of the iteration and the distance to the known masses region, shows that a correlation exists between the error and the residual neutron-proton interaction, produced mainly by the implicit assumption that V varies smoothly along the nuclear landscape.

Review of the ITER diagnostics suite for erosion, deposition, dust and tritium measurements

NASA Astrophysics Data System (ADS)

Reichle, R.; Andrew, P.; Bates, P.; Bede, O.; Casal, N.; Choi, C. H.; Barnsley, R.; Damiani, C.; Bertalot, L.; Dubus, G.; Ferreol, J.; Jagannathan, G.; Kocan, M.; Leipold, F.; Lisgo, S. W.; Martin, V.; Palmer, J.; Pearce, R.; Philipps, V.; Pitts, R. A.; Pampin, R.; Passedat, G.; Puiu, A.; Suarez, A.; Shigin, P.; Shu, W.; Vayakis, G.; Veshchev, E.; Walsh, M.

2015-08-01

Dust and tritium inventories in the vacuum vessel have upper limits in ITER that are set by nuclear safety requirements. Erosion, migration and re-deposition of wall material together with fuel co-deposition will be largely responsible for these inventories. The diagnostic suite required to monitor these processes, along with the set of the corresponding measurement requirements is currently under review given the recent decision by the ITER Organization to eliminate the first carbon/tungsten (C/W) divertor and begin operations with a full-W variant Pitts et al. [1]. This paper presents the result of this review as well as the status of the chosen diagnostics.

Multiple solution of linear algebraic systems by an iterative method with recomputed preconditioner in the analysis of microstrip structures

NASA Astrophysics Data System (ADS)

Ahunov, Roman R.; Kuksenko, Sergey P.; Gazizov, Talgat R.

2016-06-01

A multiple solution of linear algebraic systems with dense matrix by iterative methods is considered. To accelerate the process, the recomputing of the preconditioning matrix is used. A priory condition of the recomputing based on change of the arithmetic mean of the current solution time during the multiple solution is proposed. To confirm the effectiveness of the proposed approach, the numerical experiments using iterative methods BiCGStab and CGS for four different sets of matrices on two examples of microstrip structures are carried out. For solution of 100 linear systems the acceleration up to 1.6 times, compared to the approach without recomputing, is obtained.

Iterative-method performance evaluation for multiple vectors associated with a large-scale sparse matrix

NASA Astrophysics Data System (ADS)

Imamura, Seigo; Ono, Kenji; Yokokawa, Mitsuo

2016-07-01

Ensemble computing, which is an instance of capacity computing, is an effective computing scenario for exascale parallel supercomputers. In ensemble computing, there are multiple linear systems associated with a common coefficient matrix. We improve the performance of iterative solvers for multiple vectors by solving them at the same time, that is, by solving for the product of the matrices. We implemented several iterative methods and compared their performance. The maximum performance on Sparc VIIIfx was 7.6 times higher than that of a naïve implementation. Finally, to deal with the different convergence processes of linear systems, we introduced a control method to eliminate the calculation of already converged vectors.

Deep learning methods to guide CT image reconstruction and reduce metal artifacts

NASA Astrophysics Data System (ADS)

Gjesteby, Lars; Yang, Qingsong; Xi, Yan; Zhou, Ye; Zhang, Junping; Wang, Ge

2017-03-01

The rapidly-rising field of machine learning, including deep learning, has inspired applications across many disciplines. In medical imaging, deep learning has been primarily used for image processing and analysis. In this paper, we integrate a convolutional neural network (CNN) into the computed tomography (CT) image reconstruction process. Our first task is to monitor the quality of CT images during iterative reconstruction and decide when to stop the process according to an intelligent numerical observer instead of using a traditional stopping rule, such as a fixed error threshold or a maximum number of iterations. After training on ground truth images, the CNN was successful in guiding an iterative reconstruction process to yield high-quality images. Our second task is to improve a sinogram to correct for artifacts caused by metal objects. A large number of interpolation and normalization-based schemes were introduced for metal artifact reduction (MAR) over the past four decades. The NMAR algorithm is considered a state-of-the-art method, although residual errors often remain in the reconstructed images, especially in cases of multiple metal objects. Here we merge NMAR with deep learning in the projection domain to achieve additional correction in critical image regions. Our results indicate that deep learning can be a viable tool to address CT reconstruction challenges.

Some error bounds for K-iterated Gaussian recursive filters

NASA Astrophysics Data System (ADS)

Cuomo, Salvatore; Galletti, Ardelio; Giunta, Giulio; Marcellino, Livia

2016-10-01

Recursive filters (RFs) have achieved a central role in several research fields over the last few years. For example, they are used in image processing, in data assimilation and in electrocardiogram denoising. More in particular, among RFs, the Gaussian RFs are an efficient computational tool for approximating Gaussian-based convolutions and are suitable for digital image processing and applications of the scale-space theory. As is a common knowledge, the Gaussian RFs, applied to signals with support in a finite domain, generate distortions and artifacts, mostly localized at the boundaries. Heuristic and theoretical improvements have been proposed in literature to deal with this issue (namely boundary conditions). They include the case in which a Gaussian RF is applied more than once, i.e. the so called K-iterated Gaussian RFs. In this paper, starting from a summary of the comprehensive mathematical background, we consider the case of the K-iterated first-order Gaussian RF and provide the study of its numerical stability and some component-wise theoretical error bounds.

Iterative reactions of transient boronic acids enable sequential C-C bond formation

NASA Astrophysics Data System (ADS)

Battilocchio, Claudio; Feist, Florian; Hafner, Andreas; Simon, Meike; Tran, Duc N.; Allwood, Daniel M.; Blakemore, David C.; Ley, Steven V.

2016-04-01

The ability to form multiple carbon-carbon bonds in a controlled sequence and thus rapidly build molecular complexity in an iterative fashion is an important goal in modern chemical synthesis. In recent times, transition-metal-catalysed coupling reactions have dominated in the development of C-C bond forming processes. A desire to reduce the reliance on precious metals and a need to obtain products with very low levels of metal impurities has brought a renewed focus on metal-free coupling processes. Here, we report the in situ preparation of reactive allylic and benzylic boronic acids, obtained by reacting flow-generated diazo compounds with boronic acids, and their application in controlled iterative C-C bond forming reactions is described. Thus far we have shown the formation of up to three C-C bonds in a sequence including the final trapping of a reactive boronic acid species with an aldehyde to generate a range of new chemical structures.

Modeling Data Containing Outliers using ARIMA Additive Outlier (ARIMA-AO)

NASA Astrophysics Data System (ADS)

Saleh Ahmar, Ansari; Guritno, Suryo; Abdurakhman; Rahman, Abdul; Awi; Alimuddin; Minggi, Ilham; Arif Tiro, M.; Kasim Aidid, M.; Annas, Suwardi; Utami Sutiksno, Dian; Ahmar, Dewi S.; Ahmar, Kurniawan H.; Abqary Ahmar, A.; Zaki, Ahmad; Abdullah, Dahlan; Rahim, Robbi; Nurdiyanto, Heri; Hidayat, Rahmat; Napitupulu, Darmawan; Simarmata, Janner; Kurniasih, Nuning; Andretti Abdillah, Leon; Pranolo, Andri; Haviluddin; Albra, Wahyudin; Arifin, A. Nurani M.

2018-01-01

The aim this study is discussed on the detection and correction of data containing the additive outlier (AO) on the model ARIMA (p, d, q). The process of detection and correction of data using an iterative procedure popularized by Box, Jenkins, and Reinsel (1994). By using this method we obtained an ARIMA models were fit to the data containing AO, this model is added to the original model of ARIMA coefficients obtained from the iteration process using regression methods. In the simulation data is obtained that the data contained AO initial models are ARIMA (2,0,0) with MSE = 36,780, after the detection and correction of data obtained by the iteration of the model ARIMA (2,0,0) with the coefficients obtained from the regression Zt = 0,106+0,204Z t-1+0,401Z t-2-329X 1(t)+115X 2(t)+35,9X 3(t) and MSE = 19,365. This shows that there is an improvement of forecasting error rate data.

Adaptive iterative design (AID): a novel approach for evaluating the interactive effects of multiple stressors on aquatic organisms.

PubMed

Glaholt, Stephen P; Chen, Celia Y; Demidenko, Eugene; Bugge, Deenie M; Folt, Carol L; Shaw, Joseph R

2012-08-15

The study of stressor interactions by eco-toxicologists using nonlinear response variables is limited by required amounts of a priori knowledge, complexity of experimental designs, the use of linear models, and the lack of use of optimal designs of nonlinear models to characterize complex interactions. Therefore, we developed AID, an adaptive-iterative design for eco-toxicologist to more accurately and efficiently examine complex multiple stressor interactions. AID incorporates the power of the general linear model and A-optimal criteria with an iterative process that: 1) minimizes the required amount of a priori knowledge, 2) simplifies the experimental design, and 3) quantifies both individual and interactive effects. Once a stable model is determined, the best fit model is identified and the direction and magnitude of stressors, individually and all combinations (including complex interactions) are quantified. To validate AID, we selected five commonly co-occurring components of polluted aquatic systems, three metal stressors (Cd, Zn, As) and two water chemistry parameters (pH, hardness) to be tested using standard acute toxicity tests in which Daphnia mortality is the (nonlinear) response variable. We found after the initial data input of experimental data, although literature values (e.g. EC-values) may also be used, and after only two iterations of AID, our dose response model was stable. The model ln(Cd)*ln(Zn) was determined the best predictor of Daphnia mortality response to the combined effects of Cd, Zn, As, pH, and hardness. This model was then used to accurately identify and quantify the strength of both greater- (e.g. As*Cd) and less-than additive interactions (e.g. Cd*Zn). Interestingly, our study found only binary interactions significant, not higher order interactions. We conclude that AID is more efficient and effective at assessing multiple stressor interactions than current methods. Other applications, including life-history endpoints commonly used by regulators, could benefit from AID's efficiency in assessing water quality criteria. Copyright © 2012 Elsevier B.V. All rights reserved.

Selection dynamic of Escherichia coli host in M13 combinatorial peptide phage display libraries.

PubMed

Zanconato, Stefano; Minervini, Giovanni; Poli, Irene; De Lucrezia, Davide

2011-01-01

Phage display relies on an iterative cycle of selection and amplification of random combinatorial libraries to enrich the initial population of those peptides that satisfy a priori chosen criteria. The effectiveness of any phage display protocol depends directly on library amino acid sequence diversity and the strength of the selection procedure. In this study we monitored the dynamics of the selective pressure exerted by the host organism on a random peptide library in the absence of any additional selection pressure. The results indicate that sequence censorship exerted by Escherichia coli dramatically reduces library diversity and can significantly impair phage display effectiveness.

Using iterative learning to improve understanding during the informed consent process in a South African psychiatric genomics study.

PubMed

Campbell, Megan M; Susser, Ezra; Mall, Sumaya; Mqulwana, Sibonile G; Mndini, Michael M; Ntola, Odwa A; Nagdee, Mohamed; Zingela, Zukiswa; Van Wyk, Stephanus; Stein, Dan J

2017-01-01

Obtaining informed consent is a great challenge in global health research. There is a need for tools that can screen for and improve potential research participants' understanding of the research study at the time of recruitment. Limited empirical research has been conducted in low and middle income countries, evaluating informed consent processes in genomics research. We sought to investigate the quality of informed consent obtained in a South African psychiatric genomics study. A Xhosa language version of the University of California, San Diego Brief Assessment of Capacity to Consent Questionnaire (UBACC) was used to screen for capacity to consent and improve understanding through iterative learning in a sample of 528 Xhosa people with schizophrenia and 528 controls. We address two questions: firstly, whether research participants' understanding of the research study improved through iterative learning; and secondly, what were predictors for better understanding of the research study at the initial screening? During screening 290 (55%) cases and 172 (33%) controls scored below the 14.5 cut-off for acceptable understanding of the research study elements, however after iterative learning only 38 (7%) cases and 13 (2.5%) controls continued to score below this cut-off. Significant variables associated with increased understanding of the consent included the psychiatric nurse recruiter conducting the consent screening, higher participant level of education, and being a control. The UBACC proved an effective tool to improve understanding of research study elements during consent, for both cases and controls. The tool holds utility for complex studies such as those involving genomics, where iterative learning can be used to make significant improvements in understanding of research study elements. The UBACC may be particularly important in groups with severe mental illness and lower education levels. Study recruiters play a significant role in managing the quality of the informed consent process.

Conceptual design of ACB-CP for ITER cryogenic system

NASA Astrophysics Data System (ADS)

Jiang, Yongcheng; Xiong, Lianyou; Peng, Nan; Tang, Jiancheng; Liu, Liqiang; Zhang, Liang

2012-06-01

ACB-CP (Auxiliary Cold Box for Cryopumps) is used to supply the cryopumps system with necessary cryogen in ITER (International Thermonuclear Experimental Reactor) cryogenic distribution system. The conceptual design of ACB-CP contains thermo-hydraulic analysis, 3D structure design and strength checking. Through the thermohydraulic analysis, the main specifications of process valves, pressure safety valves, pipes, heat exchangers can be decided. During the 3D structure design process, vacuum requirement, adiabatic requirement, assembly constraints and maintenance requirement have been considered to arrange the pipes, valves and other components. The strength checking has been performed to crosscheck if the 3D design meets the strength requirements for the ACB-CP.

DSMC simulation of rarefied gas flows under cooling conditions using a new iterative wall heat flux specifying technique

NASA Astrophysics Data System (ADS)

Akhlaghi, H.; Roohi, E.; Myong, R. S.

2012-11-01

Micro/nano geometries with specified wall heat flux are widely encountered in electronic cooling and micro-/nano-fluidic sensors. We introduce a new technique to impose the desired (positive/negative) wall heat flux boundary condition in the DSMC simulations. This technique is based on an iterative progress on the wall temperature magnitude. It is found that the proposed iterative technique has a good numerical performance and could implement both positive and negative values of wall heat flux rates accurately. Using present technique, rarefied gas flow through micro-/nanochannels under specified wall heat flux conditions is simulated and unique behaviors are observed in case of channels with cooling walls. For example, contrary to the heating process, it is observed that cooling of micro/nanochannel walls would result in small variations in the density field. Upstream thermal creep effects in the cooling process decrease the velocity slip despite of the Knudsen number increase along the channel. Similarly, cooling process decreases the curvature of the pressure distribution below the linear incompressible distribution. Our results indicate that flow cooling increases the mass flow rate through the channel, and vice versa.

Application of ant colony optimization in development of models for prediction of anti-HIV-1 activity of HEPT derivatives.

