3-D phononic crystals with ultra-wide band gaps

PubMed Central

Lu, Yan; Yang, Yang; Guest, James K.; Srivastava, Ankit

2017-01-01

In this paper gradient based topology optimization (TO) is used to discover 3-D phononic structures that exhibit ultra-wide normalized all-angle all-mode band gaps. The challenging computational task of repeated 3-D phononic band-structure evaluations is accomplished by a combination of a fast mixed variational eigenvalue solver and distributed Graphic Processing Unit (GPU) parallel computations. The TO algorithm utilizes the material distribution-based approach and a gradient-based optimizer. The design sensitivity for the mixed variational eigenvalue problem is derived using the adjoint method and is implemented through highly efficient vectorization techniques. We present optimized results for two-material simple cubic (SC), body centered cubic (BCC), and face centered cubic (FCC) crystal structures and show that in each of these cases different initial designs converge to single inclusion network topologies within their corresponding primitive cells. The optimized results show that large phononic stop bands for bulk wave propagation can be achieved at lower than close packed spherical configurations leading to lighter unit cells. For tungsten carbide - epoxy crystals we identify all angle all mode normalized stop bands exceeding 100%, which is larger than what is possible with only spherical inclusions. PMID:28233812

3-D phononic crystals with ultra-wide band gaps.

PubMed

Lu, Yan; Yang, Yang; Guest, James K; Srivastava, Ankit

2017-02-24

In this paper gradient based topology optimization (TO) is used to discover 3-D phononic structures that exhibit ultra-wide normalized all-angle all-mode band gaps. The challenging computational task of repeated 3-D phononic band-structure evaluations is accomplished by a combination of a fast mixed variational eigenvalue solver and distributed Graphic Processing Unit (GPU) parallel computations. The TO algorithm utilizes the material distribution-based approach and a gradient-based optimizer. The design sensitivity for the mixed variational eigenvalue problem is derived using the adjoint method and is implemented through highly efficient vectorization techniques. We present optimized results for two-material simple cubic (SC), body centered cubic (BCC), and face centered cubic (FCC) crystal structures and show that in each of these cases different initial designs converge to single inclusion network topologies within their corresponding primitive cells. The optimized results show that large phononic stop bands for bulk wave propagation can be achieved at lower than close packed spherical configurations leading to lighter unit cells. For tungsten carbide - epoxy crystals we identify all angle all mode normalized stop bands exceeding 100%, which is larger than what is possible with only spherical inclusions.

Online Optimal Control of Connected Vehicles for Efficient Traffic Flow at Merging Roads

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

Rios-Torres, Jackeline; Malikopoulos, Andreas; Pisu, Pierluigi

2015-01-01

This paper addresses the problem of coordinating online connected vehicles at merging roads to achieve a smooth traffic flow without stop-and-go driving. We present a framework and a closed-form solution that optimize the acceleration profile of each vehicle in terms of fuel economy while avoiding collision with other vehicles at the merging zone. The proposed solution is validated through simulation and it is shown that coordination of connected vehicles can reduce significantly fuel consumption and travel time at merging roads.

Finite-Dimensional Representations for Controlled Diffusions with Delay

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

Federico, Salvatore, E-mail: salvatore.federico@unimi.it; Tankov, Peter, E-mail: tankov@math.univ-paris-diderot.fr

2015-02-15

We study stochastic delay differential equations (SDDE) where the coefficients depend on the moving averages of the state process. As a first contribution, we provide sufficient conditions under which the solution of the SDDE and a linear path functional of it admit a finite-dimensional Markovian representation. As a second contribution, we show how approximate finite-dimensional Markovian representations may be constructed when these conditions are not satisfied, and provide an estimate of the error corresponding to these approximations. These results are applied to optimal control and optimal stopping problems for stochastic systems with delay.

Expectation maximization for hard X-ray count modulation profiles

NASA Astrophysics Data System (ADS)

Benvenuto, F.; Schwartz, R.; Piana, M.; Massone, A. M.

2013-07-01

Context. This paper is concerned with the image reconstruction problem when the measured data are solar hard X-ray modulation profiles obtained from the Reuven Ramaty High Energy Solar Spectroscopic Imager (RHESSI) instrument. Aims: Our goal is to demonstrate that a statistical iterative method classically applied to the image deconvolution problem is very effective when utilized to analyze count modulation profiles in solar hard X-ray imaging based on rotating modulation collimators. Methods: The algorithm described in this paper solves the maximum likelihood problem iteratively and encodes a positivity constraint into the iterative optimization scheme. The result is therefore a classical expectation maximization method this time applied not to an image deconvolution problem but to image reconstruction from count modulation profiles. The technical reason that makes our implementation particularly effective in this application is the use of a very reliable stopping rule which is able to regularize the solution providing, at the same time, a very satisfactory Cash-statistic (C-statistic). Results: The method is applied to both reproduce synthetic flaring configurations and reconstruct images from experimental data corresponding to three real events. In this second case, the performance of expectation maximization, when compared to Pixon image reconstruction, shows a comparable accuracy and a notably reduced computational burden; when compared to CLEAN, shows a better fidelity with respect to the measurements with a comparable computational effectiveness. Conclusions: If optimally stopped, expectation maximization represents a very reliable method for image reconstruction in the RHESSI context when count modulation profiles are used as input data.

Route optimization as an instrument to improve animal welfare and economics in pre-slaughter logistics.

PubMed

Frisk, Mikael; Jonsson, Annie; Sellman, Stefan; Flisberg, Patrik; Rönnqvist, Mikael; Wennergren, Uno

2018-01-01

Each year, more than three million animals are transported from farms to abattoirs in Sweden. Animal transport is related to economic and environmental costs and a negative impact on animal welfare. Time and the number of pick-up stops between farms and abattoirs are two key parameters for animal welfare. Both are highly dependent on efficient and qualitative transportation planning, which may be difficult if done manually. We have examined the benefits of using route optimization in cattle transportation planning. To simulate the effects of various planning time windows and transportation time regulations and number of pick-up stops along each route, we have used data that represent one year of cattle transport. Our optimization model is a development of a model used in forestry transport that solves a general pick-up and delivery vehicle routing problem. The objective is to minimize transportation costs. We have shown that the length of the planning time window has a significant impact on the animal transport time, the total driving time and the total distance driven; these parameters that will not only affect animal welfare but also affect the economy and environment in the pre-slaughter logistic chain. In addition, we have shown that changes in animal transportation regulations, such as minimizing the number of allowed pick-up stops on each route or minimizing animal transportation time, will have positive effects on animal welfare measured in transportation hours and number of pick-up stops. However, this leads to an increase in working time and driven distances, leading to higher transportation costs for the transport and negative environmental impact.

Route optimization as an instrument to improve animal welfare and economics in pre-slaughter logistics

PubMed Central

2018-01-01

Each year, more than three million animals are transported from farms to abattoirs in Sweden. Animal transport is related to economic and environmental costs and a negative impact on animal welfare. Time and the number of pick-up stops between farms and abattoirs are two key parameters for animal welfare. Both are highly dependent on efficient and qualitative transportation planning, which may be difficult if done manually. We have examined the benefits of using route optimization in cattle transportation planning. To simulate the effects of various planning time windows and transportation time regulations and number of pick-up stops along each route, we have used data that represent one year of cattle transport. Our optimization model is a development of a model used in forestry transport that solves a general pick-up and delivery vehicle routing problem. The objective is to minimize transportation costs. We have shown that the length of the planning time window has a significant impact on the animal transport time, the total driving time and the total distance driven; these parameters that will not only affect animal welfare but also affect the economy and environment in the pre-slaughter logistic chain. In addition, we have shown that changes in animal transportation regulations, such as minimizing the number of allowed pick-up stops on each route or minimizing animal transportation time, will have positive effects on animal welfare measured in transportation hours and number of pick-up stops. However, this leads to an increase in working time and driven distances, leading to higher transportation costs for the transport and negative environmental impact. PMID:29513704

Optimal surveillance strategy for invasive species management when surveys stop after detection.

PubMed

Guillera-Arroita, Gurutzeta; Hauser, Cindy E; McCarthy, Michael A

2014-05-01

Invasive species are a cause for concern in natural and economic systems and require both monitoring and management. There is a trade-off between the amount of resources spent on surveying for the species and conducting early management of occupied sites, and the resources that are ultimately spent in delayed management at sites where the species was present but undetected. Previous work addressed this optimal resource allocation problem assuming that surveys continue despite detection until the initially planned survey effort is consumed. However, a more realistic scenario is often that surveys stop after detection (i.e., follow a "removal" sampling design) and then management begins. Such an approach will indicate a different optimal survey design and can be expected to be more efficient. We analyze this case and compare the expected efficiency of invasive species management programs under both survey methods. We also evaluate the impact of mis-specifying the type of sampling approach during the program design phase. We derive analytical expressions that optimize resource allocation between monitoring and management in surveillance programs when surveys stop after detection. We do this under a scenario of unconstrained resources and scenarios where survey budget is constrained. The efficiency of surveillance programs is greater if a "removal survey" design is used, with larger gains obtained when savings from early detection are high, occupancy is high, and survey costs are not much lower than early management costs at a site. Designing a surveillance program disregarding that surveys stop after detection can result in an efficiency loss. Our results help guide the design of future surveillance programs for invasive species. Addressing program design within a decision-theoretic framework can lead to a better use of available resources. We show how species prevalence, its detectability, and the benefits derived from early detection can be considered.

Optimization of new magnetorheological fluid mount for vibration control of start/stop engine mode

NASA Astrophysics Data System (ADS)

Chung, Jye Ung; Phu, Do Xuan; Choi, Seung-Bok

2015-04-01

The technologies related to saving energy/or green vehicles are actively researched. In this tendency, the problem for reducing exhausted gas is in development with various ways. Those efforts are directly related to the operation of engine which emits exhausted gas. The auto start/stop of vehicle engine when a vehicle stop at road is currently as a main stream of vehicle industry resulting in reducing exhausted gas. However, this technology automatically turns on and off engine frequently. This motion induces vehicle engine to transmit vibration of engine which has large displacement, and torsional impact to chassis. These vibrations causing uncomfortable feeling to passengers are transmitted through the steering wheel and the gear knob. In this work, in order to resolve this vibration issue, a new proposed magnetorheological (MR) fluid based engine mount (MR mount in short) is presented. The proposed MR mount is designed to satisfy large damping force in various frequency ranges. It is shown that the proposed mount can have large damping force and large force ratio which is enough to control unwanted vibrations of engine start/stop mode.

Algorithms for constructing optimal paths and statistical analysis of passenger traffic

NASA Astrophysics Data System (ADS)

Trofimov, S. P.; Druzhinina, N. G.; Trofimova, O. G.

2018-01-01

Several existing information systems of urban passenger transport (UPT) are considered. Author’s UPT network model is presented. To a passenger a new service is offered that is the best path from one stop to another stop at a specified time. The algorithm and software implementation for finding the optimal path are presented. The algorithm uses the current UPT schedule. The article also describes the algorithm of statistical analysis of trip payments by the electronic E-cards. The algorithm allows obtaining the density of passenger traffic during the day. This density is independent of the network topology and UPT schedules. The resulting density of the traffic flow can solve a number of practical problems. In particular, the forecast for the overflow of passenger transport in the «rush» hours, the quantitative comparison of different topologies transport networks, constructing of the best UPT timetable. The efficiency of the proposed integrated approach is demonstrated by the example of the model town with arbitrary dimensions.

The Optimal Observation Problem applied to a rating curve estimation including the "cost-to-wait"

NASA Astrophysics Data System (ADS)

Raso, Luciano; Werner, Micha; Weijs, Steven

2013-04-01

In order to manage a system, a decision maker (DM) tries to make the best decision under uncertainty, having partial knowledge on the effects of his/her decision. Observations reduce uncertainty, but are costly. Deciding what to observe and when to stop observing is a complementary problem that the DM has to face. The Optimal Observation Problem (OOP) offers a solution to the questions: (1) which observation is more effective? And (2) Is the next observation worth its cost? We show an application of the OOP to a rating curve estimation in the White Carter River (Scotland). The cost of extra gauging is compensated by the value of better decisions, that reduce the costs due to floods. The observational decision is then whether to gauge, and when. In the application, we include the "cost-to-wait" in the cost structure. The Algorithm find thus an optimal trade-off between getting less informative data now or wait for more informative, but later. The OOP can be used to plan a measurement campaign, also taking into account that the rating curve can change.

Evaluation of Effective Factors on Travel Time in Optimization of Bus Stops Placement Using Genetic Algorithm

NASA Astrophysics Data System (ADS)

Bargegol, Iraj; Ghorbanzadeh, Mahyar; Ghasedi, Meisam; Rastbod, Mohammad

2017-10-01

In congested cities, locating and proper designing of bus stops according to the unequal distribution of passengers is crucial issue economically and functionally, since this subject plays an important role in the use of bus system by passengers. Location of bus stops is a complicated subject; by reducing distances between stops, walking time decreases, but the total travel time may increase. In this paper, a specified corridor in the city of Rasht in north of Iran is studied. Firstly, a new formula is presented to calculate the travel time, by which the number of stops and consequently, the travel time can be optimized. An intended corridor with specified number of stops and distances between them is addressed, the related formulas to travel time are created, and its travel time is calculated. Then the corridor is modelled using a meta-heuristic method in order that the placement and the optimal distances of bus stops for that are determined. It was found that alighting and boarding time along with bus capacity are the most effective factors affecting travel time. Consequently, it is better to have more concentration on indicated factors for improving the efficiency of bus system.

MinFinder v2.0: An improved version of MinFinder

NASA Astrophysics Data System (ADS)

Tsoulos, Ioannis G.; Lagaris, Isaac E.

2008-10-01

A new version of the "MinFinder" program is presented that offers an augmented linking procedure for Fortran-77 subprograms, two additional stopping rules and a new start-point rejection mechanism that saves a significant portion of gradient and function evaluations. The method is applied on a set of standard test functions and the results are reported. New version program summaryProgram title: MinFinder v2.0 Catalogue identifier: ADWU_v2_0 Program summary URL:http://cpc.cs.qub.ac.uk/summaries/ADWU_v2_0.html Program obtainable from: CPC Program Library, Queen's University, Belfast, N. Ireland Licensing provisions: Standard CPC Licence, http://cpc.cs.qub.ac.uk/licence/licence.html No. of lines in distributed program, including test data, etc.: 14 150 No. of bytes in distributed program, including test data, etc.: 218 144 Distribution format: tar.gz Programming language used: GNU C++, GNU FORTRAN, GNU C Computer: The program is designed to be portable in all systems running the GNU C++ compiler Operating system: Linux, Solaris, FreeBSD RAM: 200 000 bytes Classification: 4.9 Catalogue identifier of previous version: ADWU_v1_0 Journal reference of previous version: Computer Physics Communications 174 (2006) 166-179 Does the new version supersede the previous version?: Yes Nature of problem: A multitude of problems in science and engineering are often reduced to minimizing a function of many variables. There are instances that a local optimum does not correspond to the desired physical solution and hence the search for a better solution is required. Local optimization techniques can be trapped in any local minimum. Global optimization is then the appropriate tool. For example, solving a non-linear system of equations via optimization, one may encounter many local minima that do not correspond to solutions, i.e. they are far from zero. Solution method: Using a uniform pdf, points are sampled from a rectangular domain. A clustering technique, based on a typical distance and a gradient criterion, is used to decide from which points a local search should be started. Further searching is terminated when all the local minima inside the search domain are thought to be found. This is accomplished via three stopping rules: the "double-box" stopping rule, the "observables" stopping rule and the "expected minimizers" stopping rule. Reasons for the new version: The link procedure for source code in Fortran 77 is enhanced, two additional stopping rules are implemented and a new criterion for accepting-start points, that economizes on function and gradient calls, is introduced. Summary of revisions:Addition of command line parameters to the utility program make_program. Augmentation of the link process for Fortran 77 subprograms, by linking the final executable with the g2c library. Addition of two probabilistic stopping rules. Introduction of a rejection mechanism to the Checking step of the original method, that reduces the number of gradient evaluations. Additional comments: A technical report describing the revisions, experiments and test runs is packaged with the source code. Running time: Depending on the objective function.

Eco-analytical Methodology in Environmental Problems Monitoring

NASA Astrophysics Data System (ADS)

Agienko, M. I.; Bondareva, E. P.; Chistyakova, G. V.; Zhironkina, O. V.; Kalinina, O. I.

2017-01-01

Among the problems common to all mankind, which solutions influence the prospects of civilization, the problem of ecological situation monitoring takes very important place. Solution of this problem requires specific methodology based on eco-analytical comprehension of global issues. Eco-analytical methodology should help searching for the optimum balance between environmental problems and accelerating scientific and technical progress. The fact that Governments, corporations, scientists and nations focus on the production and consumption of material goods cause great damage to environment. As a result, the activity of environmentalists is developing quite spontaneously, as a complement to productive activities. Therefore, the challenge posed by the environmental problems for the science is the formation of geo-analytical reasoning and the monitoring of global problems common for the whole humanity. So it is expected to find the optimal trajectory of industrial development to prevent irreversible problems in the biosphere that could stop progress of civilization.

A synergic simulation-optimization approach for analyzing biomolecular dynamics in living organisms.

PubMed

Sadegh Zadeh, Kouroush

2011-01-01

A synergic duo simulation-optimization approach was developed and implemented to study protein-substrate dynamics and binding kinetics in living organisms. The forward problem is a system of several coupled nonlinear partial differential equations which, with a given set of kinetics and diffusion parameters, can provide not only the commonly used bleached area-averaged time series in fluorescence microscopy experiments but more informative full biomolecular/drug space-time series and can be successfully used to study dynamics of both Dirac and Gaussian fluorescence-labeled biomacromolecules in vivo. The incomplete Cholesky preconditioner was coupled with the finite difference discretization scheme and an adaptive time-stepping strategy to solve the forward problem. The proposed approach was validated with analytical as well as reference solutions and used to simulate dynamics of GFP-tagged glucocorticoid receptor (GFP-GR) in mouse cancer cell during a fluorescence recovery after photobleaching experiment. Model analysis indicates that the commonly practiced bleach spot-averaged time series is not an efficient approach to extract physiological information from the fluorescence microscopy protocols. It was recommended that experimental biophysicists should use full space-time series, resulting from experimental protocols, to study dynamics of biomacromolecules and drugs in living organisms. It was also concluded that in parameterization of biological mass transfer processes, setting the norm of the gradient of the penalty function at the solution to zero is not an efficient stopping rule to end the inverse algorithm. Theoreticians should use multi-criteria stopping rules to quantify model parameters by optimization. Copyright © 2010 Elsevier Ltd. All rights reserved.

Design of limited-stop service based on the degree of unbalance of passenger demand

PubMed Central

2018-01-01

This paper presents a limited-stop service for a bus fleet to meet the unbalanced demand of passengers on a bus route and to improve the transit service of the bus route. This strategy includes two parts: a degree assessment of unbalanced passenger demand and an optimization of the limited-stop service. The degree assessment of unbalanced passenger demand, which is based on the different passenger demand between stations and the unbalance of passengers within the station, is used to judge whether implementing the limited-stop service is necessary for a bus route. The optimization of limited-stop service considers the influence of stop skipping action and bus capacity on the left-over passengers to determine the proper skipping stations for the bus fleet serving the entire route by minimizing both the waiting time and in-vehicle time of passengers and the running time of vehicles. A solution algorithm based on genetic algorithm is also presented to evaluate the degree of unbalanced passenger demand and optimize the limited-stop scheme. Then, the proper strategy is tested on a bus route in Changchun city of China. The threshold of degree assessment of unbalanced passenger demand can be calibrated and adapted to different passenger demands. PMID:29505585

Design of limited-stop service based on the degree of unbalance of passenger demand.

PubMed

Zhang, Hu; Zhao, Shuzhi; Liu, Huasheng; Liang, Shidong

2018-01-01

This paper presents a limited-stop service for a bus fleet to meet the unbalanced demand of passengers on a bus route and to improve the transit service of the bus route. This strategy includes two parts: a degree assessment of unbalanced passenger demand and an optimization of the limited-stop service. The degree assessment of unbalanced passenger demand, which is based on the different passenger demand between stations and the unbalance of passengers within the station, is used to judge whether implementing the limited-stop service is necessary for a bus route. The optimization of limited-stop service considers the influence of stop skipping action and bus capacity on the left-over passengers to determine the proper skipping stations for the bus fleet serving the entire route by minimizing both the waiting time and in-vehicle time of passengers and the running time of vehicles. A solution algorithm based on genetic algorithm is also presented to evaluate the degree of unbalanced passenger demand and optimize the limited-stop scheme. Then, the proper strategy is tested on a bus route in Changchun city of China. The threshold of degree assessment of unbalanced passenger demand can be calibrated and adapted to different passenger demands.

Mathematical modeling for optimizing skip-stop rail transit operation strategy using genetic algorithm.

DOT National Transportation Integrated Search

2012-03-01

"With skip-stop rail transit operation, transit agencies can reduce their operating costs and fleet size, : and passengers can experience reduced in-transit travel times without extra track and technological : improvement. However, since skip-stop op...

Automated and Cooperative Vehicle Merging at Highway On-Ramps

DOE PAGES

Rios-Torres, Jackeline; Malikopoulos, Andreas A.

2016-08-05

Recognition of necessities of connected and automated vehicles (CAVs) is gaining momentum. CAVs can improve both transportation network efficiency and safety through control algorithms that can harmonically use all existing information to coordinate the vehicles. This paper addresses the problem of optimally coordinating CAVs at merging roadways to achieve smooth traffic flow without stop-and-go driving. Here we present an optimization framework and an analytical closed-form solution that allows online coordination of vehicles at merging zones. The effectiveness of the efficiency of the proposed solution is validated through a simulation, and it is shown that coordination of vehicles can significantly reducemore » both fuel consumption and travel time.« less

Optimization models for prioritizing bus stop facility investments for riders with disabilities : March 2010.

DOT National Transportation Integrated Search

2010-03-01

The Americans with Disabilities Act (ADA) of 1990 prescribes the minimum requirements for bus stop accessibility by riders with disabilities. Due to limited budgets, transit agencies can only select a limited number of bus stop locations for ADA impr...

Stress and alcohol cues exert conjoint effects on go and stop signal responding in male problem drinkers.

PubMed

Zack, Martin; Woodford, Tracy M; Tremblay, Anne M; Steinberg, Lindsay; Zawertailo, Laurie A; Busto, Usoa E

2011-01-01

Stress, cues, and pharmacological priming are linked with relapse to addictive behavior. Increased salience and decreased inhibitory control are thought to mediate the effects of relapse-related stimuli. However, the functional relationship between these two processes is unclear. To address this issue, a modified Stop Signal Task was employed, which used Alcohol, Neutral, and Non-Words as Go stimuli, and lexical decision as the Go response. Subjects were 38 male problem drinkers (mean Alcohol Dependence Scale (ADS) score: 18.0). Uncontrollable noise (∼ 10 min at 110 dB) was the stressor; nonalcoholic placebo beer (P-Beer) was the cue manipulation, and alcohol (0.7 g/kg), the pharmacological prime. Half the sample received alcohol, and half P-Beer. Stress and beverage (test drink vs soft drink) were manipulated within subjects on two sessions, with half the sample receiving active manipulations together and half receiving them separately. Go response time (RT) and Stop Signal RT (SSRT) were slower to Alcohol than Neutral words. Stress augmented this bias. Alcohol and P-Beer impaired overall SSRT. Stress impaired neither overall SSRT nor Go RT. SSRT to Neutral words and Non-Words correlated inversely with Go RT to Alcohol and Neutral words, and Non-Words. ADS correlated directly with SSRT to Alcohol words. A resource allocation account was proposed, whereby diversion of limited resources to salient cues effectively yoked otherwise independent Go and Stop processes. Disturbances of prefrontal norepinephrine and dopamine were cited as possibly accounting for these effects. Treatments that optimize prefrontal catecholamine transmission may deter relapse by reducing disinhibitory effects of salient eliciting stimuli.

Stress and Alcohol Cues Exert Conjoint Effects on Go and Stop Signal Responding in Male Problem Drinkers

PubMed Central

Zack, Martin; Woodford, Tracy M; Tremblay, Anne M; Steinberg, Lindsay; Zawertailo, Laurie A; Busto, Usoa E

2011-01-01

Stress, cues, and pharmacological priming are linked with relapse to addictive behavior. Increased salience and decreased inhibitory control are thought to mediate the effects of relapse-related stimuli. However, the functional relationship between these two processes is unclear. To address this issue, a modified Stop Signal Task was employed, which used Alcohol, Neutral, and Non-Words as Go stimuli, and lexical decision as the Go response. Subjects were 38 male problem drinkers (mean Alcohol Dependence Scale (ADS) score: 18.0). Uncontrollable noise (∼10 min at 110 dB) was the stressor; nonalcoholic placebo beer (P-Beer) was the cue manipulation, and alcohol (0.7 g/kg), the pharmacological prime. Half the sample received alcohol, and half P-Beer. Stress and beverage (test drink vs soft drink) were manipulated within subjects on two sessions, with half the sample receiving active manipulations together and half receiving them separately. Go response time (RT) and Stop Signal RT (SSRT) were slower to Alcohol than Neutral words. Stress augmented this bias. Alcohol and P-Beer impaired overall SSRT. Stress impaired neither overall SSRT nor Go RT. SSRT to Neutral words and Non-Words correlated inversely with Go RT to Alcohol and Neutral words, and Non-Words. ADS correlated directly with SSRT to Alcohol words. A resource allocation account was proposed, whereby diversion of limited resources to salient cues effectively yoked otherwise independent Go and Stop processes. Disturbances of prefrontal norepinephrine and dopamine were cited as possibly accounting for these effects. Treatments that optimize prefrontal catecholamine transmission may deter relapse by reducing disinhibitory effects of salient eliciting stimuli. PMID:20927046

Optimal integer resolution for attitude determination using global positioning system signals

NASA Technical Reports Server (NTRS)

Crassidis, John L.; Markley, F. Landis; Lightsey, E. Glenn

1998-01-01

In this paper, a new motion-based algorithm for GPS integer ambiguity resolution is derived. The first step of this algorithm converts the reference sightline vectors into body frame vectors. This is accomplished by an optimal vectorized transformation of the phase difference measurements. The result of this transformation leads to the conversion of the integer ambiguities to vectorized biases. This essentially converts the problem to the familiar magnetometer-bias determination problem, for which an optimal and efficient solution exists. Also, the formulation in this paper is re-derived to provide a sequential estimate, so that a suitable stopping condition can be found during the vehicle motion. The advantages of the new algorithm include: it does not require an a-priori estimate of the vehicle's attitude; it provides an inherent integrity check using a covariance-type expression; and it can sequentially estimate the ambiguities during the vehicle motion. The only disadvantage of the new algorithm is that it requires at least three non-coplanar baselines. The performance of the new algorithm is tested on a dynamic hardware simulator.

Optimizing patient treatment decisions in an era of rapid technological advances: the case of hepatitis C treatment.

PubMed

Liu, Shan; Brandeau, Margaret L; Goldhaber-Fiebert, Jeremy D

2017-03-01

How long should a patient with a treatable chronic disease wait for more effective treatments before accepting the best available treatment? We develop a framework to guide optimal treatment decisions for a deteriorating chronic disease when treatment technologies are improving over time. We formulate an optimal stopping problem using a discrete-time, finite-horizon Markov decision process. The goal is to maximize a patient's quality-adjusted life expectancy. We derive structural properties of the model and analytically solve a three-period treatment decision problem. We illustrate the model with the example of treatment for chronic hepatitis C virus (HCV). Chronic HCV affects 3-4 million Americans and has been historically difficult to treat, but increasingly effective treatments have been commercialized in the past few years. We show that the optimal treatment decision is more likely to be to accept currently available treatment-despite expectations for future treatment improvement-for patients who have high-risk history, who are older, or who have more comorbidities. Insights from this study can guide HCV treatment decisions for individual patients. More broadly, our model can guide treatment decisions for curable chronic diseases by finding the optimal treatment policy for individual patients in a heterogeneous population.

Optimizing Patient Treatment Decisions in an Era of Rapid Technological Advances: The Case of Hepatitis C Treatment

PubMed Central

Liu, Shan; Goldhaber-Fiebert, Jeremy D.; Brandeau, Margaret L.

2015-01-01

How long should a patient with a treatable chronic disease wait for more effective treatments before accepting the best available treatment? We develop a framework to guide optimal treatment decisions for a deteriorating chronic disease when treatment technologies are improving over time. We formulate an optimal stopping problem using a discrete-time, finite-horizon Markov decision process. The goal is to maximize a patient’s quality-adjusted life expectancy. We derive structural properties of the model and analytically solve a three-period treatment decision problem. We illustrate the model with the example of treatment for chronic hepatitis C virus (HCV). Chronic HCV affects 3–4 million Americans and has been historically difficult to treat, but increasingly effective treatments have been commercialized in the past few years. We show that the optimal treatment decision is more likely to be to accept currently available treatment—despite expectations for future treatment improvement—for patients who have high-risk history, who are older, or who have more comorbidities. Insights from this study can guide HCV treatment decisions for individual patients. More broadly, our model can guide treatment decisions for curable chronic diseases by finding the optimal treatment policy for individual patients in a heterogeneous population. PMID:26188961

Study on Amortization Time and Rationality in Real Estate Investment

NASA Astrophysics Data System (ADS)

Li, Yancang; Zhou, Shujing; Suo, Juanjuan

Amortization time and rationality has been discussed a lot in real estate investment research. As the price of real estate is driven by Geometric Brown Motion (GBM), whether the mortgagors should amortize in advance has become a key issue in amortization time research. This paper presents a new method to solve the problem by using the optimal stopping time theory and option pricing theory models. We discuss the option value in amortizing decision based on this model. A simulation method is used to test this method.

Hybridization of decomposition and local search for multiobjective optimization.

PubMed

Ke, Liangjun; Zhang, Qingfu; Battiti, Roberto

2014-10-01

Combining ideas from evolutionary algorithms, decomposition approaches, and Pareto local search, this paper suggests a simple yet efficient memetic algorithm for combinatorial multiobjective optimization problems: memetic algorithm based on decomposition (MOMAD). It decomposes a combinatorial multiobjective problem into a number of single objective optimization problems using an aggregation method. MOMAD evolves three populations: 1) population P(L) for recording the current solution to each subproblem; 2) population P(P) for storing starting solutions for Pareto local search; and 3) an external population P(E) for maintaining all the nondominated solutions found so far during the search. A problem-specific single objective heuristic can be applied to these subproblems to initialize the three populations. At each generation, a Pareto local search method is first applied to search a neighborhood of each solution in P(P) to update P(L) and P(E). Then a single objective local search is applied to each perturbed solution in P(L) for improving P(L) and P(E), and reinitializing P(P). The procedure is repeated until a stopping condition is met. MOMAD provides a generic hybrid multiobjective algorithmic framework in which problem specific knowledge, well developed single objective local search and heuristics and Pareto local search methods can be hybridized. It is a population based iterative method and thus an anytime algorithm. Extensive experiments have been conducted in this paper to study MOMAD and compare it with some other state-of-the-art algorithms on the multiobjective traveling salesman problem and the multiobjective knapsack problem. The experimental results show that our proposed algorithm outperforms or performs similarly to the best so far heuristics on these two problems.

Optimization of freeform surfaces using intelligent deformation techniques for LED applications

NASA Astrophysics Data System (ADS)

Isaac, Annie Shalom; Neumann, Cornelius

2018-04-01

For many years, optical designers have great interests in designing efficient optimization algorithms to bring significant improvement to their initial design. However, the optimization is limited due to a large number of parameters present in the Non-uniform Rationaly b-Spline Surfaces. This limitation was overcome by an indirect technique known as optimization using freeform deformation (FFD). In this approach, the optical surface is placed inside a cubical grid. The vertices of this grid are modified, which deforms the underlying optical surface during the optimization. One of the challenges in this technique is the selection of appropriate vertices of the cubical grid. This is because these vertices share no relationship with the optical performance. When irrelevant vertices are selected, the computational complexity increases. Moreover, the surfaces created by them are not always feasible to manufacture, which is the same problem faced in any optimization technique while creating freeform surfaces. Therefore, this research addresses these two important issues and provides feasible design techniques to solve them. Finally, the proposed techniques are validated using two different illumination examples: street lighting lens and stop lamp for automobiles.

An Improved Teaching-Learning-Based Optimization with the Social Character of PSO for Global Optimization.

PubMed

Zou, Feng; Chen, Debao; Wang, Jiangtao

2016-01-01

An improved teaching-learning-based optimization with combining of the social character of PSO (TLBO-PSO), which is considering the teacher's behavior influence on the students and the mean grade of the class, is proposed in the paper to find the global solutions of function optimization problems. In this method, the teacher phase of TLBO is modified; the new position of the individual is determined by the old position, the mean position, and the best position of current generation. The method overcomes disadvantage that the evolution of the original TLBO might stop when the mean position of students equals the position of the teacher. To decrease the computation cost of the algorithm, the process of removing the duplicate individual in original TLBO is not adopted in the improved algorithm. Moreover, the probability of local convergence of the improved method is decreased by the mutation operator. The effectiveness of the proposed method is tested on some benchmark functions, and the results are competitive with respect to some other methods.

Solving Single Machine Total Weighted Tardiness Problem with Unequal Release Date Using Neurohybrid Particle Swarm Optimization Approach.

PubMed

Cakar, Tarik; Koker, Rasit

2015-01-01

A particle swarm optimization algorithm (PSO) has been used to solve the single machine total weighted tardiness problem (SMTWT) with unequal release date. To find the best solutions three different solution approaches have been used. To prepare subhybrid solution system, genetic algorithms (GA) and simulated annealing (SA) have been used. In the subhybrid system (GA and SA), GA obtains a solution in any stage, that solution is taken by SA and used as an initial solution. When SA finds better solution than this solution, it stops working and gives this solution to GA again. After GA finishes working the obtained solution is given to PSO. PSO searches for better solution than this solution. Later it again sends the obtained solution to GA. Three different solution systems worked together. Neurohybrid system uses PSO as the main optimizer and SA and GA have been used as local search tools. For each stage, local optimizers are used to perform exploitation to the best particle. In addition to local search tools, neurodominance rule (NDR) has been used to improve performance of last solution of hybrid-PSO system. NDR checked sequential jobs according to total weighted tardiness factor. All system is named as neurohybrid-PSO solution system.

Maximizing algebraic connectivity in air transportation networks

NASA Astrophysics Data System (ADS)

Wei, Peng

In air transportation networks the robustness of a network regarding node and link failures is a key factor for its design. An experiment based on the real air transportation network is performed to show that the algebraic connectivity is a good measure for network robustness. Three optimization problems of algebraic connectivity maximization are then formulated in order to find the most robust network design under different constraints. The algebraic connectivity maximization problem with flight routes addition or deletion is first formulated. Three methods to optimize and analyze the network algebraic connectivity are proposed. The Modified Greedy Perturbation Algorithm (MGP) provides a sub-optimal solution in a fast iterative manner. The Weighted Tabu Search (WTS) is designed to offer a near optimal solution with longer running time. The relaxed semi-definite programming (SDP) is used to set a performance upper bound and three rounding techniques are discussed to find the feasible solution. The simulation results present the trade-off among the three methods. The case study on two air transportation networks of Virgin America and Southwest Airlines show that the developed methods can be applied in real world large scale networks. The algebraic connectivity maximization problem is extended by adding the leg number constraint, which considers the traveler's tolerance for the total connecting stops. The Binary Semi-Definite Programming (BSDP) with cutting plane method provides the optimal solution. The tabu search and 2-opt search heuristics can find the optimal solution in small scale networks and the near optimal solution in large scale networks. The third algebraic connectivity maximization problem with operating cost constraint is formulated. When the total operating cost budget is given, the number of the edges to be added is not fixed. Each edge weight needs to be calculated instead of being pre-determined. It is illustrated that the edge addition and the weight assignment can not be studied separately for the problem with operating cost constraint. Therefore a relaxed SDP method with golden section search is developed to solve both at the same time. The cluster decomposition is utilized to solve large scale networks.

Quantum connectivity optimization algorithms for entanglement source deployment in a quantum multi-hop network

NASA Astrophysics Data System (ADS)

Zou, Zhen-Zhen; Yu, Xu-Tao; Zhang, Zai-Chen

2018-04-01

At first, the entanglement source deployment problem is studied in a quantum multi-hop network, which has a significant influence on quantum connectivity. Two optimization algorithms are introduced with limited entanglement sources in this paper. A deployment algorithm based on node position (DNP) improves connectivity by guaranteeing that all overlapping areas of the distribution ranges of the entanglement sources contain nodes. In addition, a deployment algorithm based on an improved genetic algorithm (DIGA) is implemented by dividing the region into grids. From the simulation results, DNP and DIGA improve quantum connectivity by 213.73% and 248.83% compared to random deployment, respectively, and the latter performs better in terms of connectivity. However, DNP is more flexible and adaptive to change, as it stops running when all nodes are covered.

Start-Stop Moment Optimization of Range Extender and Control Strategy Design for Extended -Range Electric Vehicle

NASA Astrophysics Data System (ADS)

Zhao, Jing-bo; Han, Bing-yuan; Bei, Shao-yi

2017-10-01

Range extender is the core component of E-REV, its start-stop control determines the operation modes of vehicle. This paper based on a certain type of E-REV, researched constant power control strategy of range extender in extended-range model, to target range as constraint condition, combined with different driving cycle conditions, by correcting battery SOC for range extender start-stop moment, optimized the control strategy of range extender, and established the vehicle and range extender start-stop control simulation model. Selected NEDC and UDDS conditions simulation results show that: under certain target mileage, the range extender running time reduced by 37.2% and 28.2% in the NEDC condition, and running time UDDS conditions were reduced by 40.6% and 33.5% in the UDDS condition, reached the purpose of meeting the vehicle mileage and reducing consumption and emission.

FOREX Trades: Can the Takens Algorithm Help to Obtain Steady Profit at Investment Reallocations?

NASA Astrophysics Data System (ADS)

Petrov, V. Yu.; Tribelsky, M. I.

2015-12-01

We report our preliminary results of application of the Takens algorithm to build a FOREX trade strategy, resulting in a steady long-time gain for a trader. The actual historical rates for pair EUR vs. USD are used. The values of various parameters of the problem including the "stop loss" and "take profit" thresholds are optimized to provide the maximal gain during the training period. Then, these values are employed for trades. We have succeeded to get the steady gain, if the spread is neglected. It proves that the FOREX market is predictable.

An overview of the mathematical and statistical analysis component of RICIS

NASA Technical Reports Server (NTRS)

Hallum, Cecil R.

1987-01-01

Mathematical and statistical analysis components of RICIS (Research Institute for Computing and Information Systems) can be used in the following problem areas: (1) quantification and measurement of software reliability; (2) assessment of changes in software reliability over time (reliability growth); (3) analysis of software-failure data; and (4) decision logic for whether to continue or stop testing software. Other areas of interest to NASA/JSC where mathematical and statistical analysis can be successfully employed include: math modeling of physical systems, simulation, statistical data reduction, evaluation methods, optimization, algorithm development, and mathematical methods in signal processing.

Implications of optimization cost for balancing exploration and exploitation in global search and for experimental optimization

NASA Astrophysics Data System (ADS)

Chaudhuri, Anirban

Global optimization based on expensive and time consuming simulations or experiments usually cannot be carried out to convergence, but must be stopped because of time constraints, or because the cost of the additional function evaluations exceeds the benefits of improving the objective(s). This dissertation sets to explore the implications of such budget and time constraints on the balance between exploration and exploitation and the decision of when to stop. Three different aspects are considered in terms of their effects on the balance between exploration and exploitation: 1) history of optimization, 2) fixed evaluation budget, and 3) cost as a part of objective function. To this end, this research develops modifications to the surrogate-based optimization technique, Efficient Global Optimization algorithm, that controls better the balance between exploration and exploitation, and stopping criteria facilitated by these modifications. Then the focus shifts to examining experimental optimization, which shares the issues of cost and time constraints. Through a study on optimization of thrust and power for a small flapping wing for micro air vehicles, important differences and similarities between experimental and simulation-based optimization are identified. The most important difference is that reduction of noise in experiments becomes a major time and cost issue, and a second difference is that parallelism as a way to cut cost is more challenging. The experimental optimization reveals the tendency of the surrogate to display optimistic bias near the surrogate optimum, and this tendency is then verified to also occur in simulation based optimization.

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.

Selected Topics on Decision Making for Electric Vehicles

NASA Astrophysics Data System (ADS)

Sweda, Timothy Matthew

Electric vehicles (EVs) are an attractive alternative to conventional gasoline-powered vehicles due to their lower emissions, fuel costs, and maintenance costs. Range anxiety, or the fear of running out of charge prior to reaching one's destination, remains a significant concern, however. In this dissertation, we address the issue of range anxiety by developing a set of decision support tools for both charging infrastructure providers and EV drivers. In Chapter 1, we present an agent-based information system for identifying patterns in residential EV ownership and driving activities to enable strategic deployment of new charging infrastructure. Driver agents consider their own driving activities within the simulated environment, in addition to the presence of charging stations and the vehicle ownership of others in their social networks, when purchasing a new vehicle. The Chicagoland area is used as a case study to demonstrate the model, and several deployment scenarios are analyzed. In Chapter 2, we address the problem of finding an optimal recharging policy for an EV along a given path. The path consists of a sequence of nodes, each representing a charging station, and the driver must decide where to stop and how much to recharge at each stop. We present efficient algorithms for finding an optimal policy in general instances with deterministic travel costs and homogeneous charging stations, and also for two specialized cases. In addition, we develop two heuristic procedures that we characterize analytically and explore empirically. We further analyze and test our solution methods on model variations that include stochastic travel costs and nonhomogeneous charging stations. In Chapter 3, we study the problem of finding an optimal routing and recharging policy for an electric vehicle in a grid network. Each node in the network represents a charging station and has an associated probability of being available at any point in time or occupied by another vehicle. We present an efficient algorithm for finding an optimal a priori route and recharging policy as well as heuristic methods for finding adaptive policies. We conduct numerical experiments to demonstrate the empirical performance of our solutions.

Putting it All Together: Has One-Stop Shopping Arrived?

ERIC Educational Resources Information Center

Flanagan, Patrick

1997-01-01

Reviews the current state of "one-stop shopping" for telecom services. Discusses regulatory obstacles; administrative problems with single billing; and resistance of telecom providers to change. Concludes that the leading one-stop shopping providers will be individual carriers who offer cost savings. (AEF)

On the sound insulation of acoustic metasurface using a sub-structuring approach

NASA Astrophysics Data System (ADS)

Yu, Xiang; Lu, Zhenbo; Cheng, Li; Cui, Fangsen

2017-08-01

The feasibility of using an acoustic metasurface (AMS) with acoustic stop-band property to realize sound insulation with ventilation function is investigated. An efficient numerical approach is proposed to evaluate its sound insulation performance. The AMS is excited by a reverberant sound source and the standardized sound reduction index (SRI) is numerically investigated. To facilitate the modeling, the coupling between the AMS and the adjacent acoustic fields is formulated using a sub-structuring approach. A modal based formulation is applied to both the source and receiving room, enabling an efficient calculation in the frequency range from 125 Hz to 2000 Hz. The sound pressures and the velocities at the interface are matched by using a transfer function relation based on ;patches;. For illustration purposes, numerical examples are investigated using the proposed approach. The unit cell constituting the AMS is constructed in the shape of a thin acoustic chamber with tailored inner structures, whose stop-band property is numerically analyzed and experimentally demonstrated. The AMS is shown to provide effective sound insulation of over 30 dB in the stop-band frequencies from 600 to 1600 Hz. It is also shown that the proposed approach has the potential to be applied to a broad range of AMS studies and optimization problems.

A new implementation of the programming system for structural synthesis (PROSSS-2)

NASA Technical Reports Server (NTRS)

Rogers, James L., Jr.

1984-01-01

This new implementation of the PROgramming System for Structural Synthesis (PROSSS-2) combines a general-purpose finite element computer program for structural analysis, a state-of-the-art optimization program, and several user-supplied, problem-dependent computer programs. The results are flexibility of the optimization procedure, organization, and versatility of the formulation of constraints and design variables. The analysis-optimization process results in a minimized objective function, typically the mass. The analysis and optimization programs are executed repeatedly by looping through the system until the process is stopped by a user-defined termination criterion. However, some of the analysis, such as model definition, need only be one time and the results are saved for future use. The user must write some small, simple FORTRAN programs to interface between the analysis and optimization programs. One of these programs, the front processor, converts the design variables output from the optimizer into the suitable format for input into the analyzer. Another, the end processor, retrieves the behavior variables and, optionally, their gradients from the analysis program and evaluates the objective function and constraints and optionally their gradients. These quantities are output in a format suitable for input into the optimizer. These user-supplied programs are problem-dependent because they depend primarily upon which finite elements are being used in the model. PROSSS-2 differs from the original PROSSS in that the optimizer and front and end processors have been integrated into the finite element computer program. This was done to reduce the complexity and increase portability of the system, and to take advantage of the data handling features found in the finite element program.

Multicategory nets of single-layer perceptrons: complexity and sample-size issues.

PubMed

Raudys, Sarunas; Kybartas, Rimantas; Zavadskas, Edmundas Kazimieras

2010-05-01

The standard cost function of multicategory single-layer perceptrons (SLPs) does not minimize the classification error rate. In order to reduce classification error, it is necessary to: 1) refuse the traditional cost function, 2) obtain near to optimal pairwise linear classifiers by specially organized SLP training and optimal stopping, and 3) fuse their decisions properly. To obtain better classification in unbalanced training set situations, we introduce the unbalance correcting term. It was found that fusion based on the Kulback-Leibler (K-L) distance and the Wu-Lin-Weng (WLW) method result in approximately the same performance in situations where sample sizes are relatively small. The explanation for this observation is by theoretically known verity that an excessive minimization of inexact criteria becomes harmful at times. Comprehensive comparative investigations of six real-world pattern recognition (PR) problems demonstrated that employment of SLP-based pairwise classifiers is comparable and as often as not outperforming the linear support vector (SV) classifiers in moderate dimensional situations. The colored noise injection used to design pseudovalidation sets proves to be a powerful tool for facilitating finite sample problems in moderate-dimensional PR tasks.

Symmetry breaking in optimal timing of traffic signals on an idealized two-way street.

PubMed

Panaggio, Mark J; Ottino-Löffler, Bertand J; Hu, Peiguang; Abrams, Daniel M

2013-09-01

Simple physical models based on fluid mechanics have long been used to understand the flow of vehicular traffic on freeways; analytically tractable models of flow on an urban grid, however, have not been as extensively explored. In an ideal world, traffic signals would be timed such that consecutive lights turned green just as vehicles arrived, eliminating the need to stop at each block. Unfortunately, this "green-wave" scenario is generally unworkable due to frustration imposed by competing demands of traffic moving in different directions. Until now this has typically been resolved by numerical simulation and optimization. Here, we develop a theory for the flow in an idealized system consisting of a long two-way road with periodic intersections. We show that optimal signal timing can be understood analytically and that there are counterintuitive asymmetric solutions to this signal coordination problem. We further explore how these theoretical solutions degrade as traffic conditions vary and automotive density increases.

Attention control learning in the decision space using state estimation

NASA Astrophysics Data System (ADS)

Gharaee, Zahra; Fatehi, Alireza; Mirian, Maryam S.; Nili Ahmadabadi, Majid

2016-05-01

The main goal of this paper is modelling attention while using it in efficient path planning of mobile robots. The key challenge in concurrently aiming these two goals is how to make an optimal, or near-optimal, decision in spite of time and processing power limitations, which inherently exist in a typical multi-sensor real-world robotic application. To efficiently recognise the environment under these two limitations, attention of an intelligent agent is controlled by employing the reinforcement learning framework. We propose an estimation method using estimated mixture-of-experts task and attention learning in perceptual space. An agent learns how to employ its sensory resources, and when to stop observing, by estimating its perceptual space. In this paper, static estimation of the state space in a learning task problem, which is examined in the WebotsTM simulator, is performed. Simulation results show that a robot learns how to achieve an optimal policy with a controlled cost by estimating the state space instead of continually updating sensory information.

Symmetry breaking in optimal timing of traffic signals on an idealized two-way street

NASA Astrophysics Data System (ADS)

Panaggio, Mark J.; Ottino-Löffler, Bertand J.; Hu, Peiguang; Abrams, Daniel M.

2013-09-01

Simple physical models based on fluid mechanics have long been used to understand the flow of vehicular traffic on freeways; analytically tractable models of flow on an urban grid, however, have not been as extensively explored. In an ideal world, traffic signals would be timed such that consecutive lights turned green just as vehicles arrived, eliminating the need to stop at each block. Unfortunately, this “green-wave” scenario is generally unworkable due to frustration imposed by competing demands of traffic moving in different directions. Until now this has typically been resolved by numerical simulation and optimization. Here, we develop a theory for the flow in an idealized system consisting of a long two-way road with periodic intersections. We show that optimal signal timing can be understood analytically and that there are counterintuitive asymmetric solutions to this signal coordination problem. We further explore how these theoretical solutions degrade as traffic conditions vary and automotive density increases.

Real option valuation of a decremental regulation service provided by electricity storage.

PubMed

Szabó, Dávid Zoltán; Martyr, Randall

2017-08-13

This paper is a quantitative study of a reserve contract for real-time balancing of a power system. Under this contract, the owner of a storage device, such as a battery, helps smooth fluctuations in electricity demand and supply by using the device to increase electricity consumption. The battery owner must be able to provide immediate physical cover, and should therefore have sufficient storage available in the battery before entering the contract. Accordingly, the following problem can be formulated for the battery owner: determine the optimal time to enter the contract and, if necessary, the optimal time to discharge electricity before entering the contract. This problem is formulated as one of optimal stopping, and is solved explicitly in terms of the model parameters and instantaneous values of the power system imbalance. The optimal operational strategies thus obtained ensure that the battery owner has positive expected economic profit from the contract. Furthermore, they provide explicit conditions under which the optimal discharge time is consistent with the overall objective of power system balancing. This paper also carries out a preliminary investigation of the 'lifetime value' aggregated from an infinite sequence of these balancing reserve contracts. This lifetime value, which can be viewed as a single project valuation of the battery, is shown to be positive and bounded. Therefore, in the long run such reserve contracts can be beneficial to commercial operators of electricity storage, while reducing some of the financial and operational risks in power system balancing.This article is part of the themed issue 'Energy management: flexibility, risk and optimization'. © 2017 The Author(s).

Effect of Weight Transfer on a Vehicle's Stopping Distance.

ERIC Educational Resources Information Center

Whitmire, Daniel P.; Alleman, Timothy J.

1979-01-01

An analysis of the minimum stopping distance problem is presented taking into account the effect of weight transfer on nonskidding vehicles and front- or rear-wheels-skidding vehicles. Expressions for the minimum stopping distances are given in terms of vehicle geometry and the coefficients of friction. (Author/BB)

Rational decision-making in inhibitory control.

PubMed

Shenoy, Pradeep; Yu, Angela J

2011-01-01

An important aspect of cognitive flexibility is inhibitory control, the ability to dynamically modify or cancel planned actions in response to changes in the sensory environment or task demands. We formulate a probabilistic, rational decision-making framework for inhibitory control in the stop signal paradigm. Our model posits that subjects maintain a Bayes-optimal, continually updated representation of sensory inputs, and repeatedly assess the relative value of stopping and going on a fine temporal scale, in order to make an optimal decision on when and whether to go on each trial. We further posit that they implement this continual evaluation with respect to a global objective function capturing the various reward and penalties associated with different behavioral outcomes, such as speed and accuracy, or the relative costs of stop errors and go errors. We demonstrate that our rational decision-making model naturally gives rise to basic behavioral characteristics consistently observed for this paradigm, as well as more subtle effects due to contextual factors such as reward contingencies or motivational factors. Furthermore, we show that the classical race model can be seen as a computationally simpler, perhaps neurally plausible, approximation to optimal decision-making. This conceptual link allows us to predict how the parameters of the race model, such as the stopping latency, should change with task parameters and individual experiences/ability.

Rational Decision-Making in Inhibitory Control

PubMed Central

Shenoy, Pradeep; Yu, Angela J.

2011-01-01

An important aspect of cognitive flexibility is inhibitory control, the ability to dynamically modify or cancel planned actions in response to changes in the sensory environment or task demands. We formulate a probabilistic, rational decision-making framework for inhibitory control in the stop signal paradigm. Our model posits that subjects maintain a Bayes-optimal, continually updated representation of sensory inputs, and repeatedly assess the relative value of stopping and going on a fine temporal scale, in order to make an optimal decision on when and whether to go on each trial. We further posit that they implement this continual evaluation with respect to a global objective function capturing the various reward and penalties associated with different behavioral outcomes, such as speed and accuracy, or the relative costs of stop errors and go errors. We demonstrate that our rational decision-making model naturally gives rise to basic behavioral characteristics consistently observed for this paradigm, as well as more subtle effects due to contextual factors such as reward contingencies or motivational factors. Furthermore, we show that the classical race model can be seen as a computationally simpler, perhaps neurally plausible, approximation to optimal decision-making. This conceptual link allows us to predict how the parameters of the race model, such as the stopping latency, should change with task parameters and individual experiences/ability. PMID:21647306

Efficient and Accurate Optimal Linear Phase FIR Filter Design Using Opposition-Based Harmony Search Algorithm

PubMed Central

Saha, S. K.; Dutta, R.; Choudhury, R.; Kar, R.; Mandal, D.; Ghoshal, S. P.

2013-01-01

In this paper, opposition-based harmony search has been applied for the optimal design of linear phase FIR filters. RGA, PSO, and DE have also been adopted for the sake of comparison. The original harmony search algorithm is chosen as the parent one, and opposition-based approach is applied. During the initialization, randomly generated population of solutions is chosen, opposite solutions are also considered, and the fitter one is selected as a priori guess. In harmony memory, each such solution passes through memory consideration rule, pitch adjustment rule, and then opposition-based reinitialization generation jumping, which gives the optimum result corresponding to the least error fitness in multidimensional search space of FIR filter design. Incorporation of different control parameters in the basic HS algorithm results in the balancing of exploration and exploitation of search space. Low pass, high pass, band pass, and band stop FIR filters are designed with the proposed OHS and other aforementioned algorithms individually for comparative optimization performance. A comparison of simulation results reveals the optimization efficacy of the OHS over the other optimization techniques for the solution of the multimodal, nondifferentiable, nonlinear, and constrained FIR filter design problems. PMID:23844390

Efficient and accurate optimal linear phase FIR filter design using opposition-based harmony search algorithm.

PubMed

Saha, S K; Dutta, R; Choudhury, R; Kar, R; Mandal, D; Ghoshal, S P

2013-01-01

In this paper, opposition-based harmony search has been applied for the optimal design of linear phase FIR filters. RGA, PSO, and DE have also been adopted for the sake of comparison. The original harmony search algorithm is chosen as the parent one, and opposition-based approach is applied. During the initialization, randomly generated population of solutions is chosen, opposite solutions are also considered, and the fitter one is selected as a priori guess. In harmony memory, each such solution passes through memory consideration rule, pitch adjustment rule, and then opposition-based reinitialization generation jumping, which gives the optimum result corresponding to the least error fitness in multidimensional search space of FIR filter design. Incorporation of different control parameters in the basic HS algorithm results in the balancing of exploration and exploitation of search space. Low pass, high pass, band pass, and band stop FIR filters are designed with the proposed OHS and other aforementioned algorithms individually for comparative optimization performance. A comparison of simulation results reveals the optimization efficacy of the OHS over the other optimization techniques for the solution of the multimodal, nondifferentiable, nonlinear, and constrained FIR filter design problems.

Pre-treatment patient-specific stopping power by combining list-mode proton radiography and x-ray CT

NASA Astrophysics Data System (ADS)

Collins-Fekete, Charles-Antoine; Brousmiche, Sébastien; Hansen, David C.; Beaulieu, Luc; Seco, Joao

2017-09-01

The relative stopping power (RSP) uncertainty is the largest contributor to the range uncertainty in proton therapy. The purpose of this work was to develop a systematic method that yields accurate and patient-specific RSPs by combining (1) pre-treatment x-ray CT and (2) daily proton radiography of the patient. The method was formulated as a penalized least squares optimization problem (argmin(\\Vert {A}{x}-{b}\\Vert _22 )). The parameter A represents the cumulative path-length crossed by the proton in each material, separated by thresholding on the HU. The material RSPs (water equivalent thickness/physical thickness) are denoted by x. The parameter b is the list-mode proton radiography produced using Geant4 simulations. The problem was solved using a non-negative linear-solver with {x}≥slant0 . A was computed by superposing proton trajectories calculated with a cubic or linear spline approach to the CT. The material’s RSP assigned in Geant4 were used for reference while the clinical HU-RSP calibration curve was used for comparison. The Gammex RMI-467 phantom was first investigated. The standard deviation between the estimated material RSP and the calculated RSP is 0.45%. The robustness of the techniques was then assessed as a function of the number of projections and initial proton energy. Optimization with two initial projections yields precise RSP (⩽1.0%) for 330 MeV protons. 250 MeV protons have shown higher uncertainty (⩽2.0%) due to the loss of precision in the path estimate. Anthropomorphic phantoms of the head, pelvis, and lung were subsequently evaluated. Accurate RSP has been obtained for the head (μ =0.21+/-1.63% ), the lung (μ=0.06+/-0.99% ) and the pelvis (μ=0.90+/-3.87% ). The range precision has been optimized using the calibration curves obtained with the algorithm, yielding a mean R80 difference to the reference of 0.11  ±0.09%, 0.28  ±  0.34% and 0.05 +/- 0.06% in the same order. The solution’s accuracy is limited by the assumed HU/RSP bijection, neglecting inherent degeneracy. The proposed formulation of the problem with prior knowledge x-ray CT demonstrates potential to increase the accuracy of present RSP estimates.

Pre-treatment patient-specific stopping power by combining list-mode proton radiography and x-ray CT.

PubMed

Collins-Fekete, Charles-Antoine; Brousmiche, Sébastien; Hansen, David C; Beaulieu, Luc; Seco, Joao

2017-08-03

The relative stopping power (RSP) uncertainty is the largest contributor to the range uncertainty in proton therapy. The purpose of this work was to develop a systematic method that yields accurate and patient-specific RSPs by combining (1) pre-treatment x-ray CT and (2) daily proton radiography of the patient. The method was formulated as a penalized least squares optimization problem (argmin([Formula: see text])). The parameter A represents the cumulative path-length crossed by the proton in each material, separated by thresholding on the HU. The material RSPs (water equivalent thickness/physical thickness) are denoted by x. The parameter b is the list-mode proton radiography produced using Geant4 simulations. The problem was solved using a non-negative linear-solver with [Formula: see text]. A was computed by superposing proton trajectories calculated with a cubic or linear spline approach to the CT. The material's RSP assigned in Geant4 were used for reference while the clinical HU-RSP calibration curve was used for comparison. The Gammex RMI-467 phantom was first investigated. The standard deviation between the estimated material RSP and the calculated RSP is 0.45%. The robustness of the techniques was then assessed as a function of the number of projections and initial proton energy. Optimization with two initial projections yields precise RSP (⩽1.0%) for 330 MeV protons. 250 MeV protons have shown higher uncertainty (⩽2.0%) due to the loss of precision in the path estimate. Anthropomorphic phantoms of the head, pelvis, and lung were subsequently evaluated. Accurate RSP has been obtained for the head ([Formula: see text]), the lung ([Formula: see text]) and the pelvis ([Formula: see text]). The range precision has been optimized using the calibration curves obtained with the algorithm, yielding a mean [Formula: see text] difference to the reference of 0.11  ±0.09%, 0.28  ±  0.34% and [Formula: see text] in the same order. The solution's accuracy is limited by the assumed HU/RSP bijection, neglecting inherent degeneracy. The proposed formulation of the problem with prior knowledge x-ray CT demonstrates potential to increase the accuracy of present RSP estimates.

Irrelevance of the Power Stroke for the Directionality, Stopping Force, and Optimal Efficiency of Chemically Driven Molecular Machines

PubMed Central

Astumian, R. Dean

2015-01-01

A simple model for a chemically driven molecular walker shows that the elastic energy stored by the molecule and released during the conformational change known as the power-stroke (i.e., the free-energy difference between the pre- and post-power-stroke states) is irrelevant for determining the directionality, stopping force, and efficiency of the motor. Further, the apportionment of the dependence on the externally applied force between the forward and reverse rate constants of the power-stroke (or indeed among all rate constants) is irrelevant for determining the directionality, stopping force, and efficiency of the motor. Arguments based on the principle of microscopic reversibility demonstrate that this result is general for all chemically driven molecular machines, and even more broadly that the relative energies of the states of the motor have no role in determining the directionality, stopping force, or optimal efficiency of the machine. Instead, the directionality, stopping force, and optimal efficiency are determined solely by the relative heights of the energy barriers between the states. Molecular recognition—the ability of a molecular machine to discriminate between substrate and product depending on the state of the machine—is far more important for determining the intrinsic directionality and thermodynamics of chemo-mechanical coupling than are the details of the internal mechanical conformational motions of the machine. In contrast to the conclusions for chemical driving, a power-stroke is very important for the directionality and efficiency of light-driven molecular machines and for molecular machines driven by external modulation of thermodynamic parameters. PMID:25606678

Gaussian-input Gaussian mixture model for representing density maps and atomic models.

PubMed

Kawabata, Takeshi

2018-07-01

A new Gaussian mixture model (GMM) has been developed for better representations of both atomic models and electron microscopy 3D density maps. The standard GMM algorithm employs an EM algorithm to determine the parameters. It accepted a set of 3D points with weights, corresponding to voxel or atomic centers. Although the standard algorithm worked reasonably well; however, it had three problems. First, it ignored the size (voxel width or atomic radius) of the input, and thus it could lead to a GMM with a smaller spread than the input. Second, the algorithm had a singularity problem, as it sometimes stopped the iterative procedure due to a Gaussian function with almost zero variance. Third, a map with a large number of voxels required a long computation time for conversion to a GMM. To solve these problems, we have introduced a Gaussian-input GMM algorithm, which considers the input atoms or voxels as a set of Gaussian functions. The standard EM algorithm of GMM was extended to optimize the new GMM. The new GMM has identical radius of gyration to the input, and does not suddenly stop due to the singularity problem. For fast computation, we have introduced a down-sampled Gaussian functions (DSG) by merging neighboring voxels into an anisotropic Gaussian function. It provides a GMM with thousands of Gaussian functions in a short computation time. We also have introduced a DSG-input GMM: the Gaussian-input GMM with the DSG as the input. This new algorithm is much faster than the standard algorithm. Copyright © 2018 The Author(s). Published by Elsevier Inc. All rights reserved.

Evaluation of undergraduate geologists' problem solving and cognition during field exams using a mixed methods approach

NASA Astrophysics Data System (ADS)

Balliet, Russell N.

Understanding how geologists conduct fieldwork through analysis of problem solving has significant potential impact on field instruction methods. Recent progress has been made in this area but the problem solving behaviors displayed by geologists during fieldwork and the associated underlying cognition remains poorly understood. We present research showing how geology students initiate and develop geologic models as part of the problem solving process. We qualitatively analyzed field notes and interview data from 36 undergraduate geoscientists engaged in field exams while enrolled in a six-week advanced field camp. Eight cognitive frameworks grouped in two broad categories emerged from the data that show how students develop geologic models. Students employ both single and multiple model approaches with varying degrees of success and frequency. The success of any given approach is dependent on the level of students' geologic situational awareness. The development of multiple geologic models leads to a higher rate of success in general, because of the inherent flexibility to accommodate newly collected data. Instructors should continue to teach a multiple model approach until students have the proper geologic skills to ensure a high level of situational awareness and exhibit expert characteristics in the field. In addition, we collected GPS navigation data from students during these field exams in order to understand the relationship between navigation, cognition, and performance. From the analysis of this data we found that over half of all stops are 1-4 minutes long, while very few of students' stops are longer than 9 minutes as the frequency of stops decreases as the duration increases. Regardless of performance or framework, there is an increase in shorter stops and decrease in longer stops from exam one to three, indicating that students changed the way they investigated as the field course progressed. Temporal signatures categorized by performance only show slight differences, but do indicate that there is an increase in very short and longer stops with declining performance. In contrast, higher performance is linked to an increase in short and medium length stops, suggesting that stops 4-14 minutes long are a "sweet spot" for investigation. We speculate that a high percentage of very short stops involve basic field tasks such as locating or data collection and that the decreasing frequency of long stops indicates that there is a relationship between the length of the stop and the complexity of the activities performed during that stop. Students increased experience leads to more efficient stops as they become more competent with field tasks and more versed in the regional geology. The GPS data we collected from these students while they took these notes allowing us to connect the duration of a stop to the types of notes produced during that stop. Note taking species occurred in various frequencies with the most common type being those that focused on lithologic, or lithologic & structural data collection. Stops that produced geologic models, specifically structural models, were much less frequent. The more frequent data collection stops are very short in length (typically 1-4 minutes), while the more complex stops tend to be longer in duration as the note taking gets more complex. Poor performing students had a high proportion of stops where they only collect lithologic data or stops where they don't generate any hypotheses. In contrast, successful students have more structural data and hypothesis generation in their notes. From this analysis we conclude that too much effort spent on stops with only basic data collection leaves less time for the cognitive effort required for model development, eventually leading to poor exam performance. Specifically, a higher frequency of lithologic data stops and lack of structural data leads to the development of incomplete geologic models or lack of comprehensive models altogether. Field instructors often educate their students on good note taking practices and critique the content of their students' field notebooks, and these findings can inform the content of that critique. Students' utilize many different problem solving approaches in the field, but we suggest that instructors continue to advocate a multiple model approach until students are capable of using a single model approach. In this approach students should decrease the number of geologic models they are using as the day progresses to avoid overwhelming themselves with data and hypothesis. Furthermore, field instructors need to work with students on developing their geologic investigation skills further and improving their efficiency. Specifically students need to collect a higher proportion of structural data and develop complete geologic models earlier in the day. (Abstract shortened by UMI.)

Computational Analysis and Low-Scale Constitutive Expression of Laccases Synthetic Genes GlLCC1 from Ganoderma lucidum and POXA 1B from Pleurotus ostreatus in Pichia pastoris

PubMed Central

Reyes-Guzmán, Edwin Alfredo; Poutou-Piñales, Raúl A.; Reyes-Montaño, Edgar Antonio; Pedroza-Rodríguez, Aura Marina; Rodríguez-Vázquez, Refugio; Cardozo-Bernal, Ángela M.

2015-01-01

Lacasses are multicopper oxidases that can catalyze aromatic and non-aromatic compounds concomitantly with reduction of molecular oxygen to water. Fungal laccases have generated a growing interest due to their biotechnological potential applications, such as lignocellulosic material delignification, biopulping and biobleaching, wastewater treatment, and transformation of toxic organic pollutants. In this work we selected fungal genes encoding for laccase enzymes GlLCC1 in Ganoderma lucidum and POXA 1B in Pleurotus ostreatus. These genes were optimized for codon use, GC content, and regions generating secondary structures. Laccase proposed computational models, and their interaction with ABTS [2, 2′-azino-bis(3-ethylbenzothiazoline-6-sulphonic acid)] substrate was evaluated by molecular docking. Synthetic genes were cloned under the control of Pichia pastoris glyceraldehyde-3-phosphate dehydrogenase (GAP) constitutive promoter. P. pastoris X-33 was transformed with pGAPZαA-LaccGluc-Stop and pGAPZαA-LaccPost-Stop constructs. Optimization reduced GC content by 47 and 49% for LaccGluc-Stop and LaccPost-Stop genes, respectively. A codon adaptation index of 0.84 was obtained for both genes. 3D structure analysis using SuperPose revealed LaccGluc-Stop is similar to the laccase crystallographic structure 1GYC of Trametes versicolor. Interaction analysis of the 3D models validated through ABTS, demonstrated higher substrate affinity for LaccPost-Stop, in agreement with our experimental results with enzymatic activities of 451.08 ± 6.46 UL-1 compared to activities of 0.13 ± 0.028 UL-1 for LaccGluc-Stop. This study demonstrated that G. lucidum GlLCC1 and P. ostreatus POXA 1B gene optimization resulted in constitutive gene expression under GAP promoter and α-factor leader in P. pastoris. These are important findings in light of recombinant enzyme expression system utility for environmentally friendly designed expression systems, because of the wide range of substrates that laccases can transform. This contributes to a great gamut of products in diverse settings: industry, clinical and chemical use, and environmental applications. PMID:25611746

Computational analysis and low-scale constitutive expression of laccases synthetic genes GlLCC1 from Ganoderma lucidum and POXA 1B from Pleurotus ostreatus in Pichia pastoris.

PubMed

Rivera-Hoyos, Claudia M; Morales-Álvarez, Edwin David; Poveda-Cuevas, Sergio Alejandro; Reyes-Guzmán, Edwin Alfredo; Poutou-Piñales, Raúl A; Reyes-Montaño, Edgar Antonio; Pedroza-Rodríguez, Aura Marina; Rodríguez-Vázquez, Refugio; Cardozo-Bernal, Ángela M

2015-01-01

Lacasses are multicopper oxidases that can catalyze aromatic and non-aromatic compounds concomitantly with reduction of molecular oxygen to water. Fungal laccases have generated a growing interest due to their biotechnological potential applications, such as lignocellulosic material delignification, biopulping and biobleaching, wastewater treatment, and transformation of toxic organic pollutants. In this work we selected fungal genes encoding for laccase enzymes GlLCC1 in Ganoderma lucidum and POXA 1B in Pleurotus ostreatus. These genes were optimized for codon use, GC content, and regions generating secondary structures. Laccase proposed computational models, and their interaction with ABTS [2, 2'-azino-bis(3-ethylbenzothiazoline-6-sulphonic acid)] substrate was evaluated by molecular docking. Synthetic genes were cloned under the control of Pichia pastoris glyceraldehyde-3-phosphate dehydrogenase (GAP) constitutive promoter. P. pastoris X-33 was transformed with pGAPZαA-LaccGluc-Stop and pGAPZαA-LaccPost-Stop constructs. Optimization reduced GC content by 47 and 49% for LaccGluc-Stop and LaccPost-Stop genes, respectively. A codon adaptation index of 0.84 was obtained for both genes. 3D structure analysis using SuperPose revealed LaccGluc-Stop is similar to the laccase crystallographic structure 1GYC of Trametes versicolor. Interaction analysis of the 3D models validated through ABTS, demonstrated higher substrate affinity for LaccPost-Stop, in agreement with our experimental results with enzymatic activities of 451.08 ± 6.46 UL-1 compared to activities of 0.13 ± 0.028 UL-1 for LaccGluc-Stop. This study demonstrated that G. lucidum GlLCC1 and P. ostreatus POXA 1B gene optimization resulted in constitutive gene expression under GAP promoter and α-factor leader in P. pastoris. These are important findings in light of recombinant enzyme expression system utility for environmentally friendly designed expression systems, because of the wide range of substrates that laccases can transform. This contributes to a great gamut of products in diverse settings: industry, clinical and chemical use, and environmental applications.

Traffic signal coordination and queue management in oversaturated intersection.

DOT National Transportation Integrated Search

2011-03-18

Traffic signal timing optimization when done properly, could significantly improve network : performance by reducing delay, increasing network throughput, reducing number of stops, or : increasing average speed in the network. The optimization can be...

Traffic signal coordination and queue management in oversaturated intersections.

DOT National Transportation Integrated Search

2011-03-18

Traffic signal timing optimization when done properly, could significantly improve network performance by reducing delay, increasing network throughput, reducing number of stops, or increasing average speed in the network. The optimization can become...

Brazil may stop HIV drug access; problems also reported from Argentina.

PubMed

1999-09-03

Brazil's financial crisis is threatening its HIV treatment programs, as well as programs for other diseases such as hemophilia, tuberculosis, diabetes, and malaria. The government is expected to stop providing antiretroviral therapy through the public health system in October. Meanwhile, the Argentine government stopped providing antiretroviral medications in August. Drug recycling programs are also discussed. Contact information is provided.

Performance Analysis of Stop-Skipping Scheduling Plans in Rail Transit under Time-Dependent Demand

PubMed Central

Cao, Zhichao; Yuan, Zhenzhou; Zhang, Silin

2016-01-01

Stop-skipping is a key method for alleviating congestion in rail transit, where schedules are sometimes difficult to implement. Several mechanisms have been proposed and analyzed in the literature, but very few performance comparisons are available. This study formulated train choice behavior estimation into the model considering passengers’ perception. If a passenger’s train path can be identified, this information would be useful for improving the stop-skipping schedule service. Multi-performance is a key characteristic of our proposed five stop-skipping schedules, but quantified analysis can be used to illustrate the different effects of well-known deterministic and stochastic forms. Problems in the novel category of forms were justified in the context of a single line rather than transit network. We analyzed four deterministic forms based on the well-known A/B stop-skipping operating strategy. A stochastic form was innovatively modeled as a binary integer programming problem. We present a performance analysis of our proposed model to demonstrate that stop-skipping can feasibly be used to improve the service of passengers and enhance the elasticity of train operations under demand variations along with an explicit parametric discussion. PMID:27420087

Performance Analysis of Stop-Skipping Scheduling Plans in Rail Transit under Time-Dependent Demand.

PubMed

Cao, Zhichao; Yuan, Zhenzhou; Zhang, Silin

2016-07-13

Stop-skipping is a key method for alleviating congestion in rail transit, where schedules are sometimes difficult to implement. Several mechanisms have been proposed and analyzed in the literature, but very few performance comparisons are available. This study formulated train choice behavior estimation into the model considering passengers' perception. If a passenger's train path can be identified, this information would be useful for improving the stop-skipping schedule service. Multi-performance is a key characteristic of our proposed five stop-skipping schedules, but quantified analysis can be used to illustrate the different effects of well-known deterministic and stochastic forms. Problems in the novel category of forms were justified in the context of a single line rather than transit network. We analyzed four deterministic forms based on the well-known A/B stop-skipping operating strategy. A stochastic form was innovatively modeled as a binary integer programming problem. We present a performance analysis of our proposed model to demonstrate that stop-skipping can feasibly be used to improve the service of passengers and enhance the elasticity of train operations under demand variations along with an explicit parametric discussion.

A Pause-then-Cancel model of stopping: evidence from basal ganglia neurophysiology.

PubMed

Schmidt, Robert; Berke, Joshua D

2017-04-19

Many studies have implicated the basal ganglia in the suppression of action impulses ('stopping'). Here, we discuss recent neurophysiological evidence that distinct hypothesized processes involved in action preparation and cancellation can be mapped onto distinct basal ganglia cell types and pathways. We examine how movement-related activity in the striatum is related to a 'Go' process and how going may be modulated by brief epochs of beta oscillations. We then describe how, rather than a unitary 'Stop' process, there appear to be separate, complementary 'Pause' and 'Cancel' mechanisms. We discuss the implications of these stopping subprocesses for the interpretation of the stop-signal reaction time-in particular, some activity that seems too slow to causally contribute to stopping when assuming a single Stop processes may actually be fast enough under a Pause-then-Cancel model. Finally, we suggest that combining complementary neural mechanisms that emphasize speed or accuracy respectively may serve more generally to optimize speed-accuracy trade-offs.This article is part of the themed issue 'Movement suppression: brain mechanisms for stopping and stillness'. © 2017 The Author(s).

Acquisition of initial /s/-stop and stop-/s/ sequences in Greek

PubMed Central

Syrika, Asimina; Nicolaidis, Katerina; Edwards, Jan; Beckman, Mary E.

2010-01-01

Previous work on children’s acquisition of complex sequences points to a tendency for affricates to be acquired before clusters, but there is no clear evidence of a difference in order of acquisition between clusters with /s/ that violate the Sonority Sequencing Principle (SSP), such as /s/ followed by stop in onset position, and other clusters that obey the SSP. One problem with studies that have compared the acquisition of SSP-obeying and SSP-violating clusters is that the component sounds in the two types of sequences were different. This paper examines the acquisition of initial /s/-stop and stop-/s/ sequences by sixty Greek children aged 2 through 5 years. Results showed greater accuracy for the /s/-stop relative to the stop-/s/ sequences, but no difference in accuracy between /ts/, which is usually analyzed as an affricate in Greek, and the other stop-/s/ sequences. Moreover, errors for the /s/-stop sequences and /ts/ primarily involved stop substitutions, whereas errors for /ps/ and /ks/ were more variable and often involved fricative substitutions, a pattern which may have a perceptual explanation. Finally, /ts/ showed a distinct temporal pattern relative to the stop-/s/ clusters /ps/ and /ks/, similarly to what has been reported for productions of Greek adults. PMID:22070044

STOP Analysis and Optimization of a Very-Low-Distortion Space Instrument: HST WFC3 Case Study

NASA Technical Reports Server (NTRS)

Kunt, Cengiz; Broduer, Steve (Technical Monitor)

2001-01-01

New generation optical instruments with very demanding stability requirements are being proposed and developed for space applications. STOP (Structural-Thermal-Optical Performance) analysis and optimization is crucial in meeting the very tight distortion budgets of these instruments. This presentation outlines STOP analysis and optimization approach in the context of WFC3 (Wide-Field Camera 3), which is a radial instrument designed to replace the Wide-Field Planetary Camera 2 (WFPC2) of the Hubble Space Telescope (HST). WFC3 houses two separate channels, UVIS and IR, and will have greater throughput and sensitivity than WFPC2. WFC3 line-of-sight alignment budget for the UVIS and IR channels are as small as 10 and 20 milli-arcsec, respectively. Its optical bench is the most critical subsystem effecting the optical stability of WFC3 hence our effort concentrates on the design and analysis of the bench and its interfaces. Structural analysis has accompanied the mechanical design of the bench since the initial concept study. A high fidelity structural Finite Element Model (FEM) of the bench has been developed and used for minimizing its thermally induced distortions as well as sizing it to meet the stiffness and strength requirements of a Shuttle launch. The bench is a composite honeycomb panel box structure with a very low planar Coefficient of Thermal Expansion (CTE) of approximately 0.1 ppm/C. Optic components are mounted to super-INVAR inserts bonded into the panels. The bench is kinematically supported on three HST latches via interface struts, which are tailored to exhibit negative CTE to cancel out the thermal motions of the latches. The interface struts also incorporate flexure elements to minimize the mechanical distortions coming into the bench from its enclosure. Bench FEM is coupled with the enclosure FEM to quantify these effects. Short term or on-orbit STOP analysis includes distortion due to the temperature variations of the bench, the struts, and the enclosure. Long term or ground-to-orbit STOP analysis includes distortional effects of gravity release, desorption, and assembly in addition to the ground-to-orbit temperature variations. A rigorous testing program has been implemented for verifying the material properties and the analysis predictions. STOP analysis results demonstrate that both the short-term and the long-term alignment budgets will be met. Presentation will cover design and analysis details that are critical to a successful implementation of the STOP analysis and optimization process.

Problems in modernization of automation systems at coal preparation plants

NASA Astrophysics Data System (ADS)

Myshlyaev, L. P.; Lyakhovets, M. V.; Venger, K. G.; Leontiev, I. A.; Makarov, G. V.; Salamatin, A. S.

2018-05-01

The factors influencing the process of modernization (reconstruction) of the automation systems at coal preparation plants are described. Problems such as heterogeneity of existing and developed systems, planning of reconstruction of a technological complex without taking into account modernization of automated systems, commissioning without stopping the existing technological complex, as well as problems of conducting procurement procedures are discussed. The option of stage-by-stage start-up and adjustment works in the conditions of modernization of systems without long stops of the process equipment is offered.

Optimal Control of Connected and Automated Vehicles at Roundabouts

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

Zhao, Liuhui; Malikopoulos, Andreas; Rios-Torres, Jackeline

Connectivity and automation in vehicles provide the most intriguing opportunity for enabling users to better monitor transportation network conditions and make better operating decisions to improve safety and reduce pollution, energy consumption, and travel delays. This study investigates the implications of optimally coordinating vehicles that are wirelessly connected to each other and to an infrastructure in roundabouts to achieve a smooth traffic flow without stop-and-go driving. We apply an optimization framework and an analytical solution that allows optimal coordination of vehicles for merging in such traffic scenario. The effectiveness of the efficiency of the proposed approach is validated through simulationmore » and it is shown that coordination of vehicles can reduce total travel time by 3~49% and fuel consumption by 2~27% with respect to different traffic levels. In addition, network throughput is improved by up to 25% due to elimination of stop-and-go driving behavior.« less

Tobacco cessation intervention: how to communicate with tobacco using patients.

PubMed

Stafne, E E; Bakdash, B

2000-11-15

Tobacco use is a dental as well as a medical problem. When dental team members assist their patients in becoming tobacco free, they are eliminating a causative/contributing factor for a number of oral conditions including cancer and periodontal diseases. Studies have shown that brief tobacco use cessation interventions in the dental office can be effective in helping many patients to stop using tobacco. Interventions can be optimized through understanding the stage of change the tobacco user is in when an intervention is attempted. Only then can we use the appropriate intervention at the right time. This article discusses and demonstrates a protocol for tobacco cessation interventions that can be used in the dental office.

Ringfield lithographic camera

DOEpatents

Sweatt, W.C.

1998-09-08

A projection lithography camera is presented with a wide ringfield optimized so as to make efficient use of extreme ultraviolet radiation from a large area radiation source (e.g., D{sub source} {approx_equal} 0.5 mm). The camera comprises four aspheric mirrors optically arranged on a common axis of symmetry. The camera includes an aperture stop that is accessible through a plurality of partial aperture stops to synthesize the theoretical aperture stop. Radiation from a mask is focused to form a reduced image on a wafer, relative to the mask, by reflection from the four aspheric mirrors. 11 figs.

Optimizing Intratheater Military Airlift in Iraq and Afghanistan

DTIC Science & Technology

2013-01-01

2013 Page 37 Data lenr number of stops on route r aðr ; sÞ airfield at stop number s on route r, where 1# s # lenr carryaiaj cr amount of cargo c on...comes after, and within maxloadhops of, stop s on route r: 1# s , s## lenr , s#2 s #maxloadhops Variables SELECTr integer number of times airplane...so , lenr ; c (4) X r; s#: 1, s## lenr ; aðr; s#Þ5aj SELECTr # landingaj "aj 2 A (5) The objective function (1) calculates the priority-weighted value

Acquisition of initial /s/-stop and stop-/s/sequences in Greek.

PubMed

Syrika, Asimina; Nicolaidis, Katerina; Edwards, Jan; Beckman, Mary E

2011-09-01

Previous work on children's acquisition of complex sequences points to a tendency for affricates to be acquired before clusters, but there is no clear evidence of a difference in order of acquisition between clusters with /s/ that violate the Sonority Sequencing Principle (SSP), such as /s/ followed by stop in onset position, and other clusters that obey the SSP. One problem with studies that have compared the acquisition of SSP-obeying and SSP-violating clusters is that the component sounds in the two types of sequences were different.This paper examines the acquisition of initial /s/-stop and stop-/s/ sequences by sixty Greek children aged 2 through 5 years. Results showed greater accuracy for the /s/-stop relative to the stop-/s/ sequences, but no difference in accuracy between /ts/, which is usually analyzed as an affricate in Greek, and the other stop-/s/ sequences. Moreover, errors for the /s/-stop sequences and /ts/ primarily involved stop substitutions, whereas errors for /ps/ and /ks/ were more variable and often involved fricative substitutions, a pattern which may have a perceptual explanation. Finally, /ts/ showed a distinct temporal pattern relative to the stop-/s/ clusters /ps/ and /ks/, similar to what has been reported for productions of Greek adults.

Termination of short term melatonin treatment in children with delayed Dim Light Melatonin Onset: effects on sleep, health, behavior problems, and parenting stress.

PubMed

van Maanen, Annette; Meijer, Anne Marie; Smits, Marcel G; Oort, Frans J

2011-10-01

To investigate the effects of termination of short term melatonin treatment on sleep, health, behavior, and parenting stress in children with delayed Dim Light Melatonin Onset. Forty-one children (24 boys, 17 girls; mean age=9.43 years) entered melatonin treatment for 3 weeks and then discontinued treatment by first taking a half dose for 1 week and then stopping completely for another week. Sleep was measured with sleep diaries filled in by parents and with actometers worn by children. Analyses were conducted with linear mixed models. Sleep latency was longer during the stop week compared to the treatment weeks. Sleep start was later and actual sleep time was shorter during the half dose and stop weeks compared to the treatment weeks. Sleep efficiency deteriorated in the stop week. Dim Light Melatonin Onset was earlier after treatment, but this effect disappeared after the stop week. In addition to the effects on sleep, results from questionnaires completed by parents showed that melatonin treatment also had positive effects on children's health and behavior problems and parenting stress. While health deteriorated after treatment discontinuation, the effects on behavior problems and parenting stress remained. Behavior problems at baseline did not influence the effect of melatonin treatment. This study showed that complete termination of treatment after 4 weeks of melatonin use was too early. However, clinicians may advise a lower dose after a successful treatment trial of several weeks. Copyright © 2011 Elsevier B.V. All rights reserved.

Optimal Design of a Traveling-Wave Kinetic Inductance Amplifier Operated in Three-Wave Mixing Mode

NASA Astrophysics Data System (ADS)

Erickson, Robert; Bal, Mustafa; Ku, Ksiang-Sheng; Wu, Xian; Pappas, David

In the presence of a DC bias, an injected pump, of frequency fP, and a signal, of frequency fS, undergo parametric three-way mixing (3WM) within a traveling-wave kinetic inductance (KIT) amplifier, producing an idler product of frequency fI =fP -fS . Periodic frequency stops are engineered into the coplanar waveguide of the device to enhance signal amplification. With fP placed just above the first frequency stop gap, 3WM broadband signal gain is achieved with maximum gain at fS =fP / 2 . Within a theory of the dispersion of traveling waves in the presence of these engineered loadings, which accounts for this broadband signal gain, we show how an optimal frequency-stop design may be constructed to achieve maximum signal amplification. The optimization approach we describe can be applied to the design of other nonlinear traveling-wave parametric amplifiers. This work was supported by the Army Research Office and the Laboratory for Physical Sciences under EAO221146, EAO241777, and the NIST Quantum Initiative. RPE acknowledges Grant 60NANB14D024 from the US Department of Commerce, NIST.

Online Optimization Method for Operation of Generators in a Micro Grid

NASA Astrophysics Data System (ADS)

Hayashi, Yasuhiro; Miyamoto, Hideki; Matsuki, Junya; Iizuka, Toshio; Azuma, Hitoshi

Recently a lot of studies and developments about distributed generator such as photovoltaic generation system, wind turbine generation system and fuel cell have been performed under the background of the global environment issues and deregulation of the electricity market, and the technique of these distributed generators have progressed. Especially, micro grid which consists of several distributed generators, loads and storage battery is expected as one of the new operation system of distributed generator. However, since precipitous load fluctuation occurs in micro grid for the reason of its smaller capacity compared with conventional power system, high-accuracy load forecasting and control scheme to balance of supply and demand are needed. Namely, it is necessary to improve the precision of operation in micro grid by observing load fluctuation and correcting start-stop schedule and output of generators online. But it is not easy to determine the operation schedule of each generator in short time, because the problem to determine start-up, shut-down and output of each generator in micro grid is a mixed integer programming problem. In this paper, the authors propose an online optimization method for the optimal operation schedule of generators in micro grid. The proposed method is based on enumeration method and particle swarm optimization (PSO). In the proposed method, after picking up all unit commitment patterns of each generators satisfied with minimum up time and minimum down time constraint by using enumeration method, optimal schedule and output of generators are determined under the other operational constraints by using PSO. Numerical simulation is carried out for a micro grid model with five generators and photovoltaic generation system in order to examine the validity of the proposed method.

Dissociable brain mechanisms underlying the conscious and unconscious control of behavior.

PubMed

van Gaal, Simon; Lamme, Victor A F; Fahrenfort, Johannes J; Ridderinkhof, K Richard

2011-01-01

Cognitive control allows humans to overrule and inhibit habitual responses to optimize performance in challenging situations. Contradicting traditional views, recent studies suggest that cognitive control processes can be initiated unconsciously. To further capture the relation between consciousness and cognitive control, we studied the dynamics of inhibitory control processes when triggered consciously versus unconsciously in a modified version of the stop task. Attempts to inhibit an imminent response were often successful after unmasked (visible) stop signals. Masked (invisible) stop signals rarely succeeded in instigating overt inhibition but did trigger slowing down of response times. Masked stop signals elicited a sequence of distinct ERP components that were also observed on unmasked stop signals. The N2 component correlated with the efficiency of inhibitory control when elicited by unmasked stop signals and with the magnitude of slowdown when elicited by masked stop signals. Thus, the N2 likely reflects the initiation of inhibitory control, irrespective of conscious awareness. The P3 component was much reduced in amplitude and duration on masked versus unmasked stop trials. These patterns of differences and similarities between conscious and unconscious cognitive control processes are discussed in a framework that differentiates between feedforward and feedback connections in yielding conscious experience.

Optimization of the operating conditions of gas-turbine power stations considering the effect of equipment deterioration

NASA Astrophysics Data System (ADS)

Aminov, R. Z.; Kozhevnikov, A. I.

2017-10-01

In recent years in most power systems all over the world, a trend towards the growing nonuniformity of energy consumption and generation schedules has been observed. The increase in the portion of renewable energy sources is one of the important challenges for many countries. The ill-predictable character of such energy sources necessitates a search for practical solutions. Presently, the most efficient method for compensating for nonuniform generation of the electric power by the renewable energy sources—predominantly by the wind and solar energy—is generation of power at conventional fossil-fuel-fired power stations. In Russia, this problem is caused by the increasing portion in the generating capacity structure of the nuclear power stations, which are most efficient when operating under basic conditions. Introduction of hydropower and pumped storage hydroelectric power plants and other energy-storage technologies does not cover the demand for load-following power capacities. Owing to a simple design, low construction costs, and a sufficiently high economic efficiency, gas turbine plants (GTPs) prove to be the most suitable for covering the nonuniform electric-demand schedules. However, when the gas turbines are operated under varying duty conditions, the lifetime of the primary thermostressed components is considerably reduced and, consequently, the repair costs increase. A method is proposed for determination of the total operating costs considering the deterioration of the gas turbine equipment under varying duty and start-stop conditions. A methodology for optimization of the loading modes for the gas turbine equipment is developed. The consideration of the lifetime component allows varying the optimal operating conditions and, in some cases, rejecting short-time stops of the gas turbine plants. The calculations performed in a wide range of varying fuel prices and capital investments per gas turbine equipment unit show that the economic effectiveness can be increased by 5-15% by varying the operating conditions and switching to the optimal operating modes. Consequently, irrespective of the fuel price, the application of the proposed method results in selection of the most beneficial operating conditions. Consideration of the lifetime expenditure included in the optimization criterion enables enhancement of the operating efficiency.

Ringfield lithographic camera

DOEpatents

Sweatt, William C.

1998-01-01

A projection lithography camera is presented with a wide ringfield optimized so as to make efficient use of extreme ultraviolet radiation from a large area radiation source (e.g., D.sub.source .apprxeq.0.5 mm). The camera comprises four aspheric mirrors optically arranged on a common axis of symmetry with an increased etendue for the camera system. The camera includes an aperture stop that is accessible through a plurality of partial aperture stops to synthesize the theoretical aperture stop. Radiation from a mask is focused to form a reduced image on a wafer, relative to the mask, by reflection from the four aspheric mirrors.

An efficient adaptive sampling strategy for global surrogate modeling with applications in multiphase flow simulation

NASA Astrophysics Data System (ADS)

Mo, S.; Lu, D.; Shi, X.; Zhang, G.; Ye, M.; Wu, J.

2016-12-01

Surrogate models have shown remarkable computational efficiency in hydrological simulations involving design space exploration, sensitivity analysis, uncertainty quantification, etc. The central task of constructing a global surrogate models is to achieve a prescribed approximation accuracy with as few original model executions as possible, which requires a good design strategy to optimize the distribution of data points in the parameter domains and an effective stopping criterion to automatically terminate the design process when desired approximation accuracy is achieved. This study proposes a novel adaptive sampling strategy, which starts from a small number of initial samples and adaptively selects additional samples by balancing the collection in unexplored regions and refinement in interesting areas. We define an efficient and effective evaluation metric basing on Taylor expansion to select the most promising potential samples from candidate points, and propose a robust stopping criterion basing on the approximation accuracy at new points to guarantee the achievement of desired accuracy. The numerical results of several benchmark analytical functions indicate that the proposed approach is more computationally efficient and robust than the widely used maximin distance design and two other well-known adaptive sampling strategies. The application to two complicated multiphase flow problems further demonstrates the efficiency and effectiveness of our method in constructing global surrogate models for high-dimensional and highly nonlinear problems. Acknowledgements: This work was financially supported by the National Nature Science Foundation of China grants No. 41030746 and 41172206.

Association of Subway Driver's Depressive Symptoms and Experience of Work-Related Problems.

PubMed

Jo, Sun-Jin; Yim, Hyeon Woo; Kim, Hyoung-Ryoul; Lee, Kang Sook; Park, Jong-Ik; Chang, Sung Man

2010-12-03

Subway drivers experience various types of work-related problems during their driving, and those experiences can act as risk factors for depressive symptoms. This study was conducted to investigate the association between work-related problems and subway driver's depressive symptoms. We recruited all of the 961 current subway drivers of a subway company located in Seoul, South Korea and conducted a survey of their socio-demographic and vocational characteristics, hospital visits as an outpatient or inpatient, and work-related problem experiences during the last year. Work-related problems included an accident resulting in death or injury, a conflict with a customer, a sudden stop from an emergency bell, or a near accident. Depressive symptoms were measured with the Center for Epidemiologic Studies-Depression (CES-D) instrument. The survey was performed using a self-report questionnaire from April 16 to July 13, 2007. The data of 827 drivers (86.2%) were analyzed. Experience of a conflict with a passenger (p=0.011), a sudden stop from an emergency bell (p=0.001), or a near accident (p=0.001) increased the prevalence of depressive symptoms among subway drivers. A multiple logistic regression analysis revealed that a sudden stop from an emergency bell increased the risk of depressive symptoms significantly (OR=2.59, p=0.026). Near accidents were marginally associated with a higher risk for depressive symptoms (OR=1.62, p=0.062). The experience of a sudden stop from an emergency bell increased subway driver's depressive symptoms, and near accidents may increase the risk of depressive symptoms. Therefore, interventions for the drivers who had experienced these work-related problems are needed.

The Care and Feeding of Stop-Outs

ERIC Educational Resources Information Center

Kesselman, Judi R.

1976-01-01

Student practices and administrative problems related to stopping out of college (leaving school to work and/or travel and then returning to complete one's education) are examined on the basis of interviews with stopouts and data from 100 representative 2- and 4-year colleges. (JT)

Do ICBMs Have a Future

DTIC Science & Technology

2015-06-01

21st century signaled the beginning of a cultural shift towards stopping terror organizations. The initial problem was how to stop the attacks from...hardly deter militias such as the Taliban, or terrorists such as those who attacked New York, Washington, London, Madrid, and Mumbai in recent

Reactive Collision Avoidance Algorithm

NASA Technical Reports Server (NTRS)

Scharf, Daniel; Acikmese, Behcet; Ploen, Scott; Hadaegh, Fred

2010-01-01

The reactive collision avoidance (RCA) algorithm allows a spacecraft to find a fuel-optimal trajectory for avoiding an arbitrary number of colliding spacecraft in real time while accounting for acceleration limits. In addition to spacecraft, the technology can be used for vehicles that can accelerate in any direction, such as helicopters and submersibles. In contrast to existing, passive algorithms that simultaneously design trajectories for a cluster of vehicles working to achieve a common goal, RCA is implemented onboard spacecraft only when an imminent collision is detected, and then plans a collision avoidance maneuver for only that host vehicle, thus preventing a collision in an off-nominal situation for which passive algorithms cannot. An example scenario for such a situation might be when a spacecraft in the cluster is approaching another one, but enters safe mode and begins to drift. Functionally, the RCA detects colliding spacecraft, plans an evasion trajectory by solving the Evasion Trajectory Problem (ETP), and then recovers after the collision is avoided. A direct optimization approach was used to develop the algorithm so it can run in real time. In this innovation, a parameterized class of avoidance trajectories is specified, and then the optimal trajectory is found by searching over the parameters. The class of trajectories is selected as bang-off-bang as motivated by optimal control theory. That is, an avoiding spacecraft first applies full acceleration in a constant direction, then coasts, and finally applies full acceleration to stop. The parameter optimization problem can be solved offline and stored as a look-up table of values. Using a look-up table allows the algorithm to run in real time. Given a colliding spacecraft, the properties of the collision geometry serve as indices of the look-up table that gives the optimal trajectory. For multiple colliding spacecraft, the set of trajectories that avoid all spacecraft is rapidly searched on-line. The optimal avoidance trajectory is implemented as a receding-horizon model predictive control law. Therefore, at each time step, the optimal avoidance trajectory is found and the first time step of its acceleration is applied. At the next time step of the control computer, the problem is re-solved and the new first time step is again applied. This continual updating allows the RCA algorithm to adapt to a colliding spacecraft that is making erratic course changes.

Studies of HZE particle interactions and transport for space radiation protection purposes

NASA Technical Reports Server (NTRS)

Townsend, Lawrence W.; Wilson, John W.; Schimmerling, Walter; Wong, Mervyn

1987-01-01

The main emphasis is on developing general methods for accurately predicting high-energy heavy ion (HZE) particle interactions and transport for use by researchers in mission planning studies, in evaluating astronaut self-shielding factors, and in spacecraft shield design and optimization studies. The two research tasks are: (1) to develop computationally fast and accurate solutions to the Boltzmann (transport) equation; and (2) to develop accurate HZE interaction models, from fundamental physical considerations, for use as inputs into these transport codes. Accurate solutions to the HZE transport problem have been formulated through a combination of analytical and numerical techniques. In addition, theoretical models for the input interaction parameters are under development: stopping powers, nuclear absorption cross sections, and fragmentation parameters.

Ranking of stopping criteria for log domain diffeomorphic demons application in clinical radiation therapy.

PubMed

Peroni, M; Golland, P; Sharp, G C; Baroni, G

2011-01-01

Deformable Image Registration is a complex optimization algorithm with the goal of modeling a non-rigid transformation between two images. A crucial issue in this field is guaranteeing the user a robust but computationally reasonable algorithm. We rank the performances of four stopping criteria and six stopping value computation strategies for a log domain deformable registration. The stopping criteria we test are: (a) velocity field update magnitude, (b) vector field Jacobian, (c) mean squared error, and (d) harmonic energy. Experiments demonstrate that comparing the metric value over the last three iterations with the metric minimum of between four and six previous iterations is a robust and appropriate strategy. The harmonic energy and vector field update magnitude metrics give the best results in terms of robustness and speed of convergence.

Parallel Hybrid Vehicle Optimal Storage System

NASA Technical Reports Server (NTRS)

Bloomfield, Aaron P.

2009-01-01

A paper reports the results of a Hybrid Diesel Vehicle Project focused on a parallel hybrid configuration suitable for diesel-powered, medium-sized, commercial vehicles commonly used for parcel delivery and shuttle buses, as the missions of these types of vehicles require frequent stops. During these stops, electric hybridization can effectively recover the vehicle's kinetic energy during the deceleration, store it onboard, and then use that energy to assist in the subsequent acceleration.

Long-haul truck drivers want healthful meal options at truck-stop restaurants.

PubMed

Whitfield Jacobson, Pamela J; Prawitz, Aimee D; Lukaszuk, Judith M

2007-12-01

Long-haul truckers are confined, by parking regulations and other constraints, to dining at truck-stop restaurants. Objectives were to (a) compare truckers' anthropometrics with recommended guidelines; and (b) assess eating/exercise habits, importance of healthful food choices, and attitudes about restaurants' provision of healthful options. Hypotheses were: (a) overweight/obese drivers will place less importance on healthful food choices than will drivers of optimal weight; (b) importance of healthful food choices and attitudes about their provision will be positively correlated. Questionnaires included Food Choices Index, Nutrition Attitude Survey, and demographic information; bioelectrical impedance assessed weight, body fat, and body mass index. Subjects (n=92) were truckers at a Midwestern truck-stop restaurant; 79 were overweight, 52 were obese. Mean rating of importance of healthful choices was above average. There was no difference in importance of healthful food choices for overweight/obese and optimal weight drivers, t(89)=-1.312; P=0.19. Drivers placing more importance on healthful food choices had more positive attitudes about restaurants' provision of such options, r(90)=0.74, P<0.001. Overall, drivers indicated they would choose healthful foods if available and appetizing. Registered dietitian-directed wellness programs that include education, support, and cooperation of truck-stop restaurants are critical to reduce obesity and risk of disease in this population.

A Pause-then-Cancel model of stopping: evidence from basal ganglia neurophysiology

PubMed Central

Berke, Joshua D.

2017-01-01

Many studies have implicated the basal ganglia in the suppression of action impulses (‘stopping’). Here, we discuss recent neurophysiological evidence that distinct hypothesized processes involved in action preparation and cancellation can be mapped onto distinct basal ganglia cell types and pathways. We examine how movement-related activity in the striatum is related to a ‘Go’ process and how going may be modulated by brief epochs of beta oscillations. We then describe how, rather than a unitary ‘Stop’ process, there appear to be separate, complementary ‘Pause’ and ‘Cancel’ mechanisms. We discuss the implications of these stopping subprocesses for the interpretation of the stop-signal reaction time—in particular, some activity that seems too slow to causally contribute to stopping when assuming a single Stop processes may actually be fast enough under a Pause-then-Cancel model. Finally, we suggest that combining complementary neural mechanisms that emphasize speed or accuracy respectively may serve more generally to optimize speed–accuracy trade-offs. This article is part of the themed issue ‘Movement suppression: brain mechanisms for stopping and stillness’. PMID:28242736

A movable stop mechanism for the SIRE telescope

NASA Technical Reports Server (NTRS)

Tweedt, R. E.; Poulsen, R. N.

1982-01-01

A movable stop mechanism (MSM) designed to activate flaps that change the size and shape of a telescope aperture stop on command is described. Operating at the cryogenic temperatures of the optical system, it consists primarily of a rotary solenoid that drives (activates) dual four-bar linkages in synchronism that in turn rotate the butterfly flaps into position. The design, performance characteristics, and testing of this mechanism are discussed. Specific problems that occurred during testing and the solutions that were adopted are also described.

Cat Swarm Optimization algorithm for optimal linear phase FIR filter design.

PubMed

Saha, Suman Kumar; Ghoshal, Sakti Prasad; Kar, Rajib; Mandal, Durbadal

2013-11-01

In this paper a new meta-heuristic search method, called Cat Swarm Optimization (CSO) algorithm is applied to determine the best optimal impulse response coefficients of FIR low pass, high pass, band pass and band stop filters, trying to meet the respective ideal frequency response characteristics. CSO is generated by observing the behaviour of cats and composed of two sub-models. In CSO, one can decide how many cats are used in the iteration. Every cat has its' own position composed of M dimensions, velocities for each dimension, a fitness value which represents the accommodation of the cat to the fitness function, and a flag to identify whether the cat is in seeking mode or tracing mode. The final solution would be the best position of one of the cats. CSO keeps the best solution until it reaches the end of the iteration. The results of the proposed CSO based approach have been compared to those of other well-known optimization methods such as Real Coded Genetic Algorithm (RGA), standard Particle Swarm Optimization (PSO) and Differential Evolution (DE). The CSO based results confirm the superiority of the proposed CSO for solving FIR filter design problems. The performances of the CSO based designed FIR filters have proven to be superior as compared to those obtained by RGA, conventional PSO and DE. The simulation results also demonstrate that the CSO is the best optimizer among other relevant techniques, not only in the convergence speed but also in the optimal performances of the designed filters. Copyright © 2013 ISA. Published by Elsevier Ltd. All rights reserved.

Two Topics in Data Analysis: Sample-based Optimal Transport and Analysis of Turbulent Spectra from Ship Track Data

NASA Astrophysics Data System (ADS)

Kuang, Simeng Max

This thesis contains two topics in data analysis. The first topic consists of the introduction of algorithms for sample-based optimal transport and barycenter problems. In chapter 1, a family of algorithms is introduced to solve both the L2 optimal transport problem and the Wasserstein barycenter problem. Starting from a theoretical perspective, the new algorithms are motivated from a key characterization of the barycenter measure, which suggests an update that reduces the total transportation cost and stops only when the barycenter is reached. A series of general theorems is given to prove the convergence of all the algorithms. We then extend the algorithms to solve sample-based optimal transport and barycenter problems, in which only finite sample sets are available instead of underlying probability distributions. A unique feature of the new approach is that it compares sample sets in terms of the expected values of a set of feature functions, which at the same time induce the function space of optimal maps and can be chosen by users to incorporate their prior knowledge of the data. All the algorithms are implemented and applied to various synthetic example and practical applications. On synthetic examples it is found that both the SOT algorithm and the SCB algorithm are able to find the true solution and often converge in a handful of iterations. On more challenging applications including Gaussian mixture models, color transfer and shape transform problems, the algorithms give very good results throughout despite the very different nature of the corresponding datasets. In chapter 2, a preconditioning procedure is developed for the L2 and more general optimal transport problems. The procedure is based on a family of affine map pairs, which transforms the original measures into two new measures that are closer to each other, while preserving the optimality of solutions. It is proved that the preconditioning procedure minimizes the remaining transportation cost among all admissible affine maps. The procedure can be used on both continuous measures and finite sample sets from distributions. In numerical examples, the procedure is applied to multivariate normal distributions, to a two-dimensional shape transform problem and to color transfer problems. For the second topic, we present an extension to anisotropic flows of the recently developed Helmholtz and wave-vortex decomposition method for one-dimensional spectra measured along ship or aircraft tracks in Buhler et al. (J. Fluid Mech., vol. 756, 2014, pp. 1007-1026). While in the original method the flow was assumed to be homogeneous and isotropic in the horizontal plane, we allow the flow to have a simple kind of horizontal anisotropy that is chosen in a self-consistent manner and can be deduced from the one-dimensional power spectra of the horizontal velocity fields and their cross-correlation. The key result is that an exact and robust Helmholtz decomposition of the horizontal kinetic energy spectrum can be achieved in this anisotropic flow setting, which then also allows the subsequent wave-vortex decomposition step. The new method is developed theoretically and tested with encouraging results on challenging synthetic data as well as on ocean data from the Gulf Stream.

Multi-arm group sequential designs with a simultaneous stopping rule.

PubMed

Urach, S; Posch, M

2016-12-30

Multi-arm group sequential clinical trials are efficient designs to compare multiple treatments to a control. They allow one to test for treatment effects already in interim analyses and can have a lower average sample number than fixed sample designs. Their operating characteristics depend on the stopping rule: We consider simultaneous stopping, where the whole trial is stopped as soon as for any of the arms the null hypothesis of no treatment effect can be rejected, and separate stopping, where only recruitment to arms for which a significant treatment effect could be demonstrated is stopped, but the other arms are continued. For both stopping rules, the family-wise error rate can be controlled by the closed testing procedure applied to group sequential tests of intersection and elementary hypotheses. The group sequential boundaries for the separate stopping rule also control the family-wise error rate if the simultaneous stopping rule is applied. However, we show that for the simultaneous stopping rule, one can apply improved, less conservative stopping boundaries for local tests of elementary hypotheses. We derive corresponding improved Pocock and O'Brien type boundaries as well as optimized boundaries to maximize the power or average sample number and investigate the operating characteristics and small sample properties of the resulting designs. To control the power to reject at least one null hypothesis, the simultaneous stopping rule requires a lower average sample number than the separate stopping rule. This comes at the cost of a lower power to reject all null hypotheses. Some of this loss in power can be regained by applying the improved stopping boundaries for the simultaneous stopping rule. The procedures are illustrated with clinical trials in systemic sclerosis and narcolepsy. © 2016 The Authors. Statistics in Medicine Published by John Wiley & Sons Ltd. © 2016 The Authors. Statistics in Medicine Published by John Wiley & Sons Ltd.

Stop Bullying Now! A Federal Campaign for Bullying Prevention and Intervention

ERIC Educational Resources Information Center

Bryn, Stephanie

2011-01-01

This commentary describes a national bullying prevention effort, called Stop Bullying Now!, which aims to increase awareness of the problem of bullying and related research findings, and disseminate evidence-based approaches to prevention. Drawing on the special issue's main theme of the social context of bullying, the author describes the process…

Evaluation of an accelerated 3D SPACE sequence with compressed sensing and free-stop scan mode for imaging of the knee.

PubMed

Henninger, B; Raithel, E; Kranewitter, C; Steurer, M; Jaschke, W; Kremser, C

2018-05-01

To prospectively evaluate a prototypical 3D turbo-spin-echo proton-density-weighted sequence with compressed sensing and free-stop scan mode for preventing motion artefacts (3D-PD-CS-SPACE free-stop) for knee imaging in a clinical setting. 80 patients underwent 3T magnetic resonance imaging (MRI) of the knee with our 2D routine protocol and with 3D-PD-CS-SPACE free-stop. In case of a scan-stop caused by motion (images are calculated nevertheless) the sequence was repeated without free-stop mode. All scans were evaluated by 2 radiologists concerning image quality of the 3D-PD-CS-SPACE (with and without free-stop). Important knee structures were further assessed in a lesion based analysis and compared to our reference 2D-PD-fs sequences. Image quality of the 3D-PD-CS-SPACE free-stop was found optimal in 47/80, slightly compromised in 21/80, moderately in 10/80 and severely in 2/80. In 29/80, the free-stop scan mode stopped the 3D-PD-CS-SPACE due to subject motion with a slight increase of image quality at longer effective acquisition times. Compared to the 3D-PD-CS-SPACE with free-stop, the image quality of the acquired 3D-PD-CS-SPACE without free-stop was found equal in 6/29, slightly improved in 13/29, improved with equal contours in 8/29, and improved with sharper contours in 2/29. The lesion based analysis showed a high agreement between the results from the 3D-PD-CS-SPACE free-stop and our 2D-PD-fs routine protocol (overall agreement 96.25%-100%, Cohen's Kappa 0.883-1, p < 0.001). 3D-PD-CS-SPACE free-stop is a reliable alternative for standard 2D-PD-fs protocols with acceptable acquisition times. Copyright © 2018 Elsevier B.V. All rights reserved.

Assessment of community satisfaction index of population and civil registration office in Malang municipal

NASA Astrophysics Data System (ADS)

Hakim, A. N.

2017-06-01

The demands and needs of the community will be the quality of public services in Malang increased, so that the Government of Malang as organizers and executors of public services must meet these demands. The Municipal Government in its efforts to improve public service performance, forming the regional One Stop Operator (PPTSP) with the goal will be to simplify and improve efficiency in administrative proceedings. But the existence of the one stop service is still not optimal because of the persistence of public complaints about the performance of the one stop service. This study will discuss the performance of services in service counter of Population and Civil Registration through community satisfaction index to measure the service level and the perception of satisfaction and interest to determine which variables are less optimal and need to be improved using IPA method. The results showed that the level of service at the service counter of Population and Civil Registration quite good. Meanwhile, according the results of IPA analysis, there are two important variables for the community on the performance / quality was lacking, namely the service procedure and time.

A junction-tree based learning algorithm to optimize network wide traffic control: A coordinated multi-agent framework

DOE PAGES

Zhu, Feng; Aziz, H. M. Abdul; Qian, Xinwu; ...

2015-01-31

Our study develops a novel reinforcement learning algorithm for the challenging coordinated signal control problem. Traffic signals are modeled as intelligent agents interacting with the stochastic traffic environment. The model is built on the framework of coordinated reinforcement learning. The Junction Tree Algorithm (JTA) based reinforcement learning is proposed to obtain an exact inference of the best joint actions for all the coordinated intersections. Moreover, the algorithm is implemented and tested with a network containing 18 signalized intersections in VISSIM. Finally, our results show that the JTA based algorithm outperforms independent learning (Q-learning), real-time adaptive learning, and fixed timing plansmore » in terms of average delay, number of stops, and vehicular emissions at the network level.« less

Big Data Discovery and Access Services through NOAA OneStop

NASA Astrophysics Data System (ADS)

Casey, K. S.; Neufeld, D.; Ritchey, N. A.; Relph, J.; Fischman, D.; Baldwin, R.

2017-12-01

The NOAA OneStop Project was created as a pathfinder effort to to improve the discovery of, access to, and usability of NOAA's vast and diverse collection of big data. OneStop is led by the NOAA/NESDIS National Centers for Environmental Information (NCEI), and is seen as a key NESDIS contribution to NOAA's open data and data stewardship efforts. OneStop consists of an entire framework of services, from storage and interoperable access services at the base, through metadata and catalog services in the middle, to a modern user interface experience at the top. Importantly, it is an open framework where external tools and services can connect at whichever level is most appropriate. Since the beta release of the OneStop user interface at the 2016 Fall AGU meeting, significant progress has been made improving and modernizing many NOAA data collections to optimize their use within the framework. In addition, OneStop has made progress implementing robust metadata management and catalog systems at the collection and granule level and improving the user experience with the web interface. This progress will be summarized and the results of extensive user testing including professional usability studies will be reviewed. Key big data technologies supporting the framework will be presented and a community input sought on the future directions of the OneStop Project.

[Results of a health education intervention in the continuity of breastfeeding].

PubMed

Molinero Diaz, Patricia; Burgos Rodríguez, María José; Mejía Ramírez de Arellano, Mercedes

2015-01-01

evaluate the efficacy of a nursing intervention based on active observation and resolution of the problems of breastfeeding in the period 24-48h post-partum as regards stopping breastfeeding in mothers who gave birth in Hospital General Universitario, Ciudad Real. A clinical trial was conducted on 100 healthy women who had given birth to a healthy baby in the maternity unit of the Hospital General Universitario Ciudad Real. The results showed that 39.8% of women have problems, and 72% need help to initiate the breastfeeding. Approximately 79.9% continue with breastfeeding after hospital discharge as a result of our intervention. Breastfeeding was stopped by 31.1% of the control group, and by 10.9% in the experimental group (nursing intervention), with significant differences being observed in both groups, with RR 1.29 and 95% CI; 1.04-1.61. Hypogalactia (low milk production) was the most frequent reason for stopping, with no differences in both groups. At 3 months, 16.9% had stopped breastfeeding in the control group, and 9% in the experimental group. At 6 months, 19.3% of the control group did not continue with breastfeeding versus 15.9% in the experimental group. Action, and not only intervention, protocols in the period 48h pospartum when there were problems with breastfeeding were effective for initiation breastfeeding at hospital discharge. Copyright © 2015 Elsevier España, S.L.U. All rights reserved.

Energy Monitoring and Control Systems Operator Training - Recommended Qualifications, Staffing, Job Description, and Training Requirements for EMCS Operators.

DTIC Science & Technology

1982-06-01

start/stop chiller optimization , and demand limiting were added. The system monitors a 7,000 ton chiller plant and controls 74 air handlers. The EMCS does...Modify analog limits. g. Adjust setpoints of selected controllers. h. Select manual or automatic control modes. i. Enable and disable individual points...or event schedules and controller setpoints ; make nonscheduled starts and stops of equipment or disable field panels when required for routine

Ibandronate

MedlinePlus

... or other problems with your stomach or esophagus (tube that connects the throat to the stomach); cancer; any type of infection, especially in your mouth; problems with your mouth, teeth, or gums; any condition that stops your blood ...

Exploring the nearly degenerate stop region with sbottom decays

DOE PAGES

An, Haipeng; Gu, Jiayin; Wang, Lian-Tao

2017-04-13

A light stop with mass almost degenerate with the lightest neutralino has important connections with both naturalness and dark matter relic abundance. This region is also very hard to probe at colliders. In this paper, we demonstrate the potential of searching for such stop particles at the LHC from sbottom decays, focusing on two channels with final states 2ℓ+EmissT2ℓ+ETmiss and 1b1ℓ+Emore » $$miss\\atop{T}$$1b1ℓ+E$$miss\\atop{T}$$. We also found that, if the lightest sbottom has mass around or below 1 TeV and has a significant branching ratio to decay to stop and W($$\\tilde{b}$$→$$\\tilde{t}$$W), a stop almost degenerate with neutralino can be excluded up to about 500-600 GeV at the 13 TeV LHC with 300 fb -1 data. The searches we propose are complementary to other SUSY searches at the LHC and could have the best sensitivity to the stop-bino coannihilation region. Finally, since they involve final states which have already been used in LHC searches, a reinterpretation of the search results already has sensitivity. Further optimization could deliver the full potential of these channels.« less

An Optimal Partial Differential Equations-based Stopping Criterion for Medical Image Denoising.

PubMed

Khanian, Maryam; Feizi, Awat; Davari, Ali

2014-01-01

Improving the quality of medical images at pre- and post-surgery operations are necessary for beginning and speeding up the recovery process. Partial differential equations-based models have become a powerful and well-known tool in different areas of image processing such as denoising, multiscale image analysis, edge detection and other fields of image processing and computer vision. In this paper, an algorithm for medical image denoising using anisotropic diffusion filter with a convenient stopping criterion is presented. In this regard, the current paper introduces two strategies: utilizing the efficient explicit method due to its advantages with presenting impressive software technique to effectively solve the anisotropic diffusion filter which is mathematically unstable, proposing an automatic stopping criterion, that takes into consideration just input image, as opposed to other stopping criteria, besides the quality of denoised image, easiness and time. Various medical images are examined to confirm the claim.

Managing Chemotherapy Side Effects: Bleeding Problems

MedlinePlus

... C ancer I nstitute Managing Chemotherapy Side Effects Bleeding Problems “My nurse said that chemotherapy could make ... with a clean cloth. Keep pressing until the bleeding stops. If you bruise: Put ice on the ...

Top squark with mass close to the top quark

NASA Astrophysics Data System (ADS)

Buckley, Matthew R.; Plehn, Tilman; Ramsey-Musolf, Michael J.

2014-07-01

The most natural supersymmetric solution to the hierarchy problem prefers the scalar top partner to be close in mass to the top quark. Experimental searches exclude top squarks across a wide range of masses, but a gap remains when the difference between the masses of the stop and the lightest supersymmetric particle is close to the top mass. We propose to search for stops in this regime by exploiting the azimuthal angular correlation of forward tagging jets in (s)top pair production. As shown in earlier work, this correlation is sensitive to the spin of the heavy states, allowing one to distinguish between top and stop pair production. Here, we demonstrate that this angular information can give a statistically significant stop pair production signal in the upcoming LHC run. While the appropriate simulation including parton showering and detector simulation requires some care, we find stable predictions for the angular correlation using multijet merging.

Monotop signature from the supersymmetric t t¯ H channel

NASA Astrophysics Data System (ADS)

Gonçalves, Dorival; Sakurai, Kazuki; Takeuchi, Michihisa

2016-10-01

We point out that a distinctive monotop signature is present in natural supersymmetry scenarios when a scalar top quark and Higgsinos are almost mass degenerate. This signature originates from a supersymmetric counterpart of the t t ¯H process, i.e. p p →t ˜t h ˜. Unlike monojet signatures exploiting initial state radiation, this channel can be regarded as a clear signature of a light stop and Higgsinos, allowing a direct probe of the stop and neutralino sectors. The production rate of this channel largely depends on the up-type Higgsino components in the neutralinos while the stop sector is sensitive to angular distributions of the top-quark's decay products. We develop an optimal search strategy to capture the supersymmetric t t ¯ H process and find that a high luminosity LHC can probe the stop and Higgsino sectors with mt˜1≲380 GeV and mt˜1-mχ˜1 0≲mW . Additionally, we propose a kinematic variable with which one can measure the stop mixing in this channel.

Bayesian neural adjustment of inhibitory control predicts emergence of problem stimulant use.

PubMed

Harlé, Katia M; Stewart, Jennifer L; Zhang, Shunan; Tapert, Susan F; Yu, Angela J; Paulus, Martin P

2015-11-01

Bayesian ideal observer models quantify individuals' context- and experience-dependent beliefs and expectations about their environment, which provides a powerful approach (i) to link basic behavioural mechanisms to neural processing; and (ii) to generate clinical predictors for patient populations. Here, we focus on (ii) and determine whether individual differences in the neural representation of the need to stop in an inhibitory task can predict the development of problem use (i.e. abuse or dependence) in individuals experimenting with stimulants. One hundred and fifty-seven non-dependent occasional stimulant users, aged 18-24, completed a stop-signal task while undergoing functional magnetic resonance imaging. These individuals were prospectively followed for 3 years and evaluated for stimulant use and abuse/dependence symptoms. At follow-up, 38 occasional stimulant users met criteria for a stimulant use disorder (problem stimulant users), while 50 had discontinued use (desisted stimulant users). We found that those individuals who showed greater neural responses associated with Bayesian prediction errors, i.e. the difference between actual and expected need to stop on a given trial, in right medial prefrontal cortex/anterior cingulate cortex, caudate, anterior insula, and thalamus were more likely to exhibit problem use 3 years later. Importantly, these computationally based neural predictors outperformed clinical measures and non-model based neural variables in predicting clinical status. In conclusion, young adults who show exaggerated brain processing underlying whether to 'stop' or to 'go' are more likely to develop stimulant abuse. Thus, Bayesian cognitive models provide both a computational explanation and potential predictive biomarkers of belief processing deficits in individuals at risk for stimulant addiction. © The Author (2015). Published by Oxford University Press on behalf of the Guarantors of Brain. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

An application of PSO algorithm for multi-criteria geometry optimization of printed low-pass filters based on conductive periodic structures

NASA Astrophysics Data System (ADS)

Steckiewicz, Adam; Butrylo, Boguslaw

2017-08-01

In this paper we discussed the results of a multi-criteria optimization scheme as well as numerical calculations of periodic conductive structures with selected geometry. Thin printed structures embedded on a flexible dielectric substrate may be applied as simple, cheap, passive low-pass filters with an adjustable cutoff frequency in low (up to 1 MHz) radio frequency range. The analysis of an electromagnetic phenomena in presented structures was realized on the basis of a three-dimensional numerical model of three proposed geometries of periodic elements. The finite element method (FEM) was used to obtain a solution of an electromagnetic harmonic field. Equivalent lumped electrical parameters of printed cells obtained in such manner determine the shape of an amplitude transmission characteristic of a low-pass filter. A nonlinear influence of a printed cell geometry on equivalent parameters of cells electric model, makes it difficult to find the desired optimal solution. Therefore an optimization problem of optimal cell geometry estimation with regard to an approximation of the determined amplitude transmission characteristic with an adjusted cutoff frequency, was obtained by the particle swarm optimization (PSO) algorithm. A dynamically suitable inertia factor was also introduced into the algorithm to improve a convergence to a global extremity of a multimodal objective function. Numerical results as well as PSO simulation results were characterized in terms of approximation accuracy of predefined amplitude characteristics in a pass-band, stop-band and cutoff frequency. Three geometries of varying degrees of complexity were considered and their use in signal processing systems was evaluated.

Hybrid optimization and Bayesian inference techniques for a non-smooth radiation detection problem

DOE PAGES

Stefanescu, Razvan; Schmidt, Kathleen; Hite, Jason; ...

2016-12-12

In this paper, we propose several algorithms to recover the location and intensity of a radiation source located in a simulated 250 × 180 m block of an urban center based on synthetic measurements. Radioactive decay and detection are Poisson random processes, so we employ likelihood functions based on this distribution. Owing to the domain geometry and the proposed response model, the negative logarithm of the likelihood is only piecewise continuous differentiable, and it has multiple local minima. To address these difficulties, we investigate three hybrid algorithms composed of mixed optimization techniques. For global optimization, we consider simulated annealing, particlemore » swarm, and genetic algorithm, which rely solely on objective function evaluations; that is, they do not evaluate the gradient in the objective function. By employing early stopping criteria for the global optimization methods, a pseudo-optimum point is obtained. This is subsequently utilized as the initial value by the deterministic implicit filtering method, which is able to find local extrema in non-smooth functions, to finish the search in a narrow domain. These new hybrid techniques, combining global optimization and implicit filtering address, difficulties associated with the non-smooth response, and their performances, are shown to significantly decrease the computational time over the global optimization methods. To quantify uncertainties associated with the source location and intensity, we employ the delayed rejection adaptive Metropolis and DiffeRential Evolution Adaptive Metropolis algorithms. Finally, marginal densities of the source properties are obtained, and the means of the chains compare accurately with the estimates produced by the hybrid algorithms.« less

A feasibility study of methods for stopping the depletion of ozone over Antarctica

NASA Technical Reports Server (NTRS)

1988-01-01

Ways of stopping the ozone depletion in the ozone hole over Antarctica were studied. The basic objectives were: (1) to define and understand the phenomenon of the ozone hole; (2) to determine possible methods of stopping the ozone depletion; (3) to identify unknowns about the hole and possible solutions. Two basic ways of attacking the problem were identified. First is replenishment of ozone as it is being depleted. Second is elimination of ozone destroying agents from the atmosphere. The second method is a more permanent form of the solution. Elimination and replenishment methods are discussed in detail.

Environmental Law and the Export of Pollution.

ERIC Educational Resources Information Center

Davis, John F.

1984-01-01

Environmental problems do not stop at state boundaries; they reach beyond local or national jurisdictions and require international control. Problems concerning air quality, water pollution, and indirect pollution are discussed. Environmental legislation can have a significant impact. (RM)

Flurazepam

MedlinePlus

... by slowing activity in the brain to allow sleep. ... nights after you stop taking the medication.Your sleep problems should improve within 7 to 10 days ... start taking flurazepam. Call your doctor if your sleep problems do not improve during this time, if ...

Optimal power distribution for minimizing pupil walk in a 7.5X afocal zoom lens

NASA Astrophysics Data System (ADS)

Song, Wanyue; Zhao, Yang; Berman, Rebecca; Bodell, S. Yvonne; Fennig, Eryn; Ni, Yunhui; Papa, Jonathan C.; Yang, Tianyi; Yee, Anthony J.; Moore, Duncan T.; Bentley, Julie L.

2017-11-01

An extensive design study was conducted to find the best optimal power distribution and stop location for a 7.5x afocal zoom lens that controls the pupil walk and pupil location through zoom. This afocal zoom lens is one of the three components in a VIS-SWIR high-resolution microscope for inspection of photonic chips. The microscope consists of an afocal zoom, a nine-element objective and a tube lens and has diffraction limited performance with zero vignetting. In this case, the required change in object (sample) size and resolution is achieved by the magnification change of the afocal component. This creates strict requirements for both the entrance and exit pupil locations of the afocal zoom to couple the two sides successfully. The first phase of the design study looked at conventional four group zoom lenses with positive groups in the front and back and the stop at a fixed location outside the lens but resulted in significant pupil walk. The second phase of the design study focused on several promising unconventional four-group power distribution designs with moving stops that minimized pupil walk and had an acceptable pupil location (as determined by the objective and tube lens).

Real-time electronic monitoring of a pitted and leaking gas gathering pipeline

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

Asperger, R.G.; Hewitt, P.G.

1986-08-01

Hydrogen patch, flush electrical resistance, and flush linear polarization proves wre used with flush coupons to monitor corrosion rates in a pitted and leaking sour gas gathering line. Four inhibitors were evaluated in stopping the leaks. Inhibitor residuals and the amount and ratio of water and condensate in the lines were measured at five locations along the line. The best inhibitor reduced reduced the pit-leak frequency by over a factor of 10. Inhibitor usage rate was optimized using the hydrogen patch current as a measure of the instantaneous corrosion rate. Improper pigging was identified as a cause of corrosion transients.more » This problem is discussed in relation to the pigging of pipelines in stratified flow where moving fluids are the carriers for continuously injected corrosion inhibitors.« less

Multiobjective optimization model of intersection signal timing considering emissions based on field data: A case study of Beijing.

PubMed

Kou, Weibin; Chen, Xumei; Yu, Lei; Gong, Huibo

2018-04-18

Most existing signal timing models are aimed to minimize the total delay and stops at intersections, without considering environmental factors. This paper analyzes the trade-off between vehicle emissions and traffic efficiencies on the basis of field data. First, considering the different operating modes of cruising, acceleration, deceleration, and idling, field data of emissions and Global Positioning System (GPS) are collected to estimate emission rates for heavy-duty and light-duty vehicles. Second, multiobjective signal timing optimization model is established based on a genetic algorithm to minimize delay, stops, and emissions. Finally, a case study is conducted in Beijing. Nine scenarios are designed considering different weights of emission and traffic efficiency. The results compared with those using Highway Capacity Manual (HCM) 2010 show that signal timing optimized by the model proposed in this paper can decrease vehicles delay and emissions more significantly. The optimization model can be applied in different cities, which provides supports for eco-signal design and development. Vehicle emissions are heavily at signal intersections in urban area. The multiobjective signal timing optimization model is proposed considering the trade-off between vehicle emissions and traffic efficiencies on the basis of field data. The results indicate that signal timing optimized by the model proposed in this paper can decrease vehicle emissions and delays more significantly. The optimization model can be applied in different cities, which provides supports for eco-signal design and development.

Stop the top background of the stop search

NASA Astrophysics Data System (ADS)

Bai, Yang; Cheng, Hsin-Chia; Gallicchio, Jason; Gu, Jiayin

2012-07-01

The main background for the supersymmetric stop direct production search comes from Standard Model toverline t events. For the single-lepton search channel, we introduce a few kinematic variables to further suppress this background by focusing on its dileptonic and semileptonic topologies. All are defined to have end points in the background, but not signal distributions. They can substantially improve the stop signal significance and mass reach when combined with traditional kinematic variables such as the total missing transverse energy. Among them, our variable M_{{T2}}^W hasthebestoverallperformancebecause it uses all available kinematic information, including the on-shell mass of both W's. We see 20 %-30 % improvement on the discovery significance and estimate that the 8 TeV LHC run with 20 fb-1 of data would be able to reach an exclusion limit of 650-700 GeV for direct stop production, as long as the stop decays dominantly to the top quark and a light stable neutralino. Most of the mass range required for the supersymmetric solution of the naturalness problem in the standard scenario can be covered.

Evaluation of a biocidal turbine-fuel additive.

DOT National Transportation Integrated Search

1967-08-01

Growth of microorganisms in water-contaminated, kerosene-type fuels is a widespread problem in aviation. One approach to the solution of this problem is the introduction into fuel of a chemical additive which could stop or retard growth of microbes. ...

Combined Simulated Annealing and Genetic Algorithm Approach to Bus Network Design

NASA Astrophysics Data System (ADS)

Liu, Li; Olszewski, Piotr; Goh, Pong-Chai

A new method - combined simulated annealing (SA) and genetic algorithm (GA) approach is proposed to solve the problem of bus route design and frequency setting for a given road network with fixed bus stop locations and fixed travel demand. The method involves two steps: a set of candidate routes is generated first and then the best subset of these routes is selected by the combined SA and GA procedure. SA is the main process to search for a better solution to minimize the total system cost, comprising user and operator costs. GA is used as a sub-process to generate new solutions. Bus demand assignment on two alternative paths is performed at the solution evaluation stage. The method was implemented on four theoretical grid networks of different size and a benchmark network. Several GA operators (crossover and mutation) were utilized and tested for their effectiveness. The results show that the proposed method can efficiently converge to the optimal solution on a small network but computation time increases significantly with network size. The method can also be used for other transport operation management problems.

Environmental Cues and Attempts to Change in Daily Cannabis Users: An Intensive Longitudinal Study

PubMed Central

Hughes, John R.; Naud, Shelly; Budney, Alan J.; Fingar, James R.; Callas, Peter W.

2016-01-01

Introduction We tested whether environmental cues prompt or inhibit quit or reduction attempts among heavy cannabis users. Methods We recruited 196 daily cannabis users who intended to stop or reduce at some point in the next 3 months. Users called an Interactive Voice Response system daily over 3 months to report on cues that might prompt an attempt to quit or reduce (e.g., a request to stop), cues that might inhibit a quit/reduction attempt (e.g., someone offering cannabis), cannabis use, and attempts to stop or reduce cannabis. No treatment was provided. Results Our major findings were a) cost and health/psychological problems were the most common prompting cues, and seeing others use and being offered cannabis were the most common inhibiting cues, b) the number of different types of prompting cues prospectively predicted an increase in attempts to change in a dose-related manner, c) more proximal cues appeared to be more strongly related to change, d) requests to stop or reduce, and physical or psychological problems from cannabis, best predicted change attempts, and e) inhibiting cues did not consistently predict the probability of an attempt to change. Conclusion These preliminary results suggest several environmental cues prompt attempts to change cannabis use. Thus, interventions to increase the frequency of these cues, and specifically requests to stop or reduce cannabis use, and reinforcing concerns about health and mental adverse events from cannabis use may increase cannabis reduction or cessation. PMID:26872879

Environmental cues and attempts to change in daily cannabis users: An intensive longitudinal study.

PubMed

Hughes, John R; Naud, Shelly; Budney, Alan J; Fingar, James R; Callas, Peter W

2016-04-01

We tested whether environmental cues prompt or inhibit quit or reduction attempts among heavy cannabis users. We recruited 196 daily cannabis users who intended to stop or reduce at some point in the next 3 months. Users called an Interactive Voice Response system daily over 3 months to report on cues that might prompt an attempt to quit or reduce (e.g., a request to stop), cues that might inhibit a quit/reduction attempt (e.g., someone offering cannabis), cannabis use, and attempts to stop or reduce cannabis. No treatment was provided. Our major findings were (a) cost and health/psychological problems were the most common prompting cues, and seeing others use and being offered cannabis were the most common inhibiting cues, (b) the number of different types of prompting cues prospectively predicted an increase in attempts to change in a dose-related manner, (c) more proximal cues appeared to be more strongly related to change, (d) requests to stop or reduce, and physical or psychological problems from cannabis, best predicted change attempts, and (e) inhibiting cues did not consistently predict the probability of an attempt to change. These preliminary results suggest several environmental cues prompt attempts to change cannabis use. Thus, interventions to increase the frequency of these cues, and specifically requests to stop or reduce cannabis use, and reinforcing concerns about health and mental adverse events from cannabis use, may increase cannabis reduction or cessation. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Monte Carlo calculation of proton stopping power and ranges in water for therapeutic energies

NASA Astrophysics Data System (ADS)

Bozkurt, Ahmet

2017-09-01

Monte Carlo is a statistical technique for obtaining numerical solutions to physical or mathematical problems that are analytically impractical, if not impossible, to solve. For charged particle transport problems, it presents many advantages over deterministic methods since such problems require a realistic description of the problem geometry, as well as detailed tracking of every source particle. Thus, MC can be considered as a powerful alternative to the well-known Bethe-Bloche equation where an equation with various corrections is used to obtain stopping power and ranges of electrons, positrons, protons, alphas, etc. This study presents how a stochastic method such as MC can be utilized to obtain certain quantities of practical importance related to charged particle transport. Sample simulation geometries were formed for water medium where disk shaped thin detectors were employed to compute average values of absorbed dose and flux at specific distances. For each detector cell, these quantities were utilized to evaluate the values of the range and the stopping power, as well as the shape of Bragg curve, for mono-energetic point source pencil beams of protons. The results were found to be ±2% compared to the data from the NIST compilation. It is safe to conclude that this approach can be extended to determine dosimetric quantities for other media, energies and charged particle types.

Total-variation based velocity inversion with Bregmanized operator splitting algorithm

NASA Astrophysics Data System (ADS)

Zand, Toktam; Gholami, Ali

2018-04-01

Many problems in applied geophysics can be formulated as a linear inverse problem. The associated problems, however, are large-scale and ill-conditioned. Therefore, regularization techniques are needed to be employed for solving them and generating a stable and acceptable solution. We consider numerical methods for solving such problems in this paper. In order to tackle the ill-conditioning of the problem we use blockiness as a prior information of the subsurface parameters and formulate the problem as a constrained total variation (TV) regularization. The Bregmanized operator splitting (BOS) algorithm as a combination of the Bregman iteration and the proximal forward backward operator splitting method is developed to solve the arranged problem. Two main advantages of this new algorithm are that no matrix inversion is required and that a discrepancy stopping criterion is used to stop the iterations, which allow efficient solution of large-scale problems. The high performance of the proposed TV regularization method is demonstrated using two different experiments: 1) velocity inversion from (synthetic) seismic data which is based on Born approximation, 2) computing interval velocities from RMS velocities via Dix formula. Numerical examples are presented to verify the feasibility of the proposed method for high-resolution velocity inversion.

Stopping Discipline Problems before They Start.

ERIC Educational Resources Information Center

VanDerveer, Elizabeth

1989-01-01

States that prevention of discipline problems is directly related to effective teaching strategies. Suggests that good teaching, based on well-planned lessons, proper pacing of lessons, effective classroom management, teacher assertiveness, and teacher musicality, can prevent undesirable behaviors in the music classroom. (LS)

A Class of Solvable Stopping Games

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

Alvarez, Luis H. R.

We consider a class of Dynkin games in the case where the underlying process evolves according to a one-dimensional but otherwise general diffusion. We establish general conditions under which both the value and the saddle point equilibrium exist and under which the exercise boundaries characterizing the saddle point strategy can be explicitly characterized in terms of a pair of standard first order necessary conditions for optimality. We also analyze those cases where an extremal pair of boundaries exists and investigate the overall impact of increased volatility on the equilibrium stopping strategies and their values.

Improvement and emergence of insulin restriction in women with type 1 diabetes.

PubMed

Goebel-Fabbri, Ann E; Anderson, Barbara J; Fikkan, Janna; Franko, Debra L; Pearson, Kimberly; Weinger, Katie

2011-03-01

To determine the distinguishing characteristics of women who report stopping insulin restriction at 11 years of follow-up from those continuing to endorse insulin restriction as well as those characteristics differing in patients who continue to use insulin appropriately from new insulin restrictors. This is an 11-year follow-up study of 207 women with type 1 diabetes. Insulin restriction, diabetes self-care behaviors, diabetes-specific distress, and psychiatric and eating disorder symptoms were assessed using self-report surveys. Of the original sample, 57% participated in the follow-up study. Mean age was 44 ± 12 years, diabetes duration was 28 ± 11 years, and A1C was 7.9 ± 1.3%. At follow-up, 20 of 60 baseline insulin restrictors had stopped restriction. Women who stopped reported improved diabetes self-care and distress, fewer problems with diabetes self-management, and lower levels of psychologic distress and eating disorder symptoms. Logistic regression indicated that lower levels of fear of weight gain with improved blood glucose and fewer problems with diabetes self-management predicted stopping restriction. At follow-up, 34 women (23%) reported new restriction, and a larger proportion of new insulin restrictors, relative to nonrestrictors, endorsed fear of weight gain with improved blood glucose. Findings indicate that fear of weight gain associated with improved blood glucose and problems with diabetes self-care are core issues related to both the emergence and resolution of insulin restriction. Greater attention to these concerns may help treatment teams to better meet the unique treatment needs of women struggling with insulin restriction.

Fuel efficient traffic signal operation and evaluation: Garden Grove Demonstration Project

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

Not Available

1983-02-01

The procedures and results of a case study of fuel efficient traffic signal operation and evaluation in the City of Garden Grove, California are documented. Improved traffic signal timing was developed for a 70-intersection test network in Garden Grove using an optimization tool called the TRANSYT Version 8 computer program. Full-scale field testing of five alternative timing plans was conducted using two instrumented vehicles equipped to measure traffic performance characteristics and fuel consumption. The field tests indicated that significant improvements in traffic flow and fuel consumption result from the use of timing plans generated by the TRANSYT optimization model. Changingmore » from pre-existing to an optimized timing plan yields a networkwide 5 percent reduction in total travel time, more than 10 percent reduction in both the number of stops and stopped delay time, and 6 percent reduction in fuel consumption. Projections are made of the benefits and costs of implementing such a program at the 20,000 traffic signals in networks throughout the State of California.« less

Optimizer convergence and local minima errors and their clinical importance

NASA Astrophysