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%.

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.

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.

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

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…

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…

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.

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.

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.

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.

Accelerated iterative beam angle selection in IMRT

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

Bangert, Mark, E-mail: m.bangert@dkfz.de; Unkelbach, Jan

2016-03-15

Purpose: Iterative methods for beam angle selection (BAS) for intensity-modulated radiation therapy (IMRT) planning sequentially construct a beneficial ensemble of beam directions. In a naïve implementation, the nth beam is selected by adding beam orientations one-by-one from a discrete set of candidates to an existing ensemble of (n − 1) beams. The best beam orientation is identified in a time consuming process by solving the fluence map optimization (FMO) problem for every candidate beam and selecting the beam that yields the largest improvement to the objective function value. This paper evaluates two alternative methods to accelerate iterative BAS based onmore » surrogates for the FMO objective function value. Methods: We suggest to select candidate beams not based on the FMO objective function value after convergence but (1) based on the objective function value after five FMO iterations of a gradient based algorithm and (2) based on a projected gradient of the FMO problem in the first iteration. The performance of the objective function surrogates is evaluated based on the resulting objective function values and dose statistics in a treatment planning study comprising three intracranial, three pancreas, and three prostate cases. Furthermore, iterative BAS is evaluated for an application in which a small number of noncoplanar beams complement a set of coplanar beam orientations. This scenario is of practical interest as noncoplanar setups may require additional attention of the treatment personnel for every couch rotation. Results: Iterative BAS relying on objective function surrogates yields similar results compared to naïve BAS with regard to the objective function values and dose statistics. At the same time, early stopping of the FMO and using the projected gradient during the first iteration enable reductions in computation time by approximately one to two orders of magnitude. With regard to the clinical delivery of noncoplanar IMRT treatments, we could show that optimized beam ensembles using only a few noncoplanar beam orientations often approach the plan quality of fully noncoplanar ensembles. Conclusions: We conclude that iterative BAS in combination with objective function surrogates can be a viable option to implement automated BAS at clinically acceptable computation times.« less

Accelerated iterative beam angle selection in IMRT.

PubMed

Bangert, Mark; Unkelbach, Jan

2016-03-01

Iterative methods for beam angle selection (BAS) for intensity-modulated radiation therapy (IMRT) planning sequentially construct a beneficial ensemble of beam directions. In a naïve implementation, the nth beam is selected by adding beam orientations one-by-one from a discrete set of candidates to an existing ensemble of (n - 1) beams. The best beam orientation is identified in a time consuming process by solving the fluence map optimization (FMO) problem for every candidate beam and selecting the beam that yields the largest improvement to the objective function value. This paper evaluates two alternative methods to accelerate iterative BAS based on surrogates for the FMO objective function value. We suggest to select candidate beams not based on the FMO objective function value after convergence but (1) based on the objective function value after five FMO iterations of a gradient based algorithm and (2) based on a projected gradient of the FMO problem in the first iteration. The performance of the objective function surrogates is evaluated based on the resulting objective function values and dose statistics in a treatment planning study comprising three intracranial, three pancreas, and three prostate cases. Furthermore, iterative BAS is evaluated for an application in which a small number of noncoplanar beams complement a set of coplanar beam orientations. This scenario is of practical interest as noncoplanar setups may require additional attention of the treatment personnel for every couch rotation. Iterative BAS relying on objective function surrogates yields similar results compared to naïve BAS with regard to the objective function values and dose statistics. At the same time, early stopping of the FMO and using the projected gradient during the first iteration enable reductions in computation time by approximately one to two orders of magnitude. With regard to the clinical delivery of noncoplanar IMRT treatments, we could show that optimized beam ensembles using only a few noncoplanar beam orientations often approach the plan quality of fully noncoplanar ensembles. We conclude that iterative BAS in combination with objective function surrogates can be a viable option to implement automated BAS at clinically acceptable computation times.

A Probabilistic Collocation Based Iterative Kalman Filter for Landfill Data Assimilation

NASA Astrophysics Data System (ADS)

Qiang, Z.; Zeng, L.; Wu, L.

2016-12-01

Due to the strong spatial heterogeneity of landfill, uncertainty is ubiquitous in gas transport process in landfill. To accurately characterize the landfill properties, the ensemble Kalman filter (EnKF) has been employed to assimilate the measurements, e.g., the gas pressure. As a Monte Carlo (MC) based method, the EnKF usually requires a large ensemble size, which poses a high computational cost for large scale problems. In this work, we propose a probabilistic collocation based iterative Kalman filter (PCIKF) to estimate permeability in a liquid-gas coupling model. This method employs polynomial chaos expansion (PCE) to represent and propagate the uncertainties of model parameters and states, and an iterative form of Kalman filter to assimilate the current gas pressure data. To further reduce the computation cost, the functional ANOVA (analysis of variance) decomposition is conducted, and only the first order ANOVA components are remained for PCE. Illustrated with numerical case studies, this proposed method shows significant superiority in computation efficiency compared with the traditional MC based iterative EnKF. The developed method has promising potential in reliable prediction and management of landfill gas production.

Evaluating user reputation in online rating systems via an iterative group-based ranking method

NASA Astrophysics Data System (ADS)

Gao, Jian; Zhou, Tao

2017-05-01

Reputation is a valuable asset in online social lives and it has drawn increased attention. Due to the existence of noisy ratings and spamming attacks, how to evaluate user reputation in online rating systems is especially significant. However, most of the previous ranking-based methods either follow a debatable assumption or have unsatisfied robustness. In this paper, we propose an iterative group-based ranking method by introducing an iterative reputation-allocation process into the original group-based ranking method. More specifically, the reputation of users is calculated based on the weighted sizes of the user rating groups after grouping all users by their rating similarities, and the high reputation users' ratings have larger weights in dominating the corresponding user rating groups. The reputation of users and the user rating group sizes are iteratively updated until they become stable. Results on two real data sets with artificial spammers suggest that the proposed method has better performance than the state-of-the-art methods and its robustness is considerably improved comparing with the original group-based ranking method. Our work highlights the positive role of considering users' grouping behaviors towards a better online user reputation evaluation.

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…

Tailored and Integrated Web-Based Tools for Improving Psychosocial Outcomes of Cancer Patients: The DoTTI Development Framework

PubMed Central

Bryant, Jamie; Sanson-Fisher, Rob; Tzelepis, Flora; Henskens, Frans; Paul, Christine; Stevenson, William

2014-01-01

Background Effective communication with cancer patients and their families about their disease, treatment options, and possible outcomes may improve psychosocial outcomes. However, traditional approaches to providing information to patients, including verbal information and written booklets, have a number of shortcomings centered on their limited ability to meet patient preferences and literacy levels. New-generation Web-based technologies offer an innovative and pragmatic solution for overcoming these limitations by providing a platform for interactive information seeking, information sharing, and user-centered tailoring. Objective The primary goal of this paper is to discuss the advantages of comprehensive and iterative Web-based technologies for health information provision and propose a four-phase framework for the development of Web-based information tools. Methods The proposed framework draws on our experience of constructing a Web-based information tool for hematological cancer patients and their families. The framework is based on principles for the development and evaluation of complex interventions and draws on the Agile methodology of software programming that emphasizes collaboration and iteration throughout the development process. Results The DoTTI framework provides a model for a comprehensive and iterative approach to the development of Web-based informational tools for patients. The process involves 4 phases of development: (1) Design and development, (2) Testing early iterations, (3) Testing for effectiveness, and (4) Integration and implementation. At each step, stakeholders (including researchers, clinicians, consumers, and programmers) are engaged in consultations to review progress, provide feedback on versions of the Web-based tool, and based on feedback, determine the appropriate next steps in development. Conclusions This 4-phase framework is evidence-informed and consumer-centered and could be applied widely to develop Web-based programs for a diverse range of diseases. PMID:24641991

Tailored and integrated Web-based tools for improving psychosocial outcomes of cancer patients: the DoTTI development framework.

PubMed

Smits, Rochelle; Bryant, Jamie; Sanson-Fisher, Rob; Tzelepis, Flora; Henskens, Frans; Paul, Christine; Stevenson, William

2014-03-14

Effective communication with cancer patients and their families about their disease, treatment options, and possible outcomes may improve psychosocial outcomes. However, traditional approaches to providing information to patients, including verbal information and written booklets, have a number of shortcomings centered on their limited ability to meet patient preferences and literacy levels. New-generation Web-based technologies offer an innovative and pragmatic solution for overcoming these limitations by providing a platform for interactive information seeking, information sharing, and user-centered tailoring. The primary goal of this paper is to discuss the advantages of comprehensive and iterative Web-based technologies for health information provision and propose a four-phase framework for the development of Web-based information tools. The proposed framework draws on our experience of constructing a Web-based information tool for hematological cancer patients and their families. The framework is based on principles for the development and evaluation of complex interventions and draws on the Agile methodology of software programming that emphasizes collaboration and iteration throughout the development process. The DoTTI framework provides a model for a comprehensive and iterative approach to the development of Web-based informational tools for patients. The process involves 4 phases of development: (1) Design and development, (2) Testing early iterations, (3) Testing for effectiveness, and (4) Integration and implementation. At each step, stakeholders (including researchers, clinicians, consumers, and programmers) are engaged in consultations to review progress, provide feedback on versions of the Web-based tool, and based on feedback, determine the appropriate next steps in development. This 4-phase framework is evidence-informed and consumer-centered and could be applied widely to develop Web-based programs for a diverse range of diseases.

Iterative repair for scheduling and rescheduling

NASA Technical Reports Server (NTRS)

Zweben, Monte; Davis, Eugene; Deale, Michael

1991-01-01

An iterative repair search method is described called constraint based simulated annealing. Simulated annealing is a hill climbing search technique capable of escaping local minima. The utility of the constraint based framework is shown by comparing search performance with and without the constraint framework on a suite of randomly generated problems. Results are also shown of applying the technique to the NASA Space Shuttle ground processing problem. These experiments show that the search methods scales to complex, real world problems and reflects interesting anytime behavior.

A novel surrogate-based approach for optimal design of electromagnetic-based circuits

NASA Astrophysics Data System (ADS)

Hassan, Abdel-Karim S. O.; Mohamed, Ahmed S. A.; Rabie, Azza A.; Etman, Ahmed S.

2016-02-01

A new geometric design centring approach for optimal design of central processing unit-intensive electromagnetic (EM)-based circuits is introduced. The approach uses norms related to the probability distribution of the circuit parameters to find distances from a point to the feasible region boundaries by solving nonlinear optimization problems. Based on these normed distances, the design centring problem is formulated as a max-min optimization problem. A convergent iterative boundary search technique is exploited to find the normed distances. To alleviate the computation cost associated with the EM-based circuits design cycle, space-mapping (SM) surrogates are used to create a sequence of iteratively updated feasible region approximations. In each SM feasible region approximation, the centring process using normed distances is implemented, leading to a better centre point. The process is repeated until a final design centre is attained. Practical examples are given to show the effectiveness of the new design centring method for EM-based circuits.

PID-based error signal modeling

NASA Astrophysics Data System (ADS)

Yohannes, Tesfay

1997-10-01

This paper introduces a PID based signal error modeling. The error modeling is based on the betterment process. The resulting iterative learning algorithm is introduced and a detailed proof is provided for both linear and nonlinear systems.

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.

Culturally Based Intervention Development: The Case of Latino Families Dealing with Schizophrenia

ERIC Educational Resources Information Center

Barrio, Concepcion; Yamada, Ann-Marie

2010-01-01

Objectives: This article describes the process of developing a culturally based family intervention for Spanish-speaking Latino families with a relative diagnosed with schizophrenia. Method: Our iterative intervention development process was guided by a cultural exchange framework and based on findings from an ethnographic study. We piloted this…

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.

Inferring the demographic history from DNA sequences: An importance sampling approach based on non-homogeneous processes.

PubMed

Ait Kaci Azzou, S; Larribe, F; Froda, S

2016-10-01

In Ait Kaci Azzou et al. (2015) we introduced an Importance Sampling (IS) approach for estimating the demographic history of a sample of DNA sequences, the skywis plot. More precisely, we proposed a new nonparametric estimate of a population size that changes over time. We showed on simulated data that the skywis plot can work well in typical situations where the effective population size does not undergo very steep changes. In this paper, we introduce an iterative procedure which extends the previous method and gives good estimates under such rapid variations. In the iterative calibrated skywis plot we approximate the effective population size by a piecewise constant function, whose values are re-estimated at each step. These piecewise constant functions are used to generate the waiting times of non homogeneous Poisson processes related to a coalescent process with mutation under a variable population size model. Moreover, the present IS procedure is based on a modified version of the Stephens and Donnelly (2000) proposal distribution. Finally, we apply the iterative calibrated skywis plot method to a simulated data set from a rapidly expanding exponential model, and we show that the method based on this new IS strategy correctly reconstructs the demographic history. Copyright © 2016. Published by Elsevier Inc.

The development and preliminary testing of a multimedia patient-provider survivorship communication module for breast cancer survivors.

PubMed

Wen, Kuang-Yi; Miller, Suzanne M; Stanton, Annette L; Fleisher, Linda; Morra, Marion E; Jorge, Alexandra; Diefenbach, Michael A; Ropka, Mary E; Marcus, Alfred C

2012-08-01

This paper describes the development of a theory-guided and evidence-based multimedia training module to facilitate breast cancer survivors' preparedness for effective communication with their health care providers after active treatment. The iterative developmental process used included: (1) theory and evidence-based content development and vetting; (2) user testing; (3) usability testing; and (4) participant module utilization. Formative evaluation of the training module prototype occurred through user testing (n = 12), resulting in modification of the content and layout. Usability testing (n = 10) was employed to improve module functionality. Preliminary web usage data (n = 256, mean age = 53, 94.5% White, 75% college graduate and above) showed that 59% of the participants accessed the communication module, for an average of 7 min per login. The iterative developmental process was informative in enhancing the relevance of the communication module. Preliminary web usage results demonstrate the potential feasibility of such a program. Our study demonstrates survivors' openness to the use of a web-based communication skills training module and outlines a systematic iterative user and interface program development and testing process, which can serve as a prototype for others considering such an approach. Copyright © 2012. Published by Elsevier Ireland Ltd.

The development and preliminary testing of a multimedia patient–provider survivorship communication module for breast cancer survivors

PubMed Central

Wen, Kuang-Yi; Miller, Suzanne M.; Stanton, Annette L.; Fleisher, Linda; Morra, Marion E.; Jorge, Alexandra; Diefenbach, Michael A.; Ropka, Mary E.; Marcus, Alfred C.

2012-01-01

Objective This paper describes the development of a theory-guided and evidence-based multimedia training module to facilitate breast cancer survivors’ preparedness for effective communication with their health care providers after active treatment. Methods The iterative developmental process used included: (1) theory and evidence-based content development and vetting; (2) user testing; (3) usability testing; and (4) participant module utilization. Results Formative evaluation of the training module prototype occurred through user testing (n = 12), resulting in modification of the content and layout. Usability testing (n = 10) was employed to improve module functionality. Preliminary web usage data (n = 256, mean age = 53, 94.5% White, 75% college graduate and above) showed that 59% of the participants accessed the communication module, for an average of 7 min per login. Conclusion The iterative developmental process was informative in enhancing the relevance of the communication module. Preliminary web usage results demonstrate the potential feasibility of such a program. Practice implications Our study demonstrates survivors’ openness to the use of a web-based communication skills training module and outlines a systematic iterative user and interface program development and testing process, which can serve as a prototype for others considering such an approach. PMID:22770812

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.

Nonlinear BCJR equalizer for suppression of intrachannel nonlinearities in 40 Gb/s optical communications systems.

PubMed

Djordjevic, Ivan B; Vasic, Bane

2006-05-29

A maximum a posteriori probability (MAP) symbol decoding supplemented with iterative decoding is proposed as an effective mean for suppression of intrachannel nonlinearities. The MAP detector, based on Bahl-Cocke-Jelinek-Raviv algorithm, operates on the channel trellis, a dynamical model of intersymbol interference, and provides soft-decision outputs processed further in an iterative decoder. A dramatic performance improvement is demonstrated. The main reason is that the conventional maximum-likelihood sequence detector based on Viterbi algorithm provides hard-decision outputs only, hence preventing the soft iterative decoding. The proposed scheme operates very well in the presence of strong intrachannel intersymbol interference, when other advanced forward error correction schemes fail, and it is also suitable for 40 Gb/s upgrade over existing 10 Gb/s infrastructure.

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.

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.

Iterative learning-based decentralized adaptive tracker for large-scale systems: a digital redesign approach.

PubMed

Tsai, Jason Sheng-Hong; Du, Yan-Yi; Huang, Pei-Hsiang; Guo, Shu-Mei; Shieh, Leang-San; Chen, Yuhua

2011-07-01

In this paper, a digital redesign methodology of the iterative learning-based decentralized adaptive tracker is proposed to improve the dynamic performance of sampled-data linear large-scale control systems consisting of N interconnected multi-input multi-output subsystems, so that the system output will follow any trajectory which may not be presented by the analytic reference model initially. To overcome the interference of each sub-system and simplify the controller design, the proposed model reference decentralized adaptive control scheme constructs a decoupled well-designed reference model first. Then, according to the well-designed model, this paper develops a digital decentralized adaptive tracker based on the optimal analog control and prediction-based digital redesign technique for the sampled-data large-scale coupling system. In order to enhance the tracking performance of the digital tracker at specified sampling instants, we apply the iterative learning control (ILC) to train the control input via continual learning. As a result, the proposed iterative learning-based decentralized adaptive tracker not only has robust closed-loop decoupled property but also possesses good tracking performance at both transient and steady state. Besides, evolutionary programming is applied to search for a good learning gain to speed up the learning process of ILC. Copyright © 2011 ISA. Published by Elsevier Ltd. All rights reserved.

Ultra-low-dose computed tomographic angiography with model-based iterative reconstruction compared with standard-dose imaging after endovascular aneurysm repair: a prospective pilot study.

PubMed

Naidu, Sailen G; Kriegshauser, J Scott; Paden, Robert G; He, Miao; Wu, Qing; Hara, Amy K

2014-12-01

An ultra-low-dose radiation protocol reconstructed with model-based iterative reconstruction was compared with our standard-dose protocol. This prospective study evaluated 20 men undergoing surveillance-enhanced computed tomography after endovascular aneurysm repair. All patients underwent standard-dose and ultra-low-dose venous phase imaging; images were compared after reconstruction with filtered back projection, adaptive statistical iterative reconstruction, and model-based iterative reconstruction. Objective measures of aortic contrast attenuation and image noise were averaged. Images were subjectively assessed (1 = worst, 5 = best) for diagnostic confidence, image noise, and vessel sharpness. Aneurysm sac diameter and endoleak detection were compared. Quantitative image noise was 26% less with ultra-low-dose model-based iterative reconstruction than with standard-dose adaptive statistical iterative reconstruction and 58% less than with ultra-low-dose adaptive statistical iterative reconstruction. Average subjective noise scores were not different between ultra-low-dose model-based iterative reconstruction and standard-dose adaptive statistical iterative reconstruction (3.8 vs. 4.0, P = .25). Subjective scores for diagnostic confidence were better with standard-dose adaptive statistical iterative reconstruction than with ultra-low-dose model-based iterative reconstruction (4.4 vs. 4.0, P = .002). Vessel sharpness was decreased with ultra-low-dose model-based iterative reconstruction compared with standard-dose adaptive statistical iterative reconstruction (3.3 vs. 4.1, P < .0001). Ultra-low-dose model-based iterative reconstruction and standard-dose adaptive statistical iterative reconstruction aneurysm sac diameters were not significantly different (4.9 vs. 4.9 cm); concordance for the presence of endoleak was 100% (P < .001). Compared with a standard-dose technique, an ultra-low-dose model-based iterative reconstruction protocol provides comparable image quality and diagnostic assessment at a 73% lower radiation dose.

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.

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.

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.

Discrete Fourier Transform in a Complex Vector Space

NASA Technical Reports Server (NTRS)

Dean, Bruce H. (Inventor)

2015-01-01

An image-based phase retrieval technique has been developed that can be used on board a space based iterative transformation system. Image-based wavefront sensing is computationally demanding due to the floating-point nature of the process. The discrete Fourier transform (DFT) calculation is presented in "diagonal" form. By diagonal we mean that a transformation of basis is introduced by an application of the similarity transform of linear algebra. The current method exploits the diagonal structure of the DFT in a special way, particularly when parts of the calculation do not have to be repeated at each iteration to converge to an acceptable solution in order to focus an image.

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…

Application of a dual-resolution voxelization scheme to compressed-sensing (CS)-based iterative reconstruction in digital tomosynthesis (DTS)

NASA Astrophysics Data System (ADS)

Park, S. Y.; Kim, G. A.; Cho, H. S.; Park, C. K.; Lee, D. Y.; Lim, H. W.; Lee, H. W.; Kim, K. S.; Kang, S. Y.; Park, J. E.; Kim, W. S.; Jeon, D. H.; Je, U. K.; Woo, T. H.; Oh, J. E.

2018-02-01

In recent digital tomosynthesis (DTS), iterative reconstruction methods are often used owing to the potential to provide multiplanar images of superior image quality to conventional filtered-backprojection (FBP)-based methods. However, they require enormous computational cost in the iterative process, which has still been an obstacle to put them to practical use. In this work, we propose a new DTS reconstruction method incorporated with a dual-resolution voxelization scheme in attempt to overcome these difficulties, in which the voxels outside a small region-of-interest (ROI) containing target diagnosis are binned by 2 × 2 × 2 while the voxels inside the ROI remain unbinned. We considered a compressed-sensing (CS)-based iterative algorithm with a dual-constraint strategy for more accurate DTS reconstruction. We implemented the proposed algorithm and performed a systematic simulation and experiment to demonstrate its viability. Our results indicate that the proposed method seems to be effective for reducing computational cost considerably in iterative DTS reconstruction, keeping the image quality inside the ROI not much degraded. A binning size of 2 × 2 × 2 required only about 31.9% computational memory and about 2.6% reconstruction time, compared to those for no binning case. The reconstruction quality was evaluated in terms of the root-mean-square error (RMSE), the contrast-to-noise ratio (CNR), and the universal-quality index (UQI).

Iterated unscented Kalman filter for phase unwrapping of interferometric fringes.

PubMed

Xie, Xianming

2016-08-22

A fresh phase unwrapping algorithm based on iterated unscented Kalman filter is proposed to estimate unambiguous unwrapped phase of interferometric fringes. This method is the result of combining an iterated unscented Kalman filter with a robust phase gradient estimator based on amended matrix pencil model, and an efficient quality-guided strategy based on heap sort. The iterated unscented Kalman filter that is one of the most robust methods under the Bayesian theorem frame in non-linear signal processing so far, is applied to perform simultaneously noise suppression and phase unwrapping of interferometric fringes for the first time, which can simplify the complexity and the difficulty of pre-filtering procedure followed by phase unwrapping procedure, and even can remove the pre-filtering procedure. The robust phase gradient estimator is used to efficiently and accurately obtain phase gradient information from interferometric fringes, which is needed for the iterated unscented Kalman filtering phase unwrapping model. The efficient quality-guided strategy is able to ensure that the proposed method fast unwraps wrapped pixels along the path from the high-quality area to the low-quality area of wrapped phase images, which can greatly improve the efficiency of phase unwrapping. Results obtained from synthetic data and real data show that the proposed method can obtain better solutions with an acceptable time consumption, with respect to some of the most used algorithms.

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.

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

Noise models for low counting rate coherent diffraction imaging.

PubMed

Godard, Pierre; Allain, Marc; Chamard, Virginie; Rodenburg, John

2012-11-05

Coherent diffraction imaging (CDI) is a lens-less microscopy method that extracts the complex-valued exit field from intensity measurements alone. It is of particular importance for microscopy imaging with diffraction set-ups where high quality lenses are not available. The inversion scheme allowing the phase retrieval is based on the use of an iterative algorithm. In this work, we address the question of the choice of the iterative process in the case of data corrupted by photon or electron shot noise. Several noise models are presented and further used within two inversion strategies, the ordered subset and the scaled gradient. Based on analytical and numerical analysis together with Monte-Carlo studies, we show that any physical interpretations drawn from a CDI iterative technique require a detailed understanding of the relationship between the noise model and the used inversion method. We observe that iterative algorithms often assume implicitly a noise model. For low counting rates, each noise model behaves differently. Moreover, the used optimization strategy introduces its own artefacts. Based on this analysis, we develop a hybrid strategy which works efficiently in the absence of an informed initial guess. Our work emphasises issues which should be considered carefully when inverting experimental data.

Adaptive implicit-explicit and parallel element-by-element iteration schemes

NASA Technical Reports Server (NTRS)

Tezduyar, T. E.; Liou, J.; Nguyen, T.; Poole, S.

1989-01-01

Adaptive implicit-explicit (AIE) and grouped element-by-element (GEBE) iteration schemes are presented for the finite element solution of large-scale problems in computational mechanics and physics. The AIE approach is based on the dynamic arrangement of the elements into differently treated groups. The GEBE procedure, which is a way of rewriting the EBE formulation to make its parallel processing potential and implementation more clear, is based on the static arrangement of the elements into groups with no inter-element coupling within each group. Various numerical tests performed demonstrate the savings in the CPU time and memory.

Lunar lander conceptual design: Lunar base systems study task 2.2

NASA Technical Reports Server (NTRS)

1988-01-01

This study is a first look at the problem of building a lunar lander to support a small lunar surface base. One lander, which can land 25 metric tons, one way, or take a 6 metric ton crew capsule up and down is desired. A series of trade studies are used to narrow the choices and provide some general guidelines. Given a rough baseline, the systems are then reviewed. A conceptual design is then produced. The process was only carried through one iteration. Many more iterations are needed. Assumptions and groundrules are considered.

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

Multi-criteria Integrated Resource Assessment (MIRA)

EPA Pesticide Factsheets

MIRA is an approach that facilitates stakeholder engagement for collaborative multi-objective decision making. MIRA is designed to facilitate and support an inclusive, explicit, transparent, iterative learning-based decision process.

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.

Photoacoustic image reconstruction via deep learning

NASA Astrophysics Data System (ADS)

Antholzer, Stephan; Haltmeier, Markus; Nuster, Robert; Schwab, Johannes

2018-02-01

Applying standard algorithms to sparse data problems in photoacoustic tomography (PAT) yields low-quality images containing severe under-sampling artifacts. To some extent, these artifacts can be reduced by iterative image reconstruction algorithms which allow to include prior knowledge such as smoothness, total variation (TV) or sparsity constraints. These algorithms tend to be time consuming as the forward and adjoint problems have to be solved repeatedly. Further, iterative algorithms have additional drawbacks. For example, the reconstruction quality strongly depends on a-priori model assumptions about the objects to be recovered, which are often not strictly satisfied in practical applications. To overcome these issues, in this paper, we develop direct and efficient reconstruction algorithms based on deep learning. As opposed to iterative algorithms, we apply a convolutional neural network, whose parameters are trained before the reconstruction process based on a set of training data. For actual image reconstruction, a single evaluation of the trained network yields the desired result. Our presented numerical results (using two different network architectures) demonstrate that the proposed deep learning approach reconstructs images with a quality comparable to state of the art iterative reconstruction methods.

Gauss-Seidel Iterative Method as a Real-Time Pile-Up Solver of Scintillation Pulses

NASA Astrophysics Data System (ADS)

Novak, Roman; Vencelj, Matja¿

2009-12-01

The pile-up rejection in nuclear spectroscopy has been confronted recently by several pile-up correction schemes that compensate for distortions of the signal and subsequent energy spectra artifacts as the counting rate increases. We study here a real-time capability of the event-by-event correction method, which at the core translates to solving many sets of linear equations. Tight time limits and constrained front-end electronics resources make well-known direct solvers inappropriate. We propose a novel approach based on the Gauss-Seidel iterative method, which turns out to be a stable and cost-efficient solution to improve spectroscopic resolution in the front-end electronics. We show the method convergence properties for a class of matrices that emerge in calorimetric processing of scintillation detector signals and demonstrate the ability of the method to support the relevant resolutions. The sole iteration-based error component can be brought below the sliding window induced errors in a reasonable number of iteration steps, thus allowing real-time operation. An area-efficient hardware implementation is proposed that fully utilizes the method's inherent parallelism.

Pipeline Processing with an Iterative, Context-based Detection Model

DTIC Science & Technology

2014-04-19

stripping the incoming data stream of repeating and irrelevant signals prior to running primary detectors , adaptive beamforming and matched field processing...framework, pattern detectors , correlation detectors , subspace detectors , matched field detectors , nuclear explosion monitoring 16. SECURITY CLASSIFICATION...10 5. Teleseismic paths from earthquakes in

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.

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

Stimulating Scientific Reasoning with Drawing-Based Modeling

ERIC Educational Resources Information Center

Heijnes, Dewi; van Joolingen, Wouter; Leenaars, Frank

2018-01-01

We investigate the way students' reasoning about evolution can be supported by drawing-based modeling. We modified the drawing-based modeling tool SimSketch to allow for modeling evolutionary processes. In three iterations of development and testing, students in lower secondary education worked on creating an evolutionary model. After each…

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.

Multigrid-based reconstruction algorithm for quantitative photoacoustic tomography

PubMed Central

Li, Shengfu; Montcel, Bruno; Yuan, Zhen; Liu, Wanyu; Vray, Didier

2015-01-01

This paper proposes a multigrid inversion framework for quantitative photoacoustic tomography reconstruction. The forward model of optical fluence distribution and the inverse problem are solved at multiple resolutions. A fixed-point iteration scheme is formulated for each resolution and used as a cost function. The simulated and experimental results for quantitative photoacoustic tomography reconstruction show that the proposed multigrid inversion can dramatically reduce the required number of iterations for the optimization process without loss of reliability in the results. PMID:26203371

Applying Evidence-Based Medicine in Telehealth: An Interactive Pattern Recognition Approximation

PubMed Central

Fernández-Llatas, Carlos; Meneu, Teresa; Traver, Vicente; Benedi, José-Miguel

2013-01-01

Born in the early nineteen nineties, evidence-based medicine (EBM) is a paradigm intended to promote the integration of biomedical evidence into the physicians daily practice. This paradigm requires the continuous study of diseases to provide the best scientific knowledge for supporting physicians in their diagnosis and treatments in a close way. Within this paradigm, usually, health experts create and publish clinical guidelines, which provide holistic guidance for the care for a certain disease. The creation of these clinical guidelines requires hard iterative processes in which each iteration supposes scientific progress in the knowledge of the disease. To perform this guidance through telehealth, the use of formal clinical guidelines will allow the building of care processes that can be interpreted and executed directly by computers. In addition, the formalization of clinical guidelines allows for the possibility to build automatic methods, using pattern recognition techniques, to estimate the proper models, as well as the mathematical models for optimizing the iterative cycle for the continuous improvement of the guidelines. However, to ensure the efficiency of the system, it is necessary to build a probabilistic model of the problem. In this paper, an interactive pattern recognition approach to support professionals in evidence-based medicine is formalized. PMID:24185841

Incorporating Multi-criteria Optimization and Uncertainty Analysis in the Model-Based Systems Engineering of an Autonomous Surface Craft

DTIC Science & Technology

2009-09-01

SAS Statistical Analysis Software SE Systems Engineering SEP Systems Engineering Process SHP Shaft Horsepower SIGINT Signals Intelligence......management occurs (OSD 2002). The Systems Engineering Process (SEP), displayed in Figure 2, is a comprehensive , iterative and recursive problem

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.

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.

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.

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.

Standard and reduced radiation dose liver CT images: adaptive statistical iterative reconstruction versus model-based iterative reconstruction-comparison of findings and image quality.

PubMed

Shuman, William P; Chan, Keith T; Busey, Janet M; Mitsumori, Lee M; Choi, Eunice; Koprowicz, Kent M; Kanal, Kalpana M

2014-12-01

To investigate whether reduced radiation dose liver computed tomography (CT) images reconstructed with model-based iterative reconstruction ( MBIR model-based iterative reconstruction ) might compromise depiction of clinically relevant findings or might have decreased image quality when compared with clinical standard radiation dose CT images reconstructed with adaptive statistical iterative reconstruction ( ASIR adaptive statistical iterative reconstruction ). With institutional review board approval, informed consent, and HIPAA compliance, 50 patients (39 men, 11 women) were prospectively included who underwent liver CT. After a portal venous pass with ASIR adaptive statistical iterative reconstruction images, a 60% reduced radiation dose pass was added with MBIR model-based iterative reconstruction images. One reviewer scored ASIR adaptive statistical iterative reconstruction image quality and marked findings. Two additional independent reviewers noted whether marked findings were present on MBIR model-based iterative reconstruction images and assigned scores for relative conspicuity, spatial resolution, image noise, and image quality. Liver and aorta Hounsfield units and image noise were measured. Volume CT dose index and size-specific dose estimate ( SSDE size-specific dose estimate ) were recorded. Qualitative reviewer scores were summarized. Formal statistical inference for signal-to-noise ratio ( SNR signal-to-noise ratio ), contrast-to-noise ratio ( CNR contrast-to-noise ratio ), volume CT dose index, and SSDE size-specific dose estimate was made (paired t tests), with Bonferroni adjustment. Two independent reviewers identified all 136 ASIR adaptive statistical iterative reconstruction image findings (n = 272) on MBIR model-based iterative reconstruction images, scoring them as equal or better for conspicuity, spatial resolution, and image noise in 94.1% (256 of 272), 96.7% (263 of 272), and 99.3% (270 of 272), respectively. In 50 image sets, two reviewers (n = 100) scored overall image quality as sufficient or good with MBIR model-based iterative reconstruction in 99% (99 of 100). Liver SNR signal-to-noise ratio was significantly greater for MBIR model-based iterative reconstruction (10.8 ± 2.5 [standard deviation] vs 7.7 ± 1.4, P < .001); there was no difference for CNR contrast-to-noise ratio (2.5 ± 1.4 vs 2.4 ± 1.4, P = .45). For ASIR adaptive statistical iterative reconstruction and MBIR model-based iterative reconstruction , respectively, volume CT dose index was 15.2 mGy ± 7.6 versus 6.2 mGy ± 3.6; SSDE size-specific dose estimate was 16.4 mGy ± 6.6 versus 6.7 mGy ± 3.1 (P < .001). Liver CT images reconstructed with MBIR model-based iterative reconstruction may allow up to 59% radiation dose reduction compared with the dose with ASIR adaptive statistical iterative reconstruction , without compromising depiction of findings or image quality. © RSNA, 2014.

Defining and Building an Enriched Learning and Information Environment.

ERIC Educational Resources Information Center

Goodrum, David A.; And Others

1993-01-01

Discusses the development of an Enriched Learning and Information Environment (ELIE). Highlights include technology-based and theory-based frameworks for defining ELIEs; a socio-technical definition; a conceptual prototype; a participatory design process, including iterative design through rapid prototyping; and design issues for technology…

Development and Validation of the Homeostasis Concept Inventory

ERIC Educational Resources Information Center

McFarland, Jenny L.; Price, Rebecca M.; Wenderoth, Mary Pat; Martinková, Patrícia; Cliff, William; Michael, Joel; Modell, Harold; Wright, Ann

2017-01-01

We present the Homeostasis Concept Inventory (HCI), a 20-item multiple-choice instrument that assesses how well undergraduates understand this critical physiological concept. We used an iterative process to develop a set of questions based on elements in the Homeostasis Concept Framework. This process involved faculty experts and undergraduate…

Iteration and superposition encryption scheme for image sequences based on multi-dimensional keys

NASA Astrophysics Data System (ADS)

Han, Chao; Shen, Yuzhen; Ma, Wenlin

2017-12-01

An iteration and superposition encryption scheme for image sequences based on multi-dimensional keys is proposed for high security, big capacity and low noise information transmission. Multiple images to be encrypted are transformed into phase-only images with the iterative algorithm and then are encrypted by different random phase, respectively. The encrypted phase-only images are performed by inverse Fourier transform, respectively, thus new object functions are generated. The new functions are located in different blocks and padded zero for a sparse distribution, then they propagate to a specific region at different distances by angular spectrum diffraction, respectively and are superposed in order to form a single image. The single image is multiplied with a random phase in the frequency domain and then the phase part of the frequency spectrums is truncated and the amplitude information is reserved. The random phase, propagation distances, truncated phase information in frequency domain are employed as multiple dimensional keys. The iteration processing and sparse distribution greatly reduce the crosstalk among the multiple encryption images. The superposition of image sequences greatly improves the capacity of encrypted information. Several numerical experiments based on a designed optical system demonstrate that the proposed scheme can enhance encrypted information capacity and make image transmission at a highly desired security level.

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.

Terminal iterative learning control based station stop control of a train

NASA Astrophysics Data System (ADS)

Hou, Zhongsheng; Wang, Yi; Yin, Chenkun; Tang, Tao

2011-07-01

The terminal iterative learning control (TILC) method is introduced for the first time into the field of train station stop control and three TILC-based algorithms are proposed in this study. The TILC-based train station stop control approach utilises the terminal stop position error in previous braking process to update the current control profile. The initial braking position, or the braking force, or their combination is chosen as the control input, and corresponding learning law is developed. The terminal stop position error of each algorithm is guaranteed to converge to a small region related with the initial offset of braking position with rigorous analysis. The validity of the proposed algorithms is verified by illustrative numerical examples.

Data and Workflow Management Challenges in Global Adjoint Tomography

NASA Astrophysics Data System (ADS)

Lei, W.; Ruan, Y.; Smith, J. A.; Modrak, R. T.; Orsvuran, R.; Krischer, L.; Chen, Y.; Balasubramanian, V.; Hill, J.; Turilli, M.; Bozdag, E.; Lefebvre, M. P.; Jha, S.; Tromp, J.

2017-12-01

It is crucial to take the complete physics of wave propagation into account in seismic tomography to further improve the resolution of tomographic images. The adjoint method is an efficient way of incorporating 3D wave simulations in seismic tomography. However, global adjoint tomography is computationally expensive, requiring thousands of wavefield simulations and massive data processing. Through our collaboration with the Oak Ridge National Laboratory (ORNL) computing group and an allocation on Titan, ORNL's GPU-accelerated supercomputer, we are now performing our global inversions by assimilating waveform data from over 1,000 earthquakes. The first challenge we encountered is dealing with the sheer amount of seismic data. Data processing based on conventional data formats and processing tools (such as SAC), which are not designed for parallel systems, becomes our major bottleneck. To facilitate the data processing procedures, we designed the Adaptive Seismic Data Format (ASDF) and developed a set of Python-based processing tools to replace legacy FORTRAN-based software. These tools greatly enhance reproducibility and accountability while taking full advantage of highly parallel system and showing superior scaling on modern computational platforms. The second challenge is that the data processing workflow contains more than 10 sub-procedures, making it delicate to handle and prone to human mistakes. To reduce human intervention as much as possible, we are developing a framework specifically designed for seismic inversion based on the state-of-the art workflow management research, specifically the Ensemble Toolkit (EnTK), in collaboration with the RADICAL team from Rutgers University. Using the initial developments of the EnTK, we are able to utilize the full computing power of the data processing cluster RHEA at ORNL while keeping human interaction to a minimum and greatly reducing the data processing time. Thanks to all the improvements, we are now able to perform iterations fast enough on more than a 1,000 earthquakes dataset. Starting from model GLAD-M15 (Bozdag et al., 2016), an elastic 3D model with a transversely isotropic upper mantle, we have successfully performed 5 iterations. Our goal is to finish 10 iterations, i.e., generating GLAD M25* by the end of this year.

A Structured Decision Approach for Integrating and Analyzing Community Perspectives in Re-Use Planning of Vacant Properties in Cleveland, Ohio

EPA Science Inventory

An integrated GIS-based, multi-attribute decision model deployed in a web-based platform is presented enabling an iterative, spatially explicit and collaborative analysis of relevant and available information for repurposing vacant land. The process incorporated traditional and ...

Supporting the Health and Wellness of Individuals with Psychiatric Disabilities

ERIC Educational Resources Information Center

Swarbrick, Margaret; Nemec, Patricia B.

2016-01-01

Purpose: Psychiatric rehabilitation is recognized as a field with specialized knowledge and skills required for practice. The certified psychiatric rehabilitation practitioner (CPRP) credential, an exam-based certification process, is based on a regularly updated job task analysis that, in its most recent iteration, identified the new core…

Intelligent model-based OPC

NASA Astrophysics Data System (ADS)

Huang, W. C.; Lai, C. M.; Luo, B.; Tsai, C. K.; Chih, M. H.; Lai, C. W.; Kuo, C. C.; Liu, R. G.; Lin, H. T.

2006-03-01

Optical proximity correction is the technique of pre-distorting mask layouts so that the printed patterns are as close to the desired shapes as possible. For model-based optical proximity correction, a lithographic model to predict the edge position (contour) of patterns on the wafer after lithographic processing is needed. Generally, segmentation of edges is performed prior to the correction. Pattern edges are dissected into several small segments with corresponding target points. During the correction, the edges are moved back and forth from the initial drawn position, assisted by the lithographic model, to finally settle on the proper positions. When the correction converges, the intensity predicted by the model in every target points hits the model-specific threshold value. Several iterations are required to achieve the convergence and the computation time increases with the increase of the required iterations. An artificial neural network is an information-processing paradigm inspired by biological nervous systems, such as how the brain processes information. It is composed of a large number of highly interconnected processing elements (neurons) working in unison to solve specific problems. A neural network can be a powerful data-modeling tool that is able to capture and represent complex input/output relationships. The network can accurately predict the behavior of a system via the learning procedure. A radial basis function network, a variant of artificial neural network, is an efficient function approximator. In this paper, a radial basis function network was used to build a mapping from the segment characteristics to the edge shift from the drawn position. This network can provide a good initial guess for each segment that OPC has carried out. The good initial guess reduces the required iterations. Consequently, cycle time can be shortened effectively. The optimization of the radial basis function network for this system was practiced by genetic algorithm, which is an artificially intelligent optimization method with a high probability to obtain global optimization. From preliminary results, the required iterations were reduced from 5 to 2 for a simple dumbbell-shape layout.

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

DEM Calibration Approach: design of experiment

NASA Astrophysics Data System (ADS)

Boikov, A. V.; Savelev, R. V.; Payor, V. A.

2018-05-01

The problem of DEM models calibration is considered in the article. It is proposed to divide models input parameters into those that require iterative calibration and those that are recommended to measure directly. A new method for model calibration based on the design of the experiment for iteratively calibrated parameters is proposed. The experiment is conducted using a specially designed stand. The results are processed with technical vision algorithms. Approximating functions are obtained and the error of the implemented software and hardware complex is estimated. The prospects of the obtained results are discussed.

Design or "Design"--Envisioning a Future Design Education

ERIC Educational Resources Information Center

Sless, David

2012-01-01

Challenging the common grand vision of Design, this article considers "design" as a humble re-forming process based on evidence to substantiate its results. The designer is likened to a tinker who respects previous iterations of a design and seeks to retain what is useful while improving its performance. A design process is offered,…

Image Encryption Algorithm Based on Hyperchaotic Maps and Nucleotide Sequences Database

PubMed Central

2017-01-01

Image encryption technology is one of the main means to ensure the safety of image information. Using the characteristics of chaos, such as randomness, regularity, ergodicity, and initial value sensitiveness, combined with the unique space conformation of DNA molecules and their unique information storage and processing ability, an efficient method for image encryption based on the chaos theory and a DNA sequence database is proposed. In this paper, digital image encryption employs a process of transforming the image pixel gray value by using chaotic sequence scrambling image pixel location and establishing superchaotic mapping, which maps quaternary sequences and DNA sequences, and by combining with the logic of the transformation between DNA sequences. The bases are replaced under the displaced rules by using DNA coding in a certain number of iterations that are based on the enhanced quaternary hyperchaotic sequence; the sequence is generated by Chen chaos. The cipher feedback mode and chaos iteration are employed in the encryption process to enhance the confusion and diffusion properties of the algorithm. Theoretical analysis and experimental results show that the proposed scheme not only demonstrates excellent encryption but also effectively resists chosen-plaintext attack, statistical attack, and differential attack. PMID:28392799

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.

An image hiding method based on cascaded iterative Fourier transform and public-key encryption algorithm

NASA Astrophysics Data System (ADS)

Zhang, B.; Sang, Jun; Alam, Mohammad S.

2013-03-01

An image hiding method based on cascaded iterative Fourier transform and public-key encryption algorithm was proposed. Firstly, the original secret image was encrypted into two phase-only masks M1 and M2 via cascaded iterative Fourier transform (CIFT) algorithm. Then, the public-key encryption algorithm RSA was adopted to encrypt M2 into M2' . Finally, a host image was enlarged by extending one pixel into 2×2 pixels and each element in M1 and M2' was multiplied with a superimposition coefficient and added to or subtracted from two different elements in the 2×2 pixels of the enlarged host image. To recover the secret image from the stego-image, the two masks were extracted from the stego-image without the original host image. By applying public-key encryption algorithm, the key distribution was facilitated, and also compared with the image hiding method based on optical interference, the proposed method may reach higher robustness by employing the characteristics of the CIFT algorithm. Computer simulations show that this method has good robustness against image processing.

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.

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.

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.

Cultural adaptation of evidence-based practice utilizing an iterative stakeholder process and theoretical framework: problem solving therapy for Chinese older adults

PubMed Central

Chu, Joyce P.; Huynh, Loanie; Areán, Patricia

2011-01-01

Objectives Main objectives were to familiarize the reader with a theoretical framework for modifying evidence-based interventions for cultural groups, and to provide an example of one method, Formative Method for Adapting Psychotherapies (FMAP), in the adaptation of an evidence-based intervention for a cultural group notorious for refusing mental health treatment. Methods Provider and client stakeholder input combined with an iterative testing process within the FMAP framework was utilized to create the Problem Solving Therapy—Chinese Older Adult (PST-COA) manual for depression. Data from pilot-testing the intervention with a clinically depressed Chinese elderly woman are reported. Results PST-COA is categorized as a ‘culturally-adapted’ treatment, where core mediating mechanisms of PST were preserved, but cultural themes of measurement methodology, stigma, hierarchical provider-client relationship expectations, and acculturation enhanced core components to make PST more understandable and relevant for Chinese elderly. Modifications also encompassed therapeutic framework and peripheral elements affecting engagement and retention. PST-COA applied with a depressed Chinese older adult indicated remission of clinical depression and improvement in mood. Fidelity with and acceptability of the treatment was sufficient as the client completed and reported high satisfaction with PST-COA. Conclusions PST, as a non-emotion-focused, evidence-based intervention, is a good fit for depressed Chinese elderly. Through an iterative stakeholder process of cultural adaptation, several culturally-specific modifications were applied to PST to create the PST-COA manual. PST-COA preserves core therapeutic PST elements but includes cultural adaptations in therapeutic framework and key administration and content areas that ensure greater applicability and effectiveness for the Chinese elderly community. PMID:21500283

New perspectives in face correlation: discrimination enhancement in face recognition based on iterative algorithm

NASA Astrophysics Data System (ADS)

Wang, Q.; Alfalou, A.; Brosseau, C.