PubMed

Zare-Shahabadi, Vali; Abbasitabar, Fatemeh

2010-09-01

Quantitative structure-activity relationship models were derived for 107 analogs of 1-[(2-hydroxyethoxy) methyl]-6-(phenylthio)thymine, a potent inhibitor of the HIV-1 reverse transcriptase. The activities of these compounds were investigated by means of multiple linear regression (MLR) technique. An ant colony optimization algorithm, called Memorized_ACS, was applied for selecting relevant descriptors and detecting outliers. This algorithm uses an external memory based upon knowledge incorporation from previous iterations. At first, the memory is empty, and then it is filled by running several ACS algorithms. In this respect, after each ACS run, the elite ant is stored in the memory and the process is continued to fill the memory. Here, pheromone updating is performed by all elite ants collected in the memory; this results in improvements in both exploration and exploitation behaviors of the ACS algorithm. The memory is then made empty and is filled again by performing several ACS algorithms using updated pheromone trails. This process is repeated for several iterations. At the end, the memory contains several top solutions for the problem. Number of appearance of each descriptor in the external memory is a good criterion for its importance. Finally, prediction is performed by the elitist ant, and interpretation is carried out by considering the importance of each descriptor. The best MLR model has a training error of 0.47 log (1/EC(50)) units (R(2) = 0.90) and a prediction error of 0.76 log (1/EC(50)) units (R(2) = 0.88). Copyright 2010 Wiley Periodicals, Inc.

Development of the IBD Disk: A Visual Self-administered Tool for Assessing Disability in Inflammatory Bowel Diseases.

PubMed

Ghosh, Subrata; Louis, Edouard; Beaugerie, Laurent; Bossuyt, Peter; Bouguen, Guillaume; Bourreille, Arnaud; Ferrante, Marc; Franchimont, Denis; Frost, Karen; Hebuterne, Xavier; Marshall, John K; OʼShea, Ciara; Rosenfeld, Greg; Williams, Chadwick; Peyrin-Biroulet, Laurent

2017-03-01

The Inflammatory bowel disease (IBD) Disability Index is a validated tool that evaluates functional status; however, it is used mainly in the clinical trial setting. We describe the use of an iterative Delphi consensus process to develop the IBD Disk-a shortened, self-administered adaption of the validated IBD Disability Index-to give immediate visual representation of patient-reported IBD-related disability. In the preparatory phase, the IBD CONNECT group (30 health care professionals) ranked IBD Disability Index items in the perceived order of importance. The Steering Committee then selected 10 items from the IBD Disability Index to take forward for inclusion in the IBD Disk. In the consensus phase, the items were refined and agreed by the IBD Disk Working Group (14 gastroenterologists) using an online iterative Delphi consensus process. Members could also suggest new element(s) or recommend changes to included elements. The final items for the IBD Disk were agreed in February 2016. After 4 rounds of voting, the following 10 items were agreed for inclusion in the IBD Disk: abdominal pain, body image, education and work, emotions, energy, interpersonal interactions, joint pain, regulating defecation, sexual functions, and sleep. All elements, except sexual functions, were included in the validated IBD Disability Index. The IBD Disk has the potential to be a valuable tool for use at a clinical visit. It can facilitate assessment of inflammatory bowel disease-related disability relevant to both patients and physicians, discussion on specific disability-related issues, and tracking changes in disease burden over time.

Multicriteria hierarchical iterative interactive algorithm for organizing operational modes of large heat supply systems

NASA Astrophysics Data System (ADS)

Korotkova, T. I.; Popova, V. I.

2017-11-01

The generalized mathematical model of decision-making in the problem of planning and mode selection providing required heat loads in a large heat supply system is considered. The system is multilevel, decomposed into levels of main and distribution heating networks with intermediate control stages. Evaluation of the effectiveness, reliability and safety of such a complex system is carried out immediately according to several indicators, in particular pressure, flow, temperature. This global multicriteria optimization problem with constraints is decomposed into a number of local optimization problems and the coordination problem. An agreed solution of local problems provides a solution to the global multicriterion problem of decision making in a complex system. The choice of the optimum operational mode of operation of a complex heat supply system is made on the basis of the iterative coordination process, which converges to the coordinated solution of local optimization tasks. The interactive principle of multicriteria task decision-making includes, in particular, periodic adjustment adjustments, if necessary, guaranteeing optimal safety, reliability and efficiency of the system as a whole in the process of operation. The degree of accuracy of the solution, for example, the degree of deviation of the internal air temperature from the required value, can also be changed interactively. This allows to carry out adjustment activities in the best way and to improve the quality of heat supply to consumers. At the same time, an energy-saving task is being solved to determine the minimum required values of heads at sources and pumping stations.

Writing and compiling code into biochemistry.

PubMed

Shea, Adam; Fett, Brian; Riedel, Marc D; Parhi, Keshab

2010-01-01

This paper presents a methodology for translating iterative arithmetic computation, specified as high-level programming constructs, into biochemical reactions. From an input/output specification, we generate biochemical reactions that produce output quantities of proteins as a function of input quantities performing operations such as addition, subtraction, and scalar multiplication. Iterative constructs such as "while" loops and "for" loops are implemented by transferring quantities between protein types, based on a clocking mechanism. Synthesis first is performed at a conceptual level, in terms of abstract biochemical reactions - a task analogous to high-level program compilation. Then the results are mapped onto specific biochemical reactions selected from libraries - a task analogous to machine language compilation. We demonstrate our approach through the compilation of a variety of standard iterative functions: multiplication, exponentiation, discrete logarithms, raising to a power, and linear transforms on time series. The designs are validated through transient stochastic simulation of the chemical kinetics. We are exploring DNA-based computation via strand displacement as a possible experimental chassis.

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.

Development of the low-field side reflectometer for ITER

NASA Astrophysics Data System (ADS)

Muscatello, Christopher; Anderson, James; Gattuso, Anthony; Doyle, Edward; Peebles, William; Seraydarian, Raymond; Wang, Guiding; Kramer, Gerrit; Zolfaghari, Ali; Atomics Team, General; University of California Los Angeles Team; Princeton Plasma Physics Laboratory Team

2017-10-01

The Low-Field Side Reflectometer (LFSR) for ITER will provide real-time edge density profiles every 10 ms for feedback control and every 24 μs for physics evaluation. The spatial resolution will be better than 5 mm over 30 - 165 GHz, probing the scrape-off layer to the top of the pedestal in H-mode plasmas. An antenna configuration has been selected for measurements covering anticipated plasma elevations. Laboratory validation of diagnostic performance is underway using a LFSR transmission line (TL) mockup. The 40-meter TL includes circular corrugated waveguide, length calibration feature, Gaussian telescope, vacuum windows, containment membranes, and expansion joint. Transceiver modules coupled to the input of the TL provide frequency-modulated (FM) data for evaluation of performance as a monostatic reflectometer. Results from the mockup tests are presented and show that, with some further optimization, the LFSR will meet or exceed the measurement requirements for ITER. An update of the LFSR instrumentation design status is also presented with preliminary test results. Work supported by PPPL under subcontract S013252-A.

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

Russell Feder and Mahmoud Z. Yousef

Neutronics analysis to find nuclear heating rates and personnel dose rates were conducted in support of the integration of diagnostics in to the ITER Upper Port Plugs. Simplified shielding models of the Visible-Infrared diagnostic and of the ECH heating system were incorporated in to the ITER global CAD model. Results for these systems are representative of typical designs with maximum shielding and a small aperture (Vis-IR) and minimal shielding with a large aperture (ECH). The neutronics discrete-ordinates code ATTILA® and SEVERIAN® (the ATTILA parallel processing version) was used. Material properties and the 500 MW D-T volume source were taken frommore » the ITER “Brand Model” MCNP benchmark model. A biased quadrature set equivelant to Sn=32 and a scattering degree of Pn=3 were used along with a 46-neutron and 21-gamma FENDL energy subgrouping. Total nuclear heating (neutron plug gamma heating) in the upper port plugs ranged between 380 and 350 kW for the Vis-IR and ECH cases. The ECH or Large Aperture model exhibited lower total heating but much higher peak volumetric heating on the upper port plug structure. Personnel dose rates are calculated in a three step process involving a neutron-only transport calculation, the generation of activation volume sources at pre-defined time steps and finally gamma transport analyses are run for selected time steps. ANSI-ANS 6.1.1 1977 Flux-to-Dose conversion factors were used. Dose rates were evaluated for 1 full year of 500 MW DT operation which is comprised of 3000 1800-second pulses. After one year the machine is shut down for maintenance and personnel are permitted to access the diagnostic interspace after 2-weeks if dose rates are below 100 μSv/hr. Dose rates in the Visible-IR diagnostic model after one day of shutdown were 130 μSv/hr but fell below the limit to 90 μSv/hr 2-weeks later. The Large Aperture or ECH style shielding model exhibited higher and more persistent dose rates. After 1-day the dose rate was 230 μSv/hr but was still at 120 μSv/hr 4-weeks later. __________________________________________________« less

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

Russell E. Feder and Mahmoud Z. Youssef

Neutronics analysis to find nuclear heating rates and personnel dose rates were conducted in support of the integration of diagnostics in to the ITER Upper Port Plugs. Simplified shielding models of the Visible-Infrared diagnostic and of a large aperture diagnostic were incorporated in to the ITER global CAD model. Results for these systems are representative of typical designs with maximum shielding and a small aperture (Vis-IR) and minimal shielding with a large aperture. The neutronics discrete-ordinates code ATTILA® and SEVERIAN® (the ATTILA parallel processing version) was used. Material properties and the 500 MW D-T volume source were taken from themore » ITER “Brand Model” MCNP benchmark model. A biased quadrature set equivelant to Sn=32 and a scattering degree of Pn=3 were used along with a 46-neutron and 21-gamma FENDL energy subgrouping. Total nuclear heating (neutron plug gamma heating) in the upper port plugs ranged between 380 and 350 kW for the Vis-IR and Large Aperture cases. The Large Aperture model exhibited lower total heating but much higher peak volumetric heating on the upper port plug structure. Personnel dose rates are calculated in a three step process involving a neutron-only transport calculation, the generation of activation volume sources at pre-defined time steps and finally gamma transport analyses are run for selected time steps. ANSI-ANS 6.1.1 1977 Flux-to-Dose conversion factors were used. Dose rates were evaluated for 1 full year of 500 MW DT operation which is comprised of 3000 1800-second pulses. After one year the machine is shut down for maintenance and personnel are permitted to access the diagnostic interspace after 2-weeks if dose rates are below 100 μSv/hr. Dose rates in the Visible-IR diagnostic model after one day of shutdown were 130 μSv/hr but fell below the limit to 90 μSv/hr 2-weeks later. The Large Aperture style shielding model exhibited higher and more persistent dose rates. After 1-day the dose rate was 230 μSv/hr but was still at 120 μSv/hr 4-weeks later.« less

Anisotropic scene geometry resampling with occlusion filling for 3DTV applications

NASA Astrophysics Data System (ADS)

Kim, Jangheon; Sikora, Thomas

2006-02-01

Image and video-based rendering technologies are receiving growing attention due to their photo-realistic rendering capability in free-viewpoint. However, two major limitations are ghosting and blurring due to their sampling-based mechanism. The scene geometry which supports to select accurate sampling positions is proposed using global method (i.e. approximate depth plane) and local method (i.e. disparity estimation). This paper focuses on the local method since it can yield more accurate rendering quality without large number of cameras. The local scene geometry has two difficulties which are the geometrical density and the uncovered area including hidden information. They are the serious drawback to reconstruct an arbitrary viewpoint without aliasing artifacts. To solve the problems, we propose anisotropic diffusive resampling method based on tensor theory. Isotropic low-pass filtering accomplishes anti-aliasing in scene geometry and anisotropic diffusion prevents filtering from blurring the visual structures. Apertures in coarse samples are estimated following diffusion on the pre-filtered space, the nonlinear weighting of gradient directions suppresses the amount of diffusion. Aliasing artifacts from low density are efficiently removed by isotropic filtering and the edge blurring can be solved by the anisotropic method at one process. Due to difference size of sampling gap, the resampling condition is defined considering causality between filter-scale and edge. Using partial differential equation (PDE) employing Gaussian scale-space, we iteratively achieve the coarse-to-fine resampling. In a large scale, apertures and uncovered holes can be overcoming because only strong and meaningful boundaries are selected on the resolution. The coarse-level resampling with a large scale is iteratively refined to get detail scene structure. Simulation results show the marked improvements of rendering quality.

Greedy Sampling and Incremental Surrogate Model-Based Tailoring of Aeroservoelastic Model Database for Flexible Aircraft

NASA Technical Reports Server (NTRS)

Wang, Yi; Pant, Kapil; Brenner, Martin J.; Ouellette, Jeffrey A.

2018-01-01

This paper presents a data analysis and modeling framework to tailor and develop linear parameter-varying (LPV) aeroservoelastic (ASE) model database for flexible aircrafts in broad 2D flight parameter space. The Kriging surrogate model is constructed using ASE models at a fraction of grid points within the original model database, and then the ASE model at any flight condition can be obtained simply through surrogate model interpolation. The greedy sampling algorithm is developed to select the next sample point that carries the worst relative error between the surrogate model prediction and the benchmark model in the frequency domain among all input-output channels. The process is iterated to incrementally improve surrogate model accuracy till a pre-determined tolerance or iteration budget is met. The methodology is applied to the ASE model database of a flexible aircraft currently being tested at NASA/AFRC for flutter suppression and gust load alleviation. Our studies indicate that the proposed method can reduce the number of models in the original database by 67%. Even so the ASE models obtained through Kriging interpolation match the model in the original database constructed directly from the physics-based tool with the worst relative error far below 1%. The interpolated ASE model exhibits continuously-varying gains along a set of prescribed flight conditions. More importantly, the selected grid points are distributed non-uniformly in the parameter space, a) capturing the distinctly different dynamic behavior and its dependence on flight parameters, and b) reiterating the need and utility for adaptive space sampling techniques for ASE model database compaction. The present framework is directly extendible to high-dimensional flight parameter space, and can be used to guide the ASE model development, model order reduction, robust control synthesis and novel vehicle design of flexible aircraft.

Montblanc1: GPU accelerated radio interferometer measurement equations in support of Bayesian inference for radio observations

NASA Astrophysics Data System (ADS)

Perkins, S. J.; Marais, P. C.; Zwart, J. T. L.; Natarajan, I.; Tasse, C.; Smirnov, O.

2015-09-01

We present Montblanc, a GPU implementation of the Radio interferometer measurement equation (RIME) in support of the Bayesian inference for radio observations (BIRO) technique. BIRO uses Bayesian inference to select sky models that best match the visibilities observed by a radio interferometer. To accomplish this, BIRO evaluates the RIME multiple times, varying sky model parameters to produce multiple model visibilities. χ2 values computed from the model and observed visibilities are used as likelihood values to drive the Bayesian sampling process and select the best sky model. As most of the elements of the RIME and χ2 calculation are independent of one another, they are highly amenable to parallel computation. Additionally, Montblanc caters for iterative RIME evaluation to produce multiple χ2 values. Modified model parameters are transferred to the GPU between each iteration. We implemented Montblanc as a Python package based upon NVIDIA's CUDA architecture. As such, it is easy to extend and implement different pipelines. At present, Montblanc supports point and Gaussian morphologies, but is designed for easy addition of new source profiles. Montblanc's RIME implementation is performant: On an NVIDIA K40, it is approximately 250 times faster than MEQTREES on a dual hexacore Intel E5-2620v2 CPU. Compared to the OSKAR simulator's GPU-implemented RIME components it is 7.7 and 12 times faster on the same K40 for single and double-precision floating point respectively. However, OSKAR's RIME implementation is more general than Montblanc's BIRO-tailored RIME. Theoretical analysis of Montblanc's dominant CUDA kernel suggests that it is memory bound. In practice, profiling shows that is balanced between compute and memory, as much of the data required by the problem is retained in L1 and L2 caches.

Why and how Mastering an Incremental and Iterative Software Development Process

NASA Astrophysics Data System (ADS)

Dubuc, François; Guichoux, Bernard; Cormery, Patrick; Mescam, Jean Christophe

2004-06-01

One of the key issues regularly mentioned in the current software crisis of the space domain is related to the software development process that must be performed while the system definition is not yet frozen. This is especially true for complex systems like launchers or space vehicles.Several more or less mature solutions are under study by EADS SPACE Transportation and are going to be presented in this paper. The basic principle is to develop the software through an iterative and incremental process instead of the classical waterfall approach, with the following advantages:- It permits systematic management and incorporation of requirements changes over the development cycle with a minimal cost. As far as possible the most dimensioning requirements are analyzed and developed in priority for validating very early the architecture concept without the details.- A software prototype is very quickly available. It improves the communication between system and software teams, as it enables to check very early and efficiently the common understanding of the system requirements.- It allows the software team to complete a whole development cycle very early, and thus to become quickly familiar with the software development environment (methodology, technology, tools...). This is particularly important when the team is new, or when the environment has changed since the previous development. Anyhow, it improves a lot the learning curve of the software team.These advantages seem very attractive, but mastering efficiently an iterative development process is not so easy and induces a lot of difficulties such as:- How to freeze one configuration of the system definition as a development baseline, while most of thesystem requirements are completely and naturally unstable?- How to distinguish stable/unstable and dimensioning/standard requirements?- How to plan the development of each increment?- How to link classical waterfall development milestones with an iterative approach: when should theclassical reviews be performed: Software Specification Review? Preliminary Design Review? CriticalDesign Review? Code Review? Etc...Several solutions envisaged or already deployed by EADS SPACE Transportation will be presented, both from a methodological and technological point of view:- How the MELANIE EADS ST internal methodology improves the concurrent engineering activitiesbetween GNC, software and simulation teams in a very iterative and reactive way.- How the CMM approach can help by better formalizing Requirements Management and Planningprocesses.- How the Automatic Code Generation with "certified" tools (SCADE) can still dramatically shorten thedevelopment cycle.Then the presentation will conclude by showing an evaluation of the cost and planning reduction based on a pilot application by comparing figures on two similar projects: one with the classical waterfall process, the other one with an iterative and incremental approach.

A Dynamic Model of the Initial Spares Support List Development Process

DTIC Science & Technology

1979-06-01

S117Z1NOTE NREI -NOT READI END ITERS IIT7INOTE GPEI -QUANTITY OF PARTS M. END ITER 11775NOTE FUSERF -PARTS USE RATE FACTOR U8WOTE OP U -OTHER PARTS USE...FAILURES ’I 1675R PtJER.L=(NREI.K) (QPEI) (PUSERF.K)+OPUR II7HNOTE PUSER -PARTS USE RATE II7t5NOTE NREI -NOT READY END ITEMS II756NOTE GPEI -QUANTITY

Successful classification of cocaine dependence using brain imaging: a generalizable machine learning approach.

PubMed

Mete, Mutlu; Sakoglu, Unal; Spence, Jeffrey S; Devous, Michael D; Harris, Thomas S; Adinoff, Bryon

2016-10-06

Neuroimaging studies have yielded significant advances in the understanding of neural processes relevant to the development and persistence of addiction. However, these advances have not explored extensively for diagnostic accuracy in human subjects. The aim of this study was to develop a statistical approach, using a machine learning framework, to correctly classify brain images of cocaine-dependent participants and healthy controls. In this study, a framework suitable for educing potential brain regions that differed between the two groups was developed and implemented. Single Photon Emission Computerized Tomography (SPECT) images obtained during rest or a saline infusion in three cohorts of 2-4 week abstinent cocaine-dependent participants (n = 93) and healthy controls (n = 69) were used to develop a classification model. An information theoretic-based feature selection algorithm was first conducted to reduce the number of voxels. A density-based clustering algorithm was then used to form spatially connected voxel clouds in three-dimensional space. A statistical classifier, Support Vectors Machine (SVM), was then used for participant classification. Statistically insignificant voxels of spatially connected brain regions were removed iteratively and classification accuracy was reported through the iterations. The voxel-based analysis identified 1,500 spatially connected voxels in 30 distinct clusters after a grid search in SVM parameters. Participants were successfully classified with 0.88 and 0.89 F-measure accuracies in 10-fold cross validation (10xCV) and leave-one-out (LOO) approaches, respectively. Sensitivity and specificity were 0.90 and 0.89 for LOO; 0.83 and 0.83 for 10xCV. Many of the 30 selected clusters are highly relevant to the addictive process, including regions relevant to cognitive control, default mode network related self-referential thought, behavioral inhibition, and contextual memories. Relative hyperactivity and hypoactivity of regional cerebral blood flow in brain regions in cocaine-dependent participants are presented with corresponding level of significance. The SVM-based approach successfully classified cocaine-dependent and healthy control participants using voxels selected with information theoretic-based and statistical methods from participants' SPECT data. The regions found in this study align with brain regions reported in the literature. These findings support the future use of brain imaging and SVM-based classifier in the diagnosis of substance use disorders and furthering an understanding of their underlying pathology.

Image preprocessing for improving computational efficiency in implementation of restoration and superresolution algorithms.

PubMed

Sundareshan, Malur K; Bhattacharjee, Supratik; Inampudi, Radhika; Pang, Ho-Yuen

2002-12-10

Computational complexity is a major impediment to the real-time implementation of image restoration and superresolution algorithms in many applications. Although powerful restoration algorithms have been developed within the past few years utilizing sophisticated mathematical machinery (based on statistical optimization and convex set theory), these algorithms are typically iterative in nature and require a sufficient number of iterations to be executed to achieve the desired resolution improvement that may be needed to meaningfully perform postprocessing image exploitation tasks in practice. Additionally, recent technological breakthroughs have facilitated novel sensor designs (focal plane arrays, for instance) that make it possible to capture megapixel imagery data at video frame rates. A major challenge in the processing of these large-format images is to complete the execution of the image processing steps within the frame capture times and to keep up with the output rate of the sensor so that all data captured by the sensor can be efficiently utilized. Consequently, development of novel methods that facilitate real-time implementation of image restoration and superresolution algorithms is of significant practical interest and is the primary focus of this study. The key to designing computationally efficient processing schemes lies in strategically introducing appropriate preprocessing steps together with the superresolution iterations to tailor optimized overall processing sequences for imagery data of specific formats. For substantiating this assertion, three distinct methods for tailoring a preprocessing filter and integrating it with the superresolution processing steps are outlined. These methods consist of a region-of-interest extraction scheme, a background-detail separation procedure, and a scene-derived information extraction step for implementing a set-theoretic restoration of the image that is less demanding in computation compared with the superresolution iterations. A quantitative evaluation of the performance of these algorithms for restoring and superresolving various imagery data captured by diffraction-limited sensing operations are also presented.

Methane Dual Expander Aerospike Nozzle Rocket Engine

DTIC Science & Technology

2012-03-22

include O/F ratio, thrust, and engine geometry. After thousands of iterations over the design space , the selected MDEAN engine concept has 349 s of...35 Table 7: Fluid Property Table Supported Parameters...44 Table 8: Fluid Property Input Data Independent Variable Ranges. ................................. 46 Table 9

Performance analysis of the toroidal field ITER production conductors

NASA Astrophysics Data System (ADS)

Breschi, M.; Macioce, D.; Devred, A.

2017-05-01

The production of the superconducting cables for the toroidal field (TF) magnets of the ITER machine has recently been completed at the manufacturing companies selected during the previous qualification phase. The quality assurance/quality control programs that have been implemented to ensure production uniformity across numerous suppliers include performance tests of several conductor samples from selected unit lengths. The short full-size samples (4 m long) were subjected to DC and AC tests in the SULTAN facility at CRPP in Villigen, Switzerland. In a previous work the results of the tests of the conductor performance qualification samples were reported. This work reports the analyses of the results of the tests of the production conductor samples. The results reported here concern the values of current sharing temperature, critical current, effective strain and n-value from the DC tests and the energy dissipated per cycle from the AC loss tests. A detailed comparison is also presented between the performance of the conductors and that of their constituting strands.

Bridging single and multireference coupled cluster theories with universal state selective formalism

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

Bhaskaran-Nair, Kiran; Kowalski, Karol

2013-05-28

The universal state selective (USS) multireference approach is used to construct new energy functionals which offers a unique possibility of bridging single and multireference coupled cluster theories (SR/MRCC). These functionals, which can be used to develop iterative and non-iterative approaches, utilize a special form of the trial wavefunctions, which assure additive separability (or size-consistency) of the USS energies in the non-interacting subsystem limit. When the USS formalism is combined with approximate SRCC theories, the resulting formalism can be viewed as a size-consistent version of the method of moments of coupled cluster equations (MMCC) employing a MRCC trial wavefunction. Special casesmore » of the USS formulations, which utilize single reference state specific CC (V.V. Ivanov, D.I. Lyakh, L. Adamowicz, Phys. Chem. Chem. Phys. 11, 2355 (2009)) and tailored CC (T. Kinoshita, O. Hino, R.J. Bartlett, J. Chem. Phys. 123, 074106 (2005)) expansions are also discussed.« less

RMP: Reduced-set matching pursuit approach for efficient compressed sensing signal reconstruction.

PubMed

Abdel-Sayed, Michael M; Khattab, Ahmed; Abu-Elyazeed, Mohamed F

2016-11-01

Compressed sensing enables the acquisition of sparse signals at a rate that is much lower than the Nyquist rate. Compressed sensing initially adopted [Formula: see text] minimization for signal reconstruction which is computationally expensive. Several greedy recovery algorithms have been recently proposed for signal reconstruction at a lower computational complexity compared to the optimal [Formula: see text] minimization, while maintaining a good reconstruction accuracy. In this paper, the Reduced-set Matching Pursuit (RMP) greedy recovery algorithm is proposed for compressed sensing. Unlike existing approaches which either select too many or too few values per iteration, RMP aims at selecting the most sufficient number of correlation values per iteration, which improves both the reconstruction time and error. Furthermore, RMP prunes the estimated signal, and hence, excludes the incorrectly selected values. The RMP algorithm achieves a higher reconstruction accuracy at a significantly low computational complexity compared to existing greedy recovery algorithms. It is even superior to [Formula: see text] minimization in terms of the normalized time-error product, a new metric introduced to measure the trade-off between the reconstruction time and error. RMP superior performance is illustrated with both noiseless and noisy samples.

Acceleration of linear stationary iterative processes in multiprocessor computers. II

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

Romm, Ya.E.

1982-05-01

For pt.I, see Kibernetika, vol.18, no.1, p.47 (1982). For pt.I, see Cybernetics, vol.18, no.1, p.54 (1982). Considers a reduced system of linear algebraic equations x=ax+b, where a=(a/sub ij/) is a real n*n matrix; b is a real vector with common euclidean norm >>>. It is supposed that the existence and uniqueness of solution det (0-a) not equal to e is given, where e is a unit matrix. The linear iterative process converging to x x/sup (k+1)/=fx/sup (k)/, k=0, 1, 2, ..., where the operator f translates r/sup n/ into r/sup n/. In considering implementation of the iterative process (ip) inmore » a multiprocessor system, it is assumed that the number of processors is constant, and are various values of the latter investigated; it is assumed in addition, that the processors perform elementary binary arithmetic operations of addition and multiestimates only include the time of execution of arithmetic operations. With any paralleling of individual iteration, the execution time of the ip is proportional to the number of sequential steps k+1. The author sets the task of reducing the number of sequential steps in the ip so as to execute it in a time proportional to a value smaller than k+1. He also sets the goal of formulating a method of accelerated bit serial-parallel execution of each successive step of the ip, with, in the modification sought, a reduced number of steps in a time comparable to the operation time of logical elements. 6 references.« less

Joint Transmit Power Allocation and Splitting for SWIPT Aided OFDM-IDMA in Wireless Sensor Networks

PubMed Central

Li, Shanshan; Zhou, Xiaotian; Wang, Cheng-Xiang; Yuan, Dongfeng; Zhang, Wensheng

2017-01-01

In this paper, we propose to combine Orthogonal Frequency Division Multiplexing-Interleave Division Multiple Access (OFDM-IDMA) with Simultaneous Wireless Information and Power Transfer (SWIPT), resulting in SWIPT aided OFDM-IDMA scheme for power-limited sensor networks. In the proposed system, the Receive Node (RN) applies Power Splitting (PS) to coordinate the Energy Harvesting (EH) and Information Decoding (ID) process, where the harvested energy is utilized to guarantee the iterative Multi-User Detection (MUD) of IDMA to work under sufficient number of iterations. Our objective is to minimize the total transmit power of Source Node (SN), while satisfying the requirements of both minimum harvested energy and Bit Error Rate (BER) performance from individual receive nodes. We formulate such a problem as a joint power allocation and splitting one, where the iteration number of MUD is also taken into consideration as the key parameter to affect both EH and ID constraints. To solve it, a sub-optimal algorithm is proposed to determine the power profile, PS ratio and iteration number of MUD in an iterative manner. Simulation results verify that the proposed algorithm can provide significant performance improvement. PMID:28677636

Joint Transmit Power Allocation and Splitting for SWIPT Aided OFDM-IDMA in Wireless Sensor Networks.

PubMed

Li, Shanshan; Zhou, Xiaotian; Wang, Cheng-Xiang; Yuan, Dongfeng; Zhang, Wensheng

2017-07-04

In this paper, we propose to combine Orthogonal Frequency Division Multiplexing-Interleave Division Multiple Access (OFDM-IDMA) with Simultaneous Wireless Information and Power Transfer (SWIPT), resulting in SWIPT aided OFDM-IDMA scheme for power-limited sensor networks. In the proposed system, the Receive Node (RN) applies Power Splitting (PS) to coordinate the Energy Harvesting (EH) and Information Decoding (ID) process, where the harvested energy is utilized to guarantee the iterative Multi-User Detection (MUD) of IDMA to work under sufficient number of iterations. Our objective is to minimize the total transmit power of Source Node (SN), while satisfying the requirements of both minimum harvested energy and Bit Error Rate (BER) performance from individual receive nodes. We formulate such a problem as a joint power allocation and splitting one, where the iteration number of MUD is also taken into consideration as the key parameter to affect both EH and ID constraints. To solve it, a sub-optimal algorithm is proposed to determine the power profile, PS ratio and iteration number of MUD in an iterative manner. Simulation results verify that the proposed algorithm can provide significant performance improvement.

Pseudo-time methods for constrained optimization problems governed by PDE

NASA Technical Reports Server (NTRS)

Taasan, Shlomo

1995-01-01

In this paper we present a novel method for solving optimization problems governed by partial differential equations. Existing methods are gradient information in marching toward the minimum, where the constrained PDE is solved once (sometimes only approximately) per each optimization step. Such methods can be viewed as a marching techniques on the intersection of the state and costate hypersurfaces while improving the residuals of the design equations per each iteration. In contrast, the method presented here march on the design hypersurface and at each iteration improve the residuals of the state and costate equations. The new method is usually much less expensive per iteration step since, in most problems of practical interest, the design equation involves much less unknowns that that of either the state or costate equations. Convergence is shown using energy estimates for the evolution equations governing the iterative process. Numerical tests show that the new method allows the solution of the optimization problem in a cost of solving the analysis problems just a few times, independent of the number of design parameters. The method can be applied using single grid iterations as well as with multigrid solvers.

FAST TRACK PAPER: Non-iterative multiple-attenuation methods: linear inverse solutions to non-linear inverse problems - II. BMG approximation

NASA Astrophysics Data System (ADS)

Ikelle, Luc T.; Osen, Are; Amundsen, Lasse; Shen, Yunqing

2004-12-01

The classical linear solutions to the problem of multiple attenuation, like predictive deconvolution, τ-p filtering, or F-K filtering, are generally fast, stable, and robust compared to non-linear solutions, which are generally either iterative or in the form of a series with an infinite number of terms. These qualities have made the linear solutions more attractive to seismic data-processing practitioners. However, most linear solutions, including predictive deconvolution or F-K filtering, contain severe assumptions about the model of the subsurface and the class of free-surface multiples they can attenuate. These assumptions limit their usefulness. In a recent paper, we described an exception to this assertion for OBS data. We showed in that paper that a linear and non-iterative solution to the problem of attenuating free-surface multiples which is as accurate as iterative non-linear solutions can be constructed for OBS data. We here present a similar linear and non-iterative solution for attenuating free-surface multiples in towed-streamer data. For most practical purposes, this linear solution is as accurate as the non-linear ones.

Functional materials for breeding blankets—status and developments

NASA Astrophysics Data System (ADS)

Konishi, S.; Enoeda, M.; Nakamichi, M.; Hoshino, T.; Ying, A.; Sharafat, S.; Smolentsev, S.

2017-09-01

The development of tritium breeder, neutron multiplier and flow channel insert materials for the breeding blanket of the DEMO reactor is reviewed. Present emphasis is on the ITER test blanket module (TBM); lithium metatitanate (Li2TiO3) and lithium orthosilicate (Li4SiO4) pebbles have been developed by leading TBM parties. Beryllium pebbles have been selected as the neutron multiplier. Good progress has been made in their fabrication; however, verification of the design by experiments is in the planning stage. Irradiation data are also limited, but the decrease in thermal conductivity of beryllium due to irradiation followed by swelling is a concern. Tests at ITER are regarded as a major milestone. For the DEMO reactor, improvement of the breeder has been attempted to obtain a higher lithium content, and Be12Ti and other beryllide intermetallic compounds that have superior chemical stability have been studied. LiPb eutectic has been considered as a DEMO blanket in the liquid breeder option and is used as a coolant to achieve a higher outlet temperature; a SiC flow channel insert is used to prevent magnetohydrodynamic pressure drop and corrosion. A significant technical gap between ITER TBM and DEMO is recognized, and the world fusion community is working on ITER TBM and DEMO blanket development in parallel.

Using multiple classifiers for predicting the risk of endovascular aortic aneurysm repair re-intervention through hybrid feature selection.

PubMed

Attallah, Omneya; Karthikesalingam, Alan; Holt, Peter Je; Thompson, Matthew M; Sayers, Rob; Bown, Matthew J; Choke, Eddie C; Ma, Xianghong

2017-11-01

Feature selection is essential in medical area; however, its process becomes complicated with the presence of censoring which is the unique character of survival analysis. Most survival feature selection methods are based on Cox's proportional hazard model, though machine learning classifiers are preferred. They are less employed in survival analysis due to censoring which prevents them from directly being used to survival data. Among the few work that employed machine learning classifiers, partial logistic artificial neural network with auto-relevance determination is a well-known method that deals with censoring and perform feature selection for survival data. However, it depends on data replication to handle censoring which leads to unbalanced and biased prediction results especially in highly censored data. Other methods cannot deal with high censoring. Therefore, in this article, a new hybrid feature selection method is proposed which presents a solution to high level censoring. It combines support vector machine, neural network, and K-nearest neighbor classifiers using simple majority voting and a new weighted majority voting method based on survival metric to construct a multiple classifier system. The new hybrid feature selection process uses multiple classifier system as a wrapper method and merges it with iterated feature ranking filter method to further reduce features. Two endovascular aortic repair datasets containing 91% censored patients collected from two centers were used to construct a multicenter study to evaluate the performance of the proposed approach. The results showed the proposed technique outperformed individual classifiers and variable selection methods based on Cox's model such as Akaike and Bayesian information criterions and least absolute shrinkage and selector operator in p values of the log-rank test, sensitivity, and concordance index. This indicates that the proposed classifier is more powerful in correctly predicting the risk of re-intervention enabling doctor in selecting patients' future follow-up plan.

Criteria for selecting implementation science theories and frameworks: results from an international survey.

PubMed

Birken, Sarah A; Powell, Byron J; Shea, Christopher M; Haines, Emily R; Alexis Kirk, M; Leeman, Jennifer; Rohweder, Catherine; Damschroder, Laura; Presseau, Justin

2017-10-30

Theories provide a synthesizing architecture for implementation science. The underuse, superficial use, and misuse of theories pose a substantial scientific challenge for implementation science and may relate to challenges in selecting from the many theories in the field. Implementation scientists may benefit from guidance for selecting a theory for a specific study or project. Understanding how implementation scientists select theories will help inform efforts to develop such guidance. Our objective was to identify which theories implementation scientists use, how they use theories, and the criteria used to select theories. We identified initial lists of uses and criteria for selecting implementation theories based on seminal articles and an iterative consensus process. We incorporated these lists into a self-administered survey for completion by self-identified implementation scientists. We recruited potential respondents at the 8th Annual Conference on the Science of Dissemination and Implementation in Health and via several international email lists. We used frequencies and percentages to report results. Two hundred twenty-three implementation scientists from 12 countries responded to the survey. They reported using more than 100 different theories spanning several disciplines. Respondents reported using theories primarily to identify implementation determinants, inform data collection, enhance conceptual clarity, and guide implementation planning. Of the 19 criteria presented in the survey, the criteria used by the most respondents to select theory included analytic level (58%), logical consistency/plausibility (56%), empirical support (53%), and description of a change process (54%). The criteria used by the fewest respondents included fecundity (10%), uniqueness (12%), and falsifiability (15%). Implementation scientists use a large number of criteria to select theories, but there is little consensus on which are most important. Our results suggest that the selection of implementation theories is often haphazard or driven by convenience or prior exposure. Variation in approaches to selecting theory warn against prescriptive guidance for theory selection. Instead, implementation scientists may benefit from considering the criteria that we propose in this paper and using them to justify their theory selection. Future research should seek to refine the criteria for theory selection to promote more consistent and appropriate use of theory in implementation science.

A Parameter Tuning Scheme of Sea-ice Model Based on Automatic Differentiation Technique

NASA Astrophysics Data System (ADS)

Kim, J. G.; Hovland, P. D.

2001-05-01

Automatic diferentiation (AD) technique was used to illustrate a new approach for parameter tuning scheme of an uncoupled sea-ice model. Atmospheric forcing field of 1992 obtained from NCEP data was used as enforcing variables in the study. The simulation results were compared with the observed ice movement provided by the International Arctic Buoy Programme (IABP). All of the numerical experiments were based on a widely used dynamic and thermodynamic model for simulating the seasonal sea-ice chnage of the main Arctic ocean. We selected five dynamic and thermodynamic parameters for the tuning process in which the cost function defined by the norm of the difference between observed and simulated ice drift locations was minimized. The selected parameters are the air and ocean drag coefficients, the ice strength constant, the turning angle at ice-air/ocean interface, and the bulk sensible heat transfer coefficient. The drag coefficients were the major parameters to control sea-ice movement and extent. The result of the study shows that more realistic simulations of ice thickness distribution was produced by tuning the simulated ice drift trajectories. In the tuning process, the L-BFCGS-B minimization algorithm of a quasi-Newton method was used. The derivative information required in the minimization iterations was provided by the AD processed Fortran code. Compared with a conventional approach, AD generated derivative code provided fast and robust computations of derivative information.

Quality Improvement in Critical Care: Selection and Development of Quality Indicators

PubMed Central

Martin, Claudio M.; Project, The Quality Improvement in Critical Care

2016-01-01

Background. Caring for critically ill patients is complex and resource intensive. An approach to monitor and compare the function of different intensive care units (ICUs) is needed to optimize outcomes for patients and the health system as a whole. Objective. To develop and implement quality indicators for comparing ICU characteristics and performance within and between ICUs and regions over time. Methods. Canadian jurisdictions with established ICU clinical databases were invited to participate in an iterative series of face-to-face meetings, teleconferences, and web conferences. Eighteen adult intensive care units across 14 hospitals and 5 provinces participated in the process. Results. Six domains of ICU function were identified: safe, timely, efficient, effective, patient/family satisfaction, and staff work life. Detailed operational definitions were developed for 22 quality indicators. The feasibility was demonstrated with the collection of 3.5 years of data. Statistical process control charts and graphs of composite measures were used for data display and comparisons. Medical and nursing leaders as well as administrators found the system to be an improvement over prior methods. Conclusions. Our process resulted in the selection and development of 22 indicators representing 6 domains of ICU function. We have demonstrated the feasibility of such a reporting system. This type of reporting system will demonstrate variation between units and jurisdictions to help identify and prioritize improvement efforts. PMID:27493476

E-Learning Quality Assurance: A Process-Oriented Lifecycle Model

ERIC Educational Resources Information Center

Abdous, M'hammed

2009-01-01

Purpose: The purpose of this paper is to propose a process-oriented lifecycle model for ensuring quality in e-learning development and delivery. As a dynamic and iterative process, quality assurance (QA) is intertwined with the e-learning development process. Design/methodology/approach: After reviewing the existing literature, particularly…

An exploration of inter-organisational partnership assessment tools in the context of Australian Aboriginal-mainstream partnerships: a scoping review of the literature.

PubMed

Tsou, Christina; Haynes, Emma; Warner, Wayne D; Gray, Gordon; Thompson, Sandra C

2015-04-23

The need for better partnerships between Aboriginal organisations and mainstream agencies demands attention on process and relational elements of these partnerships, and improving partnership functioning through transformative or iterative evaluation procedures. This paper presents the findings of a literature review which examines the usefulness of existing partnership tools to the Australian Aboriginal-mainstream partnership (AMP) context. Three sets of best practice principles for successful AMP were selected based on authors' knowledge and experience. Items in each set of principles were separated into process and relational elements and used to guide the analysis of partnership assessment tools. The review and analysis of partnership assessment tools were conducted in three distinct but related parts. Part 1- identify and select reviews of partnership tools; part 2 - identify and select partnership self-assessment tool; part 3 - analysis of selected tools using AMP principles. The focus on relational and process elements in the partnership tools reviewed is consistent with the focus of Australian AMP principles by reconciliation advocates; however, historical context, lived experience, cultural context and approaches of Australian Aboriginal people represent key deficiencies in the tools reviewed. The overall assessment indicated that the New York Partnership Self-Assessment Tool and the VicHealth Partnership Analysis Tools reflect the greatest number of AMP principles followed by the Nuffield Partnership Assessment Tool. The New York PSAT has the strongest alignment with the relational elements while VicHealth and Nuffield tools showed greatest alignment with the process elements in the chosen AMP principles. Partnership tools offer opportunities for providing evidence based support to partnership development. The multiplicity of tools in existence and the reported uniqueness of each partnership, mean the development of a generic partnership analysis for AMP may not be a viable option for future effort.

A Study of Morrison's Iterative Noise Removal Method. Final Report M. S. Thesis

NASA Technical Reports Server (NTRS)

Ioup, G. E.; Wright, K. A. R.

1985-01-01

Morrison's iterative noise removal method is studied by characterizing its effect upon systems of differing noise level and response function. The nature of data acquired from a linear shift invariant instrument is discussed so as to define the relationship between the input signal, the instrument response function, and the output signal. Fourier analysis is introduced, along with several pertinent theorems, as a tool to more thorough understanding of the nature of and difficulties with deconvolution. In relation to such difficulties the necessity of a noise removal process is discussed. Morrison's iterative noise removal method and the restrictions upon its application are developed. The nature of permissible response functions is discussed, as is the choice of the response functions used.

Block Gauss elimination followed by a classical iterative method for the solution of linear systems

NASA Astrophysics Data System (ADS)

Alanelli, Maria; Hadjidimos, Apostolos

2004-02-01

In the last two decades many papers have appeared in which the application of an iterative method for the solution of a linear system is preceded by a step of the Gauss elimination process in the hope that this will increase the rates of convergence of the iterative method. This combination of methods has been proven successful especially when the matrix A of the system is an M-matrix. The purpose of this paper is to extend the idea of one to more Gauss elimination steps, consider other classes of matrices A, e.g., p-cyclic consistently ordered, and generalize and improve the asymptotic convergence rates of some of the methods known so far.

Selection and utilization of assessment instruments in substance abuse treatment trials: the National Drug Abuse Treatment Clinical Trials Network experience.

PubMed

Rosa, Carmen; Ghitza, Udi; Tai, Betty

2012-07-17

Based on recommendations from a US Institute of Medicine report, the National Institute on Drug Abuse established the National Drug Abuse Treatment Clinical Trials Network (CTN) in 1999, to accelerate the translation of science-based addiction treatment research into community-based practice, and to improve the quality of addiction treatment, using science as the vehicle. One of the CTN's primary tasks is to serve as a platform to forge bi-directional communications and collaborations between providers and scientists, to enhance the relevance of research, which generates empirical results that impact practice. Among many obstacles in moving research into real-world settings, this commentary mainly describes challenges and iterative experiences in regard to how the CTN develops its research protocols, with focus on how the CTN study teams select and utilize assessment instruments, which can reasonably balance the interests of both research scientists and practicing providers when applied in CTN trials. This commentary also discusses the process by which the CTN further selects a core set of common assessment instruments that may be applied across all trials, to allow easier cross-study analyses of comparable data.

Monte Carlo modeling of time-resolved fluorescence for depth-selective interrogation of layered tissue.

PubMed

Pfefer, T Joshua; Wang, Quanzeng; Drezek, Rebekah A

2011-11-01

Computational approaches for simulation of light-tissue interactions have provided extensive insight into biophotonic procedures for diagnosis and therapy. However, few studies have addressed simulation of time-resolved fluorescence (TRF) in tissue and none have combined Monte Carlo simulations with standard TRF processing algorithms to elucidate approaches for cancer detection in layered biological tissue. In this study, we investigate how illumination-collection parameters (e.g., collection angle and source-detector separation) influence the ability to measure fluorophore lifetime and tissue layer thickness. Decay curves are simulated with a Monte Carlo TRF light propagation model. Multi-exponential iterative deconvolution is used to determine lifetimes and fractional signal contributions. The ability to detect changes in mucosal thickness is optimized by probes that selectively interrogate regions superficial to the mucosal-submucosal boundary. Optimal accuracy in simultaneous determination of lifetimes in both layers is achieved when each layer contributes 40-60% of the signal. These results indicate that depth-selective approaches to TRF have the potential to enhance disease detection in layered biological tissue and that modeling can play an important role in probe design optimization. Published by Elsevier Ireland Ltd.

The MedlinePlus public user interface: studies of design challenges and opportunities.

PubMed

Marill, Jennifer L; Miller, Naomi; Kitendaugh, Paula

2006-01-01

What are the challenges involved in designing, modifying, and improving a major health information portal that serves over sixty million page views a month? MedlinePlus, the National Library of Medicine's (NLM's) consumer health Website, is examined. Challenges are presented as six "studies," which describe selected design issues and how NLM staff resolved them. Improving MedlinePlus is an iterative process. Changes in the public user interface are ongoing, reflecting Web design trends, usability testing recommendations, user survey results, new technical requirements, and the need to grow the site in an orderly way. Testing and analysis should accompany Website design modifications. New technologies may enhance a site but also introduce problems. Further modifications to MedlinePlus will be informed by the experiences described here.

Afraid to Start Because the Outcome is Uncertain?: Social Site Characterization as a Tool for Informing Public Engagement Efforts

USGS Publications Warehouse

Wade, S.; Greenberg, S.

2009-01-01

This paper introduces the concept of social site characterization as a parallel effort to technical site characterization to be used in evaluating and planning carbon dioxides capture and storage (CCS) projects. Social site characterization, much like technical site characterization, relies on a series of iterative investigations into public attitudes towards a CCS project and the factors that will shape those views. This paper also suggests ways it can be used to design approaches for actively engaging stakeholders and communities in the deployment of CCS projects. This work is informed by observing the site selection process for FutureGen and the implementation of research projects under the Regional Carbon Sequestration Partnership Program. ?? 2009 Elsevier Ltd. All rights reserved.

Planning as an Iterative Process

NASA Technical Reports Server (NTRS)

Smith, David E.

2012-01-01

Activity planning for missions such as the Mars Exploration Rover mission presents many technical challenges, including oversubscription, consideration of time, concurrency, resources, preferences, and uncertainty. These challenges have all been addressed by the research community to varying degrees, but significant technical hurdles still remain. In addition, the integration of these capabilities into a single planning engine remains largely unaddressed. However, I argue that there is a deeper set of issues that needs to be considered namely the integration of planning into an iterative process that begins before the goals, objectives, and preferences are fully defined. This introduces a number of technical challenges for planning, including the ability to more naturally specify and utilize constraints on the planning process, the ability to generate multiple qualitatively different plans, and the ability to provide deep explanation of plans.

Realization of high quality production schedules: Structuring quality factors via iteration of user specification processes

NASA Technical Reports Server (NTRS)

Hamazaki, Takashi

1992-01-01

This paper describes an architecture for realizing high quality production schedules. Although quality is one of the most important aspects of production scheduling, it is difficult, even for a user, to specify precisely. However, it is also true that the decision as to whether a scheduler is good or bad can only be made by the user. This paper proposes the following: (1) the quality of a schedule can be represented in the form of quality factors, i.e. constraints and objectives of the domain, and their structure; (2) quality factors and their structure can be used for decision making at local decision points during the scheduling process; and (3) that they can be defined via iteration of user specification processes.

2009 Space Shuttle Probabilistic Risk Assessment Overview

NASA Technical Reports Server (NTRS)

Hamlin, Teri L.; Canga, Michael A.; Boyer, Roger L.; Thigpen, Eric B.

2010-01-01

Loss of a Space Shuttle during flight has severe consequences, including loss of a significant national asset; loss of national confidence and pride; and, most importantly, loss of human life. The Shuttle Probabilistic Risk Assessment (SPRA) is used to identify risk contributors and their significance; thus, assisting management in determining how to reduce risk. In 2006, an overview of the SPRA Iteration 2.1 was presented at PSAM 8 [1]. Like all successful PRAs, the SPRA is a living PRA and has undergone revisions since PSAM 8. The latest revision to the SPRA is Iteration 3. 1, and it will not be the last as the Shuttle program progresses and more is learned. This paper discusses the SPRA scope, overall methodology, and results, as well as provides risk insights. The scope, assumptions, uncertainties, and limitations of this assessment provide risk-informed perspective to aid management s decision-making process. In addition, this paper compares the Iteration 3.1 analysis and results to the Iteration 2.1 analysis and results presented at PSAM 8.

Implementation of the Iterative Proportion Fitting Algorithm for Geostatistical Facies Modeling

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

Li Yupeng, E-mail: yupeng@ualberta.ca; Deutsch, Clayton V.

2012-06-15

In geostatistics, most stochastic algorithm for simulation of categorical variables such as facies or rock types require a conditional probability distribution. The multivariate probability distribution of all the grouped locations including the unsampled location permits calculation of the conditional probability directly based on its definition. In this article, the iterative proportion fitting (IPF) algorithm is implemented to infer this multivariate probability. Using the IPF algorithm, the multivariate probability is obtained by iterative modification to an initial estimated multivariate probability using lower order bivariate probabilities as constraints. The imposed bivariate marginal probabilities are inferred from profiles along drill holes or wells.more » In the IPF process, a sparse matrix is used to calculate the marginal probabilities from the multivariate probability, which makes the iterative fitting more tractable and practical. This algorithm can be extended to higher order marginal probability constraints as used in multiple point statistics. The theoretical framework is developed and illustrated with estimation and simulation example.« less

Non-iterative distance constraints enforcement for cloth drapes simulation

NASA Astrophysics Data System (ADS)

Hidajat, R. L. L. G.; Wibowo, Arifin, Z.; Suyitno

2016-03-01

A cloth simulation represents the behavior of cloth objects such as flag, tablecloth, or even garments has application in clothing animation for games and virtual shops. Elastically deformable models have widely used to provide realistic and efficient simulation, however problem of overstretching is encountered. We introduce a new cloth simulation algorithm that replaces iterative distance constraint enforcement steps with non-iterative ones for preventing over stretching in a spring-mass system for cloth modeling. Our method is based on a simple position correction procedure applied at one end of a spring. In our experiments, we developed a rectangle cloth model which is initially at a horizontal position with one point is fixed, and it is allowed to drape by its own weight. Our simulation is able to achieve a plausible cloth drapes as in reality. This paper aims to demonstrate the reliability of our approach to overcome overstretches while decreasing the computational cost of the constraint enforcement process due to an iterative procedure that is eliminated.

Error Control Coding Techniques for Space and Satellite Communications

NASA Technical Reports Server (NTRS)

Lin, Shu

2000-01-01

This paper presents a concatenated turbo coding system in which a Reed-Solomom outer code is concatenated with a binary turbo inner code. In the proposed system, the outer code decoder and the inner turbo code decoder interact to achieve both good bit error and frame error performances. The outer code decoder helps the inner turbo code decoder to terminate its decoding iteration while the inner turbo code decoder provides soft-output information to the outer code decoder to carry out a reliability-based soft-decision decoding. In the case that the outer code decoding fails, the outer code decoder instructs the inner code decoder to continue its decoding iterations until the outer code decoding is successful or a preset maximum number of decoding iterations is reached. This interaction between outer and inner code decoders reduces decoding delay. Also presented in the paper are an effective criterion for stopping the iteration process of the inner code decoder and a new reliability-based decoding algorithm for nonbinary codes.

An Interactive Concatenated Turbo Coding System

NASA Technical Reports Server (NTRS)

Liu, Ye; Tang, Heng; Lin, Shu; Fossorier, Marc

1999-01-01

This paper presents a concatenated turbo coding system in which a Reed-Solomon outer code is concatenated with a binary turbo inner code. In the proposed system, the outer code decoder and the inner turbo code decoder interact to achieve both good bit error and frame error performances. The outer code decoder helps the inner turbo code decoder to terminate its decoding iteration while the inner turbo code decoder provides soft-output information to the outer code decoder to carry out a reliability-based soft- decision decoding. In the case that the outer code decoding fails, the outer code decoder instructs the inner code decoder to continue its decoding iterations until the outer code decoding is successful or a preset maximum number of decoding iterations is reached. This interaction between outer and inner code decoders reduces decoding delay. Also presented in the paper are an effective criterion for stopping the iteration process of the inner code decoder and a new reliability-based decoding algorithm for nonbinary codes.

Volumetric quantification of lung nodules in CT with iterative reconstruction (ASiR and MBIR).

PubMed

Chen, Baiyu; Barnhart, Huiman; Richard, Samuel; Robins, Marthony; Colsher, James; Samei, Ehsan

2013-11-01

Volume quantifications of lung nodules with multidetector computed tomography (CT) images provide useful information for monitoring nodule developments. The accuracy and precision of the volume quantification, however, can be impacted by imaging and reconstruction parameters. This study aimed to investigate the impact of iterative reconstruction algorithms on the accuracy and precision of volume quantification with dose and slice thickness as additional variables. Repeated CT images were acquired from an anthropomorphic chest phantom with synthetic nodules (9.5 and 4.8 mm) at six dose levels, and reconstructed with three reconstruction algorithms [filtered backprojection (FBP), adaptive statistical iterative reconstruction (ASiR), and model based iterative reconstruction (MBIR)] into three slice thicknesses. The nodule volumes were measured with two clinical software (A: Lung VCAR, B: iNtuition), and analyzed for accuracy and precision. Precision was found to be generally comparable between FBP and iterative reconstruction with no statistically significant difference noted for different dose levels, slice thickness, and segmentation software. Accuracy was found to be more variable. For large nodules, the accuracy was significantly different between ASiR and FBP for all slice thicknesses with both software, and significantly different between MBIR and FBP for 0.625 mm slice thickness with Software A and for all slice thicknesses with Software B. For small nodules, the accuracy was more similar between FBP and iterative reconstruction, with the exception of ASIR vs FBP at 1.25 mm with Software A and MBIR vs FBP at 0.625 mm with Software A. The systematic difference between the accuracy of FBP and iterative reconstructions highlights the importance of extending current segmentation software to accommodate the image characteristics of iterative reconstructions. In addition, a calibration process may help reduce the dependency of accuracy on reconstruction algorithms, such that volumes quantified from scans of different reconstruction algorithms can be compared. The little difference found between the precision of FBP and iterative reconstructions could be a result of both iterative reconstruction's diminished noise reduction at the edge of the nodules as well as the loss of resolution at high noise levels with iterative reconstruction. The findings do not rule out potential advantage of IR that might be evident in a study that uses a larger number of nodules or repeated scans.

Learning Objects: A User-Centered Design Process

ERIC Educational Resources Information Center

Branon, Rovy F., III

2011-01-01

Design research systematically creates or improves processes, products, and programs through an iterative progression connecting practice and theory (Reinking, 2008; van den Akker, 2006). Developing a new instructional systems design (ISD) processes through design research is necessary when new technologies emerge that challenge existing practices…

An Implementation Methodology and Software Tool for an Entropy Based Engineering Model for Evolving Systems

DTIC Science & Technology

2003-06-01

delivery Data Access (1980s) "What were unit sales in New England last March?" Relational databases (RDBMS), Structured Query Language ( SQL ...macros written in Visual Basic for Applications ( VBA ). 32 Iteration Two: Class Diagram Tech OASIS Export ScriptImport Filter Data ProcessingMethod 1...MS Excel * 1 VBA Macro*1 contains sends data to co nt ai ns executes * * 1 1 contains contains Figure 20. Iteration two class diagram The

Recent advances in Lanczos-based iterative methods for nonsymmetric linear systems

NASA Technical Reports Server (NTRS)

Freund, Roland W.; Golub, Gene H.; Nachtigal, Noel M.

1992-01-01

In recent years, there has been a true revival of the nonsymmetric Lanczos method. On the one hand, the possible breakdowns in the classical algorithm are now better understood, and so-called look-ahead variants of the Lanczos process have been developed, which remedy this problem. On the other hand, various new Lanczos-based iterative schemes for solving nonsymmetric linear systems have been proposed. This paper gives a survey of some of these recent developments.

Increasing feasibility of the field-programmable gate array implementation of an iterative image registration using a kernel-warping algorithm

NASA Astrophysics Data System (ADS)

Nguyen, An Hung; Guillemette, Thomas; Lambert, Andrew J.; Pickering, Mark R.; Garratt, Matthew A.

2017-09-01

Image registration is a fundamental image processing technique. It is used to spatially align two or more images that have been captured at different times, from different sensors, or from different viewpoints. There have been many algorithms proposed for this task. The most common of these being the well-known Lucas-Kanade (LK) and Horn-Schunck approaches. However, the main limitation of these approaches is the computational complexity required to implement the large number of iterations necessary for successful alignment of the images. Previously, a multi-pass image interpolation algorithm (MP-I2A) was developed to considerably reduce the number of iterations required for successful registration compared with the LK algorithm. This paper develops a kernel-warping algorithm (KWA), a modified version of the MP-I2A, which requires fewer iterations to successfully register two images and less memory space for the field-programmable gate array (FPGA) implementation than the MP-I2A. These reductions increase feasibility of the implementation of the proposed algorithm on FPGAs with very limited memory space and other hardware resources. A two-FPGA system rather than single FPGA system is successfully developed to implement the KWA in order to compensate insufficiency of hardware resources supported by one FPGA, and increase parallel processing ability and scalability of the system.

Random mutagenesis by error-prone pol plasmid replication in Escherichia coli.

PubMed

Alexander, David L; Lilly, Joshua; Hernandez, Jaime; Romsdahl, Jillian; Troll, Christopher J; Camps, Manel

2014-01-01

Directed evolution is an approach that mimics natural evolution in the laboratory with the goal of modifying existing enzymatic activities or of generating new ones. The identification of mutants with desired properties involves the generation of genetic diversity coupled with a functional selection or screen. Genetic diversity can be generated using PCR or using in vivo methods such as chemical mutagenesis or error-prone replication of the desired sequence in a mutator strain. In vivo mutagenesis methods facilitate iterative selection because they do not require cloning, but generally produce a low mutation density with mutations not restricted to specific genes or areas within a gene. For this reason, this approach is typically used to generate new biochemical properties when large numbers of mutants can be screened or selected. Here we describe protocols for an advanced in vivo mutagenesis method that is based on error-prone replication of a ColE1 plasmid bearing the gene of interest. Compared to other in vivo mutagenesis methods, this plasmid-targeted approach allows increased mutation loads and facilitates iterative selection approaches. We also describe the mutation spectrum for this mutagenesis methodology in detail, and, using cycle 3 GFP as a target for mutagenesis, we illustrate the phenotypic diversity that can be generated using our method. In sum, error-prone Pol I replication is a mutagenesis method that is ideally suited for the evolution of new biochemical activities when a functional selection is available.

Combined dry plasma etching and online metrology for manufacturing highly focusing x-ray mirrors

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

Berujon, S., E-mail: berujon@esrf.eu; Ziegler, E., E-mail: ziegler@esrf.eu; Cunha, S. da

A new figuring station was designed and installed at the ESRF beamline BM05. It allows the figuring of mirrors within an iterative process combining the advantage of online metrology with dry etching. The complete process takes place under a vacuum environment to minimize surface contamination while non-contact surfacing tools open up the possibility of performing at-wavelength metrology and eliminating placement errors. The aim is to produce mirrors whose slopes do not deviate from the stigmatic profile by more than 0.1 µrad rms while keeping surface roughness in the acceptable limit of 0.1-0.2 nm rms. The desired elliptical mirror surface shapemore » can be achieved in a few iterations in about a one day time span. This paper describes some of the important aspects of the process regarding both the online metrology and the etching process.« less

A superior edge preserving filter with a systematic analysis

NASA Technical Reports Server (NTRS)

Holladay, Kenneth W.; Rickman, Doug

1991-01-01

A new, adaptive, edge preserving filter for use in image processing is presented. It had superior performance when compared to other filters. Termed the contiguous K-average, it aggregates pixels by examining all pixels contiguous to an existing cluster and adding the pixel closest to the mean of the existing cluster. The process is iterated until K pixels were accumulated. Rather than simply compare the visual results of processing with this operator to other filters, some approaches were developed which allow quantitative evaluation of how well and filter performs. Particular attention is given to the standard deviation of noise within a feature and the stability of imagery under iterative processing. Demonstrations illustrate the performance of several filters to discriminate against noise and retain edges, the effect of filtering as a preprocessing step, and the utility of the contiguous K-average filter when used with remote sensing data.

Investigation of KDP crystal surface based on an improved bidimensional empirical mode decomposition method

NASA Astrophysics Data System (ADS)

Lu, Lei; Yan, Jihong; Chen, Wanqun; An, Shi

2018-03-01

This paper proposed a novel spatial frequency analysis method for the investigation of potassium dihydrogen phosphate (KDP) crystal surface based on an improved bidimensional empirical mode decomposition (BEMD) method. Aiming to eliminate end effects of the BEMD method and improve the intrinsic mode functions (IMFs) for the efficient identification of texture features, a denoising process was embedded in the sifting iteration of BEMD method. With removing redundant information in decomposed sub-components of KDP crystal surface, middle spatial frequencies of the cutting and feeding processes were identified. Comparative study with the power spectral density method, two-dimensional wavelet transform (2D-WT), as well as the traditional BEMD method, demonstrated that the method developed in this paper can efficiently extract texture features and reveal gradient development of KDP crystal surface. Furthermore, the proposed method was a self-adaptive data driven technique without prior knowledge, which overcame shortcomings of the 2D-WT model such as the parameters selection. Additionally, the proposed method was a promising tool for the application of online monitoring and optimal control of precision machining process.

Acceleration of GPU-based Krylov solvers via data transfer reduction

DOE PAGES

Anzt, Hartwig; Tomov, Stanimire; Luszczek, Piotr; ...

2015-04-08

Krylov subspace iterative solvers are often the method of choice when solving large sparse linear systems. At the same time, hardware accelerators such as graphics processing units continue to offer significant floating point performance gains for matrix and vector computations through easy-to-use libraries of computational kernels. However, as these libraries are usually composed of a well optimized but limited set of linear algebra operations, applications that use them often fail to reduce certain data communications, and hence fail to leverage the full potential of the accelerator. In this study, we target the acceleration of Krylov subspace iterative methods for graphicsmore » processing units, and in particular the Biconjugate Gradient Stabilized solver that significant improvement can be achieved by reformulating the method to reduce data-communications through application-specific kernels instead of using the generic BLAS kernels, e.g. as provided by NVIDIA’s cuBLAS library, and by designing a graphics processing unit specific sparse matrix-vector product kernel that is able to more efficiently use the graphics processing unit’s computing power. Furthermore, we derive a model estimating the performance improvement, and use experimental data to validate the expected runtime savings. Finally, considering that the derived implementation achieves significantly higher performance, we assert that similar optimizations addressing algorithm structure, as well as sparse matrix-vector, are crucial for the subsequent development of high-performance graphics processing units accelerated Krylov subspace iterative methods.« less

Nonnegative least-squares image deblurring: improved gradient projection approaches

NASA Astrophysics Data System (ADS)

Benvenuto, F.; Zanella, R.; Zanni, L.; Bertero, M.

2010-02-01

The least-squares approach to image deblurring leads to an ill-posed problem. The addition of the nonnegativity constraint, when appropriate, does not provide regularization, even if, as far as we know, a thorough investigation of the ill-posedness of the resulting constrained least-squares problem has still to be done. Iterative methods, converging to nonnegative least-squares solutions, have been proposed. Some of them have the 'semi-convergence' property, i.e. early stopping of the iteration provides 'regularized' solutions. In this paper we consider two of these methods: the projected Landweber (PL) method and the iterative image space reconstruction algorithm (ISRA). Even if they work well in many instances, they are not frequently used in practice because, in general, they require a large number of iterations before providing a sensible solution. Therefore, the main purpose of this paper is to refresh these methods by increasing their efficiency. Starting from the remark that PL and ISRA require only the computation of the gradient of the functional, we propose the application to these algorithms of special acceleration techniques that have been recently developed in the area of the gradient methods. In particular, we propose the application of efficient step-length selection rules and line-search strategies. Moreover, remarking that ISRA is a scaled gradient algorithm, we evaluate its behaviour in comparison with a recent scaled gradient projection (SGP) method for image deblurring. Numerical experiments demonstrate that the accelerated methods still exhibit the semi-convergence property, with a considerable gain both in the number of iterations and in the computational time; in particular, SGP appears definitely the most efficient one.

A Burning Plasma Experiment: the role of international collaboration

NASA Astrophysics Data System (ADS)

Prager, Stewart

2003-04-01

The world effort to develop fusion energy is at the threshold of a new stage in its research: the investigation of burning plasmas. A burning plasma is self-heated. The 100 million degree temperature of the plasma is maintained by the heat generated by the fusion reactions themselves, as occurs in burning stars. The fusion-generated alpha particles produce new physical phenomena that are strongly coupled together as a nonlinear complex system, posing a major plasma physics challenge. Two attractive options are being considered by the US fusion community as burning plasma facilities: the international ITER experiment and the US-based FIRE experiment. ITER (the International Thermonuclear Experimental Reactor) is a large, power-plant scale facility. It was conceived and designed by a partnership of the European Union, Japan, the Soviet Union, and the United States. At the completion of the first engineering design in 1998, the US discontinued its participation. FIRE (the Fusion Ignition Research Experiment) is a smaller, domestic facility that is at an advanced pre-conceptual design stage. Each facility has different scientific, programmatic and political implications. Selecting the optimal path for burning plasma science is itself a challenge. Recently, the Fusion Energy Sciences Advisory Committee recommended a dual path strategy in which the US seek to rejoin ITER, but be prepared to move forward with FIRE if the ITER negotiations do not reach fruition by July, 2004. Either the ITER or FIRE experiment would reveal the behavior of burning plasmas, generate large amounts of fusion power, and be a huge step in establishing the potential of fusion energy to contribute to the world's energy security.

Demons deformable registration of CT and cone-beam CT using an iterative intensity matching approach

PubMed Central

Nithiananthan, Sajendra; Schafer, Sebastian; Uneri, Ali; Mirota, Daniel J.; Stayman, J. Webster; Zbijewski, Wojciech; Brock, Kristy K.; Daly, Michael J.; Chan, Harley; Irish, Jonathan C.; Siewerdsen, Jeffrey H.

2011-01-01

Purpose: A method of intensity-based deformable registration of CT and cone-beam CT (CBCT) images is described, in which intensity correction occurs simultaneously within the iterative registration process. The method preserves the speed and simplicity of the popular Demons algorithm while providing robustness and accuracy in the presence of large mismatch between CT and CBCT voxel values (“intensity”). Methods: A variant of the Demons algorithm was developed in which an estimate of the relationship between CT and CBCT intensity values for specific materials in the image is computed at each iteration based on the set of currently overlapping voxels. This tissue-specific intensity correction is then used to estimate the registration output for that iteration and the process is repeated. The robustness of the method was tested in CBCT images of a cadaveric head exhibiting a broad range of simulated intensity variations associated with x-ray scatter, object truncation, and∕or errors in the reconstruction algorithm. The accuracy of CT-CBCT registration was also measured in six real cases, exhibiting deformations ranging from simple to complex during surgery or radiotherapy guided by a CBCT-capable C-arm or linear accelerator, respectively. Results: The iterative intensity matching approach was robust against all levels of intensity variation examined, including spatially varying errors in voxel value of a factor of 2 or more, as can be encountered in cases of high x-ray scatter. Registration accuracy without intensity matching degraded severely with increasing magnitude of intensity error and introduced image distortion. A single histogram match performed prior to registration alleviated some of these effects but was also prone to image distortion and was quantifiably less robust and accurate than the iterative approach. Within the six case registration accuracy study, iterative intensity matching Demons reduced mean TRE to (2.5±2.8) mm compared to (3.5±3.0) mm with rigid registration. Conclusions: A method was developed to iteratively correct CT-CBCT intensity disparity during Demons registration, enabling fast, intensity-based registration in CBCT-guided procedures such as surgery and radiotherapy, in which CBCT voxel values may be inaccurate. Accurate CT-CBCT registration in turn facilitates registration of multimodality preoperative image and planning data to intraoperative CBCT by way of the preoperative CT, thereby linking the intraoperative frame of reference to a wealth of preoperative information that could improve interventional guidance. PMID:21626913

Demons deformable registration of CT and cone-beam CT using an iterative intensity matching approach

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

Nithiananthan, Sajendra; Schafer, Sebastian; Uneri, Ali

2011-04-15

Purpose: A method of intensity-based deformable registration of CT and cone-beam CT (CBCT) images is described, in which intensity correction occurs simultaneously within the iterative registration process. The method preserves the speed and simplicity of the popular Demons algorithm while providing robustness and accuracy in the presence of large mismatch between CT and CBCT voxel values (''intensity''). Methods: A variant of the Demons algorithm was developed in which an estimate of the relationship between CT and CBCT intensity values for specific materials in the image is computed at each iteration based on the set of currently overlapping voxels. This tissue-specificmore » intensity correction is then used to estimate the registration output for that iteration and the process is repeated. The robustness of the method was tested in CBCT images of a cadaveric head exhibiting a broad range of simulated intensity variations associated with x-ray scatter, object truncation, and/or errors in the reconstruction algorithm. The accuracy of CT-CBCT registration was also measured in six real cases, exhibiting deformations ranging from simple to complex during surgery or radiotherapy guided by a CBCT-capable C-arm or linear accelerator, respectively. Results: The iterative intensity matching approach was robust against all levels of intensity variation examined, including spatially varying errors in voxel value of a factor of 2 or more, as can be encountered in cases of high x-ray scatter. Registration accuracy without intensity matching degraded severely with increasing magnitude of intensity error and introduced image distortion. A single histogram match performed prior to registration alleviated some of these effects but was also prone to image distortion and was quantifiably less robust and accurate than the iterative approach. Within the six case registration accuracy study, iterative intensity matching Demons reduced mean TRE to (2.5{+-}2.8) mm compared to (3.5{+-}3.0) mm with rigid registration. Conclusions: A method was developed to iteratively correct CT-CBCT intensity disparity during Demons registration, enabling fast, intensity-based registration in CBCT-guided procedures such as surgery and radiotherapy, in which CBCT voxel values may be inaccurate. Accurate CT-CBCT registration in turn facilitates registration of multimodality preoperative image and planning data to intraoperative CBCT by way of the preoperative CT, thereby linking the intraoperative frame of reference to a wealth of preoperative information that could improve interventional guidance.« less

Iterative categorization (IC): a systematic technique for analysing qualitative data

PubMed Central

2016-01-01

Abstract The processes of analysing qualitative data, particularly the stage between coding and publication, are often vague and/or poorly explained within addiction science and research more broadly. A simple but rigorous and transparent technique for analysing qualitative textual data, developed within the field of addiction, is described. The technique, iterative categorization (IC), is suitable for use with inductive and deductive codes and can support a range of common analytical approaches, e.g. thematic analysis, Framework, constant comparison, analytical induction, content analysis, conversational analysis, discourse analysis, interpretative phenomenological analysis and narrative analysis. Once the data have been coded, the only software required is a standard word processing package. Worked examples are provided. PMID:26806155

Sensitivity-Based Guided Model Calibration

NASA Astrophysics Data System (ADS)

Semnani, M.; Asadzadeh, M.

2017-12-01

A common practice in automatic calibration of hydrologic models is applying the sensitivity analysis prior to the global optimization to reduce the number of decision variables (DVs) by identifying the most sensitive ones. This two-stage process aims to improve the optimization efficiency. However, Parameter sensitivity information can be used to enhance the ability of the optimization algorithms to find good quality solutions in a fewer number of solution evaluations. This improvement can be achieved by increasing the focus of optimization on sampling from the most sensitive parameters in each iteration. In this study, the selection process of the dynamically dimensioned search (DDS) optimization algorithm is enhanced by utilizing a sensitivity analysis method to put more emphasis on the most sensitive decision variables for perturbation. The performance of DDS with the sensitivity information is compared to the original version of DDS for different mathematical test functions and a model calibration case study. Overall, the results show that DDS with sensitivity information finds nearly the same solutions as original DDS, however, in a significantly fewer number of solution evaluations.

The current state of drug discovery and a potential role for NMR metabolomics.

PubMed

Powers, Robert

2014-07-24

The pharmaceutical industry has significantly contributed to improving human health. Drugs have been attributed to both increasing life expectancy and decreasing health care costs. Unfortunately, there has been a recent decline in the creativity and productivity of the pharmaceutical industry. This is a complex issue with many contributing factors resulting from the numerous mergers, increase in out-sourcing, and the heavy dependency on high-throughput screening (HTS). While a simple solution to such a complex problem is unrealistic and highly unlikely, the inclusion of metabolomics as a routine component of the drug discovery process may provide some solutions to these problems. Specifically, as the binding affinity of a chemical lead is evolved during the iterative structure-based drug design process, metabolomics can provide feedback on the selectivity and the in vivo mechanism of action. Similarly, metabolomics can be used to evaluate and validate HTS leads. In effect, metabolomics can be used to eliminate compounds with potential efficacy and side effect problems while prioritizing well-behaved leads with druglike characteristics.

Efficient generation of discontinuity-preserving adaptive triangulations from range images.

PubMed

Garcia, Miguel Angel; Sappa, Angel Domingo

2004-10-01

This paper presents an efficient technique for generating adaptive triangular meshes from range images. The algorithm consists of two stages. First, a user-defined number of points is adaptively sampled from the given range image. Those points are chosen by taking into account the surface shapes represented in the range image in such a way that points tend to group in areas of high curvature and to disperse in low-variation regions. This selection process is done through a noniterative, inherently parallel algorithm in order to gain efficiency. Once the image has been subsampled, the second stage applies a two and one half-dimensional Delaunay triangulation to obtain an initial triangular mesh. To favor the preservation of surface and orientation discontinuities (jump and crease edges) present in the original range image, the aforementioned triangular mesh is iteratively modified by applying an efficient edge flipping technique. Results with real range images show accurate triangular approximations of the given range images with low processing times.

Communication-based behaviour support for adults with intellectual disabilities receiving dental care: A focus group study exploring dentists' decision-making and communication.

PubMed

Phadraig, Caoimhin Mac Giolla; Griffiths, Colin; McCallion, Philip; McCarron, Mary; Nunn, June

2017-01-01

A better understanding of how communication-based behaviour supports are applied with adults with intellectual disabilities may reduce reliance on restrictive practices such as holding, sedation and anaesthesia in dentistry. In this study, we explore how communication is used by dentists who provide treatment for adults with intellectual disabilities. A descriptive qualitative study, adopting synchronous online focus groups, was undertaken with six expert dentists in Ireland. Members were contacted again in pairs or individually for further data collection, analysed using thematic content analysis. Two relevant categories emerged from the data, relating to the selection and application of communication-based behaviour support for adults with intellectual disabilities. Decision-making processes were explored. Building on these categories, a co-regulating process of communication emerged as the means by which dentists iteratively apply and adapt communicative strategies. This exploration revealed rationalist and intuitive decision-making. Implications for education, practice and research are identified.

Image Processing Of Images From Peripheral-Artery Digital Subtraction Angiography (DSA) Studies

NASA Astrophysics Data System (ADS)

Wilson, David L.; Tarbox, Lawrence R.; Cist, David B.; Faul, David D.

1988-06-01

A system is being developed to test the possibility of doing peripheral, digital subtraction angiography (DSA) with a single contrast injection using a moving gantry system. Given repositioning errors that occur between the mask and contrast-containing images, factors affecting the success of subtractions following image registration have been investigated theoretically and experimentally. For a 1 mm gantry displacement, parallax and geometric image distortion (pin-cushion) both give subtraction errors following registration that are approximately 25% of the error resulting from no registration. Image processing techniques improve the subtractions. The geometric distortion effect is reduced using a piece-wise, 8 parameter unwarping method. Plots of image similarity measures versus pixel shift are well behaved and well fit by a parabola, leading to the development of an iterative, automatic registration algorithm that uses parabolic prediction of the new minimum. The registration algorithm converges quickly (less than 1 second on a MicroVAX) and is relatively immune to the region of interest (ROI) selected.

Migration velocity analysis using residual diffraction moveout: a real-data example

NASA Astrophysics Data System (ADS)

Gonzalez, Jaime A. C.; de Figueiredo, José J. S.; Coimbra, Tiago A.; Schleicher, Jörg; Novais, Amélia

2016-08-01

Unfocused seismic diffraction events carry direct information about errors in the migration-velocity model. The residual-diffraction-moveout (RDM) migration-velocity-analysis (MVA) method is a recent technique that extracts this information by means of adjusting ellipses or hyperbolas to uncollapsed migrated diffractions. In this paper, we apply this method, which has been tested so far only on synthetic data, to a real data set from the Viking Graben. After application of a plane-wave-destruction (PWD) filter to attenuate the reflected energy, the diffractions in the real data become interpretable and can be used for the RDM method. Our analysis demonstrates that the reflections need not be completely removed for this purpose. Beyond the need to identify and select diffraction events in post-stack migrated sections in the depth domain, the method has a very low computational cost and processing time. To reach an acceptable velocity model of comparable quality as one obtained with common-midpoint (CMP) processing, only two iterations were necessary.

CT Angiography after 20 Years

PubMed Central

Rubin, Geoffrey D.; Leipsic, Jonathon; Schoepf, U. Joseph; Fleischmann, Dominik; Napel, Sandy

2015-01-01

Through a marriage of spiral computed tomography (CT) and graphical volumetric image processing, CT angiography was born 20 years ago. Fueled by a series of technical innovations in CT and image processing, over the next 5–15 years, CT angiography toppled conventional angiography, the undisputed diagnostic reference standard for vascular disease for the prior 70 years, as the preferred modality for the diagnosis and characterization of most cardiovascular abnormalities. This review recounts the evolution of CT angiography from its development and early challenges to a maturing modality that has provided unique insights into cardiovascular disease characterization and management. Selected clinical challenges, which include acute aortic syndromes, peripheral vascular disease, aortic stent-graft and transcatheter aortic valve assessment, and coronary artery disease, are presented as contrasting examples of how CT angiography is changing our approach to cardiovascular disease diagnosis and management. Finally, the recently introduced capabilities for multispectral imaging, tissue perfusion imaging, and radiation dose reduction through iterative reconstruction are explored with consideration toward the continued refinement and advancement of CT angiography. PMID:24848958

Optimization of a Lunar Pallet Lander Reinforcement Structure Using a Genetic Algorithm

NASA Technical Reports Server (NTRS)

Burt, Adam O.; Hull, Patrick V.

2014-01-01

This paper presents a design automation process using optimization via a genetic algorithm to design the conceptual structure of a Lunar Pallet Lander. The goal is to determine a design that will have the primary natural frequencies at or above a target value as well as minimize the total mass. Several iterations of the process are presented. First, a concept optimization is performed to determine what class of structure would produce suitable candidate designs. From this a stiffened sheet metal approach was selected leading to optimization of beam placement through generating a two-dimensional mesh and varying the physical location of reinforcing beams. Finally, the design space is reformulated as a binary problem using 1-dimensional beam elements to truncate the design space to allow faster convergence and additional mechanical failure criteria to be included in the optimization responses. Results are presented for each design space configuration. The final flight design was derived from these results.

Evaluation of Adaptive Subdivision Method on Mobile Device

NASA Astrophysics Data System (ADS)

Rahim, Mohd Shafry Mohd; Isa, Siti Aida Mohd; Rehman, Amjad; Saba, Tanzila

2013-06-01

Recently, there are significant improvements in the capabilities of mobile devices; but rendering large 3D object is still tedious because of the constraint in resources of mobile devices. To reduce storage requirement, 3D object is simplified but certain area of curvature is compromised and the surface will not be smooth. Therefore a method to smoother selected area of a curvature is implemented. One of the popular methods is adaptive subdivision method. Experiments are performed using two data with results based on processing time, rendering speed and the appearance of the object on the devices. The result shows a downfall in frame rate performance due to the increase in the number of triangles with each level of iteration while the processing time of generating the new mesh also significantly increase. Since there is a difference in screen size between the devices the surface on the iPhone appears to have more triangles and more compact than the surface displayed on the iPad. [Figure not available: see fulltext.

Economically viable large-scale hydrogen liquefaction

NASA Astrophysics Data System (ADS)

Cardella, U.; Decker, L.; Klein, H.

2017-02-01

The liquid hydrogen demand, particularly driven by clean energy applications, will rise in the near future. As industrial large scale liquefiers will play a major role within the hydrogen supply chain, production capacity will have to increase by a multiple of today’s typical sizes. The main goal is to reduce the total cost of ownership for these plants by increasing energy efficiency with innovative and simple process designs, optimized in capital expenditure. New concepts must ensure a manageable plant complexity and flexible operability. In the phase of process development and selection, a dimensioning of key equipment for large scale liquefiers, such as turbines and compressors as well as heat exchangers, must be performed iteratively to ensure technological feasibility and maturity. Further critical aspects related to hydrogen liquefaction, e.g. fluid properties, ortho-para hydrogen conversion, and coldbox configuration, must be analysed in detail. This paper provides an overview on the approach, challenges and preliminary results in the development of efficient as well as economically viable concepts for large-scale hydrogen liquefaction.

Covariate selection with iterative principal component analysis for predicting physical

USDA-ARS?s Scientific Manuscript database

Local and regional soil data can be improved by coupling new digital soil mapping techniques with high resolution remote sensing products to quantify both spatial and absolute variation of soil properties. The objective of this research was to advance data-driven digital soil mapping techniques for ...

Solving Boltzmann and Fokker-Planck Equations Using Sparse Representation

DTIC Science & Technology

2011-05-31

material science. We have com- puted the electronic structure of 2D quantum dot system, and compared the efficiency with the benchmark software OCTOPUS . For...one self-consistent iteration step with 512 electrons, OCTOPUS costs 1091 sec, and selected inversion costs 9.76 sec. The algorithm exhibits

Constructing a Database from Multiple 2D Images for Camera Pose Estimation and Robot Localization

NASA Technical Reports Server (NTRS)

Wolf, Michael; Ansar, Adnan I.; Brennan, Shane; Clouse, Daniel S.; Padgett, Curtis W.

2012-01-01

The LMDB (Landmark Database) Builder software identifies persistent image features (landmarks) in a scene viewed multiple times and precisely estimates the landmarks 3D world positions. The software receives as input multiple 2D images of approximately the same scene, along with an initial guess of the camera poses for each image, and a table of features matched pair-wise in each frame. LMDB Builder aggregates landmarks across an arbitrarily large collection of frames with matched features. Range data from stereo vision processing can also be passed to improve the initial guess of the 3D point estimates. The LMDB Builder aggregates feature lists across all frames, manages the process to promote selected features to landmarks, and iteratively calculates the 3D landmark positions using the current camera pose estimations (via an optimal ray projection method), and then improves the camera pose estimates using the 3D landmark positions. Finally, it extracts image patches for each landmark from auto-selected key frames and constructs the landmark database. The landmark database can then be used to estimate future camera poses (and therefore localize a robotic vehicle that may be carrying the cameras) by matching current imagery to landmark database image patches and using the known 3D landmark positions to estimate the current pose.

A Model For Selecting An Environmentally Responsive Trait: Evaluating Micro-scale Fitness Through UV-C Resistance and Exposure in Escherichia coli.

NASA Astrophysics Data System (ADS)

Schenone, D. J.; Igama, S.; Marash-Whitman, D.; Sloan, C.; Okansinski, A.; Moffet, A.; Grace, J. M.; Gentry, D.

2015-12-01

Experimental evolution of microorganisms in controlled microenvironments serves as a powerful tool for understanding the relationship between micro-scale microbial interactions as well as local-to global-scale environmental factors. In response to iterative and targeted environmental pressures, mutagenesis drives the emergence of novel phenotypes. Current methods to induce expression of these phenotypes require repetitive and time intensive procedures and do not allow for the continuous monitoring of conditions such as optical density, pH and temperature. To address this shortcoming, an Automated Dynamic Directed Evolution Chamber is being developed. It will initially produce Escherichia coli cells with an elevated UV-C resistance phenotype that will ultimately be adapted for different organisms as well as studying environmental effects. A useful phenotype and environmental factor for examining this relationship is UV-C resistance and exposure. In order to build a baseline for the device's operational parameters, a UV-C assay was performed on six E. coli replicates with three exposure fluxes across seven iterations. The fluxes included a 0 second exposure (control), 6 seconds at 3.3 J/m2/s and 40 seconds at 0.5 J/m2/s. After each iteration the cells were regrown and tested for UV-C resistance. We sought to quantify the increase and variability of UV-C resistance among different fluxes, and observe changes in each replicate at each iteration in terms of variance. Under different fluxes, we observed that the 0s control showed no significant increase in resistance, while the 6s/40s fluxes showed increased resistance as the number of iterations increased. A one-million fold increase in survivability was observed after seven iterations. Through statistical analysis using Spearman's rank correlation, the 40s exposure showed signs of more consistently increased resistance, but seven iterations was insufficient to demonstrate statistical significance; to test this further, our experiments will include more iterations. Furthermore, we plan to sequence all the replicants. As adaptation dynamics under intense UV exposure leads to high rate of change, it would be useful to observe differences in tolerance-related and non-tolerance-related genes between the original and UV resistant strains.

Iterating between Tools to Create and Edit Visualizations.

PubMed

Bigelow, Alex; Drucker, Steven; Fisher, Danyel; Meyer, Miriah

2017-01-01

A common workflow for visualization designers begins with a generative tool, like D3 or Processing, to create the initial visualization; and proceeds to a drawing tool, like Adobe Illustrator or Inkscape, for editing and cleaning. Unfortunately, this is typically a one-way process: once a visualization is exported from the generative tool into a drawing tool, it is difficult to make further, data-driven changes. In this paper, we propose a bridge model to allow designers to bring their work back from the drawing tool to re-edit in the generative tool. Our key insight is to recast this iteration challenge as a merge problem - similar to when two people are editing a document and changes between them need to reconciled. We also present a specific instantiation of this model, a tool called Hanpuku, which bridges between D3 scripts and Illustrator. We show several examples of visualizations that are iteratively created using Hanpuku in order to illustrate the flexibility of the approach. We further describe several hypothetical tools that bridge between other visualization tools to emphasize the generality of the model.

Dynamics of a new family of iterative processes for quadratic polynomials

NASA Astrophysics Data System (ADS)

Gutiérrez, J. M.; Hernández, M. A.; Romero, N.

2010-03-01

In this work we show the presence of the well-known Catalan numbers in the study of the convergence and the dynamical behavior of a family of iterative methods for solving nonlinear equations. In fact, we introduce a family of methods, depending on a parameter . These methods reach the order of convergence m+2 when they are applied to quadratic polynomials with different roots. Newton's and Chebyshev's methods appear as particular choices of the family appear for m=0 and m=1, respectively. We make both analytical and graphical studies of these methods, which give rise to rational functions defined in the extended complex plane. Firstly, we prove that the coefficients of the aforementioned family of iterative processes can be written in terms of the Catalan numbers. Secondly, we make an incursion into its dynamical behavior. In fact, we show that the rational maps related to these methods can be written in terms of the entries of the Catalan triangle. Next we analyze its general convergence, by including some computer plots showing the intricate structure of the Universal Julia sets associated with the methods.

TH-AB-BRA-09: Stability Analysis of a Novel Dose Calculation Algorithm for MRI Guided Radiotherapy

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

Zelyak, O; Fallone, B; Cross Cancer Institute, Edmonton, AB

2016-06-15

Purpose: To determine the iterative deterministic solution stability of the Linear Boltzmann Transport Equation (LBTE) in the presence of magnetic fields. Methods: The LBTE with magnetic fields under investigation is derived using a discrete ordinates approach. The stability analysis is performed using analytical and numerical methods. Analytically, the spectral Fourier analysis is used to obtain the convergence rate of the source iteration procedures based on finding the largest eigenvalue of the iterative operator. This eigenvalue is a function of relevant physical parameters, such as magnetic field strength and material properties, and provides essential information about the domain of applicability requiredmore » for clinically optimal parameter selection and maximum speed of convergence. The analytical results are reinforced by numerical simulations performed using the same discrete ordinates method in angle, and a discontinuous finite element spatial approach. Results: The spectral radius for the source iteration technique of the time independent transport equation with isotropic and anisotropic scattering centers inside infinite 3D medium is equal to the ratio of differential and total cross sections. The result is confirmed numerically by solving LBTE and is in full agreement with previously published results. The addition of magnetic field reveals that the convergence becomes dependent on the strength of magnetic field, the energy group discretization, and the order of anisotropic expansion. Conclusion: The source iteration technique for solving the LBTE with magnetic fields with the discrete ordinates method leads to divergent solutions in the limiting cases of small energy discretizations and high magnetic field strengths. Future investigations into non-stationary Krylov subspace techniques as an iterative solver will be performed as this has been shown to produce greater stability than source iteration. Furthermore, a stability analysis of a discontinuous finite element space-angle approach (which has been shown to provide the greatest stability) will also be investigated. Dr. B Gino Fallone is a co-founder and CEO of MagnetTx Oncology Solutions (under discussions to license Alberta bi-planar linac MR for commercialization)« less

Evaluating the performance of two neutron spectrum unfolding codes based on iterative procedures and artificial neural networks

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

Ortiz-Rodriguez, J. M.; Reyes Alfaro, A.; Reyes Haro, A.

In this work the performance of two neutron spectrum unfolding codes based on iterative procedures and artificial neural networks is evaluated. The first one code based on traditional iterative procedures and called Neutron spectrometry and dosimetry from the Universidad Autonoma de Zacatecas (NSDUAZ) use the SPUNIT iterative algorithm and was designed to unfold neutron spectrum and calculate 15 dosimetric quantities and 7 IAEA survey meters. The main feature of this code is the automated selection of the initial guess spectrum trough a compendium of neutron spectrum compiled by the IAEA. The second one code known as Neutron spectrometry and dosimetrymore » with artificial neural networks (NDSann) is a code designed using neural nets technology. The artificial intelligence approach of neural net does not solve mathematical equations. By using the knowledge stored at synaptic weights on a neural net properly trained, the code is capable to unfold neutron spectrum and to simultaneously calculate 15 dosimetric quantities, needing as entrance data, only the rate counts measured with a Bonner spheres system. Similarities of both NSDUAZ and NSDann codes are: they follow the same easy and intuitive user's philosophy and were designed in a graphical interface under the LabVIEW programming environment. Both codes unfold the neutron spectrum expressed in 60 energy bins, calculate 15 dosimetric quantities and generate a full report in HTML format. Differences of these codes are: NSDUAZ code was designed using classical iterative approaches and needs an initial guess spectrum in order to initiate the iterative procedure. In NSDUAZ, a programming routine was designed to calculate 7 IAEA instrument survey meters using the fluence-dose conversion coefficients. NSDann code use artificial neural networks for solving the ill-conditioned equation system of neutron spectrometry problem through synaptic weights of a properly trained neural network. Contrary to iterative procedures, in neural net approach it is possible to reduce the rate counts used to unfold the neutron spectrum. To evaluate these codes a computer tool called Neutron Spectrometry and dosimetry computer tool was designed. The results obtained with this package are showed. The codes here mentioned are freely available upon request to the authors.« less

Evaluating the performance of two neutron spectrum unfolding codes based on iterative procedures and artificial neural networks

NASA Astrophysics Data System (ADS)

Ortiz-Rodríguez, J. M.; Reyes Alfaro, A.; Reyes Haro, A.; Solís Sánches, L. O.; Miranda, R. Castañeda; Cervantes Viramontes, J. M.; Vega-Carrillo, H. R.

2013-07-01

In this work the performance of two neutron spectrum unfolding codes based on iterative procedures and artificial neural networks is evaluated. The first one code based on traditional iterative procedures and called Neutron spectrometry and dosimetry from the Universidad Autonoma de Zacatecas (NSDUAZ) use the SPUNIT iterative algorithm and was designed to unfold neutron spectrum and calculate 15 dosimetric quantities and 7 IAEA survey meters. The main feature of this code is the automated selection of the initial guess spectrum trough a compendium of neutron spectrum compiled by the IAEA. The second one code known as Neutron spectrometry and dosimetry with artificial neural networks (NDSann) is a code designed using neural nets technology. The artificial intelligence approach of neural net does not solve mathematical equations. By using the knowledge stored at synaptic weights on a neural net properly trained, the code is capable to unfold neutron spectrum and to simultaneously calculate 15 dosimetric quantities, needing as entrance data, only the rate counts measured with a Bonner spheres system. Similarities of both NSDUAZ and NSDann codes are: they follow the same easy and intuitive user's philosophy and were designed in a graphical interface under the LabVIEW programming environment. Both codes unfold the neutron spectrum expressed in 60 energy bins, calculate 15 dosimetric quantities and generate a full report in HTML format. Differences of these codes are: NSDUAZ code was designed using classical iterative approaches and needs an initial guess spectrum in order to initiate the iterative procedure. In NSDUAZ, a programming routine was designed to calculate 7 IAEA instrument survey meters using the fluence-dose conversion coefficients. NSDann code use artificial neural networks for solving the ill-conditioned equation system of neutron spectrometry problem through synaptic weights of a properly trained neural network. Contrary to iterative procedures, in neural net approach it is possible to reduce the rate counts used to unfold the neutron spectrum. To evaluate these codes a computer tool called Neutron Spectrometry and dosimetry computer tool was designed. The results obtained with this package are showed. The codes here mentioned are freely available upon request to the authors.

Error minimization algorithm for comparative quantitative PCR analysis: Q-Anal.

PubMed

OConnor, William; Runquist, Elizabeth A

2008-07-01

Current methods for comparative quantitative polymerase chain reaction (qPCR) analysis, the threshold and extrapolation methods, either make assumptions about PCR efficiency that require an arbitrary threshold selection process or extrapolate to estimate relative levels of messenger RNA (mRNA) transcripts. Here we describe an algorithm, Q-Anal, that blends elements from current methods to by-pass assumptions regarding PCR efficiency and improve the threshold selection process to minimize error in comparative qPCR analysis. This algorithm uses iterative linear regression to identify the exponential phase for both target and reference amplicons and then selects, by minimizing linear regression error, a fluorescence threshold where efficiencies for both amplicons have been defined. From this defined fluorescence threshold, cycle time (Ct) and the error for both amplicons are calculated and used to determine the expression ratio. Ratios in complementary DNA (cDNA) dilution assays from qPCR data were analyzed by the Q-Anal method and compared with the threshold method and an extrapolation method. Dilution ratios determined by the Q-Anal and threshold methods were 86 to 118% of the expected cDNA ratios, but relative errors for the Q-Anal method were 4 to 10% in comparison with 4 to 34% for the threshold method. In contrast, ratios determined by an extrapolation method were 32 to 242% of the expected cDNA ratios, with relative errors of 67 to 193%. Q-Anal will be a valuable and quick method for minimizing error in comparative qPCR analysis.

Selected Gravity Models in Terms of the fit to the GOCE Kinematic Orbit in the Dynamic Orbit Determination Process

NASA Astrophysics Data System (ADS)

Bobojć, Andrzej; Drożyner, Andrzej; Rzepecka, Zofia

2017-04-01

The work includes the comparison of performance of selected geopotential models in the dynamic orbit estimation of the satellite of the Gravity Field and Steady-State Ocean Circulation Explorer (GOCE) mission. This was realized by fitting estimated orbital arcs to the official centimeter-accuracy GOCE kinematic orbit which is provided by the European Space Agency. The Cartesian coordinates of kinematic orbit were treated as observations in the orbit estimation. The initial satellite state vector components were corrected in an iterative process with respect to the J2000.0 inertial reference frame using the given geopotential model, the models describing the remaining gravitational perturbations and the solar radiation pressure. Taking the obtained solutions into account, the RMS values of orbital residuals were computed. These residuals result from the difference between the determined orbit and the reference one - the GOCE kinematic orbit. The performance of selected gravity models was also determined using various orbital arc lengths. Additionally, the RMS fit values were obtained for some gravity models truncated at given degree and order of spherical harmonic coefficients. The advantage of using the kinematic orbit is its independence from any a priori dynamical models. For the research such GOCE-independent gravity models as HUST-Grace2016s, ITU_GRACE16, ITSG-Grace2014s, ITSG-Grace2014k, GGM05S, Tongji-GRACE01, ULUX_CHAMP2013S, ITG-GRACE2010S, EIGEN-51C, EIGEN5S, EGM2008 and EGM96 were adopted.

A Block Preconditioned Conjugate Gradient-type Iterative Solver for Linear Systems in Thermal Reservoir Simulation

NASA Astrophysics Data System (ADS)

Betté, Srinivas; Diaz, Julio C.; Jines, William R.; Steihaug, Trond

1986-11-01

A preconditioned residual-norm-reducing iterative solver is described. Based on a truncated form of the generalized-conjugate-gradient method for nonsymmetric systems of linear equations, the iterative scheme is very effective for linear systems generated in reservoir simulation of thermal oil recovery processes. As a consequence of employing an adaptive implicit finite-difference scheme to solve the model equations, the number of variables per cell-block varies dynamically over the grid. The data structure allows for 5- and 9-point operators in the areal model, 5-point in the cross-sectional model, and 7- and 11-point operators in the three-dimensional model. Block-diagonal-scaling of the linear system, done prior to iteration, is found to have a significant effect on the rate of convergence. Block-incomplete-LU-decomposition (BILU) and block-symmetric-Gauss-Seidel (BSGS) methods, which result in no fill-in, are used as preconditioning procedures. A full factorization is done on the well terms, and the cells are ordered in a manner which minimizes the fill-in in the well-column due to this factorization. The convergence criterion for the linear (inner) iteration is linked to that of the nonlinear (Newton) iteration, thereby enhancing the efficiency of the computation. The algorithm, with both BILU and BSGS preconditioners, is evaluated in the context of a variety of thermal simulation problems. The solver is robust and can be used with little or no user intervention.

Numerical simulation and comparison of nonlinear self-focusing based on iteration and ray tracing

NASA Astrophysics Data System (ADS)

Li, Xiaotong; Chen, Hao; Wang, Weiwei; Ruan, Wangchao; Zhang, Luwei; Cen, Zhaofeng

2017-05-01

Self-focusing is observed in nonlinear materials owing to the interaction between laser and matter when laser beam propagates. Some of numerical simulation strategies such as the beam propagation method (BPM) based on nonlinear Schrödinger equation and ray tracing method based on Fermat's principle have applied to simulate the self-focusing process. In this paper we present an iteration nonlinear ray tracing method in that the nonlinear material is also cut into massive slices just like the existing approaches, but instead of paraxial approximation and split-step Fourier transform, a large quantity of sampled real rays are traced step by step through the system with changing refractive index and laser intensity by iteration. In this process a smooth treatment is employed to generate a laser density distribution at each slice to decrease the error caused by the under-sampling. The characteristics of this method is that the nonlinear refractive indices of the points on current slice are calculated by iteration so as to solve the problem of unknown parameters in the material caused by the causal relationship between laser intensity and nonlinear refractive index. Compared with the beam propagation method, this algorithm is more suitable for engineering application with lower time complexity, and has the calculation capacity for numerical simulation of self-focusing process in the systems including both of linear and nonlinear optical media. If the sampled rays are traced with their complex amplitudes and light paths or phases, it will be possible to simulate the superposition effects of different beam. At the end of the paper, the advantages and disadvantages of this algorithm are discussed.

Key achievements in elementary R&D on water-cooled solid breeder blanket for ITER test blanket module in JAERI

NASA Astrophysics Data System (ADS)

Suzuki, S.; Enoeda, M.; Hatano, T.; Hirose, T.; Hayashi, K.; Tanigawa, H.; Ochiai, K.; Nishitani, T.; Tobita, K.; Akiba, M.

2006-02-01

This paper presents the significant progress made in the research and development (R&D) of key technologies on the water-cooled solid breeder blanket for the ITER test blanket modules in JAERI. Development of module fabrication technology, bonding technology of armours, measurement of thermo-mechanical properties of pebble beds, neutronics studies on a blanket module mockup and tritium release behaviour from a Li2TiO3 pebble bed under neutron-pulsed operation conditions are summarized. With the improvement of the heat treatment process for blanket module fabrication, a fine-grained microstructure of F82H can be obtained by homogenizing it at 1150 °C followed by normalizing it at 930 °C after the hot isostatic pressing process. Moreover, a promising bonding process for a tungsten armour and an F82H structural material was developed using a solid-state bonding method based on uniaxial hot compression without any artificial compliant layer. As a result of high heat flux tests of F82H first wall mockups, it has been confirmed that a fatigue lifetime correlation, which was developed for the ITER divertor, can be made applicable for the F82H first wall mockup. As for R&D on the breeder material, Li2TiO3, the effect of compression loads on effective thermal conductivity of pebble beds has been clarified for the Li2TiO3 pebble bed. The tritium breeding ratio of a simulated multi-layer blanket structure has successfully been measured using 14 MeV neutrons with an accuracy of 10%. The tritium release rate from the Li2TiO3 pebble has also been successfully measured with pulsed neutron irradiation, which simulates ITER operation.

Propagation-based x-ray phase contrast imaging using an iterative phase diversity technique

NASA Astrophysics Data System (ADS)

Carroll, Aidan J.; van Riessen, Grant A.; Balaur, Eugeniu; Dolbnya, Igor P.; Tran, Giang N.; Peele, Andrew G.

2018-03-01

Through the use of a phase diversity technique, we demonstrate a near-field in-line x-ray phase contrast algorithm that provides improved object reconstruction when compared to our previous iterative methods for a homogeneous sample. Like our previous methods, the new technique uses the sample refractive index distribution during the reconstruction process. The technique complements existing monochromatic and polychromatic methods and is useful in situations where experimental phase contrast data is affected by noise.

Micromagnetic Simulation of Thermal Effects in Magnetic Nanostructures

DTIC Science & Technology

2003-01-01

NiFe magnetic nano- elements are calculated. INTRODUCTION With decreasing size of magnetic nanostructures thermal effects become increasingly important...thermal field. The thermal field is assumed to be a Gaussian random process with the following statistical properties : (H,,,(t))=0 and (H,I.(t),H,.1(t...following property DI " =VE(M’’) - [VE(M"’)• t] t =0, for k =1.m (12) 186 The optimal path can be found using an iterative scheme. In each iteration step the

Convergence of Proximal Iteratively Reweighted Nuclear Norm Algorithm for Image Processing.

PubMed

Sun, Tao; Jiang, Hao; Cheng, Lizhi

2017-08-25

The nonsmooth and nonconvex regularization has many applications in imaging science and machine learning research due to its excellent recovery performance. A proximal iteratively reweighted nuclear norm algorithm has been proposed for the nonsmooth and nonconvex matrix minimizations. In this paper, we aim to investigate the convergence of the algorithm. With the Kurdyka-Łojasiewicz property, we prove the algorithm globally converges to a critical point of the objective function. The numerical results presented in this paper coincide with our theoretical findings.