2016-04-01

Here, we report a brief review on the recent developments of correlation algorithms. Several implementation schemes and specific applications proposed in recent years are also given to illustrate powerful applications of these methods. Following a discussion and comparison of the implementation of these schemes, we believe that all-numerical implementation is the most practical choice for application of the correlation method because the advantages of optical processing cannot compensate the technical and/or financial cost needed for an optical implementation platform. We also present a simple iterative algorithm to optimize the training images of composite correlation filters. By making use of three or four iterations, the peak-to-correlation energy (PCE) value of correlation plane can be significantly enhanced. A simulation test using the Pointing Head Pose Image Database (PHPID) illustrates the effectiveness of this statement. Our method can be applied in many composite filters based on linear composition of training images as an optimization means.

An Automated Baseline Correction Method Based on Iterative Morphological Operations.

PubMed

Chen, Yunliang; Dai, Liankui

2018-05-01

Raman spectra usually suffer from baseline drift caused by fluorescence or other reasons. Therefore, baseline correction is a necessary and crucial step that must be performed before subsequent processing and analysis of Raman spectra. An automated baseline correction method based on iterative morphological operations is proposed in this work. The method can adaptively determine the structuring element first and then gradually remove the spectral peaks during iteration to get an estimated baseline. Experiments on simulated data and real-world Raman data show that the proposed method is accurate, fast, and flexible for handling different kinds of baselines in various practical situations. The comparison of the proposed method with some state-of-the-art baseline correction methods demonstrates its advantages over the existing methods in terms of accuracy, adaptability, and flexibility. Although only Raman spectra are investigated in this paper, the proposed method is hopefully to be used for the baseline correction of other analytical instrumental signals, such as IR spectra and chromatograms.

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.

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.

Parallel programming of gradient-based iterative image reconstruction schemes for optical tomography.

PubMed

Hielscher, Andreas H; Bartel, Sebastian

2004-02-01

Optical tomography (OT) is a fast developing novel imaging modality that uses near-infrared (NIR) light to obtain cross-sectional views of optical properties inside the human body. A major challenge remains the time-consuming, computational-intensive image reconstruction problem that converts NIR transmission measurements into cross-sectional images. To increase the speed of iterative image reconstruction schemes that are commonly applied for OT, we have developed and implemented several parallel algorithms on a cluster of workstations. Static process distribution as well as dynamic load balancing schemes suitable for heterogeneous clusters and varying machine performances are introduced and tested. The resulting algorithms are shown to accelerate the reconstruction process to various degrees, substantially reducing the computation times for clinically relevant problems.

Phase extraction based on iterative algorithm using five-frame crossed fringes in phase measuring deflectometry

NASA Astrophysics Data System (ADS)

Jin, Chengying; Li, Dahai; Kewei, E.; Li, Mengyang; Chen, Pengyu; Wang, Ruiyang; Xiong, Zhao

2018-06-01

In phase measuring deflectometry, two orthogonal sinusoidal fringe patterns are separately projected on the test surface and the distorted fringes reflected by the surface are recorded, each with a sequential phase shift. Then the two components of the local surface gradients are obtained by triangulation. It usually involves some complicated and time-consuming procedures (fringe projection in the orthogonal directions). In addition, the digital light devices (e.g. LCD screen and CCD camera) are not error free. There are quantization errors for each pixel of both LCD and CCD. Therefore, to avoid the complex process and improve the reliability of the phase distribution, a phase extraction algorithm with five-frame crossed fringes is presented in this paper. It is based on a least-squares iterative process. Using the proposed algorithm, phase distributions and phase shift amounts in two orthogonal directions can be simultaneously and successfully determined through an iterative procedure. Both a numerical simulation and a preliminary experiment are conducted to verify the validity and performance of this algorithm. Experimental results obtained by our method are shown, and comparisons between our experimental results and those obtained by the traditional 16-step phase-shifting algorithm and between our experimental results and those measured by the Fizeau interferometer are made.

Soft-Decision Decoding of Binary Linear Block Codes Based on an Iterative Search Algorithm

NASA Technical Reports Server (NTRS)

Lin, Shu; Kasami, Tadao; Moorthy, H. T.

1997-01-01

This correspondence presents a suboptimum soft-decision decoding scheme for binary linear block codes based on an iterative search algorithm. The scheme uses an algebraic decoder to iteratively generate a sequence of candidate codewords one at a time using a set of test error patterns that are constructed based on the reliability information of the received symbols. When a candidate codeword is generated, it is tested based on an optimality condition. If it satisfies the optimality condition, then it is the most likely (ML) codeword and the decoding stops. If it fails the optimality test, a search for the ML codeword is conducted in a region which contains the ML codeword. The search region is determined by the current candidate codeword and the reliability of the received symbols. The search is conducted through a purged trellis diagram for the given code using the Viterbi algorithm. If the search fails to find the ML codeword, a new candidate is generated using a new test error pattern, and the optimality test and search are renewed. The process of testing and search continues until either the MEL codeword is found or all the test error patterns are exhausted and the decoding process is terminated. Numerical results show that the proposed decoding scheme achieves either practically optimal performance or a performance only a fraction of a decibel away from the optimal maximum-likelihood decoding with a significant reduction in decoding complexity compared with the Viterbi decoding based on the full trellis diagram of the codes.

Detangling the Interrelationships between Self- Regulation and Ill-Structured Problem Solving in Problem-Based Learning

ERIC Educational Resources Information Center

Ge, Xun; Law, Victor; Huang, Kun

2016-01-01

One of the goals for problem-based learning (PBL) is to promote self-regulation. Although self-regulation has been studied extensively, its interrelationships with ill-structured problem solving have been unclear. In order to clarify the interrelationships, this article proposes a conceptual framework illustrating the iterative processes among…

A Framework for Designing and Developing Multimedia-Based Performance Assessment in Vocational Education

ERIC Educational Resources Information Center

de Klerk, Sebastiaan; Veldkamp, Bernard P.; Eggen, Theo J. H. M.

2018-01-01

The development of any assessment should be an iterative and careful process. Ideally, this process is guided by a well-defined framework (see for example Downing in: Downing and Haladyna (eds) "Handbook of test development," Lawrence Erlbaum Associates, Mahwah, 2006; Mislevy et al. in "On the roles of task model variables in…

Using ArcObjects for automating fireshed assessments and analyzing wildfire risk

Treesearch

Alan A. Ager; Bernhard Bahro; Mark Finney

2006-01-01

Firesheds are geographic units used by the Forest Service to delineate areas with similar fire regimes, fire history, and wildland fire risk issues. Fireshed assessment is a collaborative process where specialists design fuel treatments to mitigate wildfire risk. Fireshed assessments are an iterative process where fuel treatments are proposed for specific stands based...

Optical Computing Based on Neuronal Models

DTIC Science & Technology

1988-05-01

walking, and cognition are far too complex for existing sequential digital computers. Therefore new architectures, hardware, and algorithms modeled...collective behavior, and iterative processing into optical processing and artificial neurodynamical systems. Another intriguing promise of neural nets is...with architectures, implementations, and programming; and material research s -7- called for. Our future research in neurodynamics will continue to

Proposing a new iterative learning control algorithm based on a non-linear least square formulation - Minimising draw-in errors

NASA Astrophysics Data System (ADS)

Endelt, B.

2017-09-01

Forming operation are subject to external disturbances and changing operating conditions e.g. new material batch, increasing tool temperature due to plastic work, material properties and lubrication is sensitive to tool temperature. It is generally accepted that forming operations are not stable over time and it is not uncommon to adjust the process parameters during the first half hour production, indicating that process instability is gradually developing over time. Thus, in-process feedback control scheme might not-be necessary to stabilize the process and an alternative approach is to apply an iterative learning algorithm, which can learn from previously produced parts i.e. a self learning system which gradually reduces error based on historical process information. What is proposed in the paper is a simple algorithm which can be applied to a wide range of sheet-metal forming processes. The input to the algorithm is the final flange edge geometry and the basic idea is to reduce the least-square error between the current flange geometry and a reference geometry using a non-linear least square algorithm. The ILC scheme is applied to a square deep-drawing and the Numisheet’08 S-rail benchmark problem, the numerical tests shows that the proposed control scheme is able control and stabilise both processes.

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)

Optimization of image quality and acquisition time for lab-based X-ray microtomography using an iterative reconstruction algorithm

NASA Astrophysics Data System (ADS)

Lin, Qingyang; Andrew, Matthew; Thompson, William; Blunt, Martin J.; Bijeljic, Branko

2018-05-01

Non-invasive laboratory-based X-ray microtomography has been widely applied in many industrial and research disciplines. However, the main barrier to the use of laboratory systems compared to a synchrotron beamline is its much longer image acquisition time (hours per scan compared to seconds to minutes at a synchrotron), which results in limited application for dynamic in situ processes. Therefore, the majority of existing laboratory X-ray microtomography is limited to static imaging; relatively fast imaging (tens of minutes per scan) can only be achieved by sacrificing imaging quality, e.g. reducing exposure time or number of projections. To alleviate this barrier, we introduce an optimized implementation of a well-known iterative reconstruction algorithm that allows users to reconstruct tomographic images with reasonable image quality, but requires lower X-ray signal counts and fewer projections than conventional methods. Quantitative analysis and comparison between the iterative and the conventional filtered back-projection reconstruction algorithm was performed using a sandstone rock sample with and without liquid phases in the pore space. Overall, by implementing the iterative reconstruction algorithm, the required image acquisition time for samples such as this, with sparse object structure, can be reduced by a factor of up to 4 without measurable loss of sharpness or signal to noise ratio.

Composition of web services using Markov decision processes and dynamic programming.

PubMed

Uc-Cetina, Víctor; Moo-Mena, Francisco; Hernandez-Ucan, Rafael

2015-01-01

We propose a Markov decision process model for solving the Web service composition (WSC) problem. Iterative policy evaluation, value iteration, and policy iteration algorithms are used to experimentally validate our approach, with artificial and real data. The experimental results show the reliability of the model and the methods employed, with policy iteration being the best one in terms of the minimum number of iterations needed to estimate an optimal policy, with the highest Quality of Service attributes. Our experimental work shows how the solution of a WSC problem involving a set of 100,000 individual Web services and where a valid composition requiring the selection of 1,000 services from the available set can be computed in the worst case in less than 200 seconds, using an Intel Core i5 computer with 6 GB RAM. Moreover, a real WSC problem involving only 7 individual Web services requires less than 0.08 seconds, using the same computational power. Finally, a comparison with two popular reinforcement learning algorithms, sarsa and Q-learning, shows that these algorithms require one or two orders of magnitude and more time than policy iteration, iterative policy evaluation, and value iteration to handle WSC problems of the same complexity.

Statistical analysis of the Nb3Sn strand production for the ITER toroidal field coils

NASA Astrophysics Data System (ADS)

Vostner, A.; Jewell, M.; Pong, I.; Sullivan, N.; Devred, A.; Bessette, D.; Bevillard, G.; Mitchell, N.; Romano, G.; Zhou, C.

2017-04-01

The ITER toroidal field (TF) strand procurement initiated the largest Nb3Sn superconducting strand production hitherto. The industrial-scale production started in Japan in 2008 and finished in summer 2015. Six ITER partners (so-called Domestic Agencies, or DAs) are in charge of the procurement and involved eight different strand suppliers all over the world, of which four are using the bronze route (BR) process and four the internal-tin (IT) process. In total more than 500 tons have been produced including excess material covering losses during the conductor manufacturing process, in particular the cabling. The procurement is based on a functional specification where the main strand requirements like critical current, hysteresis losses, Cu ratio and residual resistance ratio are specified but not the strand production process or layout. This paper presents the analysis on the data acquired during the quality control (QC) process that was carried out to ensure the same conductor performance requirements are met by the different strand suppliers regardless of strand design. The strand QC is based on 100% billet testing and on applying statistical process control (SPC) limits. Throughout the production, samples adjacent to the strand pieces tested by the suppliers are cross-checked (‘verified’) by their respective DAs reference labs. The level of verification was lowered from 100% at the beginning of the procurement progressively to approximately 25% during the final phase of production. Based on the complete dataset of the TF strand production, an analysis of the SPC limits of the critical strand parameters is made and the related process capability indices are calculated. In view of the large-scale production and costs, key manufacturing parameters such as billet yield, number of breakages and piece-length distribution are also discussed. The results are compared among all the strand suppliers, focusing on the difference between BR and IT processes. Following the completion of the largest Nb3Sn strand production, our experience gained from monitoring the execution of the QC activities and from auditing the results from the measurements is summarised for future superconducting strand material procurement activities.

New-Sum: A Novel Online ABFT Scheme For General Iterative Methods

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

Tao, Dingwen; Song, Shuaiwen; Krishnamoorthy, Sriram

Emerging high-performance computing platforms, with large component counts and lower power margins, are anticipated to be more susceptible to soft errors in both logic circuits and memory subsystems. We present an online algorithm-based fault tolerance (ABFT) approach to efficiently detect and recover soft errors for general iterative methods. We design a novel checksum-based encoding scheme for matrix-vector multiplication that is resilient to both arithmetic and memory errors. Our design decouples the checksum updating process from the actual computation, and allows adaptive checksum overhead control. Building on this new encoding mechanism, we propose two online ABFT designs that can effectively recovermore » from errors when combined with a checkpoint/rollback scheme.« less

Feature Based Retention Time Alignment for Improved HDX MS Analysis

NASA Astrophysics Data System (ADS)

Venable, John D.; Scuba, William; Brock, Ansgar

2013-04-01

An algorithm for retention time alignment of mass shifted hydrogen-deuterium exchange (HDX) data based on an iterative distance minimization procedure is described. The algorithm performs pairwise comparisons in an iterative fashion between a list of features from a reference file and a file to be time aligned to calculate a retention time mapping function. Features are characterized by their charge, retention time and mass of the monoisotopic peak. The algorithm is able to align datasets with mass shifted features, which is a prerequisite for aligning hydrogen-deuterium exchange mass spectrometry datasets. Confidence assignments from the fully automated processing of a commercial HDX software package are shown to benefit significantly from retention time alignment prior to extraction of deuterium incorporation values.

Comparison of sorting algorithms to increase the range of Hartmann-Shack aberrometry.

PubMed

Bedggood, Phillip; Metha, Andrew

2010-01-01

Recently many software-based approaches have been suggested for improving the range and accuracy of Hartmann-Shack aberrometry. We compare the performance of four representative algorithms, with a focus on aberrometry for the human eye. Algorithms vary in complexity from the simplistic traditional approach to iterative spline extrapolation based on prior spot measurements. Range is assessed for a variety of aberration types in isolation using computer modeling, and also for complex wavefront shapes using a real adaptive optics system. The effects of common sources of error for ocular wavefront sensing are explored. The results show that the simplest possible iterative algorithm produces comparable range and robustness compared to the more complicated algorithms, while keeping processing time minimal to afford real-time analysis.

Comparison of sorting algorithms to increase the range of Hartmann-Shack aberrometry

NASA Astrophysics Data System (ADS)

Bedggood, Phillip; Metha, Andrew

2010-11-01

Recently many software-based approaches have been suggested for improving the range and accuracy of Hartmann-Shack aberrometry. We compare the performance of four representative algorithms, with a focus on aberrometry for the human eye. Algorithms vary in complexity from the simplistic traditional approach to iterative spline extrapolation based on prior spot measurements. Range is assessed for a variety of aberration types in isolation using computer modeling, and also for complex wavefront shapes using a real adaptive optics system. The effects of common sources of error for ocular wavefront sensing are explored. The results show that the simplest possible iterative algorithm produces comparable range and robustness compared to the more complicated algorithms, while keeping processing time minimal to afford real-time analysis.

The Research of Multiple Attenuation Based on Feedback Iteration and Independent Component Analysis

NASA Astrophysics Data System (ADS)

Xu, X.; Tong, S.; Wang, L.

2017-12-01

How to solve the problem of multiple suppression is a difficult problem in seismic data processing. The traditional technology for multiple attenuation is based on the principle of the minimum output energy of the seismic signal, this criterion is based on the second order statistics, and it can't achieve the multiple attenuation when the primaries and multiples are non-orthogonal. In order to solve the above problems, we combine the feedback iteration method based on the wave equation and the improved independent component analysis (ICA) based on high order statistics to suppress the multiple waves. We first use iterative feedback method to predict the free surface multiples of each order. Then, in order to predict multiples from real multiple in amplitude and phase, we design an expanded pseudo multi-channel matching filtering method to get a more accurate matching multiple result. Finally, we present the improved fast ICA algorithm which is based on the maximum non-Gauss criterion of output signal to the matching multiples and get better separation results of the primaries and the multiples. The advantage of our method is that we don't need any priori information to the prediction of the multiples, and can have a better separation result. The method has been applied to several synthetic data generated by finite-difference model technique and the Sigsbee2B model multiple data, the primaries and multiples are non-orthogonal in these models. The experiments show that after three to four iterations, we can get the perfect multiple results. Using our matching method and Fast ICA adaptive multiple subtraction, we can not only effectively preserve the effective wave energy in seismic records, but also can effectively suppress the free surface multiples, especially the multiples related to the middle and deep areas.

Stability of Mixed-Strategy-Based Iterative Logit Quantal Response Dynamics in Game Theory

PubMed Central

Zhuang, Qian; Di, Zengru; Wu, Jinshan

2014-01-01

Using the Logit quantal response form as the response function in each step, the original definition of static quantal response equilibrium (QRE) is extended into an iterative evolution process. QREs remain as the fixed points of the dynamic process. However, depending on whether such fixed points are the long-term solutions of the dynamic process, they can be classified into stable (SQREs) and unstable (USQREs) equilibriums. This extension resembles the extension from static Nash equilibriums (NEs) to evolutionary stable solutions in the framework of evolutionary game theory. The relation between SQREs and other solution concepts of games, including NEs and QREs, is discussed. Using experimental data from other published papers, we perform a preliminary comparison between SQREs, NEs, QREs and the observed behavioral outcomes of those experiments. For certain games, we determine that SQREs have better predictive power than QREs and NEs. PMID:25157502

A blind deconvolution method based on L1/L2 regularization prior in the gradient space

NASA Astrophysics Data System (ADS)

Cai, Ying; Shi, Yu; Hua, Xia

2018-02-01

In the process of image restoration, the result of image restoration is very different from the real image because of the existence of noise, in order to solve the ill posed problem in image restoration, a blind deconvolution method based on L1/L2 regularization prior to gradient domain is proposed. The method presented in this paper first adds a function to the prior knowledge, which is the ratio of the L1 norm to the L2 norm, and takes the function as the penalty term in the high frequency domain of the image. Then, the function is iteratively updated, and the iterative shrinkage threshold algorithm is applied to solve the high frequency image. In this paper, it is considered that the information in the gradient domain is better for the estimation of blur kernel, so the blur kernel is estimated in the gradient domain. This problem can be quickly implemented in the frequency domain by fast Fast Fourier Transform. In addition, in order to improve the effectiveness of the algorithm, we have added a multi-scale iterative optimization method. This paper proposes the blind deconvolution method based on L1/L2 regularization priors in the gradient space can obtain the unique and stable solution in the process of image restoration, which not only keeps the edges and details of the image, but also ensures the accuracy of the results.

Using Analytics to Transform a Problem-Based Case Library: An Educational Design Research Approach

ERIC Educational Resources Information Center

Schmidt, Matthew; Tawfik, Andrew A.

2018-01-01

This article describes the iterative design, development, and evaluation of a case-based learning environment focusing on an ill-structured sales management problem. We discuss our processes and situate them within the broader framework of educational design research. The learning environment evolved over the course of three design phases. A…

Enhancement Process of Didactic Strategies in a Degree Course for Pre-Service Teachers

ERIC Educational Resources Information Center

Garcias, Adolfina Pérez; Marín, Victoria I.

2017-01-01

This paper presents a study on the enhancement of didactic strategies based on the idea of personal learning environments (PLE). It was conducted through three iterative cycles during three consecutive academic years according to the phases of design-based research applied to teaching in a university course for pre-service teachers in the…

Using Design-Based Research in Informal Environments

ERIC Educational Resources Information Center

Reisman, Molly

2008-01-01

Design-Based Research (DBR) has been a tool of the learning sciences since the early 1990s, used as a way to improve and study learning environments. Using an iterative process of design with the goal of reining theories of learning, researchers and educators now use DBR seek to identify "how" to make a learning environment work. They then draw…

Computer-Supported Team-Based Learning: The Impact of Motivation, Enjoyment and Team Contributions on Learning Outcomes

ERIC Educational Resources Information Center

Gomez, Elizabeth Avery; Wu, Dezhi; Passerini, Katia

2010-01-01

The benefits of teamwork and collaboration have long been advocated by many educational theories, such as constructivist and social learning models. Among the various applications of collaborative learning, the iterative team-based learning (TBL) process proposed by Michaelsen, Fink, and Knight (2002) has been successfully used in the classroom…

A novel partial volume effects correction technique integrating deconvolution associated with denoising within an iterative PET image reconstruction

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

Merlin, Thibaut, E-mail: thibaut.merlin@telecom-bretagne.eu; Visvikis, Dimitris; Fernandez, Philippe

2015-02-15

Purpose: Partial volume effect (PVE) plays an important role in both qualitative and quantitative PET image accuracy, especially for small structures. A previously proposed voxelwise PVE correction method applied on PET reconstructed images involves the use of Lucy–Richardson deconvolution incorporating wavelet-based denoising to limit the associated propagation of noise. The aim of this study is to incorporate the deconvolution, coupled with the denoising step, directly inside the iterative reconstruction process to further improve PVE correction. Methods: The list-mode ordered subset expectation maximization (OSEM) algorithm has been modified accordingly with the application of the Lucy–Richardson deconvolution algorithm to the current estimationmore » of the image, at each reconstruction iteration. Acquisitions of the NEMA NU2-2001 IQ phantom were performed on a GE DRX PET/CT system to study the impact of incorporating the deconvolution inside the reconstruction [with and without the point spread function (PSF) model] in comparison to its application postreconstruction and to standard iterative reconstruction incorporating the PSF model. The impact of the denoising step was also evaluated. Images were semiquantitatively assessed by studying the trade-off between the intensity recovery and the noise level in the background estimated as relative standard deviation. Qualitative assessments of the developed methods were additionally performed on clinical cases. Results: Incorporating the deconvolution without denoising within the reconstruction achieved superior intensity recovery in comparison to both standard OSEM reconstruction integrating a PSF model and application of the deconvolution algorithm in a postreconstruction process. The addition of the denoising step permitted to limit the SNR degradation while preserving the intensity recovery. Conclusions: This study demonstrates the feasibility of incorporating the Lucy–Richardson deconvolution associated with a wavelet-based denoising in the reconstruction process to better correct for PVE. Future work includes further evaluations of the proposed method on clinical datasets and the use of improved PSF models.« less

Hardware architecture design of image restoration based on time-frequency domain computation

NASA Astrophysics Data System (ADS)

Wen, Bo; Zhang, Jing; Jiao, Zipeng

2013-10-01

The image restoration algorithms based on time-frequency domain computation is high maturity and applied widely in engineering. To solve the high-speed implementation of these algorithms, the TFDC hardware architecture is proposed. Firstly, the main module is designed, by analyzing the common processing and numerical calculation. Then, to improve the commonality, the iteration control module is planed for iterative algorithms. In addition, to reduce the computational cost and memory requirements, the necessary optimizations are suggested for the time-consuming module, which include two-dimensional FFT/IFFT and the plural calculation. Eventually, the TFDC hardware architecture is adopted for hardware design of real-time image restoration system. The result proves that, the TFDC hardware architecture and its optimizations can be applied to image restoration algorithms based on TFDC, with good algorithm commonality, hardware realizability and high efficiency.

An iterative learning strategy for the auto-tuning of the feedforward and feedback controller in type-1 diabetes.

PubMed

Fravolini, M L; Fabietti, P G

2014-01-01

This paper proposes a scheme for the control of the blood glucose in subjects with type-1 diabetes mellitus based on the subcutaneous (s.c.) glucose measurement and s.c. insulin administration. The tuning of the controller is based on an iterative learning strategy that exploits the repetitiveness of the daily feeding habit of a patient. The control consists of a mixed feedback and feedforward contribution whose parameters are tuned through an iterative learning process that is based on the day-by-day automated analysis of the glucose response to the infusion of exogenous insulin. The scheme does not require any a priori information on the patient insulin/glucose response, on the meal times and on the amount of ingested carbohydrates (CHOs). Thanks to the learning mechanism the scheme is able to improve its performance over time. A specific logic is also introduced for the detection and prevention of possible hypoglycaemia events. The effectiveness of the methodology has been validated using long-term simulation studies applied to a set of nine in silico patients considering realistic uncertainties on the meal times and on the quantities of ingested CHOs.

On the solution of evolution equations based on multigrid and explicit iterative methods

NASA Astrophysics Data System (ADS)

Zhukov, V. T.; Novikova, N. D.; Feodoritova, O. B.

2015-08-01

Two schemes for solving initial-boundary value problems for three-dimensional parabolic equations are studied. One is implicit and is solved using the multigrid method, while the other is explicit iterative and is based on optimal properties of the Chebyshev polynomials. In the explicit iterative scheme, the number of iteration steps and the iteration parameters are chosen as based on the approximation and stability conditions, rather than on the optimization of iteration convergence to the solution of the implicit scheme. The features of the multigrid scheme include the implementation of the intergrid transfer operators for the case of discontinuous coefficients in the equation and the adaptation of the smoothing procedure to the spectrum of the difference operators. The results produced by these schemes as applied to model problems with anisotropic discontinuous coefficients are compared.

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.

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.

FBILI method for multi-level line transfer

NASA Astrophysics Data System (ADS)

Kuzmanovska, O.; Atanacković, O.; Faurobert, M.

2017-07-01

Efficient non-LTE multilevel radiative transfer calculations are needed for a proper interpretation of astrophysical spectra. In particular, realistic simulations of time-dependent processes or multi-dimensional phenomena require that the iterative method used to solve such non-linear and non-local problem is as fast as possible. There are several multilevel codes based on efficient iterative schemes that provide a very high convergence rate, especially when combined with mathematical acceleration techniques. The Forth-and-Back Implicit Lambda Iteration (FBILI) developed by Atanacković-Vukmanović et al. [1] is a Gauss-Seidel-type iterative scheme that is characterized by a very high convergence rate without the need of complementing it with additional acceleration techniques. In this paper we make the implementation of the FBILI method to the multilevel atom line transfer in 1D more explicit. We also consider some of its variants and investigate their convergence properties by solving the benchmark problem of CaII line formation in the solar atmosphere. Finally, we compare our solutions with results obtained with the well known code MULTI.

APPROACH TO "FURTHER-REASONABLE-PROGRESS" TO ATTAIN WATER QUALITY STANDARDS

EPA Science Inventory

Watershed managers in urban areas in the US are pursuing optimum strategies or plans for managing wastewater treatment plants, stormwater systems, sanitary sewer overflows (SSO) and combined sewer overflows (CSO). Often these strategies are based on an iterative process or a "fur...

APPROACH TO "FURTHER-REASONABLE-PROGRESS" TO ATTAIN WATER QUALITY STANDARDS

EPA Science Inventory

Watershed managers in urban areas in the US are pursuing optimum strategies or plans for managing wastewater treatment plants, stormwater systems, sanitary sewer overflows (SSO) and combined sewer overflows (CSO). Often thes strategies are based on an iterative process or a "furt...

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.

Low-light-level image super-resolution reconstruction based on iterative projection photon localization algorithm

NASA Astrophysics Data System (ADS)

Ying, Changsheng; Zhao, Peng; Li, Ye

2018-01-01

The intensified charge-coupled device (ICCD) is widely used in the field of low-light-level (LLL) imaging. The LLL images captured by ICCD suffer from low spatial resolution and contrast, and the target details can hardly be recognized. Super-resolution (SR) reconstruction of LLL images captured by ICCDs is a challenging issue. The dispersion in the double-proximity-focused image intensifier is the main factor that leads to a reduction in image resolution and contrast. We divide the integration time into subintervals that are short enough to get photon images, so the overlapping effect and overstacking effect of dispersion can be eliminated. We propose an SR reconstruction algorithm based on iterative projection photon localization. In the iterative process, the photon image is sliced by projection planes, and photons are screened under the constraints of regularity. The accurate position information of the incident photons in the reconstructed SR image is obtained by the weighted centroids calculation. The experimental results show that the spatial resolution and contrast of our SR image are significantly improved.

Composition of Web Services Using Markov Decision Processes and Dynamic Programming

PubMed Central

Uc-Cetina, Víctor; Moo-Mena, Francisco; Hernandez-Ucan, Rafael

2015-01-01

We propose a Markov decision process model for solving the Web service composition (WSC) problem. Iterative policy evaluation, value iteration, and policy iteration algorithms are used to experimentally validate our approach, with artificial and real data. The experimental results show the reliability of the model and the methods employed, with policy iteration being the best one in terms of the minimum number of iterations needed to estimate an optimal policy, with the highest Quality of Service attributes. Our experimental work shows how the solution of a WSC problem involving a set of 100,000 individual Web services and where a valid composition requiring the selection of 1,000 services from the available set can be computed in the worst case in less than 200 seconds, using an Intel Core i5 computer with 6 GB RAM. Moreover, a real WSC problem involving only 7 individual Web services requires less than 0.08 seconds, using the same computational power. Finally, a comparison with two popular reinforcement learning algorithms, sarsa and Q-learning, shows that these algorithms require one or two orders of magnitude and more time than policy iteration, iterative policy evaluation, and value iteration to handle WSC problems of the same complexity. PMID:25874247

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.

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

Exploring a New Simulation Approach to Improve Clinical Reasoning Teaching and Assessment: Randomized Trial Protocol

PubMed Central

Moussa, Ahmed; Loye, Nathalie; Charlin, Bernard; Audétat, Marie-Claude

2016-01-01

Background Helping trainees develop appropriate clinical reasoning abilities is a challenging goal in an environment where clinical situations are marked by high levels of complexity and unpredictability. The benefit of simulation-based education to assess clinical reasoning skills has rarely been reported. More specifically, it is unclear if clinical reasoning is better acquired if the instructor's input occurs entirely after or is integrated during the scenario. Based on educational principles of the dual-process theory of clinical reasoning, a new simulation approach called simulation with iterative discussions (SID) is introduced. The instructor interrupts the flow of the scenario at three key moments of the reasoning process (data gathering, integration, and confirmation). After each stop, the scenario is continued where it was interrupted. Finally, a brief general debriefing ends the session. System-1 process of clinical reasoning is assessed by verbalization during management of the case, and System-2 during the iterative discussions without providing feedback. Objective The aim of this study is to evaluate the effectiveness of Simulation with Iterative Discussions versus the classical approach of simulation in developing reasoning skills of General Pediatrics and Neonatal-Perinatal Medicine residents. Methods This will be a prospective exploratory, randomized study conducted at Sainte-Justine hospital in Montreal, Qc, between January and March 2016. All post-graduate year (PGY) 1 to 6 residents will be invited to complete one SID or classical simulation 30 minutes audio video-recorded complex high-fidelity simulations covering a similar neonatology topic. Pre- and post-simulation questionnaires will be completed and a semistructured interview will be conducted after each simulation. Data analyses will use SPSS and NVivo softwares. Results This study is in its preliminary stages and the results are expected to be made available by April, 2016. Conclusions This will be the first study to explore a new simulation approach designed to enhance clinical reasoning. By assessing more closely reasoning processes throughout a simulation session, we believe that Simulation with Iterative Discussions will be an interesting and more effective approach for students. The findings of the study will benefit medical educators, education programs, and medical students. PMID:26888076

Exploring a New Simulation Approach to Improve Clinical Reasoning Teaching and Assessment: Randomized Trial Protocol.

PubMed

Pennaforte, Thomas; Moussa, Ahmed; Loye, Nathalie; Charlin, Bernard; Audétat, Marie-Claude

2016-02-17

Helping trainees develop appropriate clinical reasoning abilities is a challenging goal in an environment where clinical situations are marked by high levels of complexity and unpredictability. The benefit of simulation-based education to assess clinical reasoning skills has rarely been reported. More specifically, it is unclear if clinical reasoning is better acquired if the instructor's input occurs entirely after or is integrated during the scenario. Based on educational principles of the dual-process theory of clinical reasoning, a new simulation approach called simulation with iterative discussions (SID) is introduced. The instructor interrupts the flow of the scenario at three key moments of the reasoning process (data gathering, integration, and confirmation). After each stop, the scenario is continued where it was interrupted. Finally, a brief general debriefing ends the session. System-1 process of clinical reasoning is assessed by verbalization during management of the case, and System-2 during the iterative discussions without providing feedback. The aim of this study is to evaluate the effectiveness of Simulation with Iterative Discussions versus the classical approach of simulation in developing reasoning skills of General Pediatrics and Neonatal-Perinatal Medicine residents. This will be a prospective exploratory, randomized study conducted at Sainte-Justine hospital in Montreal, Qc, between January and March 2016. All post-graduate year (PGY) 1 to 6 residents will be invited to complete one SID or classical simulation 30 minutes audio video-recorded complex high-fidelity simulations covering a similar neonatology topic. Pre- and post-simulation questionnaires will be completed and a semistructured interview will be conducted after each simulation. Data analyses will use SPSS and NVivo softwares. This study is in its preliminary stages and the results are expected to be made available by April, 2016. This will be the first study to explore a new simulation approach designed to enhance clinical reasoning. By assessing more closely reasoning processes throughout a simulation session, we believe that Simulation with Iterative Discussions will be an interesting and more effective approach for students. The findings of the study will benefit medical educators, education programs, and medical students.

Programmable Iterative Optical Image And Data Processing

NASA Technical Reports Server (NTRS)

Jackson, Deborah J.

1995-01-01

Proposed method of iterative optical image and data processing overcomes limitations imposed by loss of optical power after repeated passes through many optical elements - especially, beam splitters. Involves selective, timed combination of optical wavefront phase conjugation and amplification to regenerate images in real time to compensate for losses in optical iteration loops; timing such that amplification turned on to regenerate desired image, then turned off so as not to regenerate other, undesired images or spurious light propagating through loops from unwanted reflections.

Iterative simulated quenching for designing irregular-spot-array generators.

PubMed

Gillet, J N; Sheng, Y

2000-07-10

We propose a novel, to our knowledge, algorithm of iterative simulated quenching with temperature rescaling for designing diffractive optical elements, based on an analogy between simulated annealing and statistical thermodynamics. The temperature is iteratively rescaled at the end of each quenching process according to ensemble statistics to bring the system back from a frozen imperfect state with a local minimum of energy to a dynamic state in a Boltzmann heat bath in thermal equilibrium at the rescaled temperature. The new algorithm achieves much lower cost function and reconstruction error and higher diffraction efficiency than conventional simulated annealing with a fast exponential cooling schedule and is easy to program. The algorithm is used to design binary-phase generators of large irregular spot arrays. The diffractive phase elements have trapezoidal apertures of varying heights, which fit ideal arbitrary-shaped apertures better than do trapezoidal apertures of fixed heights.

A novel dynamical community detection algorithm based on weighting scheme

NASA Astrophysics Data System (ADS)

Li, Ju; Yu, Kai; Hu, Ke

2015-12-01

Network dynamics plays an important role in analyzing the correlation between the function properties and the topological structure. In this paper, we propose a novel dynamical iteration (DI) algorithm, which incorporates the iterative process of membership vector with weighting scheme, i.e. weighting W and tightness T. These new elements can be used to adjust the link strength and the node compactness for improving the speed and accuracy of community structure detection. To estimate the optimal stop time of iteration, we utilize a new stability measure which is defined as the Markov random walk auto-covariance. We do not need to specify the number of communities in advance. It naturally supports the overlapping communities by associating each node with a membership vector describing the node's involvement in each community. Theoretical analysis and experiments show that the algorithm can uncover communities effectively and efficiently.

Quantum-Inspired Multidirectional Associative Memory With a Self-Convergent Iterative Learning.

PubMed

Masuyama, Naoki; Loo, Chu Kiong; Seera, Manjeevan; Kubota, Naoyuki

2018-04-01

Quantum-inspired computing is an emerging research area, which has significantly improved the capabilities of conventional algorithms. In general, quantum-inspired hopfield associative memory (QHAM) has demonstrated quantum information processing in neural structures. This has resulted in an exponential increase in storage capacity while explaining the extensive memory, and it has the potential to illustrate the dynamics of neurons in the human brain when viewed from quantum mechanics perspective although the application of QHAM is limited as an autoassociation. We introduce a quantum-inspired multidirectional associative memory (QMAM) with a one-shot learning model, and QMAM with a self-convergent iterative learning model (IQMAM) based on QHAM in this paper. The self-convergent iterative learning enables the network to progressively develop a resonance state, from inputs to outputs. The simulation experiments demonstrate the advantages of QMAM and IQMAM, especially the stability to recall reliability.

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.

Iterative Design and Testing for the Development of a Game-Based Chlamydia Awareness Intervention: A Pilot Study.

PubMed

Jiang, Rui; McKanna, James; Calabrese, Samantha; Seif El-Nasr, Magy

2017-08-01

Herein we describe a methodology for developing a game-based intervention to raise awareness of Chlamydia and other sexually transmitted infections among youth in Boston's underserved communities. We engaged in three design-based experiments. These utilized mixed methods, including playtesting and assessment methods, to examine the overall effectiveness of the game. In this case, effectiveness is defined as (1) engaging the target group, (2) increasing knowledge about Chlamydia, and (3) changing attitudes toward Chlamydia testing. These three experiments were performed using participants from different communities and with slightly different versions of the game, as we iterated through the design/feedback process. Overall, participants who played the game showed a significant increase in participants' knowledge of Chlamydia compared with those in the control group (P = 0.0002). The version of the game, including elements specifically targeting systemic thinking, showed significant improvement in participants' intent to get tested compared with the version of the game without such elements (Stage 2: P > 0.05; Stage 3: P = 0.0045). Furthermore, during both Stage 2 and Stage 3, participants showed high levels of enjoyment, mood, and participation and moderate levels of game engagement and social engagement. During Stage 3, however, participants' game engagement (P = 0.0003), social engagement (P = 0.0003), and participation (P = 0.0003) were significantly higher compared with those of Stage 2. Thus, we believe that motivation improvements from Stage 2 to 3 were also effective. Finally, participants' overall learning effectiveness was correlated with their prepositive affect (r = 0.52) and their postproblem hierarchy (r = -0.54). The game improved considerably from its initial conception through three stages of iterative design and feedback. Our assessment methods for each stage targeted and integrated learning, health, and engagement outcomes. Lessons learned through this iterative design process are a great contribution to the games for health community, especially in targeting the development of health and learning goals through game design.

Optimal Control of Micro Grid Operation Mode Seamless Switching Based on Radau Allocation Method

NASA Astrophysics Data System (ADS)

Chen, Xiaomin; Wang, Gang

2017-05-01

The seamless switching process of micro grid operation mode directly affects the safety and stability of its operation. According to the switching process from island mode to grid-connected mode of micro grid, we establish a dynamic optimization model based on two grid-connected inverters. We use Radau allocation method to discretize the model, and use Newton iteration method to obtain the optimal solution. Finally, we implement the optimization mode in MATLAB and get the optimal control trajectory of the inverters.

e-Learning Application for Machine Maintenance Process using Iterative Method in XYZ Company

NASA Astrophysics Data System (ADS)

Nurunisa, Suaidah; Kurniawati, Amelia; Pramuditya Soesanto, Rayinda; Yunan Kurnia Septo Hediyanto, Umar

2016-02-01

XYZ Company is a company based on manufacturing part for airplane, one of the machine that is categorized as key facility in the company is Millac 5H6P. As a key facility, the machines should be assured to work well and in peak condition, therefore, maintenance process is needed periodically. From the data gathering, it is known that there are lack of competency from the maintenance staff to maintain different type of machine which is not assigned by the supervisor, this indicate that knowledge which possessed by maintenance staff are uneven. The purpose of this research is to create knowledge-based e-learning application as a realization from externalization process in knowledge transfer process to maintain the machine. The application feature are adjusted for maintenance purpose using e-learning framework for maintenance process, the content of the application support multimedia for learning purpose. QFD is used in this research to understand the needs from user. The application is built using moodle with iterative method for software development cycle and UML Diagram. The result from this research is e-learning application as sharing knowledge media for maintenance staff in the company. From the test, it is known that the application make maintenance staff easy to understand the competencies.

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.

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

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.

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.

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.

Status of the Negative Ion Based Heating and Diagnostic Neutral Beams for ITER

NASA Astrophysics Data System (ADS)

Schunke, B.; Bora, D.; Hemsworth, R.; Tanga, A.

2009-03-01

The current baseline of ITER foresees 2 Heating Neutral Beam (HNB's) systems based on negative ion technology, each accelerating to 1 MeV 40 A of D- and capable of delivering 16.5 MW of D0 to the ITER plasma, with a 3rd HNB injector foreseen as an upgrade option [1]. In addition a dedicated Diagnostic Neutral Beam (DNB) accelerating 60 A of H- to 100 keV will inject ≈15 A equivalent of H0 for charge exchange recombination spectroscopy and other diagnostics. Recently the RF driven negative ion source developed by IPP Garching has replaced the filamented ion source as the reference ITER design. The RF source developed at IPP, which is approximately a quarter scale of the source needed for ITER, is expected to have reduced caesium consumption compared to the filamented arc driven ion source. The RF driven source has demonstrated adequate accelerated D- and H- current densities as well as long-pulse operation [2, 3]. It is foreseen that the HNB's and the DNB will use the same negative ion source. Experiments with a half ITER-size ion source are on-going at IPP and the operation of a full-scale ion source will be demonstrated, at full power and pulse length, in the dedicated Ion Source Test Bed (ISTF), which will be part of the Neutral Beam Test Facility (NBTF), in Padua, Italy. This facility will carry out the necessary R&D for the HNB's for ITER and demonstrate operation of the full-scale HNB beamline. An overview of the current status of the neutral beam (NB) systems and the chosen configuration will be given and the ongoing integration effort into the ITER plant will be highlighted. It will be demonstrated how installation and maintenance logistics have influenced the design, notably the top access scheme facilitating access for maintenance and installation. The impact of the ITER Design Review and recent design change requests (DCRs) will be briefly discussed, including start-up and commissioning issues. The low current hydrogen phase now envisaged for start-up imposed specific requirements for operating the HNB's at full beam power. It has been decided to address the shinethrough issue by installing wall armour protection, which increases the operational space in all scenarios. Other NB related issues identified by the Design Review process will be discussed and the possible changes to the ITER baseline indicated.

Status of the Negative Ion Based Heating and Diagnostic Neutral Beams for ITER

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

Schunke, B.; Bora, D.; Hemsworth, R.

2009-03-12

The current baseline of ITER foresees 2 Heating Neutral Beam (HNB's) systems based on negative ion technology, each accelerating to 1 MeV 40 A of D{sup -} and capable of delivering 16.5 MW of D{sup 0} to the ITER plasma, with a 3rd HNB injector foreseen as an upgrade option. In addition a dedicated Diagnostic Neutral Beam (DNB) accelerating 60 A of H{sup -} to 100 keV will inject {approx_equal}15 A equivalent of H{sup 0} for charge exchange recombination spectroscopy and other diagnostics. Recently the RF driven negative ion source developed by IPP Garching has replaced the filamented ion sourcemore » as the reference ITER design. The RF source developed at IPP, which is approximately a quarter scale of the source needed for ITER, is expected to have reduced caesium consumption compared to the filamented arc driven ion source. The RF driven source has demonstrated adequate accelerated D{sup -} and H{sup -} current densities as well as long-pulse operation. It is foreseen that the HNB's and the DNB will use the same negative ion source. Experiments with a half ITER-size ion source are on-going at IPP and the operation of a full-scale ion source will be demonstrated, at full power and pulse length, in the dedicated Ion Source Test Bed (ISTF), which will be part of the Neutral Beam Test Facility (NBTF), in Padua, Italy. This facility will carry out the necessary R and D for the HNB's for ITER and demonstrate operation of the full-scale HNB beamline. An overview of the current status of the neutral beam (NB) systems and the chosen configuration will be given and the ongoing integration effort into the ITER plant will be highlighted. It will be demonstrated how installation and maintenance logistics have influenced the design, notably the top access scheme facilitating access for maintenance and installation. The impact of the ITER Design Review and recent design change requests (DCRs) will be briefly discussed, including start-up and commissioning issues. The low current hydrogen phase now envisaged for start-up imposed specific requirements for operating the HNB's at full beam power. It has been decided to address the shinethrough issue by installing wall armour protection, which increases the operational space in all scenarios. Other NB related issues identified by the Design Review process will be discussed and the possible changes to the ITER baseline indicated.« less

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.

Design of robust iterative learning control schemes for systems with polytopic uncertainties and sector-bounded nonlinearities

NASA Astrophysics Data System (ADS)

Boski, Marcin; Paszke, Wojciech

2017-01-01

This paper deals with designing of iterative learning control schemes for uncertain systems with static nonlinearities. More specifically, the nonlinear part is supposed to be sector bounded and system matrices are assumed to range in the polytope of matrices. For systems with such nonlinearities and uncertainties the repetitive process setting is exploited to develop a linear matrix inequality based conditions for computing the feedback and feedforward (learning) controllers. These controllers guarantee acceptable dynamics along the trials and ensure convergence of the trial-to-trial error dynamics, respectively. Numerical examples illustrate the theoretical results and confirm effectiveness of the designed control scheme.

Low cost solar array project: Experimental process system development unit for producing semiconductor-grade silicon using silane-to-silicon process

NASA Technical Reports Server (NTRS)

1980-01-01

The design, fabrication, and installation of an experimental process system development unit (EPSDU) were analyzed. Supporting research and development were performed to provide an information data base usable for the EPSDU and for technological design and economical analysis for potential scale-up of the process. Iterative economic analyses were conducted for the estimated product cost for the production of semiconductor grade silicon in a facility capable of producing 1000-MT/Yr.

3D algebraic iterative reconstruction for cone-beam x-ray differential phase-contrast computed tomography.

PubMed

Fu, Jian; Hu, Xinhua; Velroyen, Astrid; Bech, Martin; Jiang, Ming; Pfeiffer, Franz

2015-01-01

Due to the potential of compact imaging systems with magnified spatial resolution and contrast, cone-beam x-ray differential phase-contrast computed tomography (DPC-CT) has attracted significant interest. The current proposed FDK reconstruction algorithm with the Hilbert imaginary filter will induce severe cone-beam artifacts when the cone-beam angle becomes large. In this paper, we propose an algebraic iterative reconstruction (AIR) method for cone-beam DPC-CT and report its experiment results. This approach considers the reconstruction process as the optimization of a discrete representation of the object function to satisfy a system of equations that describes the cone-beam DPC-CT imaging modality. Unlike the conventional iterative algorithms for absorption-based CT, it involves the derivative operation to the forward projections of the reconstructed intermediate image to take into account the differential nature of the DPC projections. This method is based on the algebraic reconstruction technique, reconstructs the image ray by ray, and is expected to provide better derivative estimates in iterations. This work comprises a numerical study of the algorithm and its experimental verification using a dataset measured with a three-grating interferometer and a mini-focus x-ray tube source. It is shown that the proposed method can reduce the cone-beam artifacts and performs better than FDK under large cone-beam angles. This algorithm is of interest for future cone-beam DPC-CT applications.

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.

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.

The Knowledge-Based Software Assistant: Beyond CASE

NASA Technical Reports Server (NTRS)

Carozzoni, Joseph A.

1993-01-01

This paper will outline the similarities and differences between two paradigms of software development. Both support the whole software life cycle and provide automation for most of the software development process, but have different approaches. The CASE approach is based on a set of tools linked by a central data repository. This tool-based approach is data driven and views software development as a series of sequential steps, each resulting in a product. The Knowledge-Based Software Assistant (KBSA) approach, a radical departure from existing software development practices, is knowledge driven and centers around a formalized software development process. KBSA views software development as an incremental, iterative, and evolutionary process with development occurring at the specification level.

Modified multiblock partial least squares path modeling algorithm with backpropagation neural networks approach

NASA Astrophysics Data System (ADS)

Yuniarto, Budi; Kurniawan, Robert

2017-03-01

PLS Path Modeling (PLS-PM) is different from covariance based SEM, where PLS-PM use an approach based on variance or component, therefore, PLS-PM is also known as a component based SEM. Multiblock Partial Least Squares (MBPLS) is a method in PLS regression which can be used in PLS Path Modeling which known as Multiblock PLS Path Modeling (MBPLS-PM). This method uses an iterative procedure in its algorithm. This research aims to modify MBPLS-PM with Back Propagation Neural Network approach. The result is MBPLS-PM algorithm can be modified using the Back Propagation Neural Network approach to replace the iterative process in backward and forward step to get the matrix t and the matrix u in the algorithm. By modifying the MBPLS-PM algorithm using Back Propagation Neural Network approach, the model parameters obtained are relatively not significantly different compared to model parameters obtained by original MBPLS-PM algorithm.

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,…

New methods of testing nonlinear hypothesis using iterative NLLS estimator

NASA Astrophysics Data System (ADS)

Mahaboob, B.; Venkateswarlu, B.; Mokeshrayalu, G.; Balasiddamuni, P.

2017-11-01

This research paper discusses the method of testing nonlinear hypothesis using iterative Nonlinear Least Squares (NLLS) estimator. Takeshi Amemiya [1] explained this method. However in the present research paper, a modified Wald test statistic due to Engle, Robert [6] is proposed to test the nonlinear hypothesis using iterative NLLS estimator. An alternative method for testing nonlinear hypothesis using iterative NLLS estimator based on nonlinear hypothesis using iterative NLLS estimator based on nonlinear studentized residuals has been proposed. In this research article an innovative method of testing nonlinear hypothesis using iterative restricted NLLS estimator is derived. Pesaran and Deaton [10] explained the methods of testing nonlinear hypothesis. This paper uses asymptotic properties of nonlinear least squares estimator proposed by Jenrich [8]. The main purpose of this paper is to provide very innovative methods of testing nonlinear hypothesis using iterative NLLS estimator, iterative NLLS estimator based on nonlinear studentized residuals and iterative restricted NLLS estimator. Eakambaram et al. [12] discussed least absolute deviation estimations versus nonlinear regression model with heteroscedastic errors and also they studied the problem of heteroscedasticity with reference to nonlinear regression models with suitable illustration. William Grene [13] examined the interaction effect in nonlinear models disused by Ai and Norton [14] and suggested ways to examine the effects that do not involve statistical testing. Peter [15] provided guidelines for identifying composite hypothesis and addressing the probability of false rejection for multiple hypotheses.

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.

Teaching Engineering Design Through Paper Rockets

ERIC Educational Resources Information Center

Welling, Jonathan; Wright, Geoffrey A.

2018-01-01

The paper rocket activity described in this article effectively teaches the engineering design process (EDP) by engaging students in a problem-based learning activity that encourages iterative design. For example, the first rockets the students build typically only fly between 30 and 100 feet. As students test and evaluate their rocket designs,…

Maintaining Web-based Bibliographies: A Case Study of Iter, the Bibliography of Renaissance Europe.

ERIC Educational Resources Information Center

Castell, Tracy

1997-01-01

Introduces Iter, a nonprofit research project developed for the World Wide Web and dedicated to increasing access to all published materials pertaining to the Renaissance and, eventually, the Middle Ages. Discusses information management issues related to building and maintaining Iter's first Web-based bibliography, focusing on printed secondary…

Electron Beam Welding: study of process capability and limitations towards development of nuclear components

NASA Astrophysics Data System (ADS)

Vadolia, Gautam R.; Premjit Singh, K.

2017-04-01

Electron Beam Welding (EBW) technology is an established and widely adopted technique in nuclear research and development area. Electron beam welding was thought of as a candidate process for ITER Vacuum Vessel Fabrication. Dhruva Reactor at BARC, Mumbai and Niobium superconducting accelerator cavity at BARC has adopted the EB welding technique as a fabrication route. Study of process capability and limitations based on available literature is consolidated in this short review paper.

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.

Development of a practice-based research program.

PubMed

Hawk, C; Long, C R; Boulanger, K

1998-01-01

To establish an infrastructure to collect accurate data from ambulatory settings. The program was developed through an iterative model governed by a process of formative evaluation. The three iterations were a needs assessment, feasibility study and pilot project. Necessary program components were identified as infrastructure, practitioner-researcher partnership, centralized data management and standardized quality assurance measures. Volunteer chiropractors and their staff collected data on patients in their practices in ambulatory settings in the U.S. and Canada. Evaluative measures were counts of participants, patients and completed forms. Standardized, validated and reliable measures collected by patient self-report were used to assess treatment outcomes. These included the SF-36 or SF-12 Health Survey, the Pain Disability Index, and the Global Well-Being Scale. For characteristics for which appropriate standardized instruments were not available, questionnaires were designed and and pilot-tested before use. Information was gathered on practice and patient characteristics and treatment outcomes, but for this report, only those data concerning process evaluation are reported. Through the three program iterations, 65 DCs collected data on 1360 patients, 663 of whom were new patients. Follow-up data recorded by doctors were obtained for more than 70% of patients; a maximum of 50% of patient-completed follow-up forms were collected in the three iterations. This program is capable of providing data for descriptive epidemiology of ambulatory patients, and, with continued effort to maximize follow-up, may have utility in providing insight into utilization patterns and patient outcomes.

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.

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.

Low pressure and high power rf sources for negative hydrogen ions for fusion applications (ITER neutral beam injection).

PubMed

Fantz, U; Franzen, P; Kraus, W; Falter, H D; Berger, M; Christ-Koch, S; Fröschle, M; Gutser, R; Heinemann, B; Martens, C; McNeely, P; Riedl, R; Speth, E; Wünderlich, D

2008-02-01

The international fusion experiment ITER requires for the plasma heating and current drive a neutral beam injection system based on negative hydrogen ion sources at 0.3 Pa. The ion source must deliver a current of 40 A D(-) for up to 1 h with an accelerated current density of 200 Am/(2) and a ratio of coextracted electrons to ions below 1. The extraction area is 0.2 m(2) from an aperture array with an envelope of 1.5 x 0.6 m(2). A high power rf-driven negative ion source has been successfully developed at the Max-Planck Institute for Plasma Physics (IPP) at three test facilities in parallel. Current densities of 330 and 230 Am/(2) have been achieved for hydrogen and deuterium, respectively, at a pressure of 0.3 Pa and an electron/ion ratio below 1 for a small extraction area (0.007 m(2)) and short pulses (<4 s). In the long pulse experiment, equipped with an extraction area of 0.02 m(2), the pulse length has been extended to 3600 s. A large rf source, with the width and half the height of the ITER source but without extraction system, is intended to demonstrate the size scaling and plasma homogeneity of rf ion sources. The source operates routinely now. First results on plasma homogeneity obtained from optical emission spectroscopy and Langmuir probes are very promising. Based on the success of the IPP development program, the high power rf-driven negative ion source has been chosen recently for the ITER beam systems in the ITER design review process.

An iterative method for the Helmholtz equation

NASA Technical Reports Server (NTRS)

Bayliss, A.; Goldstein, C. I.; Turkel, E.

1983-01-01

An iterative algorithm for the solution of the Helmholtz equation is developed. The algorithm is based on a preconditioned conjugate gradient iteration for the normal equations. The preconditioning is based on an SSOR sweep for the discrete Laplacian. Numerical results are presented for a wide variety of problems of physical interest and demonstrate the effectiveness of the algorithm.

Semi-Technical Cryogenic Molecular Sieve Bed for the Tritium Extraction System of the Test Blanket Module for ITER

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

Beloglazov, S.; Bekris, N.; Glugla, M.

2005-07-15

The tritium extraction from the ITER Helium Cooled Pebble Bed (HCPB) Test Blanket Module purge gas is proposed to be performed in a two steps process: trapping water in a cryogenic Cold Trap, and adsorption of hydrogen isotopes (H{sub 2}, HT, T{sub 2}) as well as impurities (N{sub 2}, O{sub 2}) in a Cryogenic Molecular Sieve Bed (CMSB) at 77K. A CMSB in a semi-technical scale (one-sixth of the flow rate of the ITER-HCPB) was design and constructed at the Forschungszentrum Karlsruhe. The full capacity of CMSB filled with 20 kg of MS-5A was calculated based on adsorption isotherm datamore » to be 9.4 mol of H{sub 2} at partial pressure 120 Pa. The breakthrough tests at flow rates up to 2 Nm{sup 3}h{sup -1} of He with 110 Pa of H{sub 2} conformed with good agreement the adsorption capacity of the CMSB. The mass-transfer zone was found to be relatively narrow (12.5 % of the MS Bed height) allowing to scale up the CMSB to ITER flow rates.« less

Inverse imaging of the breast with a material classification technique.

PubMed

Manry, C W; Broschat, S L

1998-03-01

In recent publications [Chew et al., IEEE Trans. Blomed. Eng. BME-9, 218-225 (1990); Borup et al., Ultrason. Imaging 14, 69-85 (1992)] the inverse imaging problem has been solved by means of a two-step iterative method. In this paper, a third step is introduced for ultrasound imaging of the breast. In this step, which is based on statistical pattern recognition, classification of tissue types and a priori knowledge of the anatomy of the breast are integrated into the iterative method. Use of this material classification technique results in more rapid convergence to the inverse solution--approximately 40% fewer iterations are required--as well as greater accuracy. In addition, tumors are detected early in the reconstruction process. Results for reconstructions of a simple two-dimensional model of the human breast are presented. These reconstructions are extremely accurate when system noise and variations in tissue parameters are not too great. However, for the algorithm used, degradation of the reconstructions and divergence from the correct solution occur when system noise and variations in parameters exceed threshold values. Even in this case, however, tumors are still identified within a few iterations.

Iterative Nonlinear Tikhonov Algorithm with Constraints for Electromagnetic Tomography

NASA Technical Reports Server (NTRS)

Xu, Feng; Deshpande, Manohar

2012-01-01

Low frequency electromagnetic tomography such as the capacitance tomography (ECT) has been proposed for monitoring and mass-gauging of gas-liquid two-phase system under microgravity condition in NASA's future long-term space missions. Due to the ill-posed inverse problem of ECT, images reconstructed using conventional linear algorithms often suffer from limitations such as low resolution and blurred edges. Hence, new efficient high resolution nonlinear imaging algorithms are needed for accurate two-phase imaging. The proposed Iterative Nonlinear Tikhonov Regularized Algorithm with Constraints (INTAC) is based on an efficient finite element method (FEM) forward model of quasi-static electromagnetic problem. It iteratively minimizes the discrepancy between FEM simulated and actual measured capacitances by adjusting the reconstructed image using the Tikhonov regularized method. More importantly, it enforces the known permittivity of two phases to the unknown pixels which exceed the reasonable range of permittivity in each iteration. This strategy does not only stabilize the converging process, but also produces sharper images. Simulations show that resolution improvement of over 2 times can be achieved by INTAC with respect to conventional approaches. Strategies to further improve spatial imaging resolution are suggested, as well as techniques to accelerate nonlinear forward model and thus increase the temporal resolution.

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.

The Depression Inventory Development Workgroup: A Collaborative, Empirically Driven Initiative to Develop a New Assessment Tool for Major Depressive Disorder.

PubMed

Vaccarino, Anthony L; Evans, Kenneth R; Kalali, Amir H; Kennedy, Sidney H; Engelhardt, Nina; Frey, Benicio N; Greist, John H; Kobak, Kenneth A; Lam, Raymond W; MacQueen, Glenda; Milev, Roumen; Placenza, Franca M; Ravindran, Arun V; Sheehan, David V; Sills, Terrence; Williams, Janet B W

2016-01-01

The Depression Inventory Development project is an initiative of the International Society for CNS Drug Development whose goal is to develop a comprehensive and psychometrically sound measurement tool to be utilized as a primary endpoint in clinical trials for major depressive disorder. Using an iterative process between field testing and psychometric analysis and drawing upon expertise of international researchers in depression, the Depression Inventory Development team has established an empirically driven and collaborative protocol for the creation of items to assess symptoms in major depressive disorder. Depression-relevant symptom clusters were identified based on expert clinical and patient input. In addition, as an aid for symptom identification and item construction, the psychometric properties of existing clinical scales (assessing depression and related indications) were evaluated using blinded datasets from pharmaceutical antidepressant drug trials. A series of field tests in patients with major depressive disorder provided the team with data to inform the iterative process of scale development. We report here an overview of the Depression Inventory Development initiative, including results of the third iteration of items assessing symptoms related to anhedonia, cognition, fatigue, general malaise, motivation, anxiety, negative thinking, pain and appetite. The strategies adopted from the Depression Inventory Development program, as an empirically driven and collaborative process for scale development, have provided the foundation to develop and validate measurement tools in other therapeutic areas as well.

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.

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

JWST Wavefront Control Toolbox

NASA Technical Reports Server (NTRS)

Shin, Shahram Ron; Aronstein, David L.

2011-01-01

A Matlab-based toolbox has been developed for the wavefront control and optimization of segmented optical surfaces to correct for possible misalignments of James Webb Space Telescope (JWST) using influence functions. The toolbox employs both iterative and non-iterative methods to converge to an optimal solution by minimizing the cost function. The toolbox could be used in either of constrained and unconstrained optimizations. The control process involves 1 to 7 degrees-of-freedom perturbations per segment of primary mirror in addition to the 5 degrees of freedom of secondary mirror. The toolbox consists of a series of Matlab/Simulink functions and modules, developed based on a "wrapper" approach, that handles the interface and data flow between existing commercial optical modeling software packages such as Zemax and Code V. The limitations of the algorithm are dictated by the constraints of the moving parts in the mirrors.

n-Iterative Exponential Forgetting Factor for EEG Signals Parameter Estimation

PubMed Central

Palma Orozco, Rosaura

2018-01-01

Electroencephalograms (EEG) signals are of interest because of their relationship with physiological activities, allowing a description of motion, speaking, or thinking. Important research has been developed to take advantage of EEG using classification or predictor algorithms based on parameters that help to describe the signal behavior. Thus, great importance should be taken to feature extraction which is complicated for the Parameter Estimation (PE)–System Identification (SI) process. When based on an average approximation, nonstationary characteristics are presented. For PE the comparison of three forms of iterative-recursive uses of the Exponential Forgetting Factor (EFF) combined with a linear function to identify a synthetic stochastic signal is presented. The one with best results seen through the functional error is applied to approximate an EEG signal for a simple classification example, showing the effectiveness of our proposal. PMID:29568310

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.

A clustering-based graph Laplacian framework for value function approximation in reinforcement learning.

PubMed

Xu, Xin; Huang, Zhenhua; Graves, Daniel; Pedrycz, Witold

2014-12-01

In order to deal with the sequential decision problems with large or continuous state spaces, feature representation and function approximation have been a major research topic in reinforcement learning (RL). In this paper, a clustering-based graph Laplacian framework is presented for feature representation and value function approximation (VFA) in RL. By making use of clustering-based techniques, that is, K-means clustering or fuzzy C-means clustering, a graph Laplacian is constructed by subsampling in Markov decision processes (MDPs) with continuous state spaces. The basis functions for VFA can be automatically generated from spectral analysis of the graph Laplacian. The clustering-based graph Laplacian is integrated with a class of approximation policy iteration algorithms called representation policy iteration (RPI) for RL in MDPs with continuous state spaces. Simulation and experimental results show that, compared with previous RPI methods, the proposed approach needs fewer sample points to compute an efficient set of basis functions and the learning control performance can be improved for a variety of parameter settings.

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.

An accelerated photo-magnetic imaging reconstruction algorithm based on an analytical forward solution and a fast Jacobian assembly method

NASA Astrophysics Data System (ADS)

Nouizi, F.; Erkol, H.; Luk, A.; Marks, M.; Unlu, M. B.; Gulsen, G.

2016-10-01

We previously introduced photo-magnetic imaging (PMI), an imaging technique that illuminates the medium under investigation with near-infrared light and measures the induced temperature increase using magnetic resonance thermometry (MRT). Using a multiphysics solver combining photon migration and heat diffusion, PMI models the spatiotemporal distribution of temperature variation and recovers high resolution optical absorption images using these temperature maps. In this paper, we present a new fast non-iterative reconstruction algorithm for PMI. This new algorithm uses analytic methods during the resolution of the forward problem and the assembly of the sensitivity matrix. We validate our new analytic-based algorithm with the first generation finite element method (FEM) based reconstruction algorithm previously developed by our team. The validation is performed using, first synthetic data and afterwards, real MRT measured temperature maps. Our new method accelerates the reconstruction process 30-fold when compared to a single iteration of the FEM-based algorithm.

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.

SU-D-206-03: Segmentation Assisted Fast Iterative Reconstruction Method for Cone-Beam CT

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

Wu, P; Mao, T; Gong, S

2016-06-15

Purpose: Total Variation (TV) based iterative reconstruction (IR) methods enable accurate CT image reconstruction from low-dose measurements with sparse projection acquisition, due to the sparsifiable feature of most CT images using gradient operator. However, conventional solutions require large amount of iterations to generate a decent reconstructed image. One major reason is that the expected piecewise constant property is not taken into consideration at the optimization starting point. In this work, we propose an iterative reconstruction method for cone-beam CT (CBCT) using image segmentation to guide the optimization path more efficiently on the regularization term at the beginning of the optimizationmore » trajectory. Methods: Our method applies general knowledge that one tissue component in the CT image contains relatively uniform distribution of CT number. This general knowledge is incorporated into the proposed reconstruction using image segmentation technique to generate the piecewise constant template on the first-pass low-quality CT image reconstructed using analytical algorithm. The template image is applied as an initial value into the optimization process. Results: The proposed method is evaluated on the Shepp-Logan phantom of low and high noise levels, and a head patient. The number of iterations is reduced by overall 40%. Moreover, our proposed method tends to generate a smoother reconstructed image with the same TV value. Conclusion: We propose a computationally efficient iterative reconstruction method for CBCT imaging. Our method achieves a better optimization trajectory and a faster convergence behavior. It does not rely on prior information and can be readily incorporated into existing iterative reconstruction framework. Our method is thus practical and attractive as a general solution to CBCT iterative reconstruction. This work is supported by the Zhejiang Provincial Natural Science Foundation of China (Grant No. LR16F010001), National High-tech R&D Program for Young Scientists by the Ministry of Science and Technology of China (Grant No. 2015AA020917).« less

Nested Conjugate Gradient Algorithm with Nested Preconditioning for Non-linear Image Restoration.

PubMed

Skariah, Deepak G; Arigovindan, Muthuvel

2017-06-19

We develop a novel optimization algorithm, which we call Nested Non-Linear Conjugate Gradient algorithm (NNCG), for image restoration based on quadratic data fitting and smooth non-quadratic regularization. The algorithm is constructed as a nesting of two conjugate gradient (CG) iterations. The outer iteration is constructed as a preconditioned non-linear CG algorithm; the preconditioning is performed by the inner CG iteration that is linear. The inner CG iteration, which performs preconditioning for outer CG iteration, itself is accelerated by an another FFT based non-iterative preconditioner. We prove that the method converges to a stationary point for both convex and non-convex regularization functionals. We demonstrate experimentally that proposed method outperforms the well-known majorization-minimization method used for convex regularization, and a non-convex inertial-proximal method for non-convex regularization functional.

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.

Simplified Negative Pressure Wound Therapy Device for Application in Low-Resource Settings.

PubMed

Zurovcik, Danielle R; Mody, Gita N; Riviello, Robert; Slocum, Alex

2015-10-01

Negative pressure wound therapy (NPWT) provides proven wound healing benefits and is often a desirable wound treatment methodology. Unfortunately, NPWT devices are not widely available in low-resource settings. To overcome the identified NPWT barriers, a simplified NPWT (sNPWT) system was designed and iteratively improved during field-based testing. The sNPWT technology, our device design iterations, and the design-based results of our field tests are described in this article. The sNPWT system includes a bellows hand pump, an occlusive drape, and a tube with tube connectors, connecting the drape to the pump. The most critical property of an sNPWT system is that it must be airtight. The details of the design iterations, which are needed to achieve an occlusive system, are explained. During the design process, the sNPWT system was tested during the earthquake relief in Haiti. This testing found that a liquid sealant was necessary to seal the drape to the periwound skin. A study conducted in Rwanda verified that a liquid latex sealant was safe to use, and that the tube connector must be connected to the drape with an airtight method during the manufacturing process. This work has shown that sNPWT is feasible in low-resource settings. Since the completion of the clinical testing, the design has been further evolved, and the developers are working with contract manufacturers to produce the final design and preparing for regulatory approval applications.

Emerging Techniques for Dose Optimization in Abdominal CT

PubMed Central

Platt, Joel F.; Goodsitt, Mitchell M.; Al-Hawary, Mahmoud M.; Maturen, Katherine E.; Wasnik, Ashish P.; Pandya, Amit

2014-01-01

Recent advances in computed tomographic (CT) scanning technique such as automated tube current modulation (ATCM), optimized x-ray tube voltage, and better use of iterative image reconstruction have allowed maintenance of good CT image quality with reduced radiation dose. ATCM varies the tube current during scanning to account for differences in patient attenuation, ensuring a more homogeneous image quality, although selection of the appropriate image quality parameter is essential for achieving optimal dose reduction. Reducing the x-ray tube voltage is best suited for evaluating iodinated structures, since the effective energy of the x-ray beam will be closer to the k-edge of iodine, resulting in a higher attenuation for the iodine. The optimal kilovoltage for a CT study should be chosen on the basis of imaging task and patient habitus. The aim of iterative image reconstruction is to identify factors that contribute to noise on CT images with use of statistical models of noise (statistical iterative reconstruction) and selective removal of noise to improve image quality. The degree of noise suppression achieved with statistical iterative reconstruction can be customized to minimize the effect of altered image quality on CT images. Unlike with statistical iterative reconstruction, model-based iterative reconstruction algorithms model both the statistical noise and the physical acquisition process, allowing CT to be performed with further reduction in radiation dose without an increase in image noise or loss of spatial resolution. Understanding these recently developed scanning techniques is essential for optimization of imaging protocols designed to achieve the desired image quality with a reduced dose. © RSNA, 2014 PMID:24428277

Analog Design for Digital Deployment of a Serious Leadership Game

NASA Technical Reports Server (NTRS)

Maxwell, Nicholas; Lang, Tristan; Herman, Jeffrey L.; Phares, Richard

2012-01-01

This paper presents the design, development, and user testing of a leadership development simulation. The authors share lessons learned from using a design process for a board game to allow for quick and inexpensive revision cycles during the development of a serious leadership development game. The goal of this leadership simulation is to accelerate the development of leadership capacity in high-potential mid-level managers (GS-15 level) in a federal government agency. Simulation design included a mixed-method needs analysis, using both quantitative and qualitative approaches to determine organizational leadership needs. Eight design iterations were conducted, including three user testing phases. Three re-design iterations followed initial development, enabling game testing as part of comprehensive instructional events. Subsequent design, development and testing processes targeted digital application to a computer- and tablet-based environment. Recommendations include pros and cons of development and learner testing of an initial analog simulation prior to full digital simulation development.

Executing SPARQL Queries over the Web of Linked Data

NASA Astrophysics Data System (ADS)

Hartig, Olaf; Bizer, Christian; Freytag, Johann-Christoph

The Web of Linked Data forms a single, globally distributed dataspace. Due to the openness of this dataspace, it is not possible to know in advance all data sources that might be relevant for query answering. This openness poses a new challenge that is not addressed by traditional research on federated query processing. In this paper we present an approach to execute SPARQL queries over the Web of Linked Data. The main idea of our approach is to discover data that might be relevant for answering a query during the query execution itself. This discovery is driven by following RDF links between data sources based on URIs in the query and in partial results. The URIs are resolved over the HTTP protocol into RDF data which is continuously added to the queried dataset. This paper describes concepts and algorithms to implement our approach using an iterator-based pipeline. We introduce a formalization of the pipelining approach and show that classical iterators may cause blocking due to the latency of HTTP requests. To avoid blocking, we propose an extension of the iterator paradigm. The evaluation of our approach shows its strengths as well as the still existing challenges.

Scalable domain decomposition solvers for stochastic PDEs in high performance computing

DOE PAGES

Desai, Ajit; Khalil, Mohammad; Pettit, Chris; ...

2017-09-21

Stochastic spectral finite element models of practical engineering systems may involve solutions of linear systems or linearized systems for non-linear problems with billions of unknowns. For stochastic modeling, it is therefore essential to design robust, parallel and scalable algorithms that can efficiently utilize high-performance computing to tackle such large-scale systems. Domain decomposition based iterative solvers can handle such systems. And though these algorithms exhibit excellent scalabilities, significant algorithmic and implementational challenges exist to extend them to solve extreme-scale stochastic systems using emerging computing platforms. Intrusive polynomial chaos expansion based domain decomposition algorithms are extended here to concurrently handle high resolutionmore » in both spatial and stochastic domains using an in-house implementation. Sparse iterative solvers with efficient preconditioners are employed to solve the resulting global and subdomain level local systems through multi-level iterative solvers. We also use parallel sparse matrix–vector operations to reduce the floating-point operations and memory requirements. Numerical and parallel scalabilities of these algorithms are presented for the diffusion equation having spatially varying diffusion coefficient modeled by a non-Gaussian stochastic process. Scalability of the solvers with respect to the number of random variables is also investigated.« less

CAD-Based Shielding Analysis for ITER Port Diagnostics

NASA Astrophysics Data System (ADS)

Serikov, Arkady; Fischer, Ulrich; Anthoine, David; Bertalot, Luciano; De Bock, Maartin; O'Connor, Richard; Juarez, Rafael; Krasilnikov, Vitaly

2017-09-01

Radiation shielding analysis conducted in support of design development of the contemporary diagnostic systems integrated inside the ITER ports is relied on the use of CAD models. This paper presents the CAD-based MCNP Monte Carlo radiation transport and activation analyses for the Diagnostic Upper and Equatorial Port Plugs (UPP #3 and EPP #8, #17). The creation process of the complicated 3D MCNP models of the diagnostics systems was substantially accelerated by application of the CAD-to-MCNP converter programs MCAM and McCad. High performance computing resources of the Helios supercomputer allowed to speed-up the MCNP parallel transport calculations with the MPI/OpenMP interface. The found shielding solutions could be universal, reducing ports R&D costs. The shield block behind the Tritium and Deposit Monitor (TDM) optical box was added to study its influence on Shut-Down Dose Rate (SDDR) in Port Interspace (PI) of EPP#17. Influence of neutron streaming along the Lost Alpha Monitor (LAM) on the neutron energy spectra calculated in the Tangential Neutron Spectrometer (TNS) of EPP#8. For the UPP#3 with Charge eXchange Recombination Spectroscopy (CXRS-core), an excessive neutron streaming along the CXRS shutter, which should be prevented in further design iteration.

Scalable domain decomposition solvers for stochastic PDEs in high performance computing

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

Desai, Ajit; Khalil, Mohammad; Pettit, Chris

Stochastic spectral finite element models of practical engineering systems may involve solutions of linear systems or linearized systems for non-linear problems with billions of unknowns. For stochastic modeling, it is therefore essential to design robust, parallel and scalable algorithms that can efficiently utilize high-performance computing to tackle such large-scale systems. Domain decomposition based iterative solvers can handle such systems. And though these algorithms exhibit excellent scalabilities, significant algorithmic and implementational challenges exist to extend them to solve extreme-scale stochastic systems using emerging computing platforms. Intrusive polynomial chaos expansion based domain decomposition algorithms are extended here to concurrently handle high resolutionmore » in both spatial and stochastic domains using an in-house implementation. Sparse iterative solvers with efficient preconditioners are employed to solve the resulting global and subdomain level local systems through multi-level iterative solvers. We also use parallel sparse matrix–vector operations to reduce the floating-point operations and memory requirements. Numerical and parallel scalabilities of these algorithms are presented for the diffusion equation having spatially varying diffusion coefficient modeled by a non-Gaussian stochastic process. Scalability of the solvers with respect to the number of random variables is also investigated.« less

Representation and alignment of sung queries for music information retrieval

NASA Astrophysics Data System (ADS)

Adams, Norman H.; Wakefield, Gregory H.

2005-09-01

The pursuit of robust and rapid query-by-humming systems, which search melodic databases using sung queries, is a common theme in music information retrieval. The retrieval aspect of this database problem has received considerable attention, whereas the front-end processing of sung queries and the data structure to represent melodies has been based on musical intuition and historical momentum. The present work explores three time series representations for sung queries: a sequence of notes, a ``smooth'' pitch contour, and a sequence of pitch histograms. The performance of the three representations is compared using a collection of naturally sung queries. It is found that the most robust performance is achieved by the representation with highest dimension, the smooth pitch contour, but that this representation presents a formidable computational burden. For all three representations, it is necessary to align the query and target in order to achieve robust performance. The computational cost of the alignment is quadratic, hence it is necessary to keep the dimension small for rapid retrieval. Accordingly, iterative deepening is employed to achieve both robust performance and rapid retrieval. Finally, the conventional iterative framework is expanded to adapt the alignment constraints based on previous iterations, further expediting retrieval without degrading performance.

Image security based on iterative random phase encoding in expanded fractional Fourier transform domains

NASA Astrophysics Data System (ADS)

Liu, Zhengjun; Chen, Hang; Blondel, Walter; Shen, Zhenmin; Liu, Shutian

2018-06-01

A novel image encryption method is proposed by using the expanded fractional Fourier transform, which is implemented with a pair of lenses. Here the centers of two lenses are separated at the cross section of axis in optical system. The encryption system is addressed with Fresnel diffraction and phase modulation for the calculation of information transmission. The iterative process with the transform unit is utilized for hiding secret image. The structure parameters of a battery of lenses can be used for additional keys. The performance of encryption method is analyzed theoretically and digitally. The results show that the security of this algorithm is enhanced markedly by the added keys.

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.

Modeling Peer Assessment as Agent Negotiation in a Computer Supported Collaborative Learning Environment

ERIC Educational Resources Information Center

Lai, K. Robert; Lan, Chung Hsien

2006-01-01

This work presents a novel method for modeling collaborative learning as multi-issue agent negotiation using fuzzy constraints. Agent negotiation is an iterative process, through which, the proposed method aggregates student marks to reduce personal bias. In the framework, students define individual fuzzy membership functions based on their…

Measuring Experiential Avoidance: A Preliminary Test of a Working Model

ERIC Educational Resources Information Center

Hayes, Steven C.; Strosahl, Kirk; Wilson, Kelly G.; Bissett, Richard T.; Pistorello, Jacqueline; Toarmino, Dosheen; Polusny, Melissa A.; Dykstra, Thane A.; Batten, Sonja V.; Bergan, John; Stewart, Sherry H.; Zvolensky, Michael J.; Eifert, Georg H.; Bond, Frank W.; Forsyth, John P.; Karekla, Maria; Mccurry, Susan M.

2004-01-01

The present study describes the development of a short, general measure of experiential avoidance, based on a specific theoretical approach to this process. A theoretically driven iterative exploratory analysis using structural equation modeling on data from a clinical sample yielded a single factor comprising 9 items. A fully confirmatory factor…

Standard and Robust Methods in Regression Imputation

ERIC Educational Resources Information Center

Moraveji, Behjat; Jafarian, Koorosh

2014-01-01

The aim of this paper is to provide an introduction of new imputation algorithms for estimating missing values from official statistics in larger data sets of data pre-processing, or outliers. The goal is to propose a new algorithm called IRMI (iterative robust model-based imputation). This algorithm is able to deal with all challenges like…

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.

Intelligent tuning method of PID parameters based on iterative learning control for atomic force microscopy.

PubMed

Liu, Hui; Li, Yingzi; Zhang, Yingxu; Chen, Yifu; Song, Zihang; Wang, Zhenyu; Zhang, Suoxin; Qian, Jianqiang

2018-01-01

Proportional-integral-derivative (PID) parameters play a vital role in the imaging process of an atomic force microscope (AFM). Traditional parameter tuning methods require a lot of manpower and it is difficult to set PID parameters in unattended working environments. In this manuscript, an intelligent tuning method of PID parameters based on iterative learning control is proposed to self-adjust PID parameters of the AFM according to the sample topography. This method gets enough information about the output signals of PID controller and tracking error, which will be used to calculate the proper PID parameters, by repeated line scanning until convergence before normal scanning to learn the topography. Subsequently, the appropriate PID parameters are obtained by fitting method and then applied to the normal scanning process. The feasibility of the method is demonstrated by the convergence analysis. Simulations and experimental results indicate that the proposed method can intelligently tune PID parameters of the AFM for imaging different topographies and thus achieve good tracking performance. Copyright © 2017 Elsevier Ltd. All rights reserved.

Ask-the-expert: Active Learning Based Knowledge Discovery Using the Expert

NASA Technical Reports Server (NTRS)

Das, Kamalika; Avrekh, Ilya; Matthews, Bryan; Sharma, Manali; Oza, Nikunj

2017-01-01

Often the manual review of large data sets, either for purposes of labeling unlabeled instances or for classifying meaningful results from uninteresting (but statistically significant) ones is extremely resource intensive, especially in terms of subject matter expert (SME) time. Use of active learning has been shown to diminish this review time significantly. However, since active learning is an iterative process of learning a classifier based on a small number of SME-provided labels at each iteration, the lack of an enabling tool can hinder the process of adoption of these technologies in real-life, in spite of their labor-saving potential. In this demo we present ASK-the-Expert, an interactive tool that allows SMEs to review instances from a data set and provide labels within a single framework. ASK-the-Expert is powered by an active learning algorithm for training a classifier in the backend. We demonstrate this system in the context of an aviation safety application, but the tool can be adopted to work as a simple review and labeling tool as well, without the use of active learning.

Ask-the-Expert: Active Learning Based Knowledge Discovery Using the Expert

NASA Technical Reports Server (NTRS)

Das, Kamalika

2017-01-01

Often the manual review of large data sets, either for purposes of labeling unlabeled instances or for classifying meaningful results from uninteresting (but statistically significant) ones is extremely resource intensive, especially in terms of subject matter expert (SME) time. Use of active learning has been shown to diminish this review time significantly. However, since active learning is an iterative process of learning a classifier based on a small number of SME-provided labels at each iteration, the lack of an enabling tool can hinder the process of adoption of these technologies in real-life, in spite of their labor-saving potential. In this demo we present ASK-the-Expert, an interactive tool that allows SMEs to review instances from a data set and provide labels within a single framework. ASK-the-Expert is powered by an active learning algorithm for training a classifier in the back end. We demonstrate this system in the context of an aviation safety application, but the tool can be adopted to work as a simple review and labeling tool as well, without the use of active learning.

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

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.

Iterative Methods for the Non-LTE Transfer of Polarized Radiation: Resonance Line Polarization in One-dimensional Atmospheres

NASA Astrophysics Data System (ADS)

Trujillo Bueno, Javier; Manso Sainz, Rafael

1999-05-01

This paper shows how to generalize to non-LTE polarization transfer some operator splitting methods that were originally developed for solving unpolarized transfer problems. These are the Jacobi-based accelerated Λ-iteration (ALI) method of Olson, Auer, & Buchler and the iterative schemes based on Gauss-Seidel and successive overrelaxation (SOR) iteration of Trujillo Bueno and Fabiani Bendicho. The theoretical framework chosen for the formulation of polarization transfer problems is the quantum electrodynamics (QED) theory of Landi Degl'Innocenti, which specifies the excitation state of the atoms in terms of the irreducible tensor components of the atomic density matrix. This first paper establishes the grounds of our numerical approach to non-LTE polarization transfer by concentrating on the standard case of scattering line polarization in a gas of two-level atoms, including the Hanle effect due to a weak microturbulent and isotropic magnetic field. We begin demonstrating that the well-known Λ-iteration method leads to the self-consistent solution of this type of problem if one initializes using the ``exact'' solution corresponding to the unpolarized case. We show then how the above-mentioned splitting methods can be easily derived from this simple Λ-iteration scheme. We show that our SOR method is 10 times faster than the Jacobi-based ALI method, while our implementation of the Gauss-Seidel method is 4 times faster. These iterative schemes lead to the self-consistent solution independently of the chosen initialization. The convergence rate of these iterative methods is very high; they do not require either the construction or the inversion of any matrix, and the computing time per iteration is similar to that of the Λ-iteration method.

A fast iterative recursive least squares algorithm for Wiener model identification of highly nonlinear systems.

PubMed

Kazemi, Mahdi; Arefi, Mohammad Mehdi

2017-03-01

In this paper, an online identification algorithm is presented for nonlinear systems in the presence of output colored noise. The proposed method is based on extended recursive least squares (ERLS) algorithm, where the identified system is in polynomial Wiener form. To this end, an unknown intermediate signal is estimated by using an inner iterative algorithm. The iterative recursive algorithm adaptively modifies the vector of parameters of the presented Wiener model when the system parameters vary. In addition, to increase the robustness of the proposed method against variations, a robust RLS algorithm is applied to the model. Simulation results are provided to show the effectiveness of the proposed approach. Results confirm that the proposed method has fast convergence rate with robust characteristics, which increases the efficiency of the proposed model and identification approach. For instance, the FIT criterion will be achieved 92% in CSTR process where about 400 data is used. Copyright © 2016 ISA. Published by Elsevier Ltd. All rights reserved.

Segmentation-based retrospective shading correction in fluorescence microscopy E. coli images for quantitative analysis

NASA Astrophysics Data System (ADS)

Mai, Fei; Chang, Chunqi; Liu, Wenqing; Xu, Weichao; Hung, Yeung S.

2009-10-01

Due to the inherent imperfections in the imaging process, fluorescence microscopy images often suffer from spurious intensity variations, which is usually referred to as intensity inhomogeneity, intensity non uniformity, shading or bias field. In this paper, a retrospective shading correction method for fluorescence microscopy Escherichia coli (E. Coli) images is proposed based on segmentation result. Segmentation and shading correction are coupled together, so we iteratively correct the shading effects based on segmentation result and refine the segmentation by segmenting the image after shading correction. A fluorescence microscopy E. Coli image can be segmented (based on its intensity value) into two classes: the background and the cells, where the intensity variation within each class is close to zero if there is no shading. Therefore, we make use of this characteristics to correct the shading in each iteration. Shading is mathematically modeled as a multiplicative component and an additive noise component. The additive component is removed by a denoising process, and the multiplicative component is estimated using a fast algorithm to minimize the intra-class intensity variation. We tested our method on synthetic images and real fluorescence E.coli images. It works well not only for visual inspection, but also for numerical evaluation. Our proposed method should be useful for further quantitative analysis especially for protein expression value comparison.

Interactive computer graphics system for structural sizing and analysis of aircraft structures

NASA Technical Reports Server (NTRS)

Bendavid, D.; Pipano, A.; Raibstein, A.; Somekh, E.

1975-01-01

A computerized system for preliminary sizing and analysis of aircraft wing and fuselage structures was described. The system is based upon repeated application of analytical program modules, which are interactively interfaced and sequence-controlled during the iterative design process with the aid of design-oriented graphics software modules. The entire process is initiated and controlled via low-cost interactive graphics terminals driven by a remote computer in a time-sharing mode.

Phased models for evaluating the performability of computing systems

NASA Technical Reports Server (NTRS)

Wu, L. T.; Meyer, J. F.

1979-01-01

A phase-by-phase modelling technique is introduced to evaluate a fault tolerant system's ability to execute different sets of computational tasks during different phases of the control process. Intraphase processes are allowed to differ from phase to phase. The probabilities of interphase state transitions are specified by interphase transition matrices. Based on constraints imposed on the intraphase and interphase transition probabilities, various iterative solution methods are developed for calculating system performability.

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…

WE-AB-303-09: Rapid Projection Computations for On-Board Digital Tomosynthesis in Radiation Therapy

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

Iliopoulos, AS; Sun, X; Pitsianis, N

2015-06-15

Purpose: To facilitate fast and accurate iterative volumetric image reconstruction from limited-angle on-board projections. Methods: Intrafraction motion hinders the clinical applicability of modern radiotherapy techniques, such as lung stereotactic body radiation therapy (SBRT). The LIVE system may impact clinical practice by recovering volumetric information via Digital Tomosynthesis (DTS), thus entailing low time and radiation dose for image acquisition during treatment. The DTS is estimated as a deformation of prior CT via iterative registration with on-board images; this shifts the challenge to the computational domain, owing largely to repeated projection computations across iterations. We address this issue by composing efficient digitalmore » projection operators from their constituent parts. This allows us to separate the static (projection geometry) and dynamic (volume/image data) parts of projection operations by means of pre-computations, enabling fast on-board processing, while also relaxing constraints on underlying numerical models (e.g. regridding interpolation kernels). Further decoupling the projectors into simpler ones ensures the incurred memory overhead remains low, within the capacity of a single GPU. These operators depend only on the treatment plan and may be reused across iterations and patients. The dynamic processing load is kept to a minimum and maps well to the GPU computational model. Results: We have integrated efficient, pre-computable modules for volumetric ray-casting and FDK-based back-projection with the LIVE processing pipeline. Our results show a 60x acceleration of the DTS computations, compared to the previous version, using a single GPU; presently, reconstruction is attained within a couple of minutes. The present implementation allows for significant flexibility in terms of the numerical and operational projection model; we are investigating the benefit of further optimizations and accurate digital projection sub-kernels. Conclusion: Composable projection operators constitute a versatile research tool which can greatly accelerate iterative registration algorithms and may be conducive to the clinical applicability of LIVE. National Institutes of Health Grant No. R01-CA184173; GPU donation by NVIDIA Corporation.« less

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.

Spatio-Temporal Super-Resolution Reconstruction of Remote-Sensing Images Based on Adaptive Multi-Scale Detail Enhancement

PubMed Central

Zhu, Hong; Tang, Xinming; Xie, Junfeng; Song, Weidong; Mo, Fan; Gao, Xiaoming

2018-01-01

There are many problems in existing reconstruction-based super-resolution algorithms, such as the lack of texture-feature representation and of high-frequency details. Multi-scale detail enhancement can produce more texture information and high-frequency information. Therefore, super-resolution reconstruction of remote-sensing images based on adaptive multi-scale detail enhancement (AMDE-SR) is proposed in this paper. First, the information entropy of each remote-sensing image is calculated, and the image with the maximum entropy value is regarded as the reference image. Subsequently, spatio-temporal remote-sensing images are processed using phase normalization, which is to reduce the time phase difference of image data and enhance the complementarity of information. The multi-scale image information is then decomposed using the L0 gradient minimization model, and the non-redundant information is processed by difference calculation and expanding non-redundant layers and the redundant layer by the iterative back-projection (IBP) technique. The different-scale non-redundant information is adaptive-weighted and fused using cross-entropy. Finally, a nonlinear texture-detail-enhancement function is built to improve the scope of small details, and the peak signal-to-noise ratio (PSNR) is used as an iterative constraint. Ultimately, high-resolution remote-sensing images with abundant texture information are obtained by iterative optimization. Real results show an average gain in entropy of up to 0.42 dB for an up-scaling of 2 and a significant promotion gain in enhancement measure evaluation for an up-scaling of 2. The experimental results show that the performance of the AMED-SR method is better than existing super-resolution reconstruction methods in terms of visual and accuracy improvements. PMID:29414893

Spatio-Temporal Super-Resolution Reconstruction of Remote-Sensing Images Based on Adaptive Multi-Scale Detail Enhancement.

PubMed

Zhu, Hong; Tang, Xinming; Xie, Junfeng; Song, Weidong; Mo, Fan; Gao, Xiaoming

2018-02-07

There are many problems in existing reconstruction-based super-resolution algorithms, such as the lack of texture-feature representation and of high-frequency details. Multi-scale detail enhancement can produce more texture information and high-frequency information. Therefore, super-resolution reconstruction of remote-sensing images based on adaptive multi-scale detail enhancement (AMDE-SR) is proposed in this paper. First, the information entropy of each remote-sensing image is calculated, and the image with the maximum entropy value is regarded as the reference image. Subsequently, spatio-temporal remote-sensing images are processed using phase normalization, which is to reduce the time phase difference of image data and enhance the complementarity of information. The multi-scale image information is then decomposed using the L ₀ gradient minimization model, and the non-redundant information is processed by difference calculation and expanding non-redundant layers and the redundant layer by the iterative back-projection (IBP) technique. The different-scale non-redundant information is adaptive-weighted and fused using cross-entropy. Finally, a nonlinear texture-detail-enhancement function is built to improve the scope of small details, and the peak signal-to-noise ratio (PSNR) is used as an iterative constraint. Ultimately, high-resolution remote-sensing images with abundant texture information are obtained by iterative optimization. Real results show an average gain in entropy of up to 0.42 dB for an up-scaling of 2 and a significant promotion gain in enhancement measure evaluation for an up-scaling of 2. The experimental results show that the performance of the AMED-SR method is better than existing super-resolution reconstruction methods in terms of visual and accuracy improvements.

Using an ensemble smoother to evaluate parameter uncertainty of an integrated hydrological model of Yanqi basin

NASA Astrophysics Data System (ADS)

Li, Ning; McLaughlin, Dennis; Kinzelbach, Wolfgang; Li, WenPeng; Dong, XinGuang

2015-10-01

Model uncertainty needs to be quantified to provide objective assessments of the reliability of model predictions and of the risk associated with management decisions that rely on these predictions. This is particularly true in water resource studies that depend on model-based assessments of alternative management strategies. In recent decades, Bayesian data assimilation methods have been widely used in hydrology to assess uncertain model parameters and predictions. In this case study, a particular data assimilation algorithm, the Ensemble Smoother with Multiple Data Assimilation (ESMDA) (Emerick and Reynolds, 2012), is used to derive posterior samples of uncertain model parameters and forecasts for a distributed hydrological model of Yanqi basin, China. This model is constructed using MIKESHE/MIKE11software, which provides for coupling between surface and subsurface processes (DHI, 2011a-d). The random samples in the posterior parameter ensemble are obtained by using measurements to update 50 prior parameter samples generated with a Latin Hypercube Sampling (LHS) procedure. The posterior forecast samples are obtained from model runs that use the corresponding posterior parameter samples. Two iterative sample update methods are considered: one based on an a perturbed observation Kalman filter update and one based on a square root Kalman filter update. These alternatives give nearly the same results and converge in only two iterations. The uncertain parameters considered include hydraulic conductivities, drainage and river leakage factors, van Genuchten soil property parameters, and dispersion coefficients. The results show that the uncertainty in many of the parameters is reduced during the smoother updating process, reflecting information obtained from the observations. Some of the parameters are insensitive and do not benefit from measurement information. The correlation coefficients among certain parameters increase in each iteration, although they generally stay below 0.50.

Implementing the Science Assessment Standards: Developing and validating a set of laboratory assessment tasks in high school biology

NASA Astrophysics Data System (ADS)

Saha, Gouranga Chandra

Very often a number of factors, especially time, space and money, deter many science educators from using inquiry-based, hands-on, laboratory practical tasks as alternative assessment instruments in science. A shortage of valid inquiry-based laboratory tasks for high school biology has been cited. Driven by this need, this study addressed the following three research questions: (1) How can laboratory-based performance tasks be designed and developed that are doable by students for whom they are designed/written? (2) Do student responses to the laboratory-based performance tasks validly represent at least some of the intended process skills that new biology learning goals want students to acquire? (3) Are the laboratory-based performance tasks psychometrically consistent as individual tasks and as a set? To answer these questions, three tasks were used from the six biology tasks initially designed and developed by an iterative process of trial testing. Analyses of data from 224 students showed that performance-based laboratory tasks that are doable by all students require careful and iterative process of development. Although the students demonstrated more skill in performing than planning and reasoning, their performances at the item level were very poor for some items. Possible reasons for the poor performances have been discussed and suggestions on how to remediate the deficiencies have been made. Empirical evidences for validity and reliability of the instrument have been presented both from the classical and the modern validity criteria point of view. Limitations of the study have been identified. Finally implications of the study and directions for further research have been discussed.

SU-F-BRCD-09: Total Variation (TV) Based Fast Convergent Iterative CBCT Reconstruction with GPU Acceleration.

PubMed

Xu, Q; Yang, D; Tan, J; Anastasio, M

2012-06-01

To improve image quality and reduce imaging dose in CBCT for radiation therapy applications and to realize near real-time image reconstruction based on use of a fast convergence iterative algorithm and acceleration by multi-GPUs. An iterative image reconstruction that sought to minimize a weighted least squares cost function that employed total variation (TV) regularization was employed to mitigate projection data incompleteness and noise. To achieve rapid 3D image reconstruction (< 1 min), a highly optimized multiple-GPU implementation of the algorithm was developed. The convergence rate and reconstruction accuracy were evaluated using a modified 3D Shepp-Logan digital phantom and a Catphan-600 physical phantom. The reconstructed images were compared with the clinical FDK reconstruction results. Digital phantom studies showed that only 15 iterations and 60 iterations are needed to achieve algorithm convergence for 360-view and 60-view cases, respectively. The RMSE was reduced to 10-4 and 10-2, respectively, by using 15 iterations for each case. Our algorithm required 5.4s to complete one iteration for the 60-view case using one Tesla C2075 GPU. The few-view study indicated that our iterative algorithm has great potential to reduce the imaging dose and preserve good image quality. For the physical Catphan studies, the images obtained from the iterative algorithm possessed better spatial resolution and higher SNRs than those obtained from by use of a clinical FDK reconstruction algorithm. We have developed a fast convergence iterative algorithm for CBCT image reconstruction. The developed algorithm yielded images with better spatial resolution and higher SNR than those produced by a commercial FDK tool. In addition, from the few-view study, the iterative algorithm has shown great potential for significantly reducing imaging dose. We expect that the developed reconstruction approach will facilitate applications including IGART and patient daily CBCT-based treatment localization. © 2012 American Association of Physicists in Medicine.

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.

Optimization Control of the Color-Coating Production Process for Model Uncertainty

PubMed Central

He, Dakuo; Wang, Zhengsong; Yang, Le; Mao, Zhizhong

2016-01-01

Optimized control of the color-coating production process (CCPP) aims at reducing production costs and improving economic efficiency while meeting quality requirements. However, because optimization control of the CCPP is hampered by model uncertainty, a strategy that considers model uncertainty is proposed. Previous work has introduced a mechanistic model of CCPP based on process analysis to simulate the actual production process and generate process data. The partial least squares method is then applied to develop predictive models of film thickness and economic efficiency. To manage the model uncertainty, the robust optimization approach is introduced to improve the feasibility of the optimized solution. Iterative learning control is then utilized to further refine the model uncertainty. The constrained film thickness is transformed into one of the tracked targets to overcome the drawback that traditional iterative learning control cannot address constraints. The goal setting of economic efficiency is updated continuously according to the film thickness setting until this reaches its desired value. Finally, fuzzy parameter adjustment is adopted to ensure that the economic efficiency and film thickness converge rapidly to their optimized values under the constraint conditions. The effectiveness of the proposed optimization control strategy is validated by simulation results. PMID:27247563

Optimization Control of the Color-Coating Production Process for Model Uncertainty.

PubMed

He, Dakuo; Wang, Zhengsong; Yang, Le; Mao, Zhizhong

2016-01-01

Optimized control of the color-coating production process (CCPP) aims at reducing production costs and improving economic efficiency while meeting quality requirements. However, because optimization control of the CCPP is hampered by model uncertainty, a strategy that considers model uncertainty is proposed. Previous work has introduced a mechanistic model of CCPP based on process analysis to simulate the actual production process and generate process data. The partial least squares method is then applied to develop predictive models of film thickness and economic efficiency. To manage the model uncertainty, the robust optimization approach is introduced to improve the feasibility of the optimized solution. Iterative learning control is then utilized to further refine the model uncertainty. The constrained film thickness is transformed into one of the tracked targets to overcome the drawback that traditional iterative learning control cannot address constraints. The goal setting of economic efficiency is updated continuously according to the film thickness setting until this reaches its desired value. Finally, fuzzy parameter adjustment is adopted to ensure that the economic efficiency and film thickness converge rapidly to their optimized values under the constraint conditions. The effectiveness of the proposed optimization control strategy is validated by simulation results.

Research on error control and compensation in magnetorheological finishing.

PubMed

Dai, Yifan; Hu, Hao; Peng, Xiaoqiang; Wang, Jianmin; Shi, Feng

2011-07-01

Although magnetorheological finishing (MRF) is a deterministic finishing technology, the machining results always fall short of simulation precision in the actual process, and it cannot meet the precision requirements just through a single treatment but after several iterations. We investigate the reasons for this problem through simulations and experiments. Through controlling and compensating the chief errors in the manufacturing procedure, such as removal function calculation error, positioning error of the removal function, and dynamic performance limitation of the CNC machine, the residual error convergence ratio (ratio of figure error before and after processing) in a single process is obviously increased, and higher figure precision is achieved. Finally, an improved technical process is presented based on these researches, and the verification experiment is accomplished on the experimental device we developed. The part is a circular plane mirror of fused silica material, and the surface figure error is improved from the initial λ/5 [peak-to-valley (PV) λ=632.8 nm], λ/30 [root-mean-square (rms)] to the final λ/40 (PV), λ/330 (rms) just through one iteration in 4.4 min. Results show that a higher convergence ratio and processing precision can be obtained by adopting error control and compensation techniques in MRF.

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.

Bounded-Angle Iterative Decoding of LDPC Codes

NASA Technical Reports Server (NTRS)

Dolinar, Samuel; Andrews, Kenneth; Pollara, Fabrizio; Divsalar, Dariush

2009-01-01

Bounded-angle iterative decoding is a modified version of conventional iterative decoding, conceived as a means of reducing undetected-error rates for short low-density parity-check (LDPC) codes. For a given code, bounded-angle iterative decoding can be implemented by means of a simple modification of the decoder algorithm, without redesigning the code. Bounded-angle iterative decoding is based on a representation of received words and code words as vectors in an n-dimensional Euclidean space (where n is an integer).

Statistical shape model-based reconstruction of a scaled, patient-specific surface model of the pelvis from a single standard AP x-ray radiograph

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

Zheng Guoyan

2010-04-15

Purpose: The aim of this article is to investigate the feasibility of using a statistical shape model (SSM)-based reconstruction technique to derive a scaled, patient-specific surface model of the pelvis from a single standard anteroposterior (AP) x-ray radiograph and the feasibility of estimating the scale of the reconstructed surface model by performing a surface-based 3D/3D matching. Methods: Data sets of 14 pelvises (one plastic bone, 12 cadavers, and one patient) were used to validate the single-image based reconstruction technique. This reconstruction technique is based on a hybrid 2D/3D deformable registration process combining a landmark-to-ray registration with a SSM-based 2D/3D reconstruction.more » The landmark-to-ray registration was used to find an initial scale and an initial rigid transformation between the x-ray image and the SSM. The estimated scale and rigid transformation were used to initialize the SSM-based 2D/3D reconstruction. The optimal reconstruction was then achieved in three stages by iteratively matching the projections of the apparent contours extracted from a 3D model derived from the SSM to the image contours extracted from the x-ray radiograph: Iterative affine registration, statistical instantiation, and iterative regularized shape deformation. The image contours are first detected by using a semiautomatic segmentation tool based on the Livewire algorithm and then approximated by a set of sparse dominant points that are adaptively sampled from the detected contours. The unknown scales of the reconstructed models were estimated by performing a surface-based 3D/3D matching between the reconstructed models and the associated ground truth models that were derived from a CT-based reconstruction method. Such a matching also allowed for computing the errors between the reconstructed models and the associated ground truth models. Results: The technique could reconstruct the surface models of all 14 pelvises directly from the landmark-based initialization. Depending on the surface-based matching techniques, the reconstruction errors were slightly different. When a surface-based iterative affine registration was used, an average reconstruction error of 1.6 mm was observed. This error was increased to 1.9 mm, when a surface-based iterative scaled rigid registration was used. Conclusions: It is feasible to reconstruct a scaled, patient-specific surface model of the pelvis from single standard AP x-ray radiograph using the present approach. The unknown scale of the reconstructed model can be estimated by performing a surface-based 3D/3D matching.« less

Stimulating Scientific Reasoning with Drawing-Based Modeling

NASA Astrophysics Data System (ADS)

Heijnes, Dewi; van Joolingen, Wouter; Leenaars, Frank

2018-02-01

We investigate the way students' reasoning about evolution can be supported by drawing-based modeling. We modified the drawing-based modeling tool SimSketch to allow for modeling evolutionary processes. In three iterations of development and testing, students in lower secondary education worked on creating an evolutionary model. After each iteration, the user interface and instructions were adjusted based on students' remarks and the teacher's observations. Students' conversations were analyzed on reasoning complexity as a measurement of efficacy of the modeling tool and the instructions. These findings were also used to compose a set of recommendations for teachers and curriculum designers for using and constructing models in the classroom. Our findings suggest that to stimulate scientific reasoning in students working with a drawing-based modeling, tool instruction about the tool and the domain should be integrated. In creating models, a sufficient level of scaffolding is necessary. Without appropriate scaffolds, students are not able to create the model. With scaffolding that is too high, students may show reasoning that incorrectly assigns external causes to behavior in the model.

Iterative Refinement of Transmission Map for Stereo Image Defogging Using a Dual Camera Sensor.

PubMed

Kim, Heegwang; Park, Jinho; Park, Hasil; Paik, Joonki

2017-12-09

Recently, the stereo imaging-based image enhancement approach has attracted increasing attention in the field of video analysis. This paper presents a dual camera-based stereo image defogging algorithm. Optical flow is first estimated from the stereo foggy image pair, and the initial disparity map is generated from the estimated optical flow. Next, an initial transmission map is generated using the initial disparity map. Atmospheric light is then estimated using the color line theory. The defogged result is finally reconstructed using the estimated transmission map and atmospheric light. The proposed method can refine the transmission map iteratively. Experimental results show that the proposed method can successfully remove fog without color distortion. The proposed method can be used as a pre-processing step for an outdoor video analysis system and a high-end smartphone with a dual camera system.

Lunar lander conceptual design

NASA Technical Reports Server (NTRS)

Stecklein, J. M.; Petro, A. J.; Stump, W. R.; Adorjan, A. S.; Chambers, T. V.; Donofrio, M.; Hirasaki, J. K.; Morris, O. G.; Nudd, G.; Rawlings, R. P.

1992-01-01

This paper is a first look at the problems of building a lunar lander to support a small lunar surface base. A series of trade studies was performed to define the lander. The initial trades concerned choosing number of stages, payload mass, parking orbit altitude, and propellant type. Other important trades and issues included plane change capability, propellant loading and maintenance location, and reusability considerations. Given a rough baseline, the systems were then reviewed. A conceptual design was then produced. The process was carried through only one iteration. Many more iterations are needed. A transportation system using reusable, aerobraked orbital transfer vehicles (OTV's) is assumed. These OTV's are assumed to be based and maintained at a low Earth orbit (LEO) space station, optimized for transportation functions. Single- and two-stage OTV stacks are considered. The OTV's make the translunar injection (TLI), lunar orbit insertion (LOI), and trans-Earth injection (TEI) burns, as well as midcourse and perigee raise maneuvers.

Iterative Refinement of Transmission Map for Stereo Image Defogging Using a Dual Camera Sensor

PubMed Central

Park, Jinho; Park, Hasil

2017-01-01

Recently, the stereo imaging-based image enhancement approach has attracted increasing attention in the field of video analysis. This paper presents a dual camera-based stereo image defogging algorithm. Optical flow is first estimated from the stereo foggy image pair, and the initial disparity map is generated from the estimated optical flow. Next, an initial transmission map is generated using the initial disparity map. Atmospheric light is then estimated using the color line theory. The defogged result is finally reconstructed using the estimated transmission map and atmospheric light. The proposed method can refine the transmission map iteratively. Experimental results show that the proposed method can successfully remove fog without color distortion. The proposed method can be used as a pre-processing step for an outdoor video analysis system and a high-end smartphone with a dual camera system. PMID:29232826

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.

Automatic Synthesis of UML Designs from Requirements in an Iterative Process

NASA Technical Reports Server (NTRS)

Schumann, Johann; Whittle, Jon; Clancy, Daniel (Technical Monitor)

2001-01-01

The Unified Modeling Language (UML) is gaining wide popularity for the design of object-oriented systems. UML combines various object-oriented graphical design notations under one common framework. A major factor for the broad acceptance of UML is that it can be conveniently used in a highly iterative, Use Case (or scenario-based) process (although the process is not a part of UML). Here, the (pre-) requirements for the software are specified rather informally as Use Cases and a set of scenarios. A scenario can be seen as an individual trace of a software artifact. Besides first sketches of a class diagram to illustrate the static system breakdown, scenarios are a favorite way of communication with the customer, because scenarios describe concrete interactions between entities and are thus easy to understand. Scenarios with a high level of detail are often expressed as sequence diagrams. Later in the design and implementation stage (elaboration and implementation phases), a design of the system's behavior is often developed as a set of statecharts. From there (and the full-fledged class diagram), actual code development is started. Current commercial UML tools support this phase by providing code generators for class diagrams and statecharts. In practice, it can be observed that the transition from requirements to design to code is a highly iterative process. In this talk, a set of algorithms is presented which perform reasonable synthesis and transformations between different UML notations (sequence diagrams, Object Constraint Language (OCL) constraints, statecharts). More specifically, we will discuss the following transformations: Statechart synthesis, introduction of hierarchy, consistency of modifications, and "design-debugging".

Optimised Iteration in Coupled Monte Carlo - Thermal-Hydraulics Calculations

NASA Astrophysics Data System (ADS)

Hoogenboom, J. Eduard; Dufek, Jan

2014-06-01

This paper describes an optimised iteration scheme for the number of neutron histories and the relaxation factor in successive iterations of coupled Monte Carlo and thermal-hydraulic reactor calculations based on the stochastic iteration method. The scheme results in an increasing number of neutron histories for the Monte Carlo calculation in successive iteration steps and a decreasing relaxation factor for the spatial power distribution to be used as input to the thermal-hydraulics calculation. The theoretical basis is discussed in detail and practical consequences of the scheme are shown, among which a nearly linear increase per iteration of the number of cycles in the Monte Carlo calculation. The scheme is demonstrated for a full PWR type fuel assembly. Results are shown for the axial power distribution during several iteration steps. A few alternative iteration method are also tested and it is concluded that the presented iteration method is near optimal.

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…

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.)

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.

Color and Contour Based Identification of Stem of Coconut Bunch

NASA Astrophysics Data System (ADS)

Kannan Megalingam, Rajesh; Manoharan, Sakthiprasad K.; Reddy, Rajesh G.; Sriteja, Gone; Kashyap, Ashwin

2017-08-01

Vision is the key component of Artificial Intelligence and Automated Robotics. Sensors or Cameras are the sight organs for a robot. Only through this, they are able to locate themselves or identify the shape of a regular or an irregular object. This paper presents the method of Identification of an object based on color and contour recognition using a camera through digital image processing techniques for robotic applications. In order to identify the contour, shape matching technique is used, which takes the input data from the database provided, and uses it to identify the contour by checking for shape match. The shape match is based on the idea of iterating through each contour of the threshold image. The color is identified on HSV Scale, by approximating the desired range of values from the database. HSV data along with iteration is used for identifying a quadrilateral, which is our required contour. This algorithm could also be used in a non-deterministic plane, which only uses HSV values exclusively.

Spectral information enhancement using wavelet-based iterative filtering for in vivo gamma spectrometry.

PubMed

Paul, Sabyasachi; Sarkar, P K

2013-04-01

Use of wavelet transformation in stationary signal processing has been demonstrated for denoising the measured spectra and characterisation of radionuclides in the in vivo monitoring analysis, where difficulties arise due to very low activity level to be estimated in biological systems. The large statistical fluctuations often make the identification of characteristic gammas from radionuclides highly uncertain, particularly when interferences from progenies are also present. A new wavelet-based noise filtering methodology has been developed for better detection of gamma peaks in noisy data. This sequential, iterative filtering method uses the wavelet multi-resolution approach for noise rejection and an inverse transform after soft 'thresholding' over the generated coefficients. Analyses of in vivo monitoring data of (235)U and (238)U were carried out using this method without disturbing the peak position and amplitude while achieving a 3-fold improvement in the signal-to-noise ratio, compared with the original measured spectrum. When compared with other data-filtering techniques, the wavelet-based method shows the best results.

Traffic Aware Planner for Cockpit-Based Trajectory Optimization

NASA Technical Reports Server (NTRS)

Woods, Sharon E.; Vivona, Robert A.; Henderson, Jeffrey; Wing, David J.; Burke, Kelly A.

2016-01-01

The Traffic Aware Planner (TAP) software application is a cockpit-based advisory tool designed to be hosted on an Electronic Flight Bag and to enable and test the NASA concept of Traffic Aware Strategic Aircrew Requests (TASAR). The TASAR concept provides pilots with optimized route changes (including altitude) that reduce fuel burn and/or flight time, avoid interactions with known traffic, weather and restricted airspace, and may be used by the pilots to request a route and/or altitude change from Air Traffic Control. Developed using an iterative process, TAP's latest improvements include human-machine interface design upgrades and added functionality based on the results of human-in-the-loop simulation experiments and flight trials. Architectural improvements have been implemented to prepare the system for operational-use trials with partner commercial airlines. Future iterations will enhance coordination with airline dispatch and add functionality to improve the acceptability of TAP-generated route-change requests to pilots, dispatchers, and air traffic controllers.

Establishing the Canadian HIV Women's Sexual and Reproductive Health Cohort Study (CHIWOS): Operationalizing Community-based Research in a Large National Quantitative Study.

PubMed

Loutfy, Mona; Greene, Saara; Kennedy, V Logan; Lewis, Johanna; Thomas-Pavanel, Jamie; Conway, Tracey; de Pokomandy, Alexandra; O'Brien, Nadia; Carter, Allison; Tharao, Wangari; Nicholson, Valerie; Beaver, Kerrigan; Dubuc, Danièle; Gahagan, Jacqueline; Proulx-Boucher, Karène; Hogg, Robert S; Kaida, Angela

2016-08-19

Community-based research has gained increasing recognition in health research over the last two decades. Such participatory research approaches are lauded for their ability to anchor research in lived experiences, ensuring cultural appropriateness, accessing local knowledge, reaching marginalized communities, building capacity, and facilitating research-to-action. While having these positive attributes, the community-based health research literature is predominantly composed of small projects, using qualitative methods, and set within geographically limited communities. Its use in larger health studies, including clinical trials and cohorts, is limited. We present the Canadian HIV Women's Sexual and Reproductive Health Cohort Study (CHIWOS), a large-scale, multi-site, national, longitudinal quantitative study that has operationalized community-based research in all steps of the research process. Successes, challenges and further considerations are offered. Through the integration of community-based research principles, we have been successful in: facilitating a two-year long formative phase for this study; developing a novel survey instrument with national involvement; training 39 Peer Research Associates (PRAs); offering ongoing comprehensive support to PRAs; and engaging in an ongoing iterative community-based research process. Our community-based research approach within CHIWOS demanded that we be cognizant of challenges managing a large national team, inherent power imbalances and challenges with communication, compensation and volunteering considerations, and extensive delays in institutional processes. It is important to consider the iterative nature of community-based research and to work through tensions that emerge given the diverse perspectives of numerous team members. Community-based research, as an approach to large-scale quantitative health research projects, is an increasingly viable methodological option. Community-based research has several advantages that go hand-in-hand with its obstacles. We offer guidance on implementing this approach, such that the process can be better planned and result in success.

A new model for graduate education and innovation in medical technology.

PubMed

Yazdi, Youseph; Acharya, Soumyadipta

2013-09-01

We describe a new model of graduate education in bioengineering innovation and design- a year long Master's degree program that educates engineers in the process of healthcare technology innovation for both advanced and low-resource global markets. Students are trained in an iterative "Spiral Innovation" approach that ensures early, staged, and repeated examination of all key elements of a successful medical device. This includes clinical immersion based problem identification and assessment (at Johns Hopkins Medicine and abroad), team based concept and business model development, and project planning based on iterative technical and business plan de-risking. The experiential, project based learning process is closely supported by several core courses in business, design, and engineering. Students in the program work on two team based projects, one focused on addressing healthcare needs in advanced markets and a second focused on low-resource settings. The program recently completed its fourth year of existence, and has graduated 61 students, who have continued on to industry or startups (one half), additional graduate education, or medical school (one third), or our own Global Health Innovation Fellowships. Over the 4 years, the program has sponsored 10 global health teams and 14 domestic/advanced market medtech teams, and launched 5 startups, of which 4 are still active. Projects have attracted over US$2.5M in follow-on awards and grants, that are supporting the continued development of over a dozen projects.

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

ERIC Educational Resources Information Center

Mikula, Brendon D.; Heckler, Andrew F.

2017-01-01

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

The Affordances of Design-Based Research for Studying Multicultural Literature Instruction: Reflections and Insights from a Teacher-Researcher Collaboration

ERIC Educational Resources Information Center

Thein, Amanda Haertling; Barbas, Patricia; Carnevali, Christine; Fox, Ashleigh; Mahoney, Amanda; Vensel, Scott

2012-01-01

This paper details a teacher-researcher effort to investigate effective instructional practices for teaching multicultural literature through a collaborative, iterative process of inquiry driven by tentative, theoretical principles. The study began with a distillation of recent scholarship on multicultural literature response into a set of…

Researchers Apply Lesson Study: A Cycle of Lesson Planning, Implementation, and Revision

ERIC Educational Resources Information Center

Regan, Kelley S.; Evmenova, Anya S.; Kurz, Leigh Ann; Hughes, Melissa D.; Sacco, Donna; Ahn, Soo Y.; MacVittie, Nichole; Good, Kevin; Boykin, Andrea; Schwartzer, Jessica; Chirinos, David S.

2016-01-01

Scripted lesson plans and/or professional development alone may not be sufficient to encourage teachers to reflect on the quality of their teaching and improve their teaching. One learning tool that teachers may use to improve their teaching is Lesson Study (LS). LS is a collaborative process involving educators, based on concepts of iteration and…

The Iterative Design of a Mobile Learning Application to Support Scientific Inquiry

ERIC Educational Resources Information Center

Marty, Paul F.; Mendenhall, Anne; Douglas, Ian; Southerland, Sherry A.; Sampson, Victor; Kazmer, Michelle M.; Alemanne, Nicole; Clark, Amanda; Schellinger, Jennifer

2013-01-01

The ubiquity of mobile devices makes them well suited for field-based learning experiences that require students to gather data as part of the process of developing scientific inquiry practices. The usefulness of these devices, however, is strongly influenced by the nature of the applications students use to collect data in the field. To…

Design and Use of Interactive Social Stories for Children with Autism Spectrum Disorder (ASD)

ERIC Educational Resources Information Center

Sani-Bozkurt, Sunagul; Vuran, Sezgin; Akbulut, Yavuz

2017-01-01

The current study aimed to design technology-supported interactive social stories to teach social skills to children with autism spectrum disorder (ASD). A design-based research was implemented with children with ASD along with the participation of their mothers, teachers, peers and field experts. An iterative remediation process was followed…

Research at ITER towards DEMO: Specific reactor diagnostic studies to be carried out on ITER

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

Krasilnikov, A. V.; Kaschuck, Y. A.; Vershkov, V. A.

2014-08-21

In ITER diagnostics will operate in the very hard radiation environment of fusion reactor. Extensive technology studies are carried out during development of the ITER diagnostics and procedures of their calibration and remote handling. Results of these studies and practical application of the developed diagnostics on ITER will provide the direct input to DEMO diagnostic development. The list of DEMO measurement requirements and diagnostics will be determined during ITER experiments on the bases of ITER plasma physics results and success of particular diagnostic application in reactor-like ITER plasma. Majority of ITER diagnostic already passed the conceptual design phase and representmore » the state of the art in fusion plasma diagnostic development. The number of related to DEMO results of ITER diagnostic studies such as design and prototype manufacture of: neutron and γ–ray diagnostics, neutral particle analyzers, optical spectroscopy including first mirror protection and cleaning technics, reflectometry, refractometry, tritium retention measurements etc. are discussed.« less

Research at ITER towards DEMO: Specific reactor diagnostic studies to be carried out on ITER

NASA Astrophysics Data System (ADS)

Krasilnikov, A. V.; Kaschuck, Y. A.; Vershkov, V. A.; Petrov, A. A.; Petrov, V. G.; Tugarinov, S. N.

2014-08-01

In ITER diagnostics will operate in the very hard radiation environment of fusion reactor. Extensive technology studies are carried out during development of the ITER diagnostics and procedures of their calibration and remote handling. Results of these studies and practical application of the developed diagnostics on ITER will provide the direct input to DEMO diagnostic development. The list of DEMO measurement requirements and diagnostics will be determined during ITER experiments on the bases of ITER plasma physics results and success of particular diagnostic application in reactor-like ITER plasma. Majority of ITER diagnostic already passed the conceptual design phase and represent the state of the art in fusion plasma diagnostic development. The number of related to DEMO results of ITER diagnostic studies such as design and prototype manufacture of: neutron and γ-ray diagnostics, neutral particle analyzers, optical spectroscopy including first mirror protection and cleaning technics, reflectometry, refractometry, tritium retention measurements etc. are discussed.

Parallel AFSA algorithm accelerating based on MIC architecture

NASA Astrophysics Data System (ADS)

Zhou, Junhao; Xiao, Hong; Huang, Yifan; Li, Yongzhao; Xu, Yuanrui

2017-05-01

Analysis AFSA past for solving the traveling salesman problem, the algorithm efficiency is often a big problem, and the algorithm processing method, it does not fully responsive to the characteristics of the traveling salesman problem to deal with, and therefore proposes a parallel join improved AFSA process. The simulation with the current TSP known optimal solutions were analyzed, the results showed that the AFSA iterations improved less, on the MIC cards doubled operating efficiency, efficiency significantly.

A rule based computer aided design system

NASA Technical Reports Server (NTRS)

Premack, T.

1986-01-01

A Computer Aided Design (CAD) system is presented which supports the iterative process of design, the dimensional continuity between mating parts, and the hierarchical structure of the parts in their assembled configuration. Prolog, an interactive logic programming language, is used to represent and interpret the data base. The solid geometry representing the parts is defined in parameterized form using the swept volume method. The system is demonstrated with a design of a spring piston.

Experiences with a generator tool for building clinical application modules.

PubMed

Kuhn, K A; Lenz, R; Elstner, T; Siegele, H; Moll, R

2003-01-01

To elaborate main system characteristics and relevant deployment experiences for the health information system (HIS) Orbis/OpenMed, which is in widespread use in Germany, Austria, and Switzerland. In a deployment phase of 3 years in a 1.200 bed university hospital, where the system underwent significant improvements, the system's functionality and its software design have been analyzed in detail. We focus on an integrated CASE tool for generating embedded clinical applications and for incremental system evolution. We present a participatory and iterative software engineering process developed for efficient utilization of such a tool. The system's functionality is comparable to other commercial products' functionality; its components are embedded in a vendor-specific application framework, and standard interfaces are being used for connecting subsystems. The integrated generator tool is a remarkable feature; it became a key factor of our project. Tool generated applications are workflow enabled and embedded into the overall data base schema. Rapid prototyping and iterative refinement are supported, so application modules can be adapted to the users' work practice. We consider tools supporting an iterative and participatory software engineering process highly relevant for health information system architects. The potential of a system to continuously evolve and to be effectively adapted to changing needs may be more important than sophisticated but hard-coded HIS functionality. More work will focus on HIS software design and on software engineering. Methods and tools are needed for quick and robust adaptation of systems to health care processes and changing requirements.

The development of Drink Less: an alcohol reduction smartphone app for excessive drinkers.

PubMed

Garnett, Claire; Crane, David; West, Robert; Brown, Jamie; Michie, Susan

2018-05-04

Excessive alcohol consumption poses a serious problem for public health. Digital behavior change interventions have the potential to help users reduce their drinking. In accordance with Open Science principles, this paper describes the development of a smartphone app to help individuals who drink excessively to reduce their alcohol consumption. Following the UK Medical Research Council's guidance and the Multiphase Optimization Strategy, development consisted of two phases: (i) selection of intervention components and (ii) design and development work to implement the chosen components into modules to be evaluated further for inclusion in the app. Phase 1 involved a scoping literature review, expert consensus study and content analysis of existing alcohol apps. Findings were integrated within a broad model of behavior change (Capability, Opportunity, Motivation-Behavior). Phase 2 involved a highly iterative process and used the "Person-Based" approach to promote engagement. From Phase 1, five intervention components were selected: (i) Normative Feedback, (ii) Cognitive Bias Re-training, (iii) Self-monitoring and Feedback, (iv) Action Planning, and (v) Identity Change. Phase 2 indicated that each of these components presented different challenges for implementation as app modules; all required multiple iterations and design changes to arrive at versions that would be suitable for inclusion in a subsequent evaluation study. The development of the Drink Less app involved a thorough process of component identification with a scoping literature review, expert consensus, and review of other apps. Translation of the components into app modules required a highly iterative process involving user testing and design modification.

Chicago Classification Criteria of Esophageal Motility Disorders Defined in High Resolution Esophageal Pressure Topography (EPT)†

PubMed Central

Bredenoord, Albert J; Fox, Mark; Kahrilas, Peter J; Pandolfino, John E; Schwizer, Werner; Smout, AJPM; Conklin, Jeffrey L; Cook, Ian J; Gyawali, Prakash; Hebbard, Geoffrey; Holloway, Richard H; Ke, Meiyun; Keller, Jutta; Mittal, Ravinder K; Peters, Jeff; Richter, Joel; Roman, Sabine; Rommel, Nathalie; Sifrim, Daniel; Tutuian, Radu; Valdovinos, Miguel; Vela, Marcelo F; Zerbib, Frank

2011-01-01

Background The Chicago Classification of esophageal motility was developed to facilitate the interpretation of clinical high resolution esophageal pressure topography (EPT) studies, concurrent with the widespread adoption of this technology into clinical practice. The Chicago Classification has been, and will continue to be, an evolutionary process, molded first by published evidence pertinent to the clinical interpretation of high resolution manometry (HRM) studies and secondarily by group experience when suitable evidence is lacking. Methods This publication summarizes the state of our knowledge as of the most recent meeting of the International High Resolution Manometry Working Group in Ascona, Switzerland in April 2011. The prior iteration of the Chicago Classification was updated through a process of literature analysis and discussion. Key Results The major changes in this document from the prior iteration are largely attributable to research studies published since the prior iteration, in many cases research conducted in response to prior deliberations of the International High Resolution Manometry Working Group. The classification now includes criteria for subtyping achalasia, EGJ outflow obstruction, motility disorders not observed in normal subjects (Distal esophageal spasm, Hypercontractile esophagus, and Absent peristalsis), and statistically defined peristaltic abnormalities (Weak peristalsis, Frequent failed peristalsis, Rapid contractions with normal latency, and Hypertensive peristalsis). Conclusions & Inferences The Chicago Classification is an algorithmic scheme for diagnosis of esophageal motility disorders from clinical EPT studies. Moving forward, we anticipate continuing this process with increased emphasis placed on natural history studies and outcome data based on the classification. PMID:22248109

Chicago classification criteria of esophageal motility disorders defined in high resolution esophageal pressure topography.

PubMed

Bredenoord, A J; Fox, M; Kahrilas, P J; Pandolfino, J E; Schwizer, W; Smout, A J P M

2012-03-01

The Chicago Classification of esophageal motility was developed to facilitate the interpretation of clinical high resolution esophageal pressure topography (EPT) studies, concurrent with the widespread adoption of this technology into clinical practice. The Chicago Classification has been an evolutionary process, molded first by published evidence pertinent to the clinical interpretation of high resolution manometry (HRM) studies and secondarily by group experience when suitable evidence is lacking. This publication summarizes the state of our knowledge as of the most recent meeting of the International High Resolution Manometry Working Group in Ascona, Switzerland in April 2011. The prior iteration of the Chicago Classification was updated through a process of literature analysis and discussion. The major changes in this document from the prior iteration are largely attributable to research studies published since the prior iteration, in many cases research conducted in response to prior deliberations of the International High Resolution Manometry Working Group. The classification now includes criteria for subtyping achalasia, EGJ outflow obstruction, motility disorders not observed in normal subjects (Distal esophageal spasm, Hypercontractile esophagus, and Absent peristalsis), and statistically defined peristaltic abnormalities (Weak peristalsis, Frequent failed peristalsis, Rapid contractions with normal latency, and Hypertensive peristalsis). The Chicago Classification is an algorithmic scheme for diagnosis of esophageal motility disorders from clinical EPT studies. Moving forward, we anticipate continuing this process with increased emphasis placed on natural history studies and outcome data based on the classification. © 2012 Blackwell Publishing Ltd.

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.

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.

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.

A Model and Simple Iterative Algorithm for Redundancy Analysis.

ERIC Educational Resources Information Center

Fornell, Claes; And Others

1988-01-01

This paper shows that redundancy maximization with J. K. Johansson's extension can be accomplished via a simple iterative algorithm based on H. Wold's Partial Least Squares. The model and the iterative algorithm for the least squares approach to redundancy maximization are presented. (TJH)

Iterative Nonlocal Total Variation Regularization Method for Image Restoration

PubMed Central

Xu, Huanyu; Sun, Quansen; Luo, Nan; Cao, Guo; Xia, Deshen

2013-01-01

In this paper, a Bregman iteration based total variation image restoration algorithm is proposed. Based on the Bregman iteration, the algorithm splits the original total variation problem into sub-problems that are easy to solve. Moreover, non-local regularization is introduced into the proposed algorithm, and a method to choose the non-local filter parameter locally and adaptively is proposed. Experiment results show that the proposed algorithms outperform some other regularization methods. PMID:23776560

Iterative channel decoding of FEC-based multiple-description codes.

PubMed

Chang, Seok-Ho; Cosman, Pamela C; Milstein, Laurence B

2012-03-01

Multiple description coding has been receiving attention as a robust transmission framework for multimedia services. This paper studies the iterative decoding of FEC-based multiple description codes. The proposed decoding algorithms take advantage of the error detection capability of Reed-Solomon (RS) erasure codes. The information of correctly decoded RS codewords is exploited to enhance the error correction capability of the Viterbi algorithm at the next iteration of decoding. In the proposed algorithm, an intradescription interleaver is synergistically combined with the iterative decoder. The interleaver does not affect the performance of noniterative decoding but greatly enhances the performance when the system is iteratively decoded. We also address the optimal allocation of RS parity symbols for unequal error protection. For the optimal allocation in iterative decoding, we derive mathematical equations from which the probability distributions of description erasures can be generated in a simple way. The performance of the algorithm is evaluated over an orthogonal frequency-division multiplexing system. The results show that the performance of the multiple description codes is significantly enhanced.

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).

Fully iterative scatter corrected digital breast tomosynthesis using GPU-based fast Monte Carlo simulation and composition ratio update

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

Kim, Kyungsang; Ye, Jong Chul, E-mail: jong.ye@kaist.ac.kr; Lee, Taewon

2015-09-15

Purpose: In digital breast tomosynthesis (DBT), scatter correction is highly desirable, as it improves image quality at low doses. Because the DBT detector panel is typically stationary during the source rotation, antiscatter grids are not generally compatible with DBT; thus, a software-based scatter correction is required. This work proposes a fully iterative scatter correction method that uses a novel fast Monte Carlo simulation (MCS) with a tissue-composition ratio estimation technique for DBT imaging. Methods: To apply MCS to scatter estimation, the material composition in each voxel should be known. To overcome the lack of prior accurate knowledge of tissue compositionmore » for DBT, a tissue-composition ratio is estimated based on the observation that the breast tissues are principally composed of adipose and glandular tissues. Using this approximation, the composition ratio can be estimated from the reconstructed attenuation coefficients, and the scatter distribution can then be estimated by MCS using the composition ratio. The scatter estimation and image reconstruction procedures can be performed iteratively until an acceptable accuracy is achieved. For practical use, (i) the authors have implemented a fast MCS using a graphics processing unit (GPU), (ii) the MCS is simplified to transport only x-rays in the energy range of 10–50 keV, modeling Rayleigh and Compton scattering and the photoelectric effect using the tissue-composition ratio of adipose and glandular tissues, and (iii) downsampling is used because the scatter distribution varies rather smoothly. Results: The authors have demonstrated that the proposed method can accurately estimate the scatter distribution, and that the contrast-to-noise ratio of the final reconstructed image is significantly improved. The authors validated the performance of the MCS by changing the tissue thickness, composition ratio, and x-ray energy. The authors confirmed that the tissue-composition ratio estimation was quite accurate under a variety of conditions. Our GPU-based fast MCS implementation took approximately 3 s to generate each angular projection for a 6 cm thick breast, which is believed to make this process acceptable for clinical applications. In addition, the clinical preferences of three radiologists were evaluated; the preference for the proposed method compared to the preference for the convolution-based method was statistically meaningful (p < 0.05, McNemar test). Conclusions: The proposed fully iterative scatter correction method and the GPU-based fast MCS using tissue-composition ratio estimation successfully improved the image quality within a reasonable computational time, which may potentially increase the clinical utility of DBT.« less

Optimization applications in aircraft engine design and test

NASA Technical Reports Server (NTRS)

Pratt, T. K.

1984-01-01

Starting with the NASA-sponsored STAEBL program, optimization methods based primarily upon the versatile program COPES/CONMIN were introduced over the past few years to a broad spectrum of engineering problems in structural optimization, engine design, engine test, and more recently, manufacturing processes. By automating design and testing processes, many repetitive and costly trade-off studies have been replaced by optimization procedures. Rather than taking engineers and designers out of the loop, optimization has, in fact, put them more in control by providing sophisticated search techniques. The ultimate decision whether to accept or reject an optimal feasible design still rests with the analyst. Feedback obtained from this decision process has been invaluable since it can be incorporated into the optimization procedure to make it more intelligent. On several occasions, optimization procedures have produced novel designs, such as the nonsymmetric placement of rotor case stiffener rings, not anticipated by engineering designers. In another case, a particularly difficult resonance contraint could not be satisfied using hand iterations for a compressor blade, when the STAEBL program was applied to the problem, a feasible solution was obtained in just two iterations.

Reducing sick leave of Dutch vocational school students: adaptation of a sick leave protocol using the intervention mapping process.

PubMed

de Kroon, Marlou L A; Bulthuis, Jozien; Mulder, Wico; Schaafsma, Frederieke G; Anema, Johannes R

2016-12-01

Since the extent of sick leave and the problems of vocational school students are relatively large, we aimed to tailor a sick leave protocol at Dutch lower secondary education schools to the particular context of vocational schools. Four steps of the iterative process of Intervention Mapping (IM) to adapt this protocol were carried out: (1) performing a needs assessment and defining a program objective, (2) determining the performance and change objectives, (3) identifying theory-based methods and practical strategies and (4) developing a program plan. Interviews with students using structured questionnaires, in-depth interviews with relevant stakeholders, a literature research and, finally, a pilot implementation were carried out. A sick leave protocol was developed that was feasible and acceptable for all stakeholders. The main barriers for widespread implementation are time constraints in both monitoring and acting upon sick leave by school and youth health care. The iterative process of IM has shown its merits in the adaptation of the manual 'A quick return to school is much better' to a sick leave protocol for vocational school students.

Spectral-element simulations of wave propagation in complex exploration-industry models: Imaging and adjoint tomography

NASA Astrophysics Data System (ADS)

Luo, Y.; Nissen-Meyer, T.; Morency, C.; Tromp, J.

2008-12-01

Seismic imaging in the exploration industry is often based upon ray-theoretical migration techniques (e.g., Kirchhoff) or other ideas which neglect some fraction of the seismic wavefield (e.g., wavefield continuation for acoustic-wave first arrivals) in the inversion process. In a companion paper we discuss the possibility of solving the full physical forward problem (i.e., including visco- and poroelastic, anisotropic media) using the spectral-element method. With such a tool at hand, we can readily apply the adjoint method to tomographic inversions, i.e., iteratively improving an initial 3D background model to fit the data. In the context of this inversion process, we draw connections between kernels in adjoint tomography and basic imaging principles in migration. We show that the images obtained by migration are nothing but particular kinds of adjoint kernels (mainly density kernels). Migration is basically a first step in the iterative inversion process of adjoint tomography. We apply the approach to basic 2D problems involving layered structures, overthrusting faults, topography, salt domes, and poroelastic regions.

Capture and isotopic exchange method for water and hydrogen isotopes on zeolite catalysts up to technical scale for pre-study of processing highly tritiated water

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

Michling, R.; Braun, A.; Cristescu, I.

2015-03-15

Highly tritiated water (HTW) may be generated at ITER by various processes and, due to the excessive radio toxicity, the self-radiolysis and the exceedingly corrosive property of HTW, a potential hazard is associated with its storage and process. Therefore, the capture and exchange method for HTW utilizing Molecular Sieve Beds (MSB) was investigated in view of adsorption capacity, isotopic exchange performance and process parameters. For the MSB, different types of zeolite were selected. All zeolite materials were additionally coated with platinum. The following work comprised the selection of the most efficient zeolite candidate based on detailed parametric studies during themore » H{sub 2}/D{sub 2}O laboratory scale exchange experiments (about 25 g zeolite per bed) at the Tritium Laboratory Karlsruhe (TLK). For the zeolite, characterization analytical techniques such as Infrared Spectroscopy, Thermogravimetry and online mass spectrometry were implemented. Followed by further investigation of the selected zeolite catalyst under full technical operation, a MSB (about 22 kg zeolite) was processed with hydrogen flow rates up to 60 mol*h{sup -1} and deuterated water loads up to 1.6 kg in view of later ITER processing of arising HTW. (authors)« less

Baseline Architecture of ITER Control System

NASA Astrophysics Data System (ADS)

Wallander, A.; Di Maio, F.; Journeaux, J.-Y.; Klotz, W.-D.; Makijarvi, P.; Yonekawa, I.

2011-08-01

The control system of ITER consists of thousands of computers processing hundreds of thousands of signals. The control system, being the primary tool for operating the machine, shall integrate, control and coordinate all these computers and signals and allow a limited number of staff to operate the machine from a central location with minimum human intervention. The primary functions of the ITER control system are plant control, supervision and coordination, both during experimental pulses and 24/7 continuous operation. The former can be split in three phases; preparation of the experiment by defining all parameters; executing the experiment including distributed feed-back control and finally collecting, archiving, analyzing and presenting all data produced by the experiment. We define the control system as a set of hardware and software components with well defined characteristics. The architecture addresses the organization of these components and their relationship to each other. We distinguish between physical and functional architecture, where the former defines the physical connections and the latter the data flow between components. In this paper, we identify the ITER control system based on the plant breakdown structure. Then, the control system is partitioned into a workable set of bounded subsystems. This partition considers at the same time the completeness and the integration of the subsystems. The components making up subsystems are identified and defined, a naming convention is introduced and the physical networks defined. Special attention is given to timing and real-time communication for distributed control. Finally we discuss baseline technologies for implementing the proposed architecture based on analysis, market surveys, prototyping and benchmarking carried out during the last year.

A protection system for the JET ITER-like wall based on imaging diagnostics.

PubMed

Arnoux, G; Devaux, S; Alves, D; Balboa, I; Balorin, C; Balshaw, N; Beldishevski, M; Carvalho, P; Clever, M; Cramp, S; de Pablos, J-L; de la Cal, E; Falie, D; Garcia-Sanchez, P; Felton, R; Gervaise, V; Goodyear, A; Horton, A; Jachmich, S; Huber, A; Jouve, M; Kinna, D; Kruezi, U; Manzanares, A; Martin, V; McCullen, P; Moncada, V; Obrejan, K; Patel, K; Lomas, P J; Neto, A; Rimini, F; Ruset, C; Schweer, B; Sergienko, G; Sieglin, B; Soleto, A; Stamp, M; Stephen, A; Thomas, P D; Valcárcel, D F; Williams, J; Wilson, J; Zastrow, K-D

2012-10-01

The new JET ITER-like wall (made of beryllium and tungsten) is more fragile than the former carbon fiber composite wall and requires active protection to prevent excessive heat loads on the plasma facing components (PFC). Analog CCD cameras operating in the near infrared wavelength are used to measure surface temperature of the PFCs. Region of interest (ROI) analysis is performed in real time and the maximum temperature measured in each ROI is sent to the vessel thermal map. The protection of the ITER-like wall system started in October 2011 and has already successfully led to a safe landing of the plasma when hot spots were observed on the Be main chamber PFCs. Divertor protection is more of a challenge due to dust deposits that often generate false hot spots. In this contribution we describe the camera, data capture and real time processing systems. We discuss the calibration strategy for the temperature measurements with cross validation with thermal IR cameras and bi-color pyrometers. Most importantly, we demonstrate that a protection system based on CCD cameras can work and show examples of hot spot detections that stop the plasma pulse. The limits of such a design and the associated constraints on the operations are also presented.

Effect of Low-Dose MDCT and Iterative Reconstruction on Trabecular Bone Microstructure Assessment.

PubMed

Kopp, Felix K; Holzapfel, Konstantin; Baum, Thomas; Nasirudin, Radin A; Mei, Kai; Garcia, Eduardo G; Burgkart, Rainer; Rummeny, Ernst J; Kirschke, Jan S; Noël, Peter B

2016-01-01

We investigated the effects of low-dose multi detector computed tomography (MDCT) in combination with statistical iterative reconstruction algorithms on trabecular bone microstructure parameters. Twelve donated vertebrae were scanned with the routine radiation exposure used in our department (standard-dose) and a low-dose protocol. Reconstructions were performed with filtered backprojection (FBP) and maximum-likelihood based statistical iterative reconstruction (SIR). Trabecular bone microstructure parameters were assessed and statistically compared for each reconstruction. Moreover, fracture loads of the vertebrae were biomechanically determined and correlated to the assessed microstructure parameters. Trabecular bone microstructure parameters based on low-dose MDCT and SIR significantly correlated with vertebral bone strength. There was no significant difference between microstructure parameters calculated on low-dose SIR and standard-dose FBP images. However, the results revealed a strong dependency on the regularization strength applied during SIR. It was observed that stronger regularization might corrupt the microstructure analysis, because the trabecular structure is a very small detail that might get lost during the regularization process. As a consequence, the introduction of SIR for trabecular bone microstructure analysis requires a specific optimization of the regularization parameters. Moreover, in comparison to other approaches, superior noise-resolution trade-offs can be found with the proposed methods.

A protection system for the JET ITER-like wall based on imaging diagnosticsa)

NASA Astrophysics Data System (ADS)

Arnoux, G.; Devaux, S.; Alves, D.; Balboa, I.; Balorin, C.; Balshaw, N.; Beldishevski, M.; Carvalho, P.; Clever, M.; Cramp, S.; de Pablos, J.-L.; de la Cal, E.; Falie, D.; Garcia-Sanchez, P.; Felton, R.; Gervaise, V.; Goodyear, A.; Horton, A.; Jachmich, S.; Huber, A.; Jouve, M.; Kinna, D.; Kruezi, U.; Manzanares, A.; Martin, V.; McCullen, P.; Moncada, V.; Obrejan, K.; Patel, K.; Lomas, P. J.; Neto, A.; Rimini, F.; Ruset, C.; Schweer, B.; Sergienko, G.; Sieglin, B.; Soleto, A.; Stamp, M.; Stephen, A.; Thomas, P. D.; Valcárcel, D. F.; Williams, J.; Wilson, J.; Zastrow, K.-D.; JET-EFDA Contributors

2012-10-01

The new JET ITER-like wall (made of beryllium and tungsten) is more fragile than the former carbon fiber composite wall and requires active protection to prevent excessive heat loads on the plasma facing components (PFC). Analog CCD cameras operating in the near infrared wavelength are used to measure surface temperature of the PFCs. Region of interest (ROI) analysis is performed in real time and the maximum temperature measured in each ROI is sent to the vessel thermal map. The protection of the ITER-like wall system started in October 2011 and has already successfully led to a safe landing of the plasma when hot spots were observed on the Be main chamber PFCs. Divertor protection is more of a challenge due to dust deposits that often generate false hot spots. In this contribution we describe the camera, data capture and real time processing systems. We discuss the calibration strategy for the temperature measurements with cross validation with thermal IR cameras and bi-color pyrometers. Most importantly, we demonstrate that a protection system based on CCD cameras can work and show examples of hot spot detections that stop the plasma pulse. The limits of such a design and the associated constraints on the operations are also presented.

Targeted exploration and analysis of large cross-platform human transcriptomic compendia

PubMed Central

Zhu, Qian; Wong, Aaron K; Krishnan, Arjun; Aure, Miriam R; Tadych, Alicja; Zhang, Ran; Corney, David C; Greene, Casey S; Bongo, Lars A; Kristensen, Vessela N; Charikar, Moses; Li, Kai; Troyanskaya, Olga G.

2016-01-01

We present SEEK (http://seek.princeton.edu), a query-based search engine across very large transcriptomic data collections, including thousands of human data sets from almost 50 microarray and next-generation sequencing platforms. SEEK uses a novel query-level cross-validation-based algorithm to automatically prioritize data sets relevant to the query and a robust search approach to identify query-coregulated genes, pathways, and processes. SEEK provides cross-platform handling, multi-gene query search, iterative metadata-based search refinement, and extensive visualization-based analysis options. PMID:25581801

Feature-based three-dimensional registration for repetitive geometry in machine vision

PubMed Central

Gong, Yuanzheng; Seibel, Eric J.

2016-01-01

As an important step in three-dimensional (3D) machine vision, 3D registration is a process of aligning two or multiple 3D point clouds that are collected from different perspectives together into a complete one. The most popular approach to register point clouds is to minimize the difference between these point clouds iteratively by Iterative Closest Point (ICP) algorithm. However, ICP does not work well for repetitive geometries. To solve this problem, a feature-based 3D registration algorithm is proposed to align the point clouds that are generated by vision-based 3D reconstruction. By utilizing texture information of the object and the robustness of image features, 3D correspondences can be retrieved so that the 3D registration of two point clouds is to solve a rigid transformation. The comparison of our method and different ICP algorithms demonstrates that our proposed algorithm is more accurate, efficient and robust for repetitive geometry registration. Moreover, this method can also be used to solve high depth uncertainty problem caused by little camera baseline in vision-based 3D reconstruction. PMID:28286703

Parallelizing flow-accumulation calculations on graphics processing units—From iterative DEM preprocessing algorithm to recursive multiple-flow-direction algorithm

NASA Astrophysics Data System (ADS)

Qin, Cheng-Zhi; Zhan, Lijun

2012-06-01

As one of the important tasks in digital terrain analysis, the calculation of flow accumulations from gridded digital elevation models (DEMs) usually involves two steps in a real application: (1) using an iterative DEM preprocessing algorithm to remove the depressions and flat areas commonly contained in real DEMs, and (2) using a recursive flow-direction algorithm to calculate the flow accumulation for every cell in the DEM. Because both algorithms are computationally intensive, quick calculation of the flow accumulations from a DEM (especially for a large area) presents a practical challenge to personal computer (PC) users. In recent years, rapid increases in hardware capacity of the graphics processing units (GPUs) provided in modern PCs have made it possible to meet this challenge in a PC environment. Parallel computing on GPUs using a compute-unified-device-architecture (CUDA) programming model has been explored to speed up the execution of the single-flow-direction algorithm (SFD). However, the parallel implementation on a GPU of the multiple-flow-direction (MFD) algorithm, which generally performs better than the SFD algorithm, has not been reported. Moreover, GPU-based parallelization of the DEM preprocessing step in the flow-accumulation calculations has not been addressed. This paper proposes a parallel approach to calculate flow accumulations (including both iterative DEM preprocessing and a recursive MFD algorithm) on a CUDA-compatible GPU. For the parallelization of an MFD algorithm (MFD-md), two different parallelization strategies using a GPU are explored. The first parallelization strategy, which has been used in the existing parallel SFD algorithm on GPU, has the problem of computing redundancy. Therefore, we designed a parallelization strategy based on graph theory. The application results show that the proposed parallel approach to calculate flow accumulations on a GPU performs much faster than either sequential algorithms or other parallel GPU-based algorithms based on existing parallelization strategies.

Overview of International Thermonuclear Experimental Reactor (ITER) engineering design activities*

NASA Astrophysics Data System (ADS)

Shimomura, Y.

1994-05-01

The International Thermonuclear Experimental Reactor (ITER) [International Thermonuclear Experimental Reactor (ITER) (International Atomic Energy Agency, Vienna, 1988), ITER Documentation Series, No. 1] project is a multiphased project, presently proceeding under the auspices of the International Atomic Energy Agency according to the terms of a four-party agreement among the European Atomic Energy Community (EC), the Government of Japan (JA), the Government of the Russian Federation (RF), and the Government of the United States (US), ``the Parties.'' The ITER project is based on the tokamak, a Russian invention, and has since been brought to a high level of development in all major fusion programs in the world. The objective of ITER is to demonstrate the scientific and technological feasibility of fusion energy for peaceful purposes. The ITER design is being developed, with support from the Parties' four Home Teams and is in progress by the Joint Central Team. An overview of ITER Design activities is presented.

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.

Optimal tracking control for a class of nonlinear discrete-time systems with time delays based on heuristic dynamic programming.

PubMed

Zhang, Huaguang; Song, Ruizhuo; Wei, Qinglai; Zhang, Tieyan

2011-12-01

In this paper, a novel heuristic dynamic programming (HDP) iteration algorithm is proposed to solve the optimal tracking control problem for a class of nonlinear discrete-time systems with time delays. The novel algorithm contains state updating, control policy iteration, and performance index iteration. To get the optimal states, the states are also updated. Furthermore, the "backward iteration" is applied to state updating. Two neural networks are used to approximate the performance index function and compute the optimal control policy for facilitating the implementation of HDP iteration algorithm. At last, we present two examples to demonstrate the effectiveness of the proposed HDP iteration algorithm.

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.

The Iterative Research Cycle: Process-Based Model Evaluation

NASA Astrophysics Data System (ADS)

Vrugt, J. A.

2014-12-01

The ever increasing pace of computational power, along with continued advances in measurement technologies and improvements in process understanding has stimulated the development of increasingly complex physics based models that simulate a myriad of processes at different spatial and temporal scales. Reconciling these high-order system models with perpetually larger volumes of field data is becoming more and more difficult, particularly because classical likelihood-based fitting methods lack the power to detect and pinpoint deficiencies in the model structure. In this talk I will give an overview of our latest research on process-based model calibration and evaluation. This approach, rooted in Bayesian theory, uses summary metrics of the calibration data rather than the data itself to help detect which component(s) of the model is (are) malfunctioning and in need of improvement. A few case studies involving hydrologic and geophysical models will be used to demonstrate the proposed methodology.

Through-Flow Calculations in Axial Turbomachinery

DTIC Science & Technology

1976-10-01

coilditions should be next on the agenda. Authors’ response: I think the process is essentially iterative between SI and S2 solutions. If SI surfaces...secondary flows in high Mach number situations. Concerning Gelder’s approach, i think that your remark is rather optimistic. We use a method based on...my remarks on Gelder’s work were based on calculations made by Gelder himself. One or two other people have managed to get the calculation through

Iterative Processes and Reciprocal Controlling Relationships in a Systemic Intervention

ERIC Educational Resources Information Center

Krapfl, Jon E.; Cooke, John; Sullivan, Timothy; Cogar, William

2009-01-01

This account describes the total reengineering of an organization with the attendant changes to the culture, the nature of the work, the rethinking of the organizational purpose, and the identification of a new customer base and new concepts of how the organization will reach it. The case is presented not as scientific research but as a case of…

Addressing the Barriers to Agile Development in DoD

DTIC Science & Technology

2015-05-01

Acquisition Small, Frequent Releases Iteratively Developed Review Working Software Vice Extensive Docs Responsive to Changes...Distribution Unlimited. Case Number 15-1457’ JCIDS IT Box Model  Streamlined requirements process for software >$15M  JROC approves IS-ICD...Services (FAR Part 37) Product-based Pay for the time and expertise of an Agile development contractor Contract for a defined software delivery

Pipeline Processing With an Iterative, Context-Based Detection Model

DTIC Science & Technology

2015-04-19

pattern detectors , correlation detectors , subspace detectors , matched field detectors , nuclear explosion monitoring 16. SECURITY CLASSIFICATION OF: 17...38 13. 3 days of SPAO-BHZ data which is dominated by signals from nearby icequakes. .... 39 14. (Top) 94 detections produced by detector ...92532 and (bottom) 148 detections from detector 92541 produced during the first run of the framework. .................................. 40 15. The 49

MODEL-Based Methodology for System of Systems Architecture Development with Application to the Recapitalization of the Future Towing and Salvage Platform

DTIC Science & Technology

2008-09-01

SEP) is a comprehensive , iterative and recursive problem solving process, applied sequentially top-down by integrated teams. It transforms needs...central integrated design repository. It includes a comprehensive behavior modeling notation to understand the dynamics of a design. CORE is a MBSE...37 F. DYNAMIC POSITIONING..........................................................................38 G. FIREFIGHTING

Distant Supervision with Transductive Learning for Adverse Drug Reaction Identification from Electronic Medical Records

PubMed Central

Ikeda, Mitsuru

2017-01-01

Information extraction and knowledge discovery regarding adverse drug reaction (ADR) from large-scale clinical texts are very useful and needy processes. Two major difficulties of this task are the lack of domain experts for labeling examples and intractable processing of unstructured clinical texts. Even though most previous works have been conducted on these issues by applying semisupervised learning for the former and a word-based approach for the latter, they face with complexity in an acquisition of initial labeled data and ignorance of structured sequence of natural language. In this study, we propose automatic data labeling by distant supervision where knowledge bases are exploited to assign an entity-level relation label for each drug-event pair in texts, and then, we use patterns for characterizing ADR relation. The multiple-instance learning with expectation-maximization method is employed to estimate model parameters. The method applies transductive learning to iteratively reassign a probability of unknown drug-event pair at the training time. By investigating experiments with 50,998 discharge summaries, we evaluate our method by varying large number of parameters, that is, pattern types, pattern-weighting models, and initial and iterative weightings of relations for unlabeled data. Based on evaluations, our proposed method outperforms the word-based feature for NB-EM (iEM), MILR, and TSVM with F1 score of 11.3%, 9.3%, and 6.5% improvement, respectively. PMID:29090077

Anatomical-based partial volume correction for low-dose dedicated cardiac SPECT/CT

NASA Astrophysics Data System (ADS)

Liu, Hui; Chan, Chung; Grobshtein, Yariv; Ma, Tianyu; Liu, Yaqiang; Wang, Shi; Stacy, Mitchel R.; Sinusas, Albert J.; Liu, Chi

2015-09-01

Due to the limited spatial resolution, partial volume effect has been a major degrading factor on quantitative accuracy in emission tomography systems. This study aims to investigate the performance of several anatomical-based partial volume correction (PVC) methods for a dedicated cardiac SPECT/CT system (GE Discovery NM/CT 570c) with focused field-of-view over a clinically relevant range of high and low count levels for two different radiotracer distributions. These PVC methods include perturbation geometry transfer matrix (pGTM), pGTM followed by multi-target correction (MTC), pGTM with known concentration in blood pool, the former followed by MTC and our newly proposed methods, which perform the MTC method iteratively, where the mean values in all regions are estimated and updated by the MTC-corrected images each time in the iterative process. The NCAT phantom was simulated for cardiovascular imaging with 99mTc-tetrofosmin, a myocardial perfusion agent, and 99mTc-red blood cell (RBC), a pure intravascular imaging agent. Images were acquired at six different count levels to investigate the performance of PVC methods in both high and low count levels for low-dose applications. We performed two large animal in vivo cardiac imaging experiments following injection of 99mTc-RBC for evaluation of intramyocardial blood volume (IMBV). The simulation results showed our proposed iterative methods provide superior performance than other existing PVC methods in terms of image quality, quantitative accuracy, and reproducibility (standard deviation), particularly for low-count data. The iterative approaches are robust for both 99mTc-tetrofosmin perfusion imaging and 99mTc-RBC imaging of IMBV and blood pool activity even at low count levels. The animal study results indicated the effectiveness of PVC to correct the overestimation of IMBV due to blood pool contamination. In conclusion, the iterative PVC methods can achieve more accurate quantification, particularly for low count cardiac SPECT studies, typically obtained from low-dose protocols, gated studies, and dynamic applications.

An Iterative Closest Points Algorithm for Registration of 3D Laser Scanner Point Clouds with Geometric Features.

PubMed

He, Ying; Liang, Bin; Yang, Jun; Li, Shunzhi; He, Jin

2017-08-11

The Iterative Closest Points (ICP) algorithm is the mainstream algorithm used in the process of accurate registration of 3D point cloud data. The algorithm requires a proper initial value and the approximate registration of two point clouds to prevent the algorithm from falling into local extremes, but in the actual point cloud matching process, it is difficult to ensure compliance with this requirement. In this paper, we proposed the ICP algorithm based on point cloud features (GF-ICP). This method uses the geometrical features of the point cloud to be registered, such as curvature, surface normal and point cloud density, to search for the correspondence relationships between two point clouds and introduces the geometric features into the error function to realize the accurate registration of two point clouds. The experimental results showed that the algorithm can improve the convergence speed and the interval of convergence without setting a proper initial value.

An Iterative Closest Points Algorithm for Registration of 3D Laser Scanner Point Clouds with Geometric Features

PubMed Central

Liang, Bin; Yang, Jun; Li, Shunzhi; He, Jin

2017-01-01

The Iterative Closest Points (ICP) algorithm is the mainstream algorithm used in the process of accurate registration of 3D point cloud data. The algorithm requires a proper initial value and the approximate registration of two point clouds to prevent the algorithm from falling into local extremes, but in the actual point cloud matching process, it is difficult to ensure compliance with this requirement. In this paper, we proposed the ICP algorithm based on point cloud features (GF-ICP). This method uses the geometrical features of the point cloud to be registered, such as curvature, surface normal and point cloud density, to search for the correspondence relationships between two point clouds and introduces the geometric features into the error function to realize the accurate registration of two point clouds. The experimental results showed that the algorithm can improve the convergence speed and the interval of convergence without setting a proper initial value. PMID:28800096

Phase retrieval in annulus sector domain by non-iterative methods

NASA Astrophysics Data System (ADS)

Wang, Xiao; Mao, Heng; Zhao, Da-zun

2008-03-01

Phase retrieval could be achieved by solving the intensity transport equation (ITE) under the paraxial approximation. For the case of uniform illumination, Neumann boundary condition is involved and it makes the solving process more complicated. The primary mirror is usually designed segmented in the telescope with large aperture, and the shape of a segmented piece is often like an annulus sector. Accordingly, It is necessary to analyze the phase retrieval in the annulus sector domain. Two non-iterative methods are considered for recovering the phase. The matrix method is based on the decomposition of the solution into a series of orthogonalized polynomials, while the frequency filtering method depends on the inverse computation process of ITE. By the simulation, it is found that both methods can eliminate the effect of Neumann boundary condition, save a lot of computation time and recover the distorted phase well. The wavefront error (WFE) RMS can be less than 0.05 wavelength, even when some noise is added.

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…

Technical Note: FreeCT_ICD: An Open Source Implementation of a Model-Based Iterative Reconstruction Method using Coordinate Descent Optimization for CT Imaging Investigations.

PubMed

Hoffman, John M; Noo, Frédéric; Young, Stefano; Hsieh, Scott S; McNitt-Gray, Michael

2018-06-01

To facilitate investigations into the impacts of acquisition and reconstruction parameters on quantitative imaging, radiomics and CAD using CT imaging, we previously released an open source implementation of a conventional weighted filtered backprojection reconstruction called FreeCT_wFBP. Our purpose was to extend that work by providing an open-source implementation of a model-based iterative reconstruction method using coordinate descent optimization, called FreeCT_ICD. Model-based iterative reconstruction offers the potential for substantial radiation dose reduction, but can impose substantial computational processing and storage requirements. FreeCT_ICD is an open source implementation of a model-based iterative reconstruction method that provides a reasonable tradeoff between these requirements. This was accomplished by adapting a previously proposed method that allows the system matrix to be stored with a reasonable memory requirement. The method amounts to describing the attenuation coefficient using rotating slices that follow the helical geometry. In the initially-proposed version, the rotating slices are themselves described using blobs. We have replaced this description by a unique model that relies on tri-linear interpolation together with the principles of Joseph's method. This model offers an improvement in memory requirement while still allowing highly accurate reconstruction for conventional CT geometries. The system matrix is stored column-wise and combined with an iterative coordinate descent (ICD) optimization. The result is FreeCT_ICD, which is a reconstruction program developed on the Linux platform using C++ libraries and the open source GNU GPL v2.0 license. The software is capable of reconstructing raw projection data of helical CT scans. In this work, the software has been described and evaluated by reconstructing datasets exported from a clinical scanner which consisted of an ACR accreditation phantom dataset and a clinical pediatric thoracic scan. For the ACR phantom, image quality was comparable to clinical reconstructions as well as reconstructions using open-source FreeCT_wFBP software. The pediatric thoracic scan also yielded acceptable results. In addition, we did not observe any deleterious impact in image quality associated with the utilization of rotating slices. These evaluations also demonstrated reasonable tradeoffs in storage requirements and computational demands. FreeCT_ICD is an open-source implementation of a model-based iterative reconstruction method that extends the capabilities of previously released open source reconstruction software and provides the ability to perform vendor-independent reconstructions of clinically acquired raw projection data. This implementation represents a reasonable tradeoff between storage and computational requirements and has demonstrated acceptable image quality in both simulated and clinical image datasets. This article is protected by copyright. All rights reserved. This article is protected by copyright. All rights reserved.

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.

Varying-energy CT imaging method based on EM-TV

NASA Astrophysics Data System (ADS)

Chen, Ping; Han, Yan

2016-11-01

For complicated structural components with wide x-ray attenuation ranges, conventional fixed-energy computed tomography (CT) imaging cannot obtain all the structural information. This limitation results in a shortage of CT information because the effective thickness of the components along the direction of x-ray penetration exceeds the limit of the dynamic range of the x-ray imaging system. To address this problem, a varying-energy x-ray CT imaging method is proposed. In this new method, the tube voltage is adjusted several times with the fixed lesser interval. Next, the fusion of grey consistency and logarithm demodulation are applied to obtain full and lower noise projection with a high dynamic range (HDR). In addition, for the noise suppression problem of the analytical method, EM-TV (expectation maximization-total Jvariation) iteration reconstruction is used. In the process of iteration, the reconstruction result obtained at one x-ray energy is used as the initial condition of the next iteration. An accompanying experiment demonstrates that this EM-TV reconstruction can also extend the dynamic range of x-ray imaging systems and provide a higher reconstruction quality relative to the fusion reconstruction method.

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

An algebraic iterative reconstruction technique for differential X-ray phase-contrast computed tomography.

PubMed

Fu, Jian; Schleede, Simone; Tan, Renbo; Chen, Liyuan; Bech, Martin; Achterhold, Klaus; Gifford, Martin; Loewen, Rod; Ruth, Ronald; Pfeiffer, Franz

2013-09-01

Iterative reconstruction has a wide spectrum of proven advantages in the field of conventional X-ray absorption-based computed tomography (CT). In this paper, we report on an algebraic iterative reconstruction technique for grating-based differential phase-contrast CT (DPC-CT). Due to the differential nature of DPC-CT projections, a differential operator and a smoothing operator are added to the iterative reconstruction, compared to the one commonly used for absorption-based CT data. This work comprises a numerical study of the algorithm and its experimental verification using a dataset measured at a two-grating interferometer setup. Since the algorithm is easy to implement and allows for the extension to various regularization possibilities, we expect a significant impact of the method for improving future medical and industrial DPC-CT applications. Copyright © 2012. Published by Elsevier GmbH.

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

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.

Improving Access to Care for Warfighters: Virtual Worlds Technology to Enhance Primary Care Training in Post-Traumatic Stress and Motivational Interviewing

DTIC Science & Technology

2017-10-01

chronic mental and physical health problems. Therefore, the project aims to: (1) iteratively design a new web-based PTS and Motivational Interviewing...result in missed opportunities to intervene to prevent chronic mental and physical health problems. The project aims are to: (1) iteratively design a new...intervene to prevent chronic mental and physical health problems. We propose to: (1) Iteratively design a new web-based PTS and Motivational

Image enhancement in positron emission mammography

NASA Astrophysics Data System (ADS)

Slavine, Nikolai V.; Seiler, Stephen; McColl, Roderick W.; Lenkinski, Robert E.

2017-02-01

Purpose: To evaluate an efficient iterative deconvolution method (RSEMD) for improving the quantitative accuracy of previously reconstructed breast images by commercial positron emission mammography (PEM) scanner. Materials and Methods: The RSEMD method was tested on breast phantom data and clinical PEM imaging data. Data acquisition was performed on a commercial Naviscan Flex Solo II PEM camera. This method was applied to patient breast images previously reconstructed with Naviscan software (MLEM) to determine improvements in resolution, signal to noise ratio (SNR) and contrast to noise ratio (CNR.) Results: In all of the patients' breast studies the post-processed images proved to have higher resolution and lower noise as compared with images reconstructed by conventional methods. In general, the values of SNR reached a plateau at around 6 iterations with an improvement factor of about 2 for post-processed Flex Solo II PEM images. Improvements in image resolution after the application of RSEMD have also been demonstrated. Conclusions: A rapidly converging, iterative deconvolution algorithm with a novel resolution subsets-based approach RSEMD that operates on patient DICOM images has been used for quantitative improvement in breast imaging. The RSEMD method can be applied to clinical PEM images to improve image quality to diagnostically acceptable levels and will be crucial in order to facilitate diagnosis of tumor progression at the earliest stages. The RSEMD method can be considered as an extended Richardson-Lucy algorithm with multiple resolution levels (resolution subsets).

Implementing partnership-driven clinical federated electronic health record data sharing networks.

PubMed

Stephens, Kari A; Anderson, Nicholas; Lin, Ching-Ping; Estiri, Hossein

2016-09-01

Building federated data sharing architectures requires supporting a range of data owners, effective and validated semantic alignment between data resources, and consistent focus on end-users. Establishing these resources requires development methodologies that support internal validation of data extraction and translation processes, sustaining meaningful partnerships, and delivering clear and measurable system utility. We describe findings from two federated data sharing case examples that detail critical factors, shared outcomes, and production environment results. Two federated data sharing pilot architectures developed to support network-based research associated with the University of Washington's Institute of Translational Health Sciences provided the basis for the findings. A spiral model for implementation and evaluation was used to structure iterations of development and support knowledge share between the two network development teams, which cross collaborated to support and manage common stages. We found that using a spiral model of software development and multiple cycles of iteration was effective in achieving early network design goals. Both networks required time and resource intensive efforts to establish a trusted environment to create the data sharing architectures. Both networks were challenged by the need for adaptive use cases to define and test utility. An iterative cyclical model of development provided a process for developing trust with data partners and refining the design, and supported measureable success in the development of new federated data sharing architectures. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Adapting an in-person patient-caregiver communication intervention to a tailored web-based format.

PubMed

Zulman, Donna M; Schafenacker, Ann; Barr, Kathryn L C; Moore, Ian T; Fisher, Jake; McCurdy, Kathryn; Derry, Holly A; Saunders, Edward W; An, Lawrence C; Northouse, Laurel

2012-03-01

Interventions that target cancer patients and their caregivers have been shown to improve patient-caregiver communication, support, and emotional well-being. To adapt an in-person communication intervention for cancer patients and caregivers to a web-based format, and to examine the usability and acceptability of the web-based program among representative users. A tailored, interactive web-based communication program for cancer patients and their family caregivers was developed based on an existing in-person, nurse-delivered intervention. The development process involved: (1) building a multidisciplinary team of content and web design experts, (2) combining key components of the in-person intervention with the unique tailoring and interactive features of a web-based platform, and (3) conducting focus groups and usability testing to obtain feedback from representative program users at multiple time points. Four focus groups with 2-3 patient-caregiver pairs per group (n = 22 total participants) and two iterations of usability testing with four patient-caregiver pairs per session (n = 16 total participants) were conducted. Response to the program's structure, design, and content was favorable, even among users who were older or had limited computer and Internet experience. The program received high ratings for ease of use and overall usability (mean System Usability Score of 89.5 out of 100). Many elements of a nurse-delivered patient-caregiver intervention can be successfully adapted to a web-based format. A multidisciplinary design team and an iterative evaluation process with representative users were instrumental in the development of a usable and well-received web-based program. Copyright © 2011 John Wiley & Sons, Ltd.

Brief Report: Adapting an In-Person Patient-Caregiver Communication Intervention to a Tailored Web-Based Format

PubMed Central

Zulman, Donna M.; Schafenacker, Ann; Barr, Kathryn L.C.; Moore, Ian T.; Fisher, Jake; McCurdy, Kathryn; Derry, Holly A.; Saunders, Edward W.; An, Lawrence C.; Northouse, Laurel

2011-01-01

Background Interventions that target cancer patients and their caregivers have been shown to improve communication, support, and emotional well-being. Objective To adapt an in-person communication intervention for cancer patients and caregivers to a web-based format, and to examine the usability and acceptability of the web-based program among representative users. Methods A tailored, interactive web-based communication program for cancer patients and their family caregivers was developed based on an existing in-person, nurse-delivered intervention. The development process involved: 1) building a multidisciplinary team of content and web design experts, 2) combining key components of the in-person intervention with the unique tailoring and interactive features of a web-based platform, and 3) conducting focus groups and usability testing to obtain feedback from representative program users at multiple time points. Results Four focus groups with 2 to 3 patient-caregiver pairs per group (n = 22 total participants) and two iterations of usability testing with 4 patient-caregiver pairs per session (n = 16 total participants) were conducted. Response to the program's structure, design, and content was favorable, even among users who were older or had limited computer and internet experience. The program received high ratings for ease of use and overall usability (mean System Usability Score of 89.5 out of 100). Conclusions Many elements of a nurse-delivered patient-caregiver intervention can be successfully adapted to a web-based format. A multidisciplinary design team and an iterative evaluation process with representative users were instrumental in the development of a usable and well-received web-based program. PMID:21830255

Consolidated principles for screening based on a systematic review and consensus process.

PubMed

Dobrow, Mark J; Hagens, Victoria; Chafe, Roger; Sullivan, Terrence; Rabeneck, Linda

2018-04-09

In 1968, Wilson and Jungner published 10 principles of screening that often represent the de facto starting point for screening decisions today; 50 years on, are these principles still the right ones? Our objectives were to review published work that presents principles for population-based screening decisions since Wilson and Jungner's seminal publication, and to conduct a Delphi consensus process to assess the review results. We conducted a systematic review and modified Delphi consensus process. We searched multiple databases for articles published in English in 1968 or later that were intended to guide population-based screening decisions, described development and modification of principles, and presented principles as a set or list. Identified sets were compared for basic characteristics (e.g., number, categorization), a citation analysis was conducted, and principles were iteratively synthesized and consolidated into categories to assess evolution. Participants in the consensus process assessed the level of agreement with the importance and interpretability of the consolidated screening principles. We identified 41 sets and 367 unique principles. Each unique principle was coded to 12 consolidated decision principles that were further categorized as disease/condition, test/intervention or program/system principles. Program or system issues were the focus of 3 of Wilson and Jungner's 10 principles, but comprised almost half of all unique principles identified in the review. The 12 consolidated principles were assessed through 2 rounds of the consensus process, leading to specific refinements to improve their relevance and interpretability. No gaps or missing principles were identified. Wilson and Jungner's principles are remarkably enduring, but increasingly reflect a truncated version of contemporary thinking on screening that does not fully capture subsequent focus on program or system principles. Ultimately, this review and consensus process provides a comprehensive and iterative modernization of guidance to inform population-based screening decisions. © 2018 Joule Inc. or its licensors.

Consolidated principles for screening based on a systematic review and consensus process

PubMed Central

Hagens, Victoria; Chafe, Roger; Sullivan, Terrence; Rabeneck, Linda

2018-01-01

BACKGROUND: In 1968, Wilson and Jungner published 10 principles of screening that often represent the de facto starting point for screening decisions today; 50 years on, are these principles still the right ones? Our objectives were to review published work that presents principles for population-based screening decisions since Wilson and Jungner’s seminal publication, and to conduct a Delphi consensus process to assess the review results. METHODS: We conducted a systematic review and modified Delphi consensus process. We searched multiple databases for articles published in English in 1968 or later that were intended to guide population-based screening decisions, described development and modification of principles, and presented principles as a set or list. Identified sets were compared for basic characteristics (e.g., number, categorization), a citation analysis was conducted, and principles were iteratively synthesized and consolidated into categories to assess evolution. Participants in the consensus process assessed the level of agreement with the importance and interpretability of the consolidated screening principles. RESULTS: We identified 41 sets and 367 unique principles. Each unique principle was coded to 12 consolidated decision principles that were further categorized as disease/condition, test/intervention or program/system principles. Program or system issues were the focus of 3 of Wilson and Jungner’s 10 principles, but comprised almost half of all unique principles identified in the review. The 12 consolidated principles were assessed through 2 rounds of the consensus process, leading to specific refinements to improve their relevance and interpretability. No gaps or missing principles were identified. INTERPRETATION: Wilson and Jungner’s principles are remarkably enduring, but increasingly reflect a truncated version of contemporary thinking on screening that does not fully capture subsequent focus on program or system principles. Ultimately, this review and consensus process provides a comprehensive and iterative modernization of guidance to inform population-based screening decisions. PMID:29632037

Error analysis in inverse scatterometry. I. Modeling.

PubMed

Al-Assaad, Rayan M; Byrne, Dale M

2007-02-01

Scatterometry is an optical technique that has been studied and tested in recent years in semiconductor fabrication metrology for critical dimensions. Previous work presented an iterative linearized method to retrieve surface-relief profile parameters from reflectance measurements upon diffraction. With the iterative linear solution model in this work, rigorous models are developed to represent the random and deterministic or offset errors in scatterometric measurements. The propagation of different types of error from the measurement data to the profile parameter estimates is then presented. The improvement in solution accuracies is then demonstrated with theoretical and experimental data by adjusting for the offset errors. In a companion paper (in process) an improved optimization method is presented to account for unknown offset errors in the measurements based on the offset error model.

String-averaging incremental subgradients for constrained convex optimization with applications to reconstruction of tomographic images

NASA Astrophysics Data System (ADS)

Massambone de Oliveira, Rafael; Salomão Helou, Elias; Fontoura Costa, Eduardo

2016-11-01

We present a method for non-smooth convex minimization which is based on subgradient directions and string-averaging techniques. In this approach, the set of available data is split into sequences (strings) and a given iterate is processed independently along each string, possibly in parallel, by an incremental subgradient method (ISM). The end-points of all strings are averaged to form the next iterate. The method is useful to solve sparse and large-scale non-smooth convex optimization problems, such as those arising in tomographic imaging. A convergence analysis is provided under realistic, standard conditions. Numerical tests are performed in a tomographic image reconstruction application, showing good performance for the convergence speed when measured as the decrease ratio of the objective function, in comparison to classical ISM.

Un algorithme efficace d'intégration plastique pour un matériau obéissant au critère anisotrope de Hill

NASA Astrophysics Data System (ADS)

Titeux, Isabelle; Li, Yuming M.; Debray, Karl; Guo, Ying-Qiao

2004-11-01

This Note deals with an efficient algorithm to carry out the plastic integration and compute the stresses due to large strains for materials satisfying the Hill's anisotropic yield criterion. The classical algorithm of plastic integration such as 'Return Mapping Method' is largely used for nonlinear analyses of structures and numerical simulations of forming processes, but it requires an iterative schema and may have convergence problems. A new direct algorithm based on a scalar method is developed which allows us to directly obtain the plastic multiplier without an iteration procedure; thus the computation time is largely reduced and the numerical problems are avoided. To cite this article: I. Titeux et al., C. R. Mecanique 332 (2004).

Fast non-interferometric iterative phase retrieval for holographic data storage.

PubMed

Lin, Xiao; Huang, Yong; Shimura, Tsutomu; Fujimura, Ryushi; Tanaka, Yoshito; Endo, Masao; Nishimoto, Hajimu; Liu, Jinpeng; Li, Yang; Liu, Ying; Tan, Xiaodi

2017-12-11

Fast non-interferometric phase retrieval is a very important technique for phase-encoded holographic data storage and other phase based applications due to its advantage of easy implementation, simple system setup, and robust noise tolerance. Here we present an iterative non-interferometric phase retrieval for 4-level phase encoded holographic data storage based on an iterative Fourier transform algorithm and known portion of the encoded data, which increases the storage code rate to two-times that of an amplitude based method. Only a single image at the Fourier plane of the beam is captured for the iterative reconstruction. Since beam intensity at the Fourier plane of the reconstructed beam is more concentrated than the reconstructed beam itself, the requirement of diffractive efficiency of the recording media is reduced, which will improve the dynamic range of recording media significantly. The phase retrieval only requires 10 iterations to achieve a less than 5% phase data error rate, which is successfully demonstrated by recording and reconstructing a test image data experimentally. We believe our method will further advance the holographic data storage technique in the era of big data.

Final Report on ITER Task Agreement 81-10

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

Brad J. Merrill

An International Thermonuclear Experimental Reactor (ITER) Implementing Task Agreement (ITA) on Magnet Safety was established between the ITER International Organization (IO) and the Idaho National Laboratory (INL) Fusion Safety Program (FSP) during calendar year 2004. The objectives of this ITA were to add new capabilities to the MAGARC code and to use this updated version of MAGARC to analyze unmitigated superconductor quench events for both poloidal field (PF) and toroidal field (TF) coils of the ITER design. This report documents the completion of the work scope for this ITA. Based on the results obtained for this ITA, an unmitigated quenchmore » event in an ITER larger PF coil does not appear to be as severe an accident as in an ITER TF coil.« less

Process Correlation Analysis Model for Process Improvement Identification

PubMed Central

Park, Sooyong

2014-01-01

Software process improvement aims at improving the development process of software systems. It is initiated by process assessment identifying strengths and weaknesses and based on the findings, improvement plans are developed. In general, a process reference model (e.g., CMMI) is used throughout the process of software process improvement as the base. CMMI defines a set of process areas involved in software development and what to be carried out in process areas in terms of goals and practices. Process areas and their elements (goals and practices) are often correlated due to the iterative nature of software development process. However, in the current practice, correlations of process elements are often overlooked in the development of an improvement plan, which diminishes the efficiency of the plan. This is mainly attributed to significant efforts and the lack of required expertise. In this paper, we present a process correlation analysis model that helps identify correlations of process elements from the results of process assessment. This model is defined based on CMMI and empirical data of improvement practices. We evaluate the model using industrial data. PMID:24977170

Process correlation analysis model for process improvement identification.

PubMed

Choi, Su-jin; Kim, Dae-Kyoo; Park, Sooyong

2014-01-01

Software process improvement aims at improving the development process of software systems. It is initiated by process assessment identifying strengths and weaknesses and based on the findings, improvement plans are developed. In general, a process reference model (e.g., CMMI) is used throughout the process of software process improvement as the base. CMMI defines a set of process areas involved in software development and what to be carried out in process areas in terms of goals and practices. Process areas and their elements (goals and practices) are often correlated due to the iterative nature of software development process. However, in the current practice, correlations of process elements are often overlooked in the development of an improvement plan, which diminishes the efficiency of the plan. This is mainly attributed to significant efforts and the lack of required expertise. In this paper, we present a process correlation analysis model that helps identify correlations of process elements from the results of process assessment. This model is defined based on CMMI and empirical data of improvement practices. We evaluate the model using industrial data.

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.

Low-dose CT image reconstruction using gain intervention-based dictionary learning

NASA Astrophysics Data System (ADS)

Pathak, Yadunath; Arya, K. V.; Tiwari, Shailendra

2018-05-01

Computed tomography (CT) approach is extensively utilized in clinical diagnoses. However, X-ray residue in human body may introduce somatic damage such as cancer. Owing to radiation risk, research has focused on the radiation exposure distributed to patients through CT investigations. Therefore, low-dose CT has become a significant research area. Many researchers have proposed different low-dose CT reconstruction techniques. But, these techniques suffer from various issues such as over smoothing, artifacts, noise, etc. Therefore, in this paper, we have proposed a novel integrated low-dose CT reconstruction technique. The proposed technique utilizes global dictionary-based statistical iterative reconstruction (GDSIR) and adaptive dictionary-based statistical iterative reconstruction (ADSIR)-based reconstruction techniques. In case the dictionary (D) is predetermined, then GDSIR can be used and if D is adaptively defined then ADSIR is appropriate choice. The gain intervention-based filter is also used as a post-processing technique for removing the artifacts from low-dose CT reconstructed images. Experiments have been done by considering the proposed and other low-dose CT reconstruction techniques on well-known benchmark CT images. Extensive experiments have shown that the proposed technique outperforms the available approaches.

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.

Using a web-based, iterative education model to enhance clinical clerkships.

PubMed

Alexander, Erik K; Bloom, Nurit; Falchuk, Kenneth H; Parker, Michael

2006-10-01

Although most clinical clerkship curricula are designed to provide all students consistent exposure to defined course objectives, it is clear that individual students are diverse in their backgrounds and baseline knowledge. Ideally, the learning process should be individualized towards the strengths and weakness of each student, but, until recently, this has proved prohibitively time-consuming. The authors describe a program to develop and evaluate an iterative, Web-based educational model assessing medical students' knowledge deficits and allowing targeted teaching shortly after their identification. Beginning in 2002, a new educational model was created, validated, and applied in a prospective fashion to medical students during an internal medicine clerkship at Harvard Medical School. Using a Web-based platform, five validated questions were delivered weekly and a specific knowledge deficiency identified. Teaching targeted to the deficiency was provided to an intervention cohort of five to seven students in each clerkship, though not to controls (the remaining 7-10 students). Effectiveness of this model was assessed by performance on the following week's posttest question. Specific deficiencies were readily identified weekly using this model. Throughout the year, however, deficiencies varied unpredictably. Teaching targeted to deficiencies resulted in significantly better performance on follow-up questioning compared to the performance of those who did not receive this intervention. This model was easily applied in an additive fashion to the current curriculum, and student acceptance was high. The authors conclude that a Web-based, iterative assessment model can effectively target specific curricular needs unique to each group; focus teaching in a rapid, formative, and highly efficient manner; and may improve the efficiency of traditional clerkship teaching.

Automatic target recognition using a feature-based optical neural network

NASA Technical Reports Server (NTRS)

Chao, Tien-Hsin

1992-01-01

An optical neural network based upon the Neocognitron paradigm (K. Fukushima et al. 1983) is introduced. A novel aspect of the architectural design is shift-invariant multichannel Fourier optical correlation within each processing layer. Multilayer processing is achieved by iteratively feeding back the output of the feature correlator to the input spatial light modulator and updating the Fourier filters. By training the neural net with characteristic features extracted from the target images, successful pattern recognition with intra-class fault tolerance and inter-class discrimination is achieved. A detailed system description is provided. Experimental demonstration of a two-layer neural network for space objects discrimination is also presented.

Elastic-plastic mixed-iterative finite element analysis: Implementation and performance assessment

NASA Technical Reports Server (NTRS)

Sutjahjo, Edhi; Chamis, Christos C.

1993-01-01

An elastic-plastic algorithm based on Von Mises and associative flow criteria is implemented in MHOST-a mixed iterative finite element analysis computer program developed by NASA Lewis Research Center. The performance of the resulting elastic-plastic mixed-iterative analysis is examined through a set of convergence studies. Membrane and bending behaviors of 4-node quadrilateral shell finite elements are tested for elastic-plastic performance. Generally, the membrane results are excellent, indicating the implementation of elastic-plastic mixed-iterative analysis is appropriate.

An Iterative Interplanetary Scintillation (IPS) Analysis Using Time-dependent 3-D MHD Models as Kernels

NASA Astrophysics Data System (ADS)

Jackson, B. V.; Yu, H. S.; Hick, P. P.; Buffington, A.; Odstrcil, D.; Kim, T. K.; Pogorelov, N. V.; Tokumaru, M.; Bisi, M. M.; Kim, J.; Yun, J.

2017-12-01

The University of California, San Diego has developed an iterative remote-sensing time-dependent three-dimensional (3-D) reconstruction technique which provides volumetric maps of density, velocity, and magnetic field. We have applied this technique in near real time for over 15 years with a kinematic model approximation to fit data from ground-based interplanetary scintillation (IPS) observations. Our modeling concept extends volumetric data from an inner boundary placed above the Alfvén surface out to the inner heliosphere. We now use this technique to drive 3-D MHD models at their inner boundary and generate output 3-D data files that are fit to remotely-sensed observations (in this case IPS observations), and iterated. These analyses are also iteratively fit to in-situ spacecraft measurements near Earth. To facilitate this process, we have developed a traceback from input 3-D MHD volumes to yield an updated boundary in density, temperature, and velocity, which also includes magnetic-field components. Here we will show examples of this analysis using the ENLIL 3D-MHD and the University of Alabama Multi-Scale Fluid-Kinetic Simulation Suite (MS-FLUKSS) heliospheric codes. These examples help refine poorly-known 3-D MHD variables (i.e., density, temperature), and parameters (gamma) by fitting heliospheric remotely-sensed data between the region near the solar surface and in-situ measurements near Earth.

Kernel approach to molecular similarity based on iterative graph similarity.

PubMed

Rupp, Matthias; Proschak, Ewgenij; Schneider, Gisbert

2007-01-01

Similarity measures for molecules are of basic importance in chemical, biological, and pharmaceutical applications. We introduce a molecular similarity measure defined directly on the annotated molecular graph, based on iterative graph similarity and optimal assignments. We give an iterative algorithm for the computation of the proposed molecular similarity measure, prove its convergence and the uniqueness of the solution, and provide an upper bound on the required number of iterations necessary to achieve a desired precision. Empirical evidence for the positive semidefiniteness of certain parametrizations of our function is presented. We evaluated our molecular similarity measure by using it as a kernel in support vector machine classification and regression applied to several pharmaceutical and toxicological data sets, with encouraging results.

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.

Unsupervised iterative detection of land mines in highly cluttered environments.

PubMed

Batman, Sinan; Goutsias, John

2003-01-01

An unsupervised iterative scheme is proposed for land mine detection in heavily cluttered scenes. This scheme is based on iterating hybrid multispectral filters that consist of a decorrelating linear transform coupled with a nonlinear morphological detector. Detections extracted from the first pass are used to improve results in subsequent iterations. The procedure stops after a predetermined number of iterations. The proposed scheme addresses several weaknesses associated with previous adaptations of morphological approaches to land mine detection. Improvement in detection performance, robustness with respect to clutter inhomogeneities, a completely unsupervised operation, and computational efficiency are the main highlights of the method. Experimental results reveal excellent performance.

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.…

Creating ISO/EN 13606 archetypes based on clinical information needs.

PubMed

Rinner, Christoph; Kohler, Michael; Hübner-Bloder, Gudrun; Saboor, Samrend; Ammenwerth, Elske; Duftschmid, Georg

2011-01-01

Archetypes model individual EHR contents and build the basis of the dual-model approach used in the ISO/EN 13606 EHR architecture. We present an approach to create archetypes using an iterative development process. It includes automated generation of electronic case report forms from archetypes. We evaluated our approach by developing 128 archetypes which represent 446 clinical information items from the diabetes domain.

Research and Teaching: Using Models from the Literature and Iterative Feedback to Teach Students to Construct Effective Data Figures for Poster Presentations

ERIC Educational Resources Information Center

Gray, Christine E.; Contreras-Shannon, Veronica E.

2017-01-01

Analyzing, interpreting, and clearly presenting real data are skills we hope to develop in all students, majors and nonmajors alike. These process skills require lots of practice coupled with targeted feedback from instructors or mentors. Here we present a pedagogy implemented within a course-based research experience that is designed to help…

Alternatives for Developing User Documentation for Applications Software

DTIC Science & Technology

1991-09-01

style that is designed to match adult reading behaviors, using reader-based writing techniques, developing effective graphics , creating reference aids...involves research, analysis, design , and testing. The writer must have a solid understanding of the technical aspects of the document being prepared, good...ABSTRACT The preparation of software documentation is an iterative process that involves research, analysis, design , and testing. The writer must have

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.

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

PubMed

Tučník, Petr; Bureš, Vladimír

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.

A fast feedback method to design easy-molding freeform optical system with uniform illuminance and high light control efficiency.

PubMed

Hongtao, Li; Shichao, Chen; Yanjun, Han; Yi, Luo

2013-01-14

A feedback method combined with fitting technique based on variable separation mapping is proposed to design freeform optical systems for an extended LED source with prescribed illumination patterns, especially with uniform illuminance distribution. Feedback process performs well with extended sources, while fitting technique contributes not only to the decrease of pieces of sub-surfaces in discontinuous freeform lenses which may cause loss in manufacture, but also the reduction in the number of feedback iterations. It is proved that light control efficiency can be improved by 5%, while keeping a high uniformity of 82%, with only two feedback iterations and one fitting operation can improve. Furthermore, the polar angle θ and azimuthal angle φ is used to specify the light direction from the light source, and the (θ,φ)-(x,y) based mapping and feedback strategy makes sure that even few discontinuous sections along the equi-φ plane exist in the system, they are perpendicular to the base plane, making it eligible for manufacturing the surfaces using injection molding.

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.

Research on adaptive optics image restoration algorithm based on improved joint maximum a posteriori method

NASA Astrophysics Data System (ADS)

Zhang, Lijuan; Li, Yang; Wang, Junnan; Liu, Ying

2018-03-01

In this paper, we propose a point spread function (PSF) reconstruction method and joint maximum a posteriori (JMAP) estimation method for the adaptive optics image restoration. Using the JMAP method as the basic principle, we establish the joint log likelihood function of multi-frame adaptive optics (AO) images based on the image Gaussian noise models. To begin with, combining the observed conditions and AO system characteristics, a predicted PSF model for the wavefront phase effect is developed; then, we build up iterative solution formulas of the AO image based on our proposed algorithm, addressing the implementation process of multi-frame AO images joint deconvolution method. We conduct a series of experiments on simulated and real degraded AO images to evaluate our proposed algorithm. Compared with the Wiener iterative blind deconvolution (Wiener-IBD) algorithm and Richardson-Lucy IBD algorithm, our algorithm has better restoration effects including higher peak signal-to-noise ratio ( PSNR) and Laplacian sum ( LS) value than the others. The research results have a certain application values for actual AO image restoration.

An implementation of the QMR method based on coupled two-term recurrences

NASA Technical Reports Server (NTRS)

Freund, Roland W.; Nachtigal, Noeel M.

1992-01-01

The authors have proposed a new Krylov subspace iteration, the quasi-minimal residual algorithm (QMR), for solving non-Hermitian linear systems. In the original implementation of the QMR method, the Lanczos process with look-ahead is used to generate basis vectors for the underlying Krylov subspaces. In the Lanczos algorithm, these basis vectors are computed by means of three-term recurrences. It has been observed that, in finite precision arithmetic, vector iterations based on three-term recursions are usually less robust than mathematically equivalent coupled two-term vector recurrences. This paper presents a look-ahead algorithm that constructs the Lanczos basis vectors by means of coupled two-term recursions. Implementation details are given, and the look-ahead strategy is described. A new implementation of the QMR method, based on this coupled two-term algorithm, is described. A simplified version of the QMR algorithm without look-ahead is also presented, and the special case of QMR for complex symmetric linear systems is considered. Results of numerical experiments comparing the original and the new implementations of the QMR method are reported.

Digital adaptive optics confocal microscopy based on iterative retrieval of optical aberration from a guidestar hologram

PubMed Central

Liu, Changgeng; Thapa, Damber; Yao, Xincheng

2017-01-01

Guidestar hologram based digital adaptive optics (DAO) is one recently emerging active imaging modality. It records each complex distorted line field reflected or scattered from the sample by an off-axis digital hologram, measures the optical aberration from a separate off-axis digital guidestar hologram, and removes the optical aberration from the distorted line fields by numerical processing. In previously demonstrated DAO systems, the optical aberration was directly retrieved from the guidestar hologram by taking its Fourier transform and extracting the phase term. For the direct retrieval method (DRM), when the sample is not coincident with the guidestar focal plane, the accuracy of the optical aberration retrieved by DRM undergoes a fast decay, leading to quality deterioration of corrected images. To tackle this problem, we explore here an image metrics-based iterative method (MIM) to retrieve the optical aberration from the guidestar hologram. Using an aberrated objective lens and scattering samples, we demonstrate that MIM can improve the accuracy of the retrieved aberrations from both focused and defocused guidestar holograms, compared to DRM, to improve the robustness of the DAO. PMID:28380937

Calibration free beam hardening correction for cardiac CT perfusion imaging

NASA Astrophysics Data System (ADS)

Levi, Jacob; Fahmi, Rachid; Eck, Brendan L.; Fares, Anas; Wu, Hao; Vembar, Mani; Dhanantwari, Amar; Bezerra, Hiram G.; Wilson, David L.

2016-03-01

Myocardial perfusion imaging using CT (MPI-CT) and coronary CTA have the potential to make CT an ideal noninvasive gate-keeper for invasive coronary angiography. However, beam hardening artifacts (BHA) prevent accurate blood flow calculation in MPI-CT. BH Correction (BHC) methods require either energy-sensitive CT, not widely available, or typically a calibration-based method. We developed a calibration-free, automatic BHC (ABHC) method suitable for MPI-CT. The algorithm works with any BHC method and iteratively determines model parameters using proposed BHA-specific cost function. In this work, we use the polynomial BHC extended to three materials. The image is segmented into soft tissue, bone, and iodine images, based on mean HU and temporal enhancement. Forward projections of bone and iodine images are obtained, and in each iteration polynomial correction is applied. Corrections are then back projected and combined to obtain the current iteration's BHC image. This process is iterated until cost is minimized. We evaluate the algorithm on simulated and physical phantom images and on preclinical MPI-CT data. The scans were obtained on a prototype spectral detector CT (SDCT) scanner (Philips Healthcare). Mono-energetic reconstructed images were used as the reference. In the simulated phantom, BH streak artifacts were reduced from 12+/-2HU to 1+/-1HU and cupping was reduced by 81%. Similarly, in physical phantom, BH streak artifacts were reduced from 48+/-6HU to 1+/-5HU and cupping was reduced by 86%. In preclinical MPI-CT images, BHA was reduced from 28+/-6 HU to less than 4+/-4HU at peak enhancement. Results suggest that the algorithm can be used to reduce BHA in conventional CT and improve MPI-CT accuracy.

An improved 2D MoF method by using high order derivatives

NASA Astrophysics Data System (ADS)

Chen, Xiang; Zhang, Xiong

2017-11-01

The MoF (Moment of Fluid) method is one of the most accurate approaches among various interface reconstruction algorithms. Alike other second order methods, the MoF method needs to solve an implicit optimization problem to obtain the optimal approximate interface, so an iteration process is inevitable under most circumstances. In order to solve the optimization efficiently, the properties of the objective function are worthy of studying. In 2D problems, the first order derivative has been deduced and applied in the previous researches. In this paper, the high order derivatives of the objective function are deduced on the convex polygon. We show that the nth (n ≥ 2) order derivatives are discontinuous, and the number of the discontinuous points is two times the number of the polygon edge. A rotation algorithm is proposed to successively calculate these discontinuous points, thus the target interval where the optimal solution is located can be determined. Since the high order derivatives of the objective function are continuous in the target interval, the iteration schemes based on high order derivatives can be used to improve the convergence rate. Moreover, when iterating in the target interval, the value of objective function and its derivatives can be directly updated without explicitly solving the volume conservation equation. The direct update makes a further improvement of the efficiency especially when the number of edges of the polygon is increasing. The Halley's method, which is based on the first three order derivatives, is applied as the iteration scheme in this paper and the numerical results indicate that the CPU time is about half of the previous method on the quadrilateral cell and is about one sixth on the decagon cell.

Can SNOMED CT be squeezed without losing its shape?

PubMed

López-García, Pablo; Schulz, Stefan

2016-09-21

In biomedical applications where the size and complexity of SNOMED CT become problematic, using a smaller subset that can act as a reasonable substitute is usually preferred. In a special class of use cases-like ontology-based quality assurance, or when performing scaling experiments for real-time performance-it is essential that modules show a similar shape than SNOMED CT in terms of concept distribution per sub-hierarchy. Exactly how to extract such balanced modules remains unclear, as most previous work on ontology modularization has focused on other problems. In this study, we investigate to what extent extracting balanced modules that preserve the original shape of SNOMED CT is possible, by presenting and evaluating an iterative algorithm. We used a graph-traversal modularization approach based on an input signature. To conform to our definition of a balanced module, we implemented an iterative algorithm that carefully bootstraped and dynamically adjusted the signature at each step. We measured the error for each sub-hierarchy and defined convergence as a residual sum of squares <1. Using 2000 concepts as an initial signature, our algorithm converged after seven iterations and extracted a module 4.7 % the size of SNOMED CT. Seven sub-hierarhies were either over or under-represented within a range of 1-8 %. Our study shows that balanced modules from large terminologies can be extracted using ontology graph-traversal modularization techniques under certain conditions: that the process is repeated a number of times, the input signature is dynamically adjusted in each iteration, and a moderate under/over-representation of some hierarchies is tolerated. In the case of SNOMED CT, our results conclusively show that it can be squeezed to less than 5 % of its size without any sub-hierarchy losing its shape more than 8 %, which is likely sufficient in most use cases.

GPU-accelerated iterative reconstruction from Compton scattered data using a matched pair of conic projector and backprojector.

PubMed

Nguyen, Van-Giang; Lee, Soo-Jin

2016-07-01

Iterative reconstruction from Compton scattered data is known to be computationally more challenging than that from conventional line-projection based emission data in that the gamma rays that undergo Compton scattering are modeled as conic projections rather than line projections. In conventional tomographic reconstruction, to parallelize the projection and backprojection operations using the graphics processing unit (GPU), approximated methods that use an unmatched pair of ray-tracing forward projector and voxel-driven backprojector have been widely used. In this work, we propose a new GPU-accelerated method for Compton camera reconstruction which is more accurate by using exactly matched pair of projector and backprojector. To calculate conic forward projection, we first sample the cone surface into conic rays and accumulate the intersecting chord lengths of the conic rays passing through voxels using a fast ray-tracing method (RTM). For conic backprojection, to obtain the true adjoint of the conic forward projection, while retaining the computational efficiency of the GPU, we use a voxel-driven RTM which is essentially the same as the standard RTM used for the conic forward projector. Our simulation results show that, while the new method is about 3 times slower than the approximated method, it is still about 16 times faster than the CPU-based method without any loss of accuracy. The net conclusion is that our proposed method is guaranteed to retain the reconstruction accuracy regardless of the number of iterations by providing a perfectly matched projector-backprojector pair, which makes iterative reconstruction methods for Compton imaging faster and more accurate. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

On the Short Horizon of Spontaneous Iterative Reasoning in Logical Puzzles and Games

ERIC Educational Resources Information Center

Mazzocco, Ketti; Cherubini, Anna Maria; Cherubini, Paolo

2013-01-01

A reasoning strategy is iterative when the initial conclusion suggested by a set of premises is integrated into that set of premises in order to yield additional conclusions. Previous experimental studies on game theory-based strategic games (such as the beauty contest game) observed difficulty in reasoning iteratively, which has been partly…

Efficient design of nanoplasmonic waveguide devices using the space mapping algorithm.

PubMed

Dastmalchi, Pouya; Veronis, Georgios

2013-12-30

We show that the space mapping algorithm, originally developed for microwave circuit optimization, can enable the efficient design of nanoplasmonic waveguide devices which satisfy a set of desired specifications. Space mapping utilizes a physics-based coarse model to approximate a fine model accurately describing a device. Here the fine model is a full-wave finite-difference frequency-domain (FDFD) simulation of the device, while the coarse model is based on transmission line theory. We demonstrate that simply optimizing the transmission line model of the device is not enough to obtain a device which satisfies all the required design specifications. On the other hand, when the iterative space mapping algorithm is used, it converges fast to a design which meets all the specifications. In addition, full-wave FDFD simulations of only a few candidate structures are required before the iterative process is terminated. Use of the space mapping algorithm therefore results in large reductions in the required computation time when compared to any direct optimization method of the fine FDFD model.

Combined neural network/Phillips-Tikhonov approach to aerosol retrievals over land from the NASA Research Scanning Polarimeter

NASA Astrophysics Data System (ADS)

Di Noia, Antonio; Hasekamp, Otto P.; Wu, Lianghai; van Diedenhoven, Bastiaan; Cairns, Brian; Yorks, John E.

2017-11-01

In this paper, an algorithm for the retrieval of aerosol and land surface properties from airborne spectropolarimetric measurements - combining neural networks and an iterative scheme based on Phillips-Tikhonov regularization - is described. The algorithm - which is an extension of a scheme previously designed for ground-based retrievals - is applied to measurements from the Research Scanning Polarimeter (RSP) on board the NASA ER-2 aircraft. A neural network, trained on a large data set of synthetic measurements, is applied to perform aerosol retrievals from real RSP data, and the neural network retrievals are subsequently used as a first guess for the Phillips-Tikhonov retrieval. The resulting algorithm appears capable of accurately retrieving aerosol optical thickness, fine-mode effective radius and aerosol layer height from RSP data. Among the advantages of using a neural network as initial guess for an iterative algorithm are a decrease in processing time and an increase in the number of converging retrievals.

MWR3C physical retrievals of precipitable water vapor and cloud liquid water path

DOE Data Explorer

Cadeddu, Maria

2016-10-12

The data set contains physical retrievals of PWV and cloud LWP retrieved from MWR3C measurements during the MAGIC campaign. Additional data used in the retrieval process include radiosondes and ceilometer. The retrieval is based on an optimal estimation technique that starts from a first guess and iteratively repeats the forward model calculations until a predefined convergence criterion is satisfied. The first guess is a vector of [PWV,LWP] from the neural network retrieval fields in the netcdf file. When convergence is achieved the 'a posteriori' covariance is computed and its square root is expressed in the file as the retrieval 1-sigma uncertainty. The closest radiosonde profile is used for the radiative transfer calculations and ceilometer data are used to constrain the cloud base height. The RMS error between the brightness temperatures is computed at the last iterations as a consistency check and is written in the last column of the output file.

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.

2.5D transient electromagnetic inversion with OCCAM method

NASA Astrophysics Data System (ADS)

Li, R.; Hu, X.

2016-12-01

In the application of time-domain electromagnetic method (TEM), some multidimensional inversion schemes are applied for imaging in the past few decades to overcome great error produced by 1D model inversion when the subsurface structure is complex. The current mainstream multidimensional inversion for EM data, with the finite-difference time-domain (FDTD) forward method, mainly implemented by Nonlinear Conjugate Gradient (NLCG). But the convergence rate of NLCG heavily depends on Lagrange multiplier and maybe fail to converge. We use the OCCAM inversion method to avoid the weakness. OCCAM inversion is proven to be a more stable and reliable method to image the subsurface 2.5D electrical conductivity. Firstly, we simulate the 3D transient EM fields governed by Maxwell's equations with FDTD method. Secondly, we use the OCCAM inversion scheme with the appropriate objective error functional we established to image the 2.5D structure. And the data space OCCAM's inversion (DASOCC) strategy based on OCCAM scheme were given in this paper. The sensitivity matrix is calculated with the method of time-integrated back-propagated fields. Imaging result of example model shown in Fig. 1 have proven that the OCCAM scheme is an efficient inversion method for TEM with FDTD method. The processes of the inversion iterations have shown the great ability of convergence with few iterations. Summarizing the process of the imaging, we can make the following conclusions. Firstly, the 2.5D imaging in FDTD system with OCCAM inversion demonstrates that we could get desired imaging results for the resistivity structure in the homogeneous half-space. Secondly, the imaging results usually do not over-depend on the initial model, but the iteration times can be reduced distinctly if the background resistivity of initial model get close to the truthful model. So it is batter to set the initial model based on the other geologic information in the application. When the background resistivity fit the truthful model well, the imaging of anomalous body only need a few iteration steps. Finally, the speed of imaging vertical boundaries is slower than the speed of imaging the horizontal boundaries.

Development of iterative techniques for the solution of unsteady compressible viscous flows

NASA Technical Reports Server (NTRS)

Sankar, Lakshmi N.; Hixon, Duane

1992-01-01

The development of efficient iterative solution methods for the numerical solution of two- and three-dimensional compressible Navier-Stokes equations is discussed. Iterative time marching methods have several advantages over classical multi-step explicit time marching schemes, and non-iterative implicit time marching schemes. Iterative schemes have better stability characteristics than non-iterative explicit and implicit schemes. In this work, another approach based on the classical conjugate gradient method, known as the Generalized Minimum Residual (GMRES) algorithm is investigated. The GMRES algorithm has been used in the past by a number of researchers for solving steady viscous and inviscid flow problems. Here, we investigate the suitability of this algorithm for solving the system of non-linear equations that arise in unsteady Navier-Stokes solvers at each time step.

Devil is in the details: Using logic models to investigate program process.

PubMed

Peyton, David J; Scicchitano, Michael

2017-12-01

Theory-based logic models are commonly developed as part of requirements for grant funding. As a tool to communicate complex social programs, theory based logic models are an effective visual communication. However, after initial development, theory based logic models are often abandoned and remain in their initial form despite changes in the program process. This paper examines the potential benefits of committing time and resources to revising the initial theory driven logic model and developing detailed logic models that describe key activities to accurately reflect the program and assist in effective program management. The authors use a funded special education teacher preparation program to exemplify the utility of drill down logic models. The paper concludes with lessons learned from the iterative revision process and suggests how the process can lead to more flexible and calibrated program management. Copyright © 2017 Elsevier Ltd. All rights reserved.

Efficient Solution of Three-Dimensional Problems of Acoustic and Electromagnetic Scattering by Open Surfaces

NASA Technical Reports Server (NTRS)

Turc, Catalin; Anand, Akash; Bruno, Oscar; Chaubell, Julian

2011-01-01

We present a computational methodology (a novel Nystrom approach based on use of a non-overlapping patch technique and Chebyshev discretizations) for efficient solution of problems of acoustic and electromagnetic scattering by open surfaces. Our integral equation formulations (1) Incorporate, as ansatz, the singular nature of open-surface integral-equation solutions, and (2) For the Electric Field Integral Equation (EFIE), use analytical regularizes that effectively reduce the number of iterations required by iterative linear-algebra solution based on Krylov-subspace iterative solvers.

Performance Analysis of Iterative Channel Estimation and Multiuser Detection in Multipath DS-CDMA Channels

NASA Astrophysics Data System (ADS)

Li, Husheng; Betz, Sharon M.; Poor, H. Vincent

2007-05-01

This paper examines the performance of decision feedback based iterative channel estimation and multiuser detection in channel coded aperiodic DS-CDMA systems operating over multipath fading channels. First, explicit expressions describing the performance of channel estimation and parallel interference cancellation based multiuser detection are developed. These results are then combined to characterize the evolution of the performance of a system that iterates among channel estimation, multiuser detection and channel decoding. Sufficient conditions for convergence of this system to a unique fixed point are developed.

Solution algorithm of dwell time in slope-based figuring model

NASA Astrophysics Data System (ADS)

Li, Yong; Zhou, Lin

2017-10-01

Surface slope profile is commonly used to evaluate X-ray reflective optics, which is used in synchrotron radiation beam. Moreover, the measurement result of measuring instrument for X-ray reflective optics is usually the surface slope profile rather than the surface height profile. To avoid the conversion error, the slope-based figuring model is introduced introduced by processing the X-ray reflective optics based on surface height-based model. However, the pulse iteration method, which can quickly obtain the dell time solution of the traditional height-based figuring model, is not applied to the slope-based figuring model because property of the slope removal function have both positive and negative values and complex asymmetric structure. To overcome this problem, we established the optimal mathematical model for the dwell time solution, By introducing the upper and lower limits of the dwell time and the time gradient constraint. Then we used the constrained least squares algorithm to solve the dwell time in slope-based figuring model. To validate the proposed algorithm, simulations and experiments are conducted. A flat mirror with effective aperture of 80 mm is polished on the ion beam machine. After iterative polishing three times, the surface slope profile error of the workpiece is converged from RMS 5.65 μrad to RMS 1.12 μrad.

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.

Evaluation of the OSC-TV iterative reconstruction algorithm for cone-beam optical CT

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

Matenine, Dmitri, E-mail: dmitri.matenine.1@ulaval.ca; Mascolo-Fortin, Julia, E-mail: julia.mascolo-fortin.1@ulaval.ca; Goussard, Yves, E-mail: yves.goussard@polymtl.ca

Purpose: The present work evaluates an iterative reconstruction approach, namely, the ordered subsets convex (OSC) algorithm with regularization via total variation (TV) minimization in the field of cone-beam optical computed tomography (optical CT). One of the uses of optical CT is gel-based 3D dosimetry for radiation therapy, where it is employed to map dose distributions in radiosensitive gels. Model-based iterative reconstruction may improve optical CT image quality and contribute to a wider use of optical CT in clinical gel dosimetry. Methods: This algorithm was evaluated using experimental data acquired by a cone-beam optical CT system, as well as complementary numericalmore » simulations. A fast GPU implementation of OSC-TV was used to achieve reconstruction times comparable to those of conventional filtered backprojection. Images obtained via OSC-TV were compared with the corresponding filtered backprojections. Spatial resolution and uniformity phantoms were scanned and respective reconstructions were subject to evaluation of the modulation transfer function, image uniformity, and accuracy. The artifacts due to refraction and total signal loss from opaque objects were also studied. Results: The cone-beam optical CT data reconstructions showed that OSC-TV outperforms filtered backprojection in terms of image quality, thanks to a model-based simulation of the photon attenuation process. It was shown to significantly improve the image spatial resolution and reduce image noise. The accuracy of the estimation of linear attenuation coefficients remained similar to that obtained via filtered backprojection. Certain image artifacts due to opaque objects were reduced. Nevertheless, the common artifact due to the gel container walls could not be eliminated. Conclusions: The use of iterative reconstruction improves cone-beam optical CT image quality in many ways. The comparisons between OSC-TV and filtered backprojection presented in this paper demonstrate that OSC-TV can potentially improve the rendering of spatial features and reduce cone-beam optical CT artifacts.« less

Evaluation of the OSC-TV iterative reconstruction algorithm for cone-beam optical CT.

PubMed

Matenine, Dmitri; Mascolo-Fortin, Julia; Goussard, Yves; Després, Philippe

2015-11-01

The present work evaluates an iterative reconstruction approach, namely, the ordered subsets convex (OSC) algorithm with regularization via total variation (TV) minimization in the field of cone-beam optical computed tomography (optical CT). One of the uses of optical CT is gel-based 3D dosimetry for radiation therapy, where it is employed to map dose distributions in radiosensitive gels. Model-based iterative reconstruction may improve optical CT image quality and contribute to a wider use of optical CT in clinical gel dosimetry. This algorithm was evaluated using experimental data acquired by a cone-beam optical CT system, as well as complementary numerical simulations. A fast GPU implementation of OSC-TV was used to achieve reconstruction times comparable to those of conventional filtered backprojection. Images obtained via OSC-TV were compared with the corresponding filtered backprojections. Spatial resolution and uniformity phantoms were scanned and respective reconstructions were subject to evaluation of the modulation transfer function, image uniformity, and accuracy. The artifacts due to refraction and total signal loss from opaque objects were also studied. The cone-beam optical CT data reconstructions showed that OSC-TV outperforms filtered backprojection in terms of image quality, thanks to a model-based simulation of the photon attenuation process. It was shown to significantly improve the image spatial resolution and reduce image noise. The accuracy of the estimation of linear attenuation coefficients remained similar to that obtained via filtered backprojection. Certain image artifacts due to opaque objects were reduced. Nevertheless, the common artifact due to the gel container walls could not be eliminated. The use of iterative reconstruction improves cone-beam optical CT image quality in many ways. The comparisons between OSC-TV and filtered backprojection presented in this paper demonstrate that OSC-TV can potentially improve the rendering of spatial features and reduce cone-beam optical CT artifacts.

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…

High-Performance Agent-Based Modeling Applied to Vocal Fold Inflammation and Repair.

PubMed

Seekhao, Nuttiiya; Shung, Caroline; JaJa, Joseph; Mongeau, Luc; Li-Jessen, Nicole Y K

2018-01-01

Fast and accurate computational biology models offer the prospect of accelerating the development of personalized medicine. A tool capable of estimating treatment success can help prevent unnecessary and costly treatments and potential harmful side effects. A novel high-performance Agent-Based Model (ABM) was adopted to simulate and visualize multi-scale complex biological processes arising in vocal fold inflammation and repair. The computational scheme was designed to organize the 3D ABM sub-tasks to fully utilize the resources available on current heterogeneous platforms consisting of multi-core CPUs and many-core GPUs. Subtasks are further parallelized and convolution-based diffusion is used to enhance the performance of the ABM simulation. The scheme was implemented using a client-server protocol allowing the results of each iteration to be analyzed and visualized on the server (i.e., in-situ ) while the simulation is running on the same server. The resulting simulation and visualization software enables users to interact with and steer the course of the simulation in real-time as needed. This high-resolution 3D ABM framework was used for a case study of surgical vocal fold injury and repair. The new framework is capable of completing the simulation, visualization and remote result delivery in under 7 s per iteration, where each iteration of the simulation represents 30 min in the real world. The case study model was simulated at the physiological scale of a human vocal fold. This simulation tracks 17 million biological cells as well as a total of 1.7 billion signaling chemical and structural protein data points. The visualization component processes and renders all simulated biological cells and 154 million signaling chemical data points. The proposed high-performance 3D ABM was verified through comparisons with empirical vocal fold data. Representative trends of biomarker predictions in surgically injured vocal folds were observed.

High-Performance Agent-Based Modeling Applied to Vocal Fold Inflammation and Repair

PubMed Central

Seekhao, Nuttiiya; Shung, Caroline; JaJa, Joseph; Mongeau, Luc; Li-Jessen, Nicole Y. K.

2018-01-01

Fast and accurate computational biology models offer the prospect of accelerating the development of personalized medicine. A tool capable of estimating treatment success can help prevent unnecessary and costly treatments and potential harmful side effects. A novel high-performance Agent-Based Model (ABM) was adopted to simulate and visualize multi-scale complex biological processes arising in vocal fold inflammation and repair. The computational scheme was designed to organize the 3D ABM sub-tasks to fully utilize the resources available on current heterogeneous platforms consisting of multi-core CPUs and many-core GPUs. Subtasks are further parallelized and convolution-based diffusion is used to enhance the performance of the ABM simulation. The scheme was implemented using a client-server protocol allowing the results of each iteration to be analyzed and visualized on the server (i.e., in-situ) while the simulation is running on the same server. The resulting simulation and visualization software enables users to interact with and steer the course of the simulation in real-time as needed. This high-resolution 3D ABM framework was used for a case study of surgical vocal fold injury and repair. The new framework is capable of completing the simulation, visualization and remote result delivery in under 7 s per iteration, where each iteration of the simulation represents 30 min in the real world. The case study model was simulated at the physiological scale of a human vocal fold. This simulation tracks 17 million biological cells as well as a total of 1.7 billion signaling chemical and structural protein data points. The visualization component processes and renders all simulated biological cells and 154 million signaling chemical data points. The proposed high-performance 3D ABM was verified through comparisons with empirical vocal fold data. Representative trends of biomarker predictions in surgically injured vocal folds were observed. PMID:29706894

Scenario-based fitted Q-iteration for adaptive control of water reservoir systems under uncertainty

NASA Astrophysics Data System (ADS)

Bertoni, Federica; Giuliani, Matteo; Castelletti, Andrea

2017-04-01

Over recent years, mathematical models have largely been used to support planning and management of water resources systems. Yet, the increasing uncertainties in their inputs - due to increased variability in the hydrological regimes - are a major challenge to the optimal operations of these systems. Such uncertainty, boosted by projected changing climate, violates the stationarity principle generally used for describing hydro-meteorological processes, which assumes time persisting statistical characteristics of a given variable as inferred by historical data. As this principle is unlikely to be valid in the future, the probability density function used for modeling stochastic disturbances (e.g., inflows) becomes an additional uncertain parameter of the problem, which can be described in a deterministic and set-membership based fashion. This study contributes a novel method for designing optimal, adaptive policies for controlling water reservoir systems under climate-related uncertainty. The proposed method, called scenario-based Fitted Q-Iteration (sFQI), extends the original Fitted Q-Iteration algorithm by enlarging the state space to include the space of the uncertain system's parameters (i.e., the uncertain climate scenarios). As a result, sFQI embeds the set-membership uncertainty of the future inflow scenarios in the action-value function and is able to approximate, with a single learning process, the optimal control policy associated to any scenario included in the uncertainty set. The method is demonstrated on a synthetic water system, consisting of a regulated lake operated for ensuring reliable water supply to downstream users. Numerical results show that the sFQI algorithm successfully identifies adaptive solutions to operate the system under different inflow scenarios, which outperform the control policy designed under historical conditions. Moreover, the sFQI policy generalizes over inflow scenarios not directly experienced during the policy design, thus alleviating the risk of mis-adaptation, namely the design of a solution fully adapted to a scenario that is different from the one that will actually realize.

Improved event positioning in a gamma ray detector using an iterative position-weighted centre-of-gravity algorithm.

PubMed

Liu, Chen-Yi; Goertzen, Andrew L

2013-07-21

An iterative position-weighted centre-of-gravity algorithm was developed and tested for positioning events in a silicon photomultiplier (SiPM)-based scintillation detector for positron emission tomography. The algorithm used a Gaussian-based weighting function centred at the current estimate of the event location. The algorithm was applied to the signals from a 4 × 4 array of SiPM detectors that used individual channel readout and a LYSO:Ce scintillator array. Three scintillator array configurations were tested: single layer with 3.17 mm crystal pitch, matched to the SiPM size; single layer with 1.5 mm crystal pitch; and dual layer with 1.67 mm crystal pitch and a ½ crystal offset in the X and Y directions between the two layers. The flood histograms generated by this algorithm were shown to be superior to those generated by the standard centre of gravity. The width of the Gaussian weighting function of the algorithm was optimized for different scintillator array setups. The optimal width of the Gaussian curve was found to depend on the amount of light spread. The algorithm required less than 20 iterations to calculate the position of an event. The rapid convergence of this algorithm will readily allow for implementation on a front-end detector processing field programmable gate array for use in improved real-time event positioning and identification.

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.

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

Clarke, Kester Diederik

The intent of this report is to document a procedure used at LANL for HIP bonding aluminum cladding to U-10Mo fuel foils using a formed HIP can for the Domestic Reactor Conversion program in the NNSA Office of Material, Management and Minimization, and provide some details that may not have been published elsewhere. The HIP process is based on the procedures that have been used to develop the formed HIP can process, including the baseline process developed at Idaho National Laboratory (INL). The HIP bonding cladding process development is summarized in the listed references. Further iterations with Babcock & Wilcoxmore » (B&W) to refine the process to meet production and facility requirements is expected.« less

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.

Sparsity-constrained PET image reconstruction with learned dictionaries

NASA Astrophysics Data System (ADS)

Tang, Jing; Yang, Bao; Wang, Yanhua; Ying, Leslie

2016-09-01

PET imaging plays an important role in scientific and clinical measurement of biochemical and physiological processes. Model-based PET image reconstruction such as the iterative expectation maximization algorithm seeking the maximum likelihood solution leads to increased noise. The maximum a posteriori (MAP) estimate removes divergence at higher iterations. However, a conventional smoothing prior or a total-variation (TV) prior in a MAP reconstruction algorithm causes over smoothing or blocky artifacts in the reconstructed images. We propose to use dictionary learning (DL) based sparse signal representation in the formation of the prior for MAP PET image reconstruction. The dictionary to sparsify the PET images in the reconstruction process is learned from various training images including the corresponding MR structural image and a self-created hollow sphere. Using simulated and patient brain PET data with corresponding MR images, we study the performance of the DL-MAP algorithm and compare it quantitatively with a conventional MAP algorithm, a TV-MAP algorithm, and a patch-based algorithm. The DL-MAP algorithm achieves improved bias and contrast (or regional mean values) at comparable noise to what the other MAP algorithms acquire. The dictionary learned from the hollow sphere leads to similar results as the dictionary learned from the corresponding MR image. Achieving robust performance in various noise-level simulation and patient studies, the DL-MAP algorithm with a general dictionary demonstrates its potential in quantitative PET imaging.

Layout compliance for triple patterning lithography: an iterative approach

NASA Astrophysics Data System (ADS)

Yu, Bei; Garreton, Gilda; Pan, David Z.

2014-10-01

As the semiconductor process further scales down, the industry encounters many lithography-related issues. In the 14nm logic node and beyond, triple patterning lithography (TPL) is one of the most promising techniques for Metal1 layer and possibly Via0 layer. As one of the most challenging problems in TPL, recently layout decomposition efforts have received more attention from both industry and academia. Ideally the decomposer should point out locations in the layout that are not triple patterning decomposable and therefore manual intervention by designers is required. A traditional decomposition flow would be an iterative process, where each iteration consists of an automatic layout decomposition step and manual layout modification task. However, due to the NP-hardness of triple patterning layout decomposition, automatic full chip level layout decomposition requires long computational time and therefore design closure issues continue to linger around in the traditional flow. Challenged by this issue, we present a novel incremental layout decomposition framework to facilitate accelerated iterative decomposition. In the first iteration, our decomposer not only points out all conflicts, but also provides the suggestions to fix them. After the layout modification, instead of solving the full chip problem from scratch, our decomposer can provide a quick solution for a selected portion of layout. We believe this framework is efficient, in terms of performance and designer friendly.

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.

Real-time blind image deconvolution based on coordinated framework of FPGA and DSP

NASA Astrophysics Data System (ADS)

Wang, Ze; Li, Hang; Zhou, Hua; Liu, Hongjun

2015-10-01

Image restoration takes a crucial place in several important application domains. With the increasing of computation requirement as the algorithms become much more complexity, there has been a significant rise in the need for accelerating implementation. In this paper, we focus on an efficient real-time image processing system for blind iterative deconvolution method by means of the Richardson-Lucy (R-L) algorithm. We study the characteristics of algorithm, and an image restoration processing system based on the coordinated framework of FPGA and DSP (CoFD) is presented. Single precision floating-point processing units with small-scale cascade and special FFT/IFFT processing modules are adopted to guarantee the accuracy of the processing. Finally, Comparing experiments are done. The system could process a blurred image of 128×128 pixels within 32 milliseconds, and is up to three or four times faster than the traditional multi-DSPs systems.

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.

Density control in ITER: an iterative learning control and robust control approach

NASA Astrophysics Data System (ADS)

Ravensbergen, T.; de Vries, P. C.; Felici, F.; Blanken, T. C.; Nouailletas, R.; Zabeo, L.

2018-01-01

Plasma density control for next generation tokamaks, such as ITER, is challenging because of multiple reasons. The response of the usual gas valve actuators in future, larger fusion devices, might be too slow for feedback control. Both pellet fuelling and the use of feedforward-based control may help to solve this problem. Also, tight density limits arise during ramp-up, due to operational limits related to divertor detachment and radiative collapses. As the number of shots available for controller tuning will be limited in ITER, in this paper, iterative learning control (ILC) is proposed to determine optimal feedforward actuator inputs based on tracking errors, obtained in previous shots. This control method can take the actuator and density limits into account and can deal with large actuator delays. However, a purely feedforward-based density control may not be sufficient due to the presence of disturbances and shot-to-shot differences. Therefore, robust control synthesis is used to construct a robustly stabilizing feedback controller. In simulations, it is shown that this combined controller strategy is able to achieve good tracking performance in the presence of shot-to-shot differences, tight constraints, and model mismatches.

Engineering the on-axis intensity of Bessel beam by a feedback tuning loop

NASA Astrophysics Data System (ADS)

Li, Runze; Yu, Xianghua; Yang, Yanlong; Peng, Tong; Yao, Baoli; Zhang, Chunmin; Ye, Tong

2018-02-01

The Bessel beam belongs to a typical class of non-diffractive optical fields that are characterized by their invariant focal profiles along the propagation direction. However, ideal Bessel beams only rigorously exist in theory; Bessel beams generated in the lab are quasi-Bessel beams with finite focal extensions and varying intensity profiles along the propagation axis. The ability to engineer the on-axis intensity profile to the desired shape is essential for many applications. Here we demonstrate an iterative optimization-based approach to engineering the on-axis intensity of Bessel beams. The genetic algorithm is used to demonstrate this approach. Starting with a traditional axicon phase mask, in the design process, the computed on-axis beam profile is fed into a feedback tuning loop of an iterative optimization process, which searches for an optimal radial phase distribution that can generate a generalized Bessel beam with the desired onaxis intensity profile. The experimental implementation involves a fine-tuning process that adjusts the originally targeted profile so that the optimization process can optimize the phase mask to yield an improved on-axis profile. Our proposed method has been demonstrated in engineering several zeroth-order Bessel beams with customized on-axis profiles. High accuracy and high energy throughput merit its use in many applications.

Development of a multimedia educational programme for first-time hearing aid users: a participatory design.

PubMed

Ferguson, Melanie; Leighton, Paul; Brandreth, Marian; Wharrad, Heather

2018-05-02

To develop content for a series of interactive video tutorials (or reusable learning objects, RLOs) for first-time adult hearing aid users, to enhance knowledge of hearing aids and communication. RLO content was based on an electronically-delivered Delphi review, workshops, and iterative peer-review and feedback using a mixed-methods participatory approach. An expert panel of 33 hearing healthcare professionals, and workshops involving 32 hearing aid users and 11 audiologists. This ensured that social, emotional and practical experiences of the end-user alongside clinical validity were captured. Content for evidence-based, self-contained RLOs based on pedagogical principles was developed for delivery via DVD for television, PC or internet. Content was developed based on Delphi review statements about essential information that reached consensus (≥90%), visual representations of relevant concepts relating to hearing aids and communication, and iterative peer-review and feedback of content. This participatory approach recognises and involves key stakeholders in the design process to create content for a user-friendly multimedia educational intervention, to supplement the clinical management of first-time hearing aid users. We propose participatory methodologies are used in the development of content for e-learning interventions in hearing-related research and clinical practice.

An iterative method for near-field Fresnel region polychromatic phase contrast imaging

NASA Astrophysics Data System (ADS)

Carroll, Aidan J.; van Riessen, Grant A.; Balaur, Eugeniu; Dolbnya, Igor P.; Tran, Giang N.; Peele, Andrew G.

2017-07-01

We present an iterative method for polychromatic phase contrast imaging that is suitable for broadband illumination and which allows for the quantitative determination of the thickness of an object given the refractive index of the sample material. Experimental and simulation results suggest the iterative method provides comparable image quality and quantitative object thickness determination when compared to the analytical polychromatic transport of intensity and contrast transfer function methods. The ability of the iterative method to work over a wider range of experimental conditions means the iterative method is a suitable candidate for use with polychromatic illumination and may deliver more utility for laboratory-based x-ray sources, which typically have a broad spectrum.

LDPC-based iterative joint source-channel decoding for JPEG2000.

PubMed

Pu, Lingling; Wu, Zhenyu; Bilgin, Ali; Marcellin, Michael W; Vasic, Bane

2007-02-01

A framework is proposed for iterative joint source-channel decoding of JPEG2000 codestreams. At the encoder, JPEG2000 is used to perform source coding with certain error-resilience (ER) modes, and LDPC codes are used to perform channel coding. During decoding, the source decoder uses the ER modes to identify corrupt sections of the codestream and provides this information to the channel decoder. Decoding is carried out jointly in an iterative fashion. Experimental results indicate that the proposed method requires fewer iterations and improves overall system performance.

Advanced density profile reflectometry; the state-of-the-art and measurement prospects for ITER

NASA Astrophysics Data System (ADS)

Doyle, E. J.

2006-10-01

Dramatic progress in millimeter-wave technology has allowed the realization of a key goal for ITER diagnostics, the routine measurement of the plasma density profile from millimeter-wave radar (reflectometry) measurements. In reflectometry, the measured round-trip group delay of a probe beam reflected from a plasma cutoff is used to infer the density distribution in the plasma. Reflectometer systems implemented by UCLA on a number of devices employ frequency-modulated continuous-wave (FM-CW), ultrawide-bandwidth, high-resolution radar systems. One such system on DIII-D has routinely demonstrated measurements of the density profile over a range of electron density of 0-6.4x10^19,m-3, with ˜25 μs time and ˜4 mm radial resolution, meeting key ITER requirements. This progress in performance was made possible by multiple advances in the areas of millimeter-wave technology, novel measurement techniques, and improved understanding, including: (i) fast sweep, solid-state, wide bandwidth sources and power amplifiers, (ii) dual polarization measurements to expand the density range, (iii) adaptive radar-based data analysis with parallel processing on a Unix cluster, (iv) high memory depth data acquisition, and (v) advances in full wave code modeling. The benefits of advanced system performance will be illustrated using measurements from a wide range of phenomena, including ELM and fast-ion driven mode dynamics, L-H transition studies and plasma-wall interaction. The measurement capabilities demonstrated by these systems provide a design basis for the development of the main ITER profile reflectometer system. This talk will explore the extent to which these reflectometer system designs, results and experience can be translated to ITER, and will identify what new studies and experimental tests are essential.

Formulation for Simultaneous Aerodynamic Analysis and Design Optimization

NASA Technical Reports Server (NTRS)

Hou, G. W.; Taylor, A. C., III; Mani, S. V.; Newman, P. A.

1993-01-01

An efficient approach for simultaneous aerodynamic analysis and design optimization is presented. This approach does not require the performance of many flow analyses at each design optimization step, which can be an expensive procedure. Thus, this approach brings us one step closer to meeting the challenge of incorporating computational fluid dynamic codes into gradient-based optimization techniques for aerodynamic design. An adjoint-variable method is introduced to nullify the effect of the increased number of design variables in the problem formulation. The method has been successfully tested on one-dimensional nozzle flow problems, including a sample problem with a normal shock. Implementations of the above algorithm are also presented that incorporate Newton iterations to secure a high-quality flow solution at the end of the design process. Implementations with iterative flow solvers are possible and will be required for large, multidimensional flow problems.

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.

Evaluation of the cryogenic mechanical properties of the insulation material for ITER Feeder superconducting joint

NASA Astrophysics Data System (ADS)

Wu, Zhixiong; Huang, Rongjin; Huang, ChuanJun; Yang, Yanfang; Huang, Xiongyi; Li, Laifeng

2017-12-01

The Glass-fiber reinforced plastic (GFRP) fabricated by the vacuum bag process was selected as the high voltage electrical insulation and mechanical support for the superconducting joints and the current leads for the ITER Feeder system. To evaluate the cryogenic mechanical properties of the GFRP, the mechanical properties such as the short beam strength (SBS), the tensile strength and the fatigue fracture strength after 30,000 cycles, were measured at 77K in this study. The results demonstrated that the GFRP met the design requirements of ITER.

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.

Automating Rule Strengths in Expert Systems.

DTIC Science & Technology

1987-05-01

systems were designed in an incremental, iterative way. One of the most easily identifiable phases in this process, sometimes called tuning, consists...attenuators. The designer of the knowledge-based system must determine (synthesize) or adjust (xfine, if estimates of the values are given) these...values. We consider two ways in which the designer can learn the values. We call the first model of learning the complete case and the second model the

16QAM transmission with 5.2 bits/s/Hz spectral efficiency over transoceanic distance.

PubMed

Zhang, H; Cai, J-X; Batshon, H G; Davidson, C R; Sun, Y; Mazurczyk, M; Foursa, D G; Pilipetskii, A; Mohs, G; Bergano, Neal S

2012-05-21

We transmit 160 x 100 G PDM RZ 16 QAM channels with 5.2 bits/s/Hz spectral efficiency over 6,860 km. There are more than 3 billion 16 QAM symbols, i.e., 12 billion bits, processed in total. Using coded modulation and iterative decoding between a MAP decoder and an LDPC based FEC all channels are decoded with no remaining errors.

Learning to read aloud: A neural network approach using sparse distributed memory

NASA Technical Reports Server (NTRS)

Joglekar, Umesh Dwarkanath

1989-01-01

An attempt to solve a problem of text-to-phoneme mapping is described which does not appear amenable to solution by use of standard algorithmic procedures. Experiments based on a model of distributed processing are also described. This model (sparse distributed memory (SDM)) can be used in an iterative supervised learning mode to solve the problem. Additional improvements aimed at obtaining better performance are suggested.

Powerful Design Principles and Processes: Lessons from a Case of Ambitious Civics Education Curriculum Planning. A Response to "Reinventing the High School Government Course: Rigor, Simulations, and Learning from Text"

ERIC Educational Resources Information Center

Dinkelman, Todd

2016-01-01

In "Reinventing the High School Government Course," the authors presented the latest iteration of an ambitious AP government course developed over a seven-year design-based implementation research project. Chiefly addressed to curriculum developers and civics teachers, the article elaborates key design principles, provides a description…

Suppression of tritium retention in remote areas of ITER by nonperturbative reactive gas injection.

PubMed

Tabarés, F L; Ferreira, J A; Ramos, A; van Rooij, G; Westerhout, J; Al, R; Rapp, J; Drenik, A; Mozetic, M

2010-10-22

A technique based on reactive gas injection in the afterglow region of the divertor plasma is proposed for the suppression of tritium-carbon codeposits in remote areas of ITER when operated with carbon-based divertor targets. Experiments in a divertor simulator plasma device indicate that a 4  nm/min deposition can be suppressed by addition of 1  Pa·m³ s⁻¹ ammonia flow at 10 cm from the plasma. These results bolster the concept of nonperturbative scavenger injection for tritium inventory control in carbon-based fusion plasma devices, thus paving the way for ITER operation in the active phase under a carbon-dominated, plasma facing component background.

Identification of different geologic units using fuzzy constrained resistivity tomography

NASA Astrophysics Data System (ADS)

Singh, Anand; Sharma, S. P.

2018-01-01

Different geophysical inversion strategies are utilized as a component of an interpretation process that tries to separate geologic units based on the resistivity distribution. In the present study, we present the results of separating different geologic units using fuzzy constrained resistivity tomography. This was accomplished using fuzzy c means, a clustering procedure to improve the 2D resistivity image and geologic separation within the iterative minimization through inversion. First, we developed a Matlab-based inversion technique to obtain a reliable resistivity image using different geophysical data sets (electrical resistivity and electromagnetic data). Following this, the recovered resistivity model was converted into a fuzzy constrained resistivity model by assigning the highest probability value of each model cell to the cluster utilizing fuzzy c means clustering procedure during the iterative process. The efficacy of the algorithm is demonstrated using three synthetic plane wave electromagnetic data sets and one electrical resistivity field dataset. The presented approach shows improvement on the conventional inversion approach to differentiate between different geologic units if the correct number of geologic units will be identified. Further, fuzzy constrained resistivity tomography was performed to examine the augmentation of uranium mineralization in the Beldih open cast mine as a case study. We also compared geologic units identified by fuzzy constrained resistivity tomography with geologic units interpreted from the borehole information.

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…

Computed Tomography Image Quality Evaluation of a New Iterative Reconstruction Algorithm in the Abdomen (Adaptive Statistical Iterative Reconstruction-V) a Comparison With Model-Based Iterative Reconstruction, Adaptive Statistical Iterative Reconstruction, and Filtered Back Projection Reconstructions.

PubMed

Goodenberger, Martin H; Wagner-Bartak, Nicolaus A; Gupta, Shiva; Liu, Xinming; Yap, Ramon Q; Sun, Jia; Tamm, Eric P; Jensen, Corey T

The purpose of this study was to compare abdominopelvic computed tomography images reconstructed with adaptive statistical iterative reconstruction-V (ASIR-V) with model-based iterative reconstruction (Veo 3.0), ASIR, and filtered back projection (FBP). Abdominopelvic computed tomography scans for 36 patients (26 males and 10 females) were reconstructed using FBP, ASIR (80%), Veo 3.0, and ASIR-V (30%, 60%, 90%). Mean ± SD patient age was 32 ± 10 years with mean ± SD body mass index of 26.9 ± 4.4 kg/m. Images were reviewed by 2 independent readers in a blinded, randomized fashion. Hounsfield unit, noise, and contrast-to-noise ratio (CNR) values were calculated for each reconstruction algorithm for further comparison. Phantom evaluation of low-contrast detectability (LCD) and high-contrast resolution was performed. Adaptive statistical iterative reconstruction-V 30%, ASIR-V 60%, and ASIR 80% were generally superior qualitatively compared with ASIR-V 90%, Veo 3.0, and FBP (P < 0.05). Adaptive statistical iterative reconstruction-V 90% showed superior LCD and had the highest CNR in the liver, aorta, and, pancreas, measuring 7.32 ± 3.22, 11.60 ± 4.25, and 4.60 ± 2.31, respectively, compared with the next best series of ASIR-V 60% with respective CNR values of 5.54 ± 2.39, 8.78 ± 3.15, and 3.49 ± 1.77 (P <0.0001). Veo 3.0 and ASIR 80% had the best and worst spatial resolution, respectively. Adaptive statistical iterative reconstruction-V 30% and ASIR-V 60% provided the best combination of qualitative and quantitative performance. Adaptive statistical iterative reconstruction 80% was equivalent qualitatively, but demonstrated inferior spatial resolution and LCD.

Iterative discrete ordinates solution of the equation for surface-reflected radiance

NASA Astrophysics Data System (ADS)

Radkevich, Alexander

2017-11-01

This paper presents a new method of numerical solution of the integral equation for the radiance reflected from an anisotropic surface. The equation relates the radiance at the surface level with BRDF and solutions of the standard radiative transfer problems for a slab with no reflection on its surfaces. It is also shown that the kernel of the equation satisfies the condition of the existence of a unique solution and the convergence of the successive approximations to that solution. The developed method features two basic steps: discretization on a 2D quadrature, and solving the resulting system of algebraic equations with successive over-relaxation method based on the Gauss-Seidel iterative process. Presented numerical examples show good coincidence between the surface-reflected radiance obtained with DISORT and the proposed method. Analysis of contributions of the direct and diffuse (but not yet reflected) parts of the downward radiance to the total solution is performed. Together, they represent a very good initial guess for the iterative process. This fact ensures fast convergence. The numerical evidence is given that the fastest convergence occurs with the relaxation parameter of 1 (no relaxation). An integral equation for BRDF is derived as inversion of the original equation. The potential of this new equation for BRDF retrievals is analyzed. The approach is found not viable as the BRDF equation appears to be an ill-posed problem, and it requires knowledge the surface-reflected radiance on the entire domain of both Sun and viewing zenith angles.

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.

Design of 4D x-ray tomography experiments for reconstruction using regularized iterative algorithms

NASA Astrophysics Data System (ADS)

Mohan, K. Aditya

2017-10-01

4D X-ray computed tomography (4D-XCT) is widely used to perform non-destructive characterization of time varying physical processes in various materials. The conventional approach to improving temporal resolution in 4D-XCT involves the development of expensive and complex instrumentation that acquire data faster with reduced noise. It is customary to acquire data with many tomographic views at a high signal to noise ratio. Instead, temporal resolution can be improved using regularized iterative algorithms that are less sensitive to noise and limited views. These algorithms benefit from optimization of other parameters such as the view sampling strategy while improving temporal resolution by reducing the total number of views or the detector exposure time. This paper presents the design principles of 4D-XCT experiments when using regularized iterative algorithms derived using the framework of model-based reconstruction. A strategy for performing 4D-XCT experiments is presented that allows for improving the temporal resolution by progressively reducing the number of views or the detector exposure time. Theoretical analysis of the effect of the data acquisition parameters on the detector signal to noise ratio, spatial reconstruction resolution, and temporal reconstruction resolution is also presented in this paper.

Nonconvex Nonsmooth Low Rank Minimization via Iteratively Reweighted Nuclear Norm.

PubMed

Lu, Canyi; Tang, Jinhui; Yan, Shuicheng; Lin, Zhouchen

2016-02-01

The nuclear norm is widely used as a convex surrogate of the rank function in compressive sensing for low rank matrix recovery with its applications in image recovery and signal processing. However, solving the nuclear norm-based relaxed convex problem usually leads to a suboptimal solution of the original rank minimization problem. In this paper, we propose to use a family of nonconvex surrogates of L0-norm on the singular values of a matrix to approximate the rank function. This leads to a nonconvex nonsmooth minimization problem. Then, we propose to solve the problem by an iteratively re-weighted nuclear norm (IRNN) algorithm. IRNN iteratively solves a weighted singular value thresholding problem, which has a closed form solution due to the special properties of the nonconvex surrogate functions. We also extend IRNN to solve the nonconvex problem with two or more blocks of variables. In theory, we prove that the IRNN decreases the objective function value monotonically, and any limit point is a stationary point. Extensive experiments on both synthesized data and real images demonstrate that IRNN enhances the low rank matrix recovery compared with the state-of-the-art convex algorithms.

Fully coupled simulation of multiple hydraulic fractures to propagate simultaneously from a perforated horizontal wellbore

NASA Astrophysics Data System (ADS)

Zeng, Qinglei; Liu, Zhanli; Wang, Tao; Gao, Yue; Zhuang, Zhuo

2018-02-01

In hydraulic fracturing process in shale rock, multiple fractures perpendicular to a horizontal wellbore are usually driven to propagate simultaneously by the pumping operation. In this paper, a numerical method is developed for the propagation of multiple hydraulic fractures (HFs) by fully coupling the deformation and fracturing of solid formation, fluid flow in fractures, fluid partitioning through a horizontal wellbore and perforation entry loss effect. The extended finite element method (XFEM) is adopted to model arbitrary growth of the fractures. Newton's iteration is proposed to solve these fully coupled nonlinear equations, which is more efficient comparing to the widely adopted fixed-point iteration in the literatures and avoids the need to impose fluid pressure boundary condition when solving flow equations. A secant iterative method based on the stress intensity factor (SIF) is proposed to capture different propagation velocities of multiple fractures. The numerical results are compared with theoretical solutions in literatures to verify the accuracy of the method. The simultaneous propagation of multiple HFs is simulated by the newly proposed algorithm. The coupled influences of propagation regime, stress interaction, wellbore pressure loss and perforation entry loss on simultaneous propagation of multiple HFs are investigated.

Estimation of Longitudinal Force and Sideslip Angle for Intelligent Four-Wheel Independent Drive Electric Vehicles by Observer Iteration and Information Fusion.

PubMed

Chen, Te; Chen, Long; Xu, Xing; Cai, Yingfeng; Jiang, Haobin; Sun, Xiaoqiang

2018-04-20

Exact estimation of longitudinal force and sideslip angle is important for lateral stability and path-following control of four-wheel independent driven electric vehicle. This paper presents an effective method for longitudinal force and sideslip angle estimation by observer iteration and information fusion for four-wheel independent drive electric vehicles. The electric driving wheel model is introduced into the vehicle modeling process and used for longitudinal force estimation, the longitudinal force reconstruction equation is obtained via model decoupling, the a Luenberger observer and high-order sliding mode observer are united for longitudinal force observer design, and the Kalman filter is applied to restrain the influence of noise. Via the estimated longitudinal force, an estimation strategy is then proposed based on observer iteration and information fusion, in which the Luenberger observer is applied to achieve the transcendental estimation utilizing less sensor measurements, the extended Kalman filter is used for a posteriori estimation with higher accuracy, and a fuzzy weight controller is used to enhance the adaptive ability of observer system. Simulations and experiments are carried out, and the effectiveness of proposed estimation method is verified.

Estimation of Longitudinal Force and Sideslip Angle for Intelligent Four-Wheel Independent Drive Electric Vehicles by Observer Iteration and Information Fusion

PubMed Central

Chen, Long; Xu, Xing; Cai, Yingfeng; Jiang, Haobin; Sun, Xiaoqiang

2018-01-01

Exact estimation of longitudinal force and sideslip angle is important for lateral stability and path-following control of four-wheel independent driven electric vehicle. This paper presents an effective method for longitudinal force and sideslip angle estimation by observer iteration and information fusion for four-wheel independent drive electric vehicles. The electric driving wheel model is introduced into the vehicle modeling process and used for longitudinal force estimation, the longitudinal force reconstruction equation is obtained via model decoupling, the a Luenberger observer and high-order sliding mode observer are united for longitudinal force observer design, and the Kalman filter is applied to restrain the influence of noise. Via the estimated longitudinal force, an estimation strategy is then proposed based on observer iteration and information fusion, in which the Luenberger observer is applied to achieve the transcendental estimation utilizing less sensor measurements, the extended Kalman filter is used for a posteriori estimation with higher accuracy, and a fuzzy weight controller is used to enhance the adaptive ability of observer system. Simulations and experiments are carried out, and the effectiveness of proposed estimation method is verified. PMID:29677124

Non-iterative volumetric particle reconstruction near moving bodies

NASA Astrophysics Data System (ADS)

Mendelson, Leah; Techet, Alexandra

2017-11-01

When multi-camera 3D PIV experiments are performed around a moving body, the body often obscures visibility of regions of interest in the flow field in a subset of cameras. We evaluate the performance of non-iterative particle reconstruction algorithms used for synthetic aperture PIV (SAPIV) in these partially-occluded regions. We show that when partial occlusions are present, the quality and availability of 3D tracer particle information depends on the number of cameras and reconstruction procedure used. Based on these findings, we introduce an improved non-iterative reconstruction routine for SAPIV around bodies. The reconstruction procedure combines binary masks, already required for reconstruction of the body's 3D visual hull, and a minimum line-of-sight algorithm. This approach accounts for partial occlusions without performing separate processing for each possible subset of cameras. We combine this reconstruction procedure with three-dimensional imaging on both sides of the free surface to reveal multi-fin wake interactions generated by a jumping archer fish. Sufficient particle reconstruction in near-body regions is crucial to resolving the wake structures of upstream fins (i.e., dorsal and anal fins) before and during interactions with the caudal tail.

SU-E-I-33: Initial Evaluation of Model-Based Iterative CT Reconstruction Using Standard Image Quality Phantoms

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

Gingold, E; Dave, J

2014-06-01

Purpose: The purpose of this study was to compare a new model-based iterative reconstruction with existing reconstruction methods (filtered backprojection and basic iterative reconstruction) using quantitative analysis of standard image quality phantom images. Methods: An ACR accreditation phantom (Gammex 464) and a CATPHAN600 phantom were scanned using 3 routine clinical acquisition protocols (adult axial brain, adult abdomen, and pediatric abdomen) on a Philips iCT system. Each scan was acquired using default conditions and 75%, 50% and 25% dose levels. Images were reconstructed using standard filtered backprojection (FBP), conventional iterative reconstruction (iDose4) and a prototype model-based iterative reconstruction (IMR). Phantom measurementsmore » included CT number accuracy, contrast to noise ratio (CNR), modulation transfer function (MTF), low contrast detectability (LCD), and noise power spectrum (NPS). Results: The choice of reconstruction method had no effect on CT number accuracy, or MTF (p<0.01). The CNR of a 6 HU contrast target was improved by 1–67% with iDose4 relative to FBP, while IMR improved CNR by 145–367% across all protocols and dose levels. Within each scan protocol, the CNR improvement from IMR vs FBP showed a general trend of greater improvement at lower dose levels. NPS magnitude was greatest for FBP and lowest for IMR. The NPS of the IMR reconstruction showed a pronounced decrease with increasing spatial frequency, consistent with the unusual noise texture seen in IMR images. Conclusion: Iterative Model Reconstruction reduces noise and improves contrast-to-noise ratio without sacrificing spatial resolution in CT phantom images. This offers the possibility of radiation dose reduction and improved low contrast detectability compared with filtered backprojection or conventional iterative reconstruction.« less

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.

Knowledge-based iterative model reconstruction: comparative image quality and radiation dose with a pediatric computed tomography phantom.

PubMed

Ryu, Young Jin; Choi, Young Hun; Cheon, Jung-Eun; Ha, Seongmin; Kim, Woo Sun; Kim, In-One

2016-03-01

CT of pediatric phantoms can provide useful guidance to the optimization of knowledge-based iterative reconstruction CT. To compare radiation dose and image quality of CT images obtained at different radiation doses reconstructed with knowledge-based iterative reconstruction, hybrid iterative reconstruction and filtered back-projection. We scanned a 5-year anthropomorphic phantom at seven levels of radiation. We then reconstructed CT data with knowledge-based iterative reconstruction (iterative model reconstruction [IMR] levels 1, 2 and 3; Philips Healthcare, Andover, MA), hybrid iterative reconstruction (iDose(4), levels 3 and 7; Philips Healthcare, Andover, MA) and filtered back-projection. The noise, signal-to-noise ratio and contrast-to-noise ratio were calculated. We evaluated low-contrast resolutions and detectability by low-contrast targets and subjective and objective spatial resolutions by the line pairs and wire. With radiation at 100 peak kVp and 100 mAs (3.64 mSv), the relative doses ranged from 5% (0.19 mSv) to 150% (5.46 mSv). Lower noise and higher signal-to-noise, contrast-to-noise and objective spatial resolution were generally achieved in ascending order of filtered back-projection, iDose(4) levels 3 and 7, and IMR levels 1, 2 and 3, at all radiation dose levels. Compared with filtered back-projection at 100% dose, similar noise levels were obtained on IMR level 2 images at 24% dose and iDose(4) level 3 images at 50% dose, respectively. Regarding low-contrast resolution, low-contrast detectability and objective spatial resolution, IMR level 2 images at 24% dose showed comparable image quality with filtered back-projection at 100% dose. Subjective spatial resolution was not greatly affected by reconstruction algorithm. Reduced-dose IMR obtained at 0.92 mSv (24%) showed similar image quality to routine-dose filtered back-projection obtained at 3.64 mSv (100%), and half-dose iDose(4) obtained at 1.81 mSv.

Approximate Joint Diagonalization and Geometric Mean of Symmetric Positive Definite Matrices

PubMed Central

Congedo, Marco; Afsari, Bijan; Barachant, Alexandre; Moakher, Maher

2015-01-01

We explore the connection between two problems that have arisen independently in the signal processing and related fields: the estimation of the geometric mean of a set of symmetric positive definite (SPD) matrices and their approximate joint diagonalization (AJD). Today there is a considerable interest in estimating the geometric mean of a SPD matrix set in the manifold of SPD matrices endowed with the Fisher information metric. The resulting mean has several important invariance properties and has proven very useful in diverse engineering applications such as biomedical and image data processing. While for two SPD matrices the mean has an algebraic closed form solution, for a set of more than two SPD matrices it can only be estimated by iterative algorithms. However, none of the existing iterative algorithms feature at the same time fast convergence, low computational complexity per iteration and guarantee of convergence. For this reason, recently other definitions of geometric mean based on symmetric divergence measures, such as the Bhattacharyya divergence, have been considered. The resulting means, although possibly useful in practice, do not satisfy all desirable invariance properties. In this paper we consider geometric means of covariance matrices estimated on high-dimensional time-series, assuming that the data is generated according to an instantaneous mixing model, which is very common in signal processing. We show that in these circumstances we can approximate the Fisher information geometric mean by employing an efficient AJD algorithm. Our approximation is in general much closer to the Fisher information geometric mean as compared to its competitors and verifies many invariance properties. Furthermore, convergence is guaranteed, the computational complexity is low and the convergence rate is quadratic. The accuracy of this new geometric mean approximation is demonstrated by means of simulations. PMID:25919667

Large Airborne Full Tensor Gradient Data Inversion Based on a Non-Monotone Gradient Method

NASA Astrophysics Data System (ADS)

Sun, Yong; Meng, Zhaohai; Li, Fengting

2018-03-01

Following the development of gravity gradiometer instrument technology, the full tensor gravity (FTG) data can be acquired on airborne and marine platforms. Large-scale geophysical data can be obtained using these methods, making such data sets a number of the "big data" category. Therefore, a fast and effective inversion method is developed to solve the large-scale FTG data inversion problem. Many algorithms are available to accelerate the FTG data inversion, such as conjugate gradient method. However, the conventional conjugate gradient method takes a long time to complete data processing. Thus, a fast and effective iterative algorithm is necessary to improve the utilization of FTG data. Generally, inversion processing is formulated by incorporating regularizing constraints, followed by the introduction of a non-monotone gradient-descent method to accelerate the convergence rate of FTG data inversion. Compared with the conventional gradient method, the steepest descent gradient algorithm, and the conjugate gradient algorithm, there are clear advantages of the non-monotone iterative gradient-descent algorithm. Simulated and field FTG data were applied to show the application value of this new fast inversion method.

Identification of stable areas in unreferenced laser scans for automated geomorphometric monitoring

NASA Astrophysics Data System (ADS)

Wujanz, Daniel; Avian, Michael; Krueger, Daniel; Neitzel, Frank

2018-04-01

Current research questions in the field of geomorphology focus on the impact of climate change on several processes subsequently causing natural hazards. Geodetic deformation measurements are a suitable tool to document such geomorphic mechanisms, e.g. by capturing a region of interest with terrestrial laser scanners which results in a so-called 3-D point cloud. The main problem in deformation monitoring is the transformation of 3-D point clouds captured at different points in time (epochs) into a stable reference coordinate system. In this contribution, a surface-based registration methodology is applied, termed the iterative closest proximity algorithm (ICProx), that solely uses point cloud data as input, similar to the iterative closest point algorithm (ICP). The aim of this study is to automatically classify deformations that occurred at a rock glacier and an ice glacier, as well as in a rockfall area. For every case study, two epochs were processed, while the datasets notably differ in terms of geometric characteristics, distribution and magnitude of deformation. In summary, the ICProx algorithm's classification accuracy is 70 % on average in comparison to reference data.

Recognition of genetically modified product based on affinity propagation clustering and terahertz spectroscopy

NASA Astrophysics Data System (ADS)

Liu, Jianjun; Kan, Jianquan

2018-04-01

In this paper, based on the terahertz spectrum, a new identification method of genetically modified material by support vector machine (SVM) based on affinity propagation clustering is proposed. This algorithm mainly uses affinity propagation clustering algorithm to make cluster analysis and labeling on unlabeled training samples, and in the iterative process, the existing SVM training data are continuously updated, when establishing the identification model, it does not need to manually label the training samples, thus, the error caused by the human labeled samples is reduced, and the identification accuracy of the model is greatly improved.

Iterative inversion of deformation vector fields with feedback control.

PubMed

Dubey, Abhishek; Iliopoulos, Alexandros-Stavros; Sun, Xiaobai; Yin, Fang-Fang; Ren, Lei

2018-05-14

Often, the inverse deformation vector field (DVF) is needed together with the corresponding forward DVF in four-dimesional (4D) reconstruction and dose calculation, adaptive radiation therapy, and simultaneous deformable registration. This study aims at improving both accuracy and efficiency of iterative algorithms for DVF inversion, and advancing our understanding of divergence and latency conditions. We introduce a framework of fixed-point iteration algorithms with active feedback control for DVF inversion. Based on rigorous convergence analysis, we design control mechanisms for modulating the inverse consistency (IC) residual of the current iterate, to be used as feedback into the next iterate. The control is designed adaptively to the input DVF with the objective to enlarge the convergence area and expedite convergence. Three particular settings of feedback control are introduced: constant value over the domain throughout the iteration; alternating values between iteration steps; and spatially variant values. We also introduce three spectral measures of the displacement Jacobian for characterizing a DVF. These measures reveal the critical role of what we term the nontranslational displacement component (NTDC) of the DVF. We carry out inversion experiments with an analytical DVF pair, and with DVFs associated with thoracic CT images of six patients at end of expiration and end of inspiration. The NTDC-adaptive iterations are shown to attain a larger convergence region at a faster pace compared to previous nonadaptive DVF inversion iteration algorithms. By our numerical experiments, alternating control yields smaller IC residuals and inversion errors than constant control. Spatially variant control renders smaller residuals and errors by at least an order of magnitude, compared to other schemes, in no more than 10 steps. Inversion results also show remarkable quantitative agreement with analysis-based predictions. Our analysis captures properties of DVF data associated with clinical CT images, and provides new understanding of iterative DVF inversion algorithms with a simple residual feedback control. Adaptive control is necessary and highly effective in the presence of nonsmall NTDCs. The adaptive iterations or the spectral measures, or both, may potentially be incorporated into deformable image registration methods. © 2018 American Association of Physicists in Medicine.

Total quality management - It works for aerospace information services

NASA Technical Reports Server (NTRS)

Erwin, James; Eberline, Carl; Colquitt, Wanda

1993-01-01

Today we are in the midst of information and 'total quality' revolutions. At the NASA STI Program's Center for AeroSpace Information (CASI), we are focused on using continuous improvements techniques to enrich today's services and products and to ensure that tomorrow's technology supports the TQM-based improvement of future STI program products and services. The Continuous Improvements Program at CASI is the foundation for Total Quality Management in products and services. The focus is customer-driven; its goal, to identify processes and procedures that can be improved and new technologies that can be integrated with the processes to gain efficiencies, provide effectiveness, and promote customer satisfaction. This Program seeks to establish quality through an iterative defect prevention approach that is based on the incorporation of standards and measurements into the processing cycle.

The Verification-based Analysis of Reliable Multicast Protocol

NASA Technical Reports Server (NTRS)

Wu, Yunqing

1996-01-01

Reliable Multicast Protocol (RMP) is a communication protocol that provides an atomic, totally ordered, reliable multicast service on top of unreliable IP Multicasting. In this paper, we develop formal models for R.W using existing automatic verification systems, and perform verification-based analysis on the formal RMP specifications. We also use the formal models of RW specifications to generate a test suite for conformance testing of the RMP implementation. Throughout the process of RMP development, we follow an iterative, interactive approach that emphasizes concurrent and parallel progress between the implementation and verification processes. Through this approach, we incorporate formal techniques into our development process, promote a common understanding for the protocol, increase the reliability of our software, and maintain high fidelity between the specifications of RMP and its implementation.

Preliminary consideration of CFETR ITER-like case diagnostic system.

PubMed

Li, G S; Yang, Y; Wang, Y M; Ming, T F; Han, X; Liu, S C; Wang, E H; Liu, Y K; Yang, W J; Li, G Q; Hu, Q S; Gao, X

2016-11-01

Chinese Fusion Engineering Test Reactor (CFETR) is a new superconducting tokamak device being designed in China, which aims at bridging the gap between ITER and DEMO, where DEMO is a tokamak demonstration fusion reactor. Two diagnostic cases, ITER-like case and towards DEMO case, have been considered for CFETR early and later operating phases, respectively. In this paper, some preliminary consideration of ITER-like case will be presented. Based on ITER diagnostic system, three versions of increased complexity and coverage of the ITER-like case diagnostic system have been developed with different goals and functions. Version A aims only machine protection and basic control. Both of version B and version C are mainly for machine protection, basic and advanced control, but version C has an increased level of redundancy necessary for improved measurements capability. The performance of these versions and needed R&D work are outlined.

Preliminary consideration of CFETR ITER-like case diagnostic system

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

Li, G. S.; Liu, Y. K.; Gao, X.

2016-11-15

Chinese Fusion Engineering Test Reactor (CFETR) is a new superconducting tokamak device being designed in China, which aims at bridging the gap between ITER and DEMO, where DEMO is a tokamak demonstration fusion reactor. Two diagnostic cases, ITER-like case and towards DEMO case, have been considered for CFETR early and later operating phases, respectively. In this paper, some preliminary consideration of ITER-like case will be presented. Based on ITER diagnostic system, three versions of increased complexity and coverage of the ITER-like case diagnostic system have been developed with different goals and functions. Version A aims only machine protection and basicmore » control. Both of version B and version C are mainly for machine protection, basic and advanced control, but version C has an increased level of redundancy necessary for improved measurements capability. The performance of these versions and needed R&D work are outlined.« less

Iterative CT reconstruction using coordinate descent with ordered subsets of data

NASA Astrophysics Data System (ADS)

Noo, F.; Hahn, K.; Schöndube, H.; Stierstorfer, K.

2016-04-01

Image reconstruction based on iterative minimization of a penalized weighted least-square criteria has become an important topic of research in X-ray computed tomography. This topic is motivated by increasing evidence that such a formalism may enable a significant reduction in dose imparted to the patient while maintaining or improving image quality. One important issue associated with this iterative image reconstruction concept is slow convergence and the associated computational effort. For this reason, there is interest in finding methods that produce approximate versions of the targeted image with a small number of iterations and an acceptable level of discrepancy. We introduce here a novel method to produce such approximations: ordered subsets in combination with iterative coordinate descent. Preliminary results demonstrate that this method can produce, within 10 iterations and using only a constant image as initial condition, satisfactory reconstructions that retain the noise properties of the targeted image.

Development of a video-based education and process change intervention to improve advance cardiopulmonary resuscitation decision-making.

PubMed

Waldron, Nicholas; Johnson, Claire E; Saul, Peter; Waldron, Heidi; Chong, Jeffrey C; Hill, Anne-Marie; Hayes, Barbara

2016-10-06

Advance cardiopulmonary resuscitation (CPR) decision-making and escalation of care discussions are variable in routine clinical practice. We aimed to explore physician barriers to advance CPR decision-making in an inpatient hospital setting and develop a pragmatic intervention to support clinicians to undertake and document routine advance care planning discussions. Two focus groups, which involved eight consultants and ten junior doctors, were conducted following a review of the current literature. A subsequent iterative consensus process developed two intervention elements: (i) an updated 'Goals of Patient Care' (GOPC) form and process; (ii) an education video and resources for teaching advance CPR decision-making and communication. A multidisciplinary group of health professionals and policy-makers with experience in systems development, education and research provided critical feedback. Three key themes emerged from the focus groups and the literature, which identified a structure for the intervention: (i) knowing what to say; (ii) knowing how to say it; (iii) wanting to say it. The themes informed the development of a video to provide education about advance CPR decision-making framework, improving communication and contextualising relevant clinical issues. Critical feedback assisted in refining the video and further guided development and evolution of a medical GOPC approach to discussing and recording medical treatment and advance care plans. Through an iterative process of consultation and review, video-based education and an expanded GOPC form and approach were developed to address physician and systemic barriers to advance CPR decision-making and documentation. Implementation and evaluation across hospital settings is required to examine utility and determine effect on quality of care.

Asymptotic (h tending to infinity) absolute stability for BDFs applied to stiff differential equations. [Backward Differentiation Formulas

NASA Technical Reports Server (NTRS)

Krogh, F. T.; Stewart, K.

1984-01-01

Methods based on backward differentiation formulas (BDFs) for solving stiff differential equations require iterating to approximate the solution of the corrector equation on each step. One hope for reducing the cost of this is to make do with iteration matrices that are known to have errors and to do no more iterations than are necessary to maintain the stability of the method. This paper, following work by Klopfenstein, examines the effect of errors in the iteration matrix on the stability of the method. Application of the results to an algorithm is discussed briefly.

An iterative solver for the 3D Helmholtz equation

NASA Astrophysics Data System (ADS)

Belonosov, Mikhail; Dmitriev, Maxim; Kostin, Victor; Neklyudov, Dmitry; Tcheverda, Vladimir

2017-09-01

We develop a frequency-domain iterative solver for numerical simulation of acoustic waves in 3D heterogeneous media. It is based on the application of a unique preconditioner to the Helmholtz equation that ensures convergence for Krylov subspace iteration methods. Effective inversion of the preconditioner involves the Fast Fourier Transform (FFT) and numerical solution of a series of boundary value problems for ordinary differential equations. Matrix-by-vector multiplication for iterative inversion of the preconditioned matrix involves inversion of the preconditioner and pointwise multiplication of grid functions. Our solver has been verified by benchmarking against exact solutions and a time-domain solver.

Compressively sampled MR image reconstruction using generalized thresholding iterative algorithm

NASA Astrophysics Data System (ADS)

Elahi, Sana; kaleem, Muhammad; Omer, Hammad

2018-01-01

Compressed sensing (CS) is an emerging area of interest in Magnetic Resonance Imaging (MRI). CS is used for the reconstruction of the images from a very limited number of samples in k-space. This significantly reduces the MRI data acquisition time. One important requirement for signal recovery in CS is the use of an appropriate non-linear reconstruction algorithm. It is a challenging task to choose a reconstruction algorithm that would accurately reconstruct the MR images from the under-sampled k-space data. Various algorithms have been used to solve the system of non-linear equations for better image quality and reconstruction speed in CS. In the recent past, iterative soft thresholding algorithm (ISTA) has been introduced in CS-MRI. This algorithm directly cancels the incoherent artifacts produced because of the undersampling in k -space. This paper introduces an improved iterative algorithm based on p -thresholding technique for CS-MRI image reconstruction. The use of p -thresholding function promotes sparsity in the image which is a key factor for CS based image reconstruction. The p -thresholding based iterative algorithm is a modification of ISTA, and minimizes non-convex functions. It has been shown that the proposed p -thresholding iterative algorithm can be used effectively to recover fully sampled image from the under-sampled data in MRI. The performance of the proposed method is verified using simulated and actual MRI data taken at St. Mary's Hospital, London. The quality of the reconstructed images is measured in terms of peak signal-to-noise ratio (PSNR), artifact power (AP), and structural similarity index measure (SSIM). The proposed approach shows improved performance when compared to other iterative algorithms based on log thresholding, soft thresholding and hard thresholding techniques at different reduction factors.

Segmentation of remotely sensed data using parallel region growing

NASA Technical Reports Server (NTRS)

Tilton, J. C.; Cox, S. C.

1983-01-01

The improved spatial resolution of the new earth resources satellites will increase the need for effective utilization of spatial information in machine processing of remotely sensed data. One promising technique is scene segmentation by region growing. Region growing can use spatial information in two ways: only spatially adjacent regions merge together, and merging criteria can be based on region-wide spatial features. A simple region growing approach is described in which the similarity criterion is based on region mean and variance (a simple spatial feature). An effective way to implement region growing for remote sensing is as an iterative parallel process on a large parallel processor. A straightforward parallel pixel-based implementation of the algorithm is explored and its efficiency is compared with sequential pixel-based, sequential region-based, and parallel region-based implementations. Experimental results from on aircraft scanner data set are presented, as is a discussioon of proposed improvements to the segmentation algorithm.

Defining competency-based evaluation objectives in family medicine

PubMed Central

Lawrence, Kathrine; Allen, Tim; Brailovsky, Carlos; Crichton, Tom; Bethune, Cheri; Donoff, Michel; Laughlin, Tom; Wetmore, Stephen; Carpentier, Marie-Pierre; Visser, Shaun

2011-01-01

Abstract Objective To develop key features for priority topics previously identified by the College of Family Physicians of Canada that, together with skill dimensions and phases of the clinical encounter, broadly describe competence in family medicine. Design Modified nominal group methodology, which was used to develop key features for each priority topic through an iterative process. Setting The College of Family Physicians of Canada. Participants An expert group of 7 family physicians and 1 educational consultant, all of whom had experience in assessing competence in family medicine. Group members represented the Canadian family medicine context with respect to region, sex, language, community type, and experience. Methods The group used a modified Delphi process to derive a detailed operational definition of competence, using multiple iterations until consensus was achieved for the items under discussion. The group met 3 to 4 times a year from 2000 to 2007. Main findings The group analyzed 99 topics and generated 773 key features. There were 2 to 20 (average 7.8) key features per topic; 63% of the key features focused on the diagnostic phase of the clinical encounter. Conclusion This project expands previous descriptions of the process of generating key features for assessment, and removes this process from the context of written examinations. A key-features analysis of topics focuses on higher-order cognitive processes of clinical competence. The project did not define all the skill dimensions of competence to the same degree, but it clearly identified those requiring further definition. This work generates part of a discipline-specific, competency-based definition of family medicine for assessment purposes. It limits the domain for assessment purposes, which is an advantage for the teaching and assessment of learners. A validation study on the content of this work would ensure that it truly reflects competence in family medicine. PMID:21998245

Adaptive environmental management of tourism in the Province of Siena, Italy using the ecological footprint.

PubMed

Patterson, Trista M; Niccolucci, Valentina; Marchettini, Nadia

2008-01-01

Adaptive management as applied to tourism policy treats management policies as experiments that probe the responses of the system as human behavior changes. We present a conceptual systems model that incorporates the gap between observed and desired levels of the ecological footprint with respect to biocapacity. Addressing this gap (or 'overshoot') can inform strategies to increase or decrease visitation or its associated consumption in the coming years. The feedback mechanism in this conceptual model incorporates a gap between observed and desired ecological footprint levels of tourists and residents. The work is based on longer-term and ongoing study of tourism impacts and ecological footprint assessments from the SPIN-Eco Project. We present historical tourism and environmental data from the province of Siena, Italy and discuss the use of discrete, static environmental indicators as part of an iterative feedback process to manage tourism within biophysical limits. We discuss a necessary shift of emphasis from certain and static numbers to a process-based management model that can reflect slow changes to biophysical resources. As underscored by ecological footprint analysis, the energy and material use associated with tourism and local activity can erode natural capital foundations if that use exceeds the area's biological capacity to support it. The dynamic, and iterative process of using such indicators as management feedback allows us to view sustainability more accurately as a transition and journey, rather than a static destination to which management must arrive.

Strain-Annealing Based Grain Boundary Engineering to Evaluate its Sole Implication on Intergranular Corrosion in Extra-Low Carbon Type 304L Austenitic Stainless Steel

NASA Astrophysics Data System (ADS)

Pradhan, S. K.; Bhuyan, P.; Kaithwas, C.; Mandal, Sumantra

2018-05-01

Strain-annealing based thermo-mechanical processing has been performed to promote grain boundary engineering (GBE) in an extra-low carbon type austenitic stainless steel without altering the grain size and residual strain to evaluate its sole influence on intergranular corrosion. Single-step processing comprising low pre-strain ( 5 and 10 pct) followed by annealing at 1273 K for 1 hour have resulted in a large fraction of Σ3 n boundaries and significant disruption in random high-angle grain boundaries (RHAGBs) connectivity. This is due to the occurrence of prolific multiple twinning in these specimens as confirmed by their large twin-related domain and twin-related grain size ratio. Among the iterative processing, the schedule comprising two cycles of 10 and 5 pct deformation followed by annealing at 1173 K for 1 hour has yielded the optimum GBE microstructure with the grain size and residual strain akin to the as-received condition. The specimens subjected to the higher number of iterations failed to realize GBE microstructures due to the occurrence of partial recrystallization. Owing to the optimum grain boundary character distribution, the GBE specimen has exhibited remarkable resistance against sensitization and intergranular corrosion as compared to the as-received condition. Furthermore, the lower depth of percolation in the GBE specimen is due to the significant disruption of RHAGBs connectivity as confirmed from its large twin-related domain and lower fractal dimension.

Strain-Annealing Based Grain Boundary Engineering to Evaluate its Sole Implication on Intergranular Corrosion in Extra-Low Carbon Type 304L Austenitic Stainless Steel

NASA Astrophysics Data System (ADS)

Pradhan, S. K.; Bhuyan, P.; Kaithwas, C.; Mandal, Sumantra

2018-07-01

Strain-annealing based thermo-mechanical processing has been performed to promote grain boundary engineering (GBE) in an extra-low carbon type austenitic stainless steel without altering the grain size and residual strain to evaluate its sole influence on intergranular corrosion. Single-step processing comprising low pre-strain ( 5 and 10 pct) followed by annealing at 1273 K for 1 hour have resulted in a large fraction of Σ3 n boundaries and significant disruption in random high-angle grain boundaries (RHAGBs) connectivity. This is due to the occurrence of prolific multiple twinning in these specimens as confirmed by their large twin-related domain and twin-related grain size ratio. Among the iterative processing, the schedule comprising two cycles of 10 and 5 pct deformation followed by annealing at 1173 K for 1 hour has yielded the optimum GBE microstructure with the grain size and residual strain akin to the as-received condition. The specimens subjected to the higher number of iterations failed to realize GBE microstructures due to the occurrence of partial recrystallization. Owing to the optimum grain boundary character distribution, the GBE specimen has exhibited remarkable resistance against sensitization and intergranular corrosion as compared to the as-received condition. Furthermore, the lower depth of percolation in the GBE specimen is due to the significant disruption of RHAGBs connectivity as confirmed from its large twin-related domain and lower fractal dimension.

Adaptive dynamic programming for discrete-time linear quadratic regulation based on multirate generalised policy iteration

NASA Astrophysics Data System (ADS)

Chun, Tae Yoon; Lee, Jae Young; Park, Jin Bae; Choi, Yoon Ho

2018-06-01

In this paper, we propose two multirate generalised policy iteration (GPI) algorithms applied to discrete-time linear quadratic regulation problems. The proposed algorithms are extensions of the existing GPI algorithm that consists of the approximate policy evaluation and policy improvement steps. The two proposed schemes, named heuristic dynamic programming (HDP) and dual HDP (DHP), based on multirate GPI, use multi-step estimation (M-step Bellman equation) at the approximate policy evaluation step for estimating the value function and its gradient called costate, respectively. Then, we show that these two methods with the same update horizon can be considered equivalent in the iteration domain. Furthermore, monotonically increasing and decreasing convergences, so called value iteration (VI)-mode and policy iteration (PI)-mode convergences, are proved to hold for the proposed multirate GPIs. Further, general convergence properties in terms of eigenvalues are also studied. The data-driven online implementation methods for the proposed HDP and DHP are demonstrated and finally, we present the results of numerical simulations performed to verify the effectiveness of the proposed methods.

Arc detection for the ICRF system on ITER

NASA Astrophysics Data System (ADS)

D'Inca, R.

2011-12-01

The ICRF system for ITER is designed to respect the high voltage breakdown limits. However arcs can still statistically happen and must be quickly detected and suppressed by shutting the RF power down. For the conception of a reliable and efficient detector, the analysis of the mechanism of arcs is necessary to find their unique signature. Numerous systems have been conceived to address the issues of arc detection. VSWR-based detectors, RF noise detectors, sound detectors, optical detectors, S-matrix based detectors. Until now, none of them has succeeded in demonstrating the fulfillment of all requirements and the studies for ITER now follow three directions: improvement of the existing concepts to fix their flaws, development of new theoretically fully compliant detectors (like the GUIDAR) and combination of several detectors to benefit from the advantages of each of them. Together with the physical and engineering challenges, the development of an arc detection system for ITER raises methodological concerns to extrapolate the results from basic experiments and present machines to the ITER scale ICRF system and to conduct a relevant risk analysis.

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)…

On the Development of a Computing Infrastructure that Facilitates IPPD from a Decision-Based Design Perspective

NASA Technical Reports Server (NTRS)

Hale, Mark A.; Craig, James I.; Mistree, Farrokh; Schrage, Daniel P.

1995-01-01

Integrated Product and Process Development (IPPD) embodies the simultaneous application of both system and quality engineering methods throughout an iterative design process. The use of IPPD results in the time-conscious, cost-saving development of engineering systems. Georgia Tech has proposed the development of an Integrated Design Engineering Simulator that will merge Integrated Product and Process Development with interdisciplinary analysis techniques and state-of-the-art computational technologies. To implement IPPD, a Decision-Based Design perspective is encapsulated in an approach that focuses on the role of the human designer in product development. The approach has two parts and is outlined in this paper. First, an architecture, called DREAMS, is being developed that facilitates design from a decision-based perspective. Second, a supporting computing infrastructure, called IMAGE, is being designed. The current status of development is given and future directions are outlined.

Real-time stereo matching using orthogonal reliability-based dynamic programming.

PubMed

Gong, Minglun; Yang, Yee-Hong

2007-03-01

A novel algorithm is presented in this paper for estimating reliable stereo matches in real time. Based on the dynamic programming-based technique we previously proposed, the new algorithm can generate semi-dense disparity maps using as few as two dynamic programming passes. The iterative best path tracing process used in traditional dynamic programming is replaced by a local minimum searching process, making the algorithm suitable for parallel execution. Most computations are implemented on programmable graphics hardware, which improves the processing speed and makes real-time estimation possible. The experiments on the four new Middlebury stereo datasets show that, on an ATI Radeon X800 card, the presented algorithm can produce reliable matches for 60% approximately 80% of pixels at the rate of 10 approximately 20 frames per second. If needed, the algorithm can be configured for generating full density disparity maps.

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

Robust design of feedback feed-forward iterative learning control based on 2D system theory for linear uncertain systems

NASA Astrophysics Data System (ADS)

Li, Zhifu; Hu, Yueming; Li, Di

2016-08-01

For a class of linear discrete-time uncertain systems, a feedback feed-forward iterative learning control (ILC) scheme is proposed, which is comprised of an iterative learning controller and two current iteration feedback controllers. The iterative learning controller is used to improve the performance along the iteration direction and the feedback controllers are used to improve the performance along the time direction. First of all, the uncertain feedback feed-forward ILC system is presented by an uncertain two-dimensional Roesser model system. Then, two robust control schemes are proposed. One can ensure that the feedback feed-forward ILC system is bounded-input bounded-output stable along time direction, and the other can ensure that the feedback feed-forward ILC system is asymptotically stable along time direction. Both schemes can guarantee the system is robust monotonically convergent along the iteration direction. Third, the robust convergent sufficient conditions are given, which contains a linear matrix inequality (LMI). Moreover, the LMI can be used to determine the gain matrix of the feedback feed-forward iterative learning controller. Finally, the simulation results are presented to demonstrate the effectiveness of the proposed schemes.

Changing the Way We Build Games: A Design-Based Research Study Examining the Implementation of Homemade PowerPoint Games in the Classroom

ERIC Educational Resources Information Center

Siko, Jason Paul

2012-01-01

This design-based research study examined the effects of a game design project on student test performance, with refinements made to the implementation after each of the three iterations of the study. The changes to the implementation over the three iterations were based on the literature for the three justifications for the use of homemade…

Development of an Online Smartphone-Based eLearning Nutrition Education Program for Low-Income Individuals.

PubMed

Stotz, Sarah; Lee, Jung Sun

2018-01-01

The objective of this report was to describe the development process of an innovative smartphone-based electronic learning (eLearning) nutrition education program targeted to Supplemental Nutrition Assistance Program-Education-eligible individuals, entitled Food eTalk. Lessons learned from the Food eTalk development process suggest that it is critical to include all key team members from the program's inception using effective inter-team communication systems, understand the unique resources needed, budget ample time for development, and employ an iterative development and evaluation model. These lessons have implications for researchers and funding agencies in developing an innovative evidence-based eLearning nutrition education program to an increasingly technology-savvy, low-income audience. Copyright © 2016 Society for Nutrition Education and Behavior. Published by Elsevier Inc. All rights reserved.

Culturally Based Intervention Development: The Case of Latino Families Dealing With Schizophrenia

PubMed Central

Barrio, Concepción; Yamada, Ann-Marie

2011-01-01

Objectives This article describes the process of developing a culturally based family intervention for Spanish-speaking Latino families with a relative diagnosed with schizophrenia. Method Our iterative intervention development process was guided by a cultural exchange framework and based on findings from an ethnographic study. We piloted this multifamily group 16-session intervention with 59 Latino families in a randomized control trial. Data were collected on family- and client-level outcomes, and poststudy focus groups were conducted with intervention participants. Results Preliminary evidence indicates that the intervention is effective by increasing illness knowledge and reducing family burden. Conclusions This work can provide a model for how to integrate cultural factors into psychosocial services and enhance interventions in real-world settings for culturally diverse populations. PMID:22121328

Optical asymmetric cryptography based on amplitude reconstruction of elliptically polarized light

NASA Astrophysics Data System (ADS)

Cai, Jianjun; Shen, Xueju; Lei, Ming

2017-11-01

We propose a novel optical asymmetric image encryption method based on amplitude reconstruction of elliptically polarized light, which is free from silhouette problem. The original image is analytically separated into two phase-only masks firstly, and then the two masks are encoded into amplitudes of the orthogonal polarization components of an elliptically polarized light. Finally, the elliptically polarized light propagates through a linear polarizer, and the output intensity distribution is recorded by a CCD camera to obtain the ciphertext. The whole encryption procedure could be implemented by using commonly used optical elements, and it combines diffusion process and confusion process. As a result, the proposed method achieves high robustness against iterative-algorithm-based attacks. Simulation results are presented to prove the validity of the proposed cryptography.

Design and Testing of Novel Lethal Ovitrap to Reduce Populations of Aedes Mosquitoes: Community-Based Participatory Research between Industry, Academia and Communities in Peru and Thailand.

PubMed

Paz-Soldan, Valerie A; Yukich, Josh; Soonthorndhada, Amara; Giron, Maziel; Apperson, Charles S; Ponnusamy, Loganathan; Schal, Coby; Morrison, Amy C; Keating, Joseph; Wesson, Dawn M

2016-01-01

Dengue virus (and Chikungunya and Zika viruses) is transmitted by Aedes aegypti and Aedes albopictus mosquitoes and causes considerable human morbidity and mortality. As there is currently no vaccine or chemoprophylaxis to protect people from dengue virus infection, vector control is the only viable option for disease prevention. The purpose of this paper is to illustrate the design and placement process for an attractive lethal ovitrap to reduce vector populations and to describe lessons learned in the development of the trap. This study was conducted in 2010 in Iquitos, Peru and Lopburi Province, Thailand and used an iterative community-based participatory approach to adjust design specifications of the trap, based on community members' perceptions and feedback, entomological findings in the lab, and design and research team observations. Multiple focus group discussions (FGD) were held over a 6 month period, stratified by age, sex and motherhood status, to inform the design process. Trap testing transitioned from the lab to within households. Through an iterative process of working with specifications from the research team, findings from the laboratory testing, and feedback from FGD, the design team narrowed trap design options from 22 to 6. Comments from the FGD centered on safety for children and pets interacting with traps, durability, maintenance issues, and aesthetics. Testing in the laboratory involved releasing groups of 50 gravid Ae. aegypti in walk-in rooms and assessing what percentage were caught in traps of different colors, with different trap cover sizes, and placed under lighter or darker locations. Two final trap models were mocked up and tested in homes for a week; one model was the top choice in both Iquitos and Lopburi. The community-based participatory process was essential for the development of novel traps that provided effective vector control, but also met the needs and concerns of community members.

Design and Testing of Novel Lethal Ovitrap to Reduce Populations of Aedes Mosquitoes: Community-Based Participatory Research between Industry, Academia and Communities in Peru and Thailand

PubMed Central

Yukich, Josh; Soonthorndhada, Amara; Giron, Maziel; Apperson, Charles S.; Ponnusamy, Loganathan; Schal, Coby; Morrison, Amy C.; Keating, Joseph; Wesson, Dawn M.

2016-01-01

Background Dengue virus (and Chikungunya and Zika viruses) is transmitted by Aedes aegypti and Aedes albopictus mosquitoes and causes considerable human morbidity and mortality. As there is currently no vaccine or chemoprophylaxis to protect people from dengue virus infection, vector control is the only viable option for disease prevention. The purpose of this paper is to illustrate the design and placement process for an attractive lethal ovitrap to reduce vector populations and to describe lessons learned in the development of the trap. Methods This study was conducted in 2010 in Iquitos, Peru and Lopburi Province, Thailand and used an iterative community-based participatory approach to adjust design specifications of the trap, based on community members’ perceptions and feedback, entomological findings in the lab, and design and research team observations. Multiple focus group discussions (FGD) were held over a 6 month period, stratified by age, sex and motherhood status, to inform the design process. Trap testing transitioned from the lab to within households. Results Through an iterative process of working with specifications from the research team, findings from the laboratory testing, and feedback from FGD, the design team narrowed trap design options from 22 to 6. Comments from the FGD centered on safety for children and pets interacting with traps, durability, maintenance issues, and aesthetics. Testing in the laboratory involved releasing groups of 50 gravid Ae. aegypti in walk-in rooms and assessing what percentage were caught in traps of different colors, with different trap cover sizes, and placed under lighter or darker locations. Two final trap models were mocked up and tested in homes for a week; one model was the top choice in both Iquitos and Lopburi. Discussion The community-based participatory process was essential for the development of novel traps that provided effective vector control, but also met the needs and concerns of community members. PMID:27532497

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.

ADART: an adaptive algebraic reconstruction algorithm for discrete tomography.

PubMed

Maestre-Deusto, F Javier; Scavello, Giovanni; Pizarro, Joaquín; Galindo, Pedro L

2011-08-01

In this paper we suggest an algorithm based on the Discrete Algebraic Reconstruction Technique (DART) which is capable of computing high quality reconstructions from substantially fewer projections than required for conventional continuous tomography. Adaptive DART (ADART) goes a step further than DART on the reduction of the number of unknowns of the associated linear system achieving a significant reduction in the pixel error rate of reconstructed objects. The proposed methodology automatically adapts the border definition criterion at each iteration, resulting in a reduction of the number of pixels belonging to the border, and consequently of the number of unknowns in the general algebraic reconstruction linear system to be solved, being this reduction specially important at the final stage of the iterative process. Experimental results show that reconstruction errors are considerably reduced using ADART when compared to original DART, both in clean and noisy environments.

FPGA-based multi-channel fluorescence lifetime analysis of Fourier multiplexed frequency-sweeping lifetime imaging

PubMed Central

Zhao, Ming; Li, Yu; Peng, Leilei

2014-01-01

We report a fast non-iterative lifetime data analysis method for the Fourier multiplexed frequency-sweeping confocal FLIM (Fm-FLIM) system [ Opt. Express22, 10221 ( 2014)24921725]. The new method, named R-method, allows fast multi-channel lifetime image analysis in the system’s FPGA data processing board. Experimental tests proved that the performance of the R-method is equivalent to that of single-exponential iterative fitting, and its sensitivity is well suited for time-lapse FLIM-FRET imaging of live cells, for example cyclic adenosine monophosphate (cAMP) level imaging with GFP-Epac-mCherry sensors. With the R-method and its FPGA implementation, multi-channel lifetime images can now be generated in real time on the multi-channel frequency-sweeping FLIM system, and live readout of FRET sensors can be performed during time-lapse imaging. PMID:25321778

An assessment of coupling algorithms for nuclear reactor core physics simulations

DOE PAGES

Hamilton, Steven; Berrill, Mark; Clarno, Kevin; ...

2016-04-01

This paper evaluates the performance of multiphysics coupling algorithms applied to a light water nuclear reactor core simulation. The simulation couples the k-eigenvalue form of the neutron transport equation with heat conduction and subchannel flow equations. We compare Picard iteration (block Gauss–Seidel) to Anderson acceleration and multiple variants of preconditioned Jacobian-free Newton–Krylov (JFNK). The performance of the methods are evaluated over a range of energy group structures and core power levels. A novel physics-based approximation to a Jacobian-vector product has been developed to mitigate the impact of expensive on-line cross section processing steps. Furthermore, numerical simulations demonstrating the efficiency ofmore » JFNK and Anderson acceleration relative to standard Picard iteration are performed on a 3D model of a nuclear fuel assembly. Both criticality (k-eigenvalue) and critical boron search problems are considered.« less

An assessment of coupling algorithms for nuclear reactor core physics simulations

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

Hamilton, Steven; Berrill, Mark; Clarno, Kevin

This paper evaluates the performance of multiphysics coupling algorithms applied to a light water nuclear reactor core simulation. The simulation couples the k-eigenvalue form of the neutron transport equation with heat conduction and subchannel flow equations. We compare Picard iteration (block Gauss–Seidel) to Anderson acceleration and multiple variants of preconditioned Jacobian-free Newton–Krylov (JFNK). The performance of the methods are evaluated over a range of energy group structures and core power levels. A novel physics-based approximation to a Jacobian-vector product has been developed to mitigate the impact of expensive on-line cross section processing steps. Furthermore, numerical simulations demonstrating the efficiency ofmore » JFNK and Anderson acceleration relative to standard Picard iteration are performed on a 3D model of a nuclear fuel assembly. Both criticality (k-eigenvalue) and critical boron search problems are considered.« less

An assessment of coupling algorithms for nuclear reactor core physics simulations

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

Hamilton, Steven, E-mail: hamiltonsp@ornl.gov; Berrill, Mark, E-mail: berrillma@ornl.gov; Clarno, Kevin, E-mail: clarnokt@ornl.gov

This paper evaluates the performance of multiphysics coupling algorithms applied to a light water nuclear reactor core simulation. The simulation couples the k-eigenvalue form of the neutron transport equation with heat conduction and subchannel flow equations. We compare Picard iteration (block Gauss–Seidel) to Anderson acceleration and multiple variants of preconditioned Jacobian-free Newton–Krylov (JFNK). The performance of the methods are evaluated over a range of energy group structures and core power levels. A novel physics-based approximation to a Jacobian-vector product has been developed to mitigate the impact of expensive on-line cross section processing steps. Numerical simulations demonstrating the efficiency of JFNKmore » and Anderson acceleration relative to standard Picard iteration are performed on a 3D model of a nuclear fuel assembly. Both criticality (k-eigenvalue) and critical boron search problems are considered.« less

High density operation for reactor-relevant power exhaust

NASA Astrophysics Data System (ADS)

Wischmeier, M.; ASDEX Upgrade Team; Jet Efda Contributors

2015-08-01

With increasing size of a tokamak device and associated fusion power gain an increasing power flux density towards the divertor needs to be handled. A solution for handling this power flux is crucial for a safe and economic operation. Using purely geometric arguments in an ITER-like divertor this power flux can be reduced by approximately a factor 100. Based on a conservative extrapolation of current technology for an integrated engineering approach to remove power deposited on plasma facing components a further reduction of the power flux density via volumetric processes in the plasma by up to a factor of 50 is required. Our current ability to interpret existing power exhaust scenarios using numerical transport codes is analyzed and an operational scenario as a potential solution for ITER like divertors under high density and highly radiating reactor-relevant conditions is presented. Alternative concepts for risk mitigation as well as strategies for moving forward are outlined.

Efficient computation paths for the systematic analysis of sensitivities

NASA Astrophysics Data System (ADS)

Greppi, Paolo; Arato, Elisabetta

2013-01-01

A systematic sensitivity analysis requires computing the model on all points of a multi-dimensional grid covering the domain of interest, defined by the ranges of variability of the inputs. The issues to efficiently perform such analyses on algebraic models are handling solution failures within and close to the feasible region and minimizing the total iteration count. Scanning the domain in the obvious order is sub-optimal in terms of total iterations and is likely to cause many solution failures. The problem of choosing a better order can be translated geometrically into finding Hamiltonian paths on certain grid graphs. This work proposes two paths, one based on a mixed-radix Gray code and the other, a quasi-spiral path, produced by a novel heuristic algorithm. Some simple, easy-to-visualize examples are presented, followed by performance results for the quasi-spiral algorithm and the practical application of the different paths in a process simulation tool.

Teachers Supporting Teachers in Urban Schools: What Iterative Research Designs Can Teach Us.

PubMed

Shernoff, Elisa S; Maríñez-Lora, Ane M; Frazier, Stacy L; Jakobsons, Lara J; Atkins, Marc S; Bonner, Deborah

2011-12-01

Despite alarming rates and negative consequences associated with urban teacher attrition, mentoring programs often fail to target the strongest predictors of attrition: effectiveness around classroom management and engaging learners; and connectedness to colleagues. Using a mixed-method iterative development framework, we highlight the process of developing and evaluating the feasibility of a multi-component professional development model for urban early career teachers. The model includes linking novices with peer-nominated key opinion leader teachers and an external coach who work together to (1) provide intensive support in evidence-based practices for classroom management and engaging learners, and (2) connect new teachers with their larger network of colleagues. Fidelity measures and focus group data illustrated varying attendance rates throughout the school year and that although seminars and professional learning communities were delivered as intended, adaptations to enhance the relevance, authenticity, level, and type of instrumental support were needed. Implications for science and practice are discussed.

Machine learning in motion control

NASA Technical Reports Server (NTRS)

Su, Renjeng; Kermiche, Noureddine

1989-01-01

The existing methodologies for robot programming originate primarily from robotic applications to manufacturing, where uncertainties of the robots and their task environment may be minimized by repeated off-line modeling and identification. In space application of robots, however, a higher degree of automation is required for robot programming because of the desire of minimizing the human intervention. We discuss a new paradigm of robotic programming which is based on the concept of machine learning. The goal is to let robots practice tasks by themselves and the operational data are used to automatically improve their motion performance. The underlying mathematical problem is to solve the problem of dynamical inverse by iterative methods. One of the key questions is how to ensure the convergence of the iterative process. There have been a few small steps taken into this important approach to robot programming. We give a representative result on the convergence problem.

Iterative Frequency Domain Decision Feedback Equalization and Decoding for Underwater Acoustic Communications

NASA Astrophysics Data System (ADS)

Zhao, Liang; Ge, Jian-Hua

2012-12-01

Single-carrier (SC) transmission with frequency-domain equalization (FDE) is today recognized as an attractive alternative to orthogonal frequency-division multiplexing (OFDM) for communication application with the inter-symbol interference (ISI) caused by multi-path propagation, especially in shallow water channel. In this paper, we investigate an iterative receiver based on minimum mean square error (MMSE) decision feedback equalizer (DFE) with symbol rate and fractional rate samplings in the frequency domain (FD) and serially concatenated trellis coded modulation (SCTCM) decoder. Based on sound speed profiles (SSP) measured in the lake and finite-element ray tracking (Bellhop) method, the shallow water channel is constructed to evaluate the performance of the proposed iterative receiver. Performance results show that the proposed iterative receiver can significantly improve the performance and obtain better data transmission than FD linear and adaptive decision feedback equalizers, especially in adopting fractional rate sampling.

Aerodynamic optimization by simultaneously updating flow variables and design parameters

NASA Technical Reports Server (NTRS)

Rizk, M. H.

1990-01-01

The application of conventional optimization schemes to aerodynamic design problems leads to inner-outer iterative procedures that are very costly. An alternative approach is presented based on the idea of updating the flow variable iterative solutions and the design parameter iterative solutions simultaneously. Two schemes based on this idea are applied to problems of correcting wind tunnel wall interference and optimizing advanced propeller designs. The first of these schemes is applicable to a limited class of two-design-parameter problems with an equality constraint. It requires the computation of a single flow solution. The second scheme is suitable for application to general aerodynamic problems. It requires the computation of several flow solutions in parallel. In both schemes, the design parameters are updated as the iterative flow solutions evolve. Computations are performed to test the schemes' efficiency, accuracy, and sensitivity to variations in the computational parameters.

Uniform convergence of multigrid V-cycle iterations for indefinite and nonsymmetric problems

NASA Technical Reports Server (NTRS)

Bramble, James H.; Kwak, Do Y.; Pasciak, Joseph E.

1993-01-01

In this paper, we present an analysis of a multigrid method for nonsymmetric and/or indefinite elliptic problems. In this multigrid method various types of smoothers may be used. One type of smoother which we consider is defined in terms of an associated symmetric problem and includes point and line, Jacobi, and Gauss-Seidel iterations. We also study smoothers based entirely on the original operator. One is based on the normal form, that is, the product of the operator and its transpose. Other smoothers studied include point and line, Jacobi, and Gauss-Seidel. We show that the uniform estimates for symmetric positive definite problems carry over to these algorithms. More precisely, the multigrid iteration for the nonsymmetric and/or indefinite problem is shown to converge at a uniform rate provided that the coarsest grid in the multilevel iteration is sufficiently fine (but not depending on the number of multigrid levels).

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.

Cloning strategy for producing brush-forming protein-based polymers.

PubMed

Henderson, Douglas B; Davis, Richey M; Ducker, William A; Van Cott, Kevin E

2005-01-01

Brush-forming polymers are being used in a variety of applications, and by using recombinant DNA technology, there exists the potential to produce protein-based polymers that incorporate unique structures and functions in these brush layers. Despite this potential, production of protein-based brush-forming polymers is not routinely performed. For the design and production of new protein-based polymers with optimal brush-forming properties, it would be desirable to have a cloning strategy that allows an iterative approach wherein the protein based-polymer product can be produced and evaluated, and then if necessary, it can be sequentially modified in a controlled manner to obtain optimal surface density and brush extension. In this work, we report on the development of a cloning strategy intended for the production of protein-based brush-forming polymers. This strategy is based on the assembly of modules of DNA that encode for blocks of protein-based polymers into a commercially available expression vector; there is no need for custom-modified vectors and no need for intermediate cloning vectors. Additionally, because the design of new protein-based biopolymers can be an iterative process, our method enables sequential modification of a protein-based polymer product. With at least 21 bacterial expression vectors and 11 yeast expression vectors compatible with this strategy, there are a number of options available for production of protein-based polymers. It is our intent that this strategy will aid in advancing the production of protein-based brush-forming polymers.

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

Dealing with gene expression missing data.

PubMed

Brás, L P; Menezes, J C

2006-05-01

Compared evaluation of different methods is presented for estimating missing values in microarray data: weighted K-nearest neighbours imputation (KNNimpute), regression-based methods such as local least squares imputation (LLSimpute) and partial least squares imputation (PLSimpute) and Bayesian principal component analysis (BPCA). The influence in prediction accuracy of some factors, such as methods' parameters, type of data relationships used in the estimation process (i.e. row-wise, column-wise or both), missing rate and pattern and type of experiment [time series (TS), non-time series (NTS) or mixed (MIX) experiments] is elucidated. Improvements based on the iterative use of data (iterative LLS and PLS imputation--ILLSimpute and IPLSimpute), the need to perform initial imputations (modified PLS and Helland PLS imputation--MPLSimpute and HPLSimpute) and the type of relationships employed (KNNarray, LLSarray, HPLSarray and alternating PLS--APLSimpute) are proposed. Overall, it is shown that data set properties (type of experiment, missing rate and pattern) affect the data similarity structure, therefore influencing the methods' performance. LLSimpute and ILLSimpute are preferable in the presence of data with a stronger similarity structure (TS and MIX experiments), whereas PLS-based methods (MPLSimpute, IPLSimpute and APLSimpute) are preferable when estimating NTS missing data.

Secret shared multiple-image encryption based on row scanning compressive ghost imaging and phase retrieval in the Fresnel domain

NASA Astrophysics Data System (ADS)

Li, Xianye; Meng, Xiangfeng; Wang, Yurong; Yang, Xiulun; Yin, Yongkai; Peng, Xiang; He, Wenqi; Dong, Guoyan; Chen, Hongyi

2017-09-01

A multiple-image encryption method is proposed that is based on row scanning compressive ghost imaging, (t, n) threshold secret sharing, and phase retrieval in the Fresnel domain. In the encryption process, after wavelet transform and Arnold transform of the target image, the ciphertext matrix can be first detected using a bucket detector. Based on a (t, n) threshold secret sharing algorithm, the measurement key used in the row scanning compressive ghost imaging can be decomposed and shared into two pairs of sub-keys, which are then reconstructed using two phase-only mask (POM) keys with fixed pixel values, placed in the input plane and transform plane 2 of the phase retrieval scheme, respectively; and the other POM key in the transform plane 1 can be generated and updated by the iterative encoding of each plaintext image. In each iteration, the target image acts as the input amplitude constraint in the input plane. During decryption, each plaintext image possessing all the correct keys can be successfully decrypted by measurement key regeneration, compression algorithm reconstruction, inverse wavelet transformation, and Fresnel transformation. Theoretical analysis and numerical simulations both verify the feasibility of the proposed method.

LDPC decoder with a limited-precision FPGA-based floating-point multiplication coprocessor

NASA Astrophysics Data System (ADS)

Moberly, Raymond; O'Sullivan, Michael; Waheed, Khurram

2007-09-01

Implementing the sum-product algorithm, in an FPGA with an embedded processor, invites us to consider a tradeoff between computational precision and computational speed. The algorithm, known outside of the signal processing community as Pearl's belief propagation, is used for iterative soft-decision decoding of LDPC codes. We determined the feasibility of a coprocessor that will perform product computations. Our FPGA-based coprocessor (design) performs computer algebra with significantly less precision than the standard (e.g. integer, floating-point) operations of general purpose processors. Using synthesis, targeting a 3,168 LUT Xilinx FPGA, we show that key components of a decoder are feasible and that the full single-precision decoder could be constructed using a larger part. Soft-decision decoding by the iterative belief propagation algorithm is impacted both positively and negatively by a reduction in the precision of the computation. Reducing precision reduces the coding gain, but the limited-precision computation can operate faster. A proposed solution offers custom logic to perform computations with less precision, yet uses the floating-point format to interface with the software. Simulation results show the achievable coding gain. Synthesis results help theorize the the full capacity and performance of an FPGA-based coprocessor.

Incorporation of star measurements for the determination of orbit and attitude parameters of a geosynchronous satellite: An iterative application of linear regression

NASA Astrophysics Data System (ADS)

Phillips, D.

1980-10-01

Currently on NOAA/NESS's VIRGS system at the World Weather Building star images are being ingested on a daily basis. The image coordinates of the star locations are measured and stored. Subsequently, the information is used to determine the attitude, the misalignment angles between the spin axis and the principal axis of the satellite, and the precession rate and direction. This is done for both the 'East' and 'West' operational geosynchronous satellites. This orientation information is then combined with image measurements of earth based landmarks to determine the orbit of each satellite. The method for determining the orbit is simple. For each landmark measurement one determines a nominal position vector for the satellite by extending a ray from the landmark's position towards the satellite and intersecting the ray with a sphere with center coinciding with the Earth's center and with radius equal to the nominal height for a geosynchronous satellite. The apparent motion of the satellite around the Earth's center is then approximated with a Keplerian model. In turn the variations of the satellite's height, as a function of time found by using this model, are used to redetermine the successive satellite positions by again using the Earth based landmark measurements and intersecting rays from these landmarks with the newly determined spheres. This process is performed iteratively until convergence is achieved. Only three iterations are required.

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.

Hydrologic Process Parameterization of Electrical Resistivity Imaging of Solute Plumes Using POD McMC

NASA Astrophysics Data System (ADS)

Awatey, M. T.; Irving, J.; Oware, E. K.

2016-12-01

Markov chain Monte Carlo (McMC) inversion frameworks are becoming increasingly popular in geophysics due to their ability to recover multiple equally plausible geologic features that honor the limited noisy measurements. Standard McMC methods, however, become computationally intractable with increasing dimensionality of the problem, for example, when working with spatially distributed geophysical parameter fields. We present a McMC approach based on a sparse proper orthogonal decomposition (POD) model parameterization that implicitly incorporates the physics of the underlying process. First, we generate training images (TIs) via Monte Carlo simulations of the target process constrained to a conceptual model. We then apply POD to construct basis vectors from the TIs. A small number of basis vectors can represent most of the variability in the TIs, leading to dimensionality reduction. A projection of the starting model into the reduced basis space generates the starting POD coefficients. At each iteration, only coefficients within a specified sampling window are resimulated assuming a Gaussian prior. The sampling window grows at a specified rate as the number of iteration progresses starting from the coefficients corresponding to the highest ranked basis to those of the least informative basis. We found this gradual increment in the sampling window to be more stable compared to resampling all the coefficients right from the first iteration. We demonstrate the performance of the algorithm with both synthetic and lab-scale electrical resistivity imaging of saline tracer experiments, employing the same set of basis vectors for all inversions. We consider two scenarios of unimodal and bimodal plumes. The unimodal plume is consistent with the hypothesis underlying the generation of the TIs whereas bimodality in plume morphology was not theorized. We show that uncertainty quantification using McMC can proceed in the reduced dimensionality space while accounting for the physics of the underlying process.

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

Automatic treatment plan re-optimization for adaptive radiotherapy guided with the initial plan DVHs.

PubMed

Li, Nan; Zarepisheh, Masoud; Uribe-Sanchez, Andres; Moore, Kevin; Tian, Zhen; Zhen, Xin; Graves, Yan Jiang; Gautier, Quentin; Mell, Loren; Zhou, Linghong; Jia, Xun; Jiang, Steve

2013-12-21

Adaptive radiation therapy (ART) can reduce normal tissue toxicity and/or improve tumor control through treatment adaptations based on the current patient anatomy. Developing an efficient and effective re-planning algorithm is an important step toward the clinical realization of ART. For the re-planning process, manual trial-and-error approach to fine-tune planning parameters is time-consuming and is usually considered unpractical, especially for online ART. It is desirable to automate this step to yield a plan of acceptable quality with minimal interventions. In ART, prior information in the original plan is available, such as dose-volume histogram (DVH), which can be employed to facilitate the automatic re-planning process. The goal of this work is to develop an automatic re-planning algorithm to generate a plan with similar, or possibly better, DVH curves compared with the clinically delivered original plan. Specifically, our algorithm iterates the following two loops. An inner loop is the traditional fluence map optimization, in which we optimize a quadratic objective function penalizing the deviation of the dose received by each voxel from its prescribed or threshold dose with a set of fixed voxel weighting factors. In outer loop, the voxel weighting factors in the objective function are adjusted according to the deviation of the current DVH curves from those in the original plan. The process is repeated until the DVH curves are acceptable or maximum iteration step is reached. The whole algorithm is implemented on GPU for high efficiency. The feasibility of our algorithm has been demonstrated with three head-and-neck cancer IMRT cases, each having an initial planning CT scan and another treatment CT scan acquired in the middle of treatment course. Compared with the DVH curves in the original plan, the DVH curves in the resulting plan using our algorithm with 30 iterations are better for almost all structures. The re-optimization process takes about 30 s using our in-house optimization engine.

A fast and robust iterative algorithm for prediction of RNA pseudoknotted secondary structures

PubMed Central

2014-01-01

Background Improving accuracy and efficiency of computational methods that predict pseudoknotted RNA secondary structures is an ongoing challenge. Existing methods based on free energy minimization tend to be very slow and are limited in the types of pseudoknots that they can predict. Incorporating known structural information can improve prediction accuracy; however, there are not many methods for prediction of pseudoknotted structures that can incorporate structural information as input. There is even less understanding of the relative robustness of these methods with respect to partial information. Results We present a new method, Iterative HFold, for pseudoknotted RNA secondary structure prediction. Iterative HFold takes as input a pseudoknot-free structure, and produces a possibly pseudoknotted structure whose energy is at least as low as that of any (density-2) pseudoknotted structure containing the input structure. Iterative HFold leverages strengths of earlier methods, namely the fast running time of HFold, a method that is based on the hierarchical folding hypothesis, and the energy parameters of HotKnots V2.0. Our experimental evaluation on a large data set shows that Iterative HFold is robust with respect to partial information, with average accuracy on pseudoknotted structures steadily increasing from roughly 54% to 79% as the user provides up to 40% of the input structure. Iterative HFold is much faster than HotKnots V2.0, while having comparable accuracy. Iterative HFold also has significantly better accuracy than IPknot on our HK-PK and IP-pk168 data sets. Conclusions Iterative HFold is a robust method for prediction of pseudoknotted RNA secondary structures, whose accuracy with more than 5% information about true pseudoknot-free structures is better than that of IPknot, and with about 35% information about true pseudoknot-free structures compares well with that of HotKnots V2.0 while being significantly faster. Iterative HFold and all data used in this work are freely available at http://www.cs.ubc.ca/~hjabbari/software.php. PMID:24884954

Picard Trajectory Approximation Iteration for Efficient Orbit Propagation

DTIC Science & Technology

2015-07-21

Eqn (8)) for an iterative ap- proximation of eccentric anomaly, and is transformed back to . The Lambert/ Kepler time – eccentric anomaly relationship...of Kepler motion based on spinor regulari- zation, Journal fur die Reine und Angewandt Mathematik 218, 204-219, 1965. [3] Levi-Civita T., Sur la...transformed back to  , ,x y z . The Lambert/ Kepler time – eccentric anomaly relationship is iterated by a Newton/Secant method to converge on the

SPIDER image processing for single-particle reconstruction of biological macromolecules from electron micrographs

PubMed Central

Shaikh, Tanvir R; Gao, Haixiao; Baxter, William T; Asturias, Francisco J; Boisset, Nicolas; Leith, Ardean; Frank, Joachim

2009-01-01

This protocol describes the reconstruction of biological molecules from the electron micrographs of single particles. Computation here is performed using the image-processing software SPIDER and can be managed using a graphical user interface, termed the SPIDER Reconstruction Engine. Two approaches are described to obtain an initial reconstruction: random-conical tilt and common lines. Once an existing model is available, reference-based alignment can be used, a procedure that can be iterated. Also described is supervised classification, a method to look for homogeneous subsets when multiple known conformations of the molecule may coexist. PMID:19180078

Efficient fuzzy C-means architecture for image segmentation.

PubMed

Li, Hui-Ya; Hwang, Wen-Jyi; Chang, Chia-Yen

2011-01-01

This paper presents a novel VLSI architecture for image segmentation. The architecture is based on the fuzzy c-means algorithm with spatial constraint for reducing the misclassification rate. In the architecture, the usual iterative operations for updating the membership matrix and cluster centroid are merged into one single updating process to evade the large storage requirement. In addition, an efficient pipelined circuit is used for the updating process for accelerating the computational speed. Experimental results show that the the proposed circuit is an effective alternative for real-time image segmentation with low area cost and low misclassification rate.

Optical implementation of neocognitron and its applications to radar signature discrimination

NASA Technical Reports Server (NTRS)

Chao, Tien-Hsin; Stoner, William W.

1991-01-01

A feature-extraction-based optoelectronic neural network is introduced. The system implementation approach applies the principle of the neocognitron paradigm first introduced by Fukushima et al. (1983). A multichannel correlator is used as a building block of a generic single layer of the neocognitron for shift-invariant feature correlation. Multilayer processing is achieved by iteratively feeding back the output of the feature correlator to the input spatial light modulator. Successful pattern recognition with intraclass fault tolerance and interclass discrimination is achieved using this optoelectronic neocognitron. Detailed system analysis is described. Experimental demonstration of radar signature processing is also provided.

Physics Model-Based Scatter Correction in Multi-Source Interior Computed Tomography.

PubMed

Gong, Hao; Li, Bin; Jia, Xun; Cao, Guohua

2018-02-01

Multi-source interior computed tomography (CT) has a great potential to provide ultra-fast and organ-oriented imaging at low radiation dose. However, X-ray cross scattering from multiple simultaneously activated X-ray imaging chains compromises imaging quality. Previously, we published two hardware-based scatter correction methods for multi-source interior CT. Here, we propose a software-based scatter correction method, with the benefit of no need for hardware modifications. The new method is based on a physics model and an iterative framework. The physics model was derived analytically, and was used to calculate X-ray scattering signals in both forward direction and cross directions in multi-source interior CT. The physics model was integrated to an iterative scatter correction framework to reduce scatter artifacts. The method was applied to phantom data from both Monte Carlo simulations and physical experimentation that were designed to emulate the image acquisition in a multi-source interior CT architecture recently proposed by our team. The proposed scatter correction method reduced scatter artifacts significantly, even with only one iteration. Within a few iterations, the reconstructed images fast converged toward the "scatter-free" reference images. After applying the scatter correction method, the maximum CT number error at the region-of-interests (ROIs) was reduced to 46 HU in numerical phantom dataset and 48 HU in physical phantom dataset respectively, and the contrast-noise-ratio at those ROIs increased by up to 44.3% and up to 19.7%, respectively. The proposed physics model-based iterative scatter correction method could be useful for scatter correction in dual-source or multi-source CT.

A new design approach to innovative spectrometers. Case study: TROPOLITE

NASA Astrophysics Data System (ADS)

Volatier, Jean-Baptiste; Baümer, Stefan; Kruizinga, Bob; Vink, Rob

2014-05-01

Designing a novel optical system is a nested iterative process. The optimization loop, from a starting point to final system is already mostly automated. However this loop is part of a wider loop which is not. This wider loop starts with an optical specification and ends with a manufacturability assessment. When designing a new spectrometer with emphasis on weight and cost, numerous iterations between the optical- and mechanical designer are inevitable. The optical designer must then be able to reliably produce optical designs based on new input gained from multidisciplinary studies. This paper presents a procedure that can automatically generate new starting points based on any kind of input or new constraint that might arise. These starting points can then be handed over to a generic optimization routine to make the design tasks extremely efficient. The optical designer job is then not to design optical systems, but to meta-design a procedure that produces optical systems paving the way for system level optimization. We present here this procedure and its application to the design of TROPOLITE a lightweight push broom imaging spectrometer.

Graphic matching based on shape contexts and reweighted random walks

NASA Astrophysics Data System (ADS)

Zhang, Mingxuan; Niu, Dongmei; Zhao, Xiuyang; Liu, Mingjun

2018-04-01

Graphic matching is a very critical issue in all aspects of computer vision. In this paper, a new graphics matching algorithm combining shape contexts and reweighted random walks was proposed. On the basis of the local descriptor, shape contexts, the reweighted random walks algorithm was modified to possess stronger robustness and correctness in the final result. Our main process is to use the descriptor of the shape contexts for the random walk on the iteration, of which purpose is to control the random walk probability matrix. We calculate bias matrix by using descriptors and then in the iteration we use it to enhance random walks' and random jumps' accuracy, finally we get the one-to-one registration result by discretization of the matrix. The algorithm not only preserves the noise robustness of reweighted random walks but also possesses the rotation, translation, scale invariance of shape contexts. Through extensive experiments, based on real images and random synthetic point sets, and comparisons with other algorithms, it is confirmed that this new method can produce excellent results in graphic matching.

Application of iterative robust model-based optimal experimental design for the calibration of biocatalytic models.

PubMed

Van Daele, Timothy; Gernaey, Krist V; Ringborg, Rolf H; Börner, Tim; Heintz, Søren; Van Hauwermeiren, Daan; Grey, Carl; Krühne, Ulrich; Adlercreutz, Patrick; Nopens, Ingmar

2017-09-01

The aim of model calibration is to estimate unique parameter values from available experimental data, here applied to a biocatalytic process. The traditional approach of first gathering data followed by performing a model calibration is inefficient, since the information gathered during experimentation is not actively used to optimize the experimental design. By applying an iterative robust model-based optimal experimental design, the limited amount of data collected is used to design additional informative experiments. The algorithm is used here to calibrate the initial reaction rate of an ω-transaminase catalyzed reaction in a more accurate way. The parameter confidence region estimated from the Fisher Information Matrix is compared with the likelihood confidence region, which is not only more accurate but also a computationally more expensive method. As a result, an important deviation between both approaches is found, confirming that linearization methods should be applied with care for nonlinear models. © 2017 American Institute of Chemical Engineers Biotechnol. Prog., 33:1278-1293, 2017. © 2017 American Institute of Chemical Engineers.

Probabilistic Cellular Automata

PubMed Central

Agapie, Alexandru; Giuclea, Marius

2014-01-01

Abstract Cellular automata are binary lattices used for modeling complex dynamical systems. The automaton evolves iteratively from one configuration to another, using some local transition rule based on the number of ones in the neighborhood of each cell. With respect to the number of cells allowed to change per iteration, we speak of either synchronous or asynchronous automata. If randomness is involved to some degree in the transition rule, we speak of probabilistic automata, otherwise they are called deterministic. With either type of cellular automaton we are dealing with, the main theoretical challenge stays the same: starting from an arbitrary initial configuration, predict (with highest accuracy) the end configuration. If the automaton is deterministic, the outcome simplifies to one of two configurations, all zeros or all ones. If the automaton is probabilistic, the whole process is modeled by a finite homogeneous Markov chain, and the outcome is the corresponding stationary distribution. Based on our previous results for the asynchronous case—connecting the probability of a configuration in the stationary distribution to its number of zero-one borders—the article offers both numerical and theoretical insight into the long-term behavior of synchronous cellular automata. PMID:24999557

Probabilistic cellular automata.

PubMed

Agapie, Alexandru; Andreica, Anca; Giuclea, Marius

2014-09-01

Cellular automata are binary lattices used for modeling complex dynamical systems. The automaton evolves iteratively from one configuration to another, using some local transition rule based on the number of ones in the neighborhood of each cell. With respect to the number of cells allowed to change per iteration, we speak of either synchronous or asynchronous automata. If randomness is involved to some degree in the transition rule, we speak of probabilistic automata, otherwise they are called deterministic. With either type of cellular automaton we are dealing with, the main theoretical challenge stays the same: starting from an arbitrary initial configuration, predict (with highest accuracy) the end configuration. If the automaton is deterministic, the outcome simplifies to one of two configurations, all zeros or all ones. If the automaton is probabilistic, the whole process is modeled by a finite homogeneous Markov chain, and the outcome is the corresponding stationary distribution. Based on our previous results for the asynchronous case-connecting the probability of a configuration in the stationary distribution to its number of zero-one borders-the article offers both numerical and theoretical insight into the long-term behavior of synchronous cellular automata.

A positional misalignment correction method for Fourier ptychographic microscopy based on simulated annealing

NASA Astrophysics Data System (ADS)

Sun, Jiasong; Zhang, Yuzhen; Chen, Qian; Zuo, Chao

2017-02-01

Fourier ptychographic microscopy (FPM) is a newly developed super-resolution technique, which employs angularly varying illuminations and a phase retrieval algorithm to surpass the diffraction limit of a low numerical aperture (NA) objective lens. In current FPM imaging platforms, accurate knowledge of LED matrix's position is critical to achieve good recovery quality. Furthermore, considering such a wide field-of-view (FOV) in FPM, different regions in the FOV have different sensitivity of LED positional misalignment. In this work, we introduce an iterative method to correct position errors based on the simulated annealing (SA) algorithm. To improve the efficiency of this correcting process, large number of iterations for several images with low illumination NAs are firstly implemented to estimate the initial values of the global positional misalignment model through non-linear regression. Simulation and experimental results are presented to evaluate the performance of the proposed method and it is demonstrated that this method can both improve the quality of the recovered object image and relax the LED elements' position accuracy requirement while aligning the FPM imaging platforms.

Gauss-Seidel and Successive Overrelaxation Methods for Radiative Transfer with Partial Frequency Redistribution

NASA Astrophysics Data System (ADS)

Sampoorna, M.; Trujillo Bueno, J.

2010-04-01

The linearly polarized solar limb spectrum that is produced by scattering processes contains a wealth of information on the physical conditions and magnetic fields of the solar outer atmosphere, but the modeling of many of its strongest spectral lines requires solving an involved non-local thermodynamic equilibrium radiative transfer problem accounting for partial redistribution (PRD) effects. Fast radiative transfer methods for the numerical solution of PRD problems are also needed for a proper treatment of hydrogen lines when aiming at realistic time-dependent magnetohydrodynamic simulations of the solar chromosphere. Here we show how the two-level atom PRD problem with and without polarization can be solved accurately and efficiently via the application of highly convergent iterative schemes based on the Gauss-Seidel and successive overrelaxation (SOR) radiative transfer methods that had been previously developed for the complete redistribution case. Of particular interest is the Symmetric SOR method, which allows us to reach the fully converged solution with an order of magnitude of improvement in the total computational time with respect to the Jacobi-based local accelerated lambda iteration method.

Novel Fourier-domain constraint for fast phase retrieval in coherent diffraction imaging.

PubMed

Latychevskaia, Tatiana; Longchamp, Jean-Nicolas; Fink, Hans-Werner

2011-09-26

Coherent diffraction imaging (CDI) for visualizing objects at atomic resolution has been realized as a promising tool for imaging single molecules. Drawbacks of CDI are associated with the difficulty of the numerical phase retrieval from experimental diffraction patterns; a fact which stimulated search for better numerical methods and alternative experimental techniques. Common phase retrieval methods are based on iterative procedures which propagate the complex-valued wave between object and detector plane. Constraints in both, the object and the detector plane are applied. While the constraint in the detector plane employed in most phase retrieval methods requires the amplitude of the complex wave to be equal to the squared root of the measured intensity, we propose a novel Fourier-domain constraint, based on an analogy to holography. Our method allows achieving a low-resolution reconstruction already in the first step followed by a high-resolution reconstruction after further steps. In comparison to conventional schemes this Fourier-domain constraint results in a fast and reliable convergence of the iterative reconstruction process. © 2011 Optical Society of America

Image quality of iterative reconstruction in cranial CT imaging: comparison of model-based iterative reconstruction (MBIR) and adaptive statistical iterative reconstruction (ASiR).

PubMed

Notohamiprodjo, S; Deak, Z; Meurer, F; Maertz, F; Mueck, F G; Geyer, L L; Wirth, S

2015-01-01

The purpose of this study was to compare cranial CT (CCT) image quality (IQ) of the MBIR algorithm with standard iterative reconstruction (ASiR). In this institutional review board (IRB)-approved study, raw data sets of 100 unenhanced CCT examinations (120 kV, 50-260 mAs, 20 mm collimation, 0.984 pitch) were reconstructed with both ASiR and MBIR. Signal-to-noise (SNR) and contrast-to-noise (CNR) were calculated from attenuation values measured in caudate nucleus, frontal white matter, anterior ventricle horn, fourth ventricle, and pons. Two radiologists, who were blinded to the reconstruction algorithms, evaluated anonymized multiplanar reformations of 2.5 mm with respect to depiction of different parenchymal structures and impact of artefacts on IQ with a five-point scale (0: unacceptable, 1: less than average, 2: average, 3: above average, 4: excellent). MBIR decreased artefacts more effectively than ASiR (p < 0.01). The median depiction score for MBIR was 3, whereas the median value for ASiR was 2 (p < 0.01). SNR and CNR were significantly higher in MBIR than ASiR (p < 0.01). MBIR showed significant improvement of IQ parameters compared to ASiR. As CCT is an examination that is frequently required, the use of MBIR may allow for substantial reduction of radiation exposure caused by medical diagnostics. • Model-Based iterative reconstruction (MBIR) effectively decreased artefacts in cranial CT. • MBIR reconstructed images were rated with significantly higher scores for image quality. • Model-Based iterative reconstruction may allow reduced-dose diagnostic examination protocols.

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.

Approximate techniques of structural reanalysis

NASA Technical Reports Server (NTRS)

Noor, A. K.; Lowder, H. E.

1974-01-01

A study is made of two approximate techniques for structural reanalysis. These include Taylor series expansions for response variables in terms of design variables and the reduced-basis method. In addition, modifications to these techniques are proposed to overcome some of their major drawbacks. The modifications include a rational approach to the selection of the reduced-basis vectors and the use of Taylor series approximation in an iterative process. For the reduced basis a normalized set of vectors is chosen which consists of the original analyzed design and the first-order sensitivity analysis vectors. The use of the Taylor series approximation as a first (initial) estimate in an iterative process, can lead to significant improvements in accuracy, even with one iteration cycle. Therefore, the range of applicability of the reanalysis technique can be extended. Numerical examples are presented which demonstrate the gain in accuracy obtained by using the proposed modification techniques, for a wide range of variations in the design variables.

Efficient solution of the simplified P N equations

DOE PAGES

Hamilton, Steven P.; Evans, Thomas M.

2014-12-23

We show new solver strategies for the multigroup SPN equations for nuclear reactor analysis. By forming the complete matrix over space, moments, and energy a robust set of solution strategies may be applied. Moreover, power iteration, shifted power iteration, Rayleigh quotient iteration, Arnoldi's method, and a generalized Davidson method, each using algebraic and physics-based multigrid preconditioners, have been compared on C5G7 MOX test problem as well as an operational PWR model. These results show that the most ecient approach is the generalized Davidson method, that is 30-40 times faster than traditional power iteration and 6-10 times faster than Arnoldi's method.

Iterative filtering decomposition based on local spectral evolution kernel

PubMed Central

Wang, Yang; Wei, Guo-Wei; Yang, Siyang

2011-01-01

The synthesizing information, achieving understanding, and deriving insight from increasingly massive, time-varying, noisy and possibly conflicting data sets are some of most challenging tasks in the present information age. Traditional technologies, such as Fourier transform and wavelet multi-resolution analysis, are inadequate to handle all of the above-mentioned tasks. The empirical model decomposition (EMD) has emerged as a new powerful tool for resolving many challenging problems in data processing and analysis. Recently, an iterative filtering decomposition (IFD) has been introduced to address the stability and efficiency problems of the EMD. Another data analysis technique is the local spectral evolution kernel (LSEK), which provides a near prefect low pass filter with desirable time-frequency localizations. The present work utilizes the LSEK to further stabilize the IFD, and offers an efficient, flexible and robust scheme for information extraction, complexity reduction, and signal and image understanding. The performance of the present LSEK based IFD is intensively validated over a wide range of data processing tasks, including mode decomposition, analysis of time-varying data, information extraction from nonlinear dynamic systems, etc. The utility, robustness and usefulness of the proposed LESK based IFD are demonstrated via a large number of applications, such as the analysis of stock market data, the decomposition of ocean wave magnitudes, the understanding of physiologic signals and information recovery from noisy images. The performance of the proposed method is compared with that of existing methods in the literature. Our results indicate that the LSEK based IFD improves both the efficiency and the stability of conventional EMD algorithms. PMID:22350559

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.

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.

A Novel Real-Time Reference Key Frame Scan Matching Method.

PubMed

Mohamed, Haytham; Moussa, Adel; Elhabiby, Mohamed; El-Sheimy, Naser; Sesay, Abu

2017-05-07

Unmanned aerial vehicles represent an effective technology for indoor search and rescue operations. Typically, most indoor missions' environments would be unknown, unstructured, and/or dynamic. Navigation of UAVs in such environments is addressed by simultaneous localization and mapping approach using either local or global approaches. Both approaches suffer from accumulated errors and high processing time due to the iterative nature of the scan matching method. Moreover, point-to-point scan matching is prone to outlier association processes. This paper proposes a low-cost novel method for 2D real-time scan matching based on a reference key frame (RKF). RKF is a hybrid scan matching technique comprised of feature-to-feature and point-to-point approaches. This algorithm aims at mitigating errors accumulation using the key frame technique, which is inspired from video streaming broadcast process. The algorithm depends on the iterative closest point algorithm during the lack of linear features which is typically exhibited in unstructured environments. The algorithm switches back to the RKF once linear features are detected. To validate and evaluate the algorithm, the mapping performance and time consumption are compared with various algorithms in static and dynamic environments. The performance of the algorithm exhibits promising navigational, mapping results and very short computational time, that indicates the potential use of the new algorithm with real-time systems.

Predicting Silk Fiber Mechanical Properties through Multiscale Simulation and Protein Design.

PubMed

Rim, Nae-Gyune; Roberts, Erin G; Ebrahimi, Davoud; Dinjaski, Nina; Jacobsen, Matthew M; Martín-Moldes, Zaira; Buehler, Markus J; Kaplan, David L; Wong, Joyce Y

2017-08-14

Silk is a promising material for biomedical applications, and much research is focused on how application-specific, mechanical properties of silk can be designed synthetically through proper amino acid sequences and processing parameters. This protocol describes an iterative process between research disciplines that combines simulation, genetic synthesis, and fiber analysis to better design silk fibers with specific mechanical properties. Computational methods are used to assess the protein polymer structure as it forms an interconnected fiber network through shearing and how this process affects fiber mechanical properties. Model outcomes are validated experimentally with the genetic design of protein polymers that match the simulation structures, fiber fabrication from these polymers, and mechanical testing of these fibers. Through iterative feedback between computation, genetic synthesis, and fiber mechanical testing, this protocol will enable a priori prediction capability of recombinant material mechanical properties via insights from the resulting molecular architecture of the fiber network based entirely on the initial protein monomer composition. This style of protocol may be applied to other fields where a research team seeks to design a biomaterial with biomedical application-specific properties. This protocol highlights when and how the three research groups (simulation, synthesis, and engineering) should be interacting to arrive at the most effective method for predictive design of their material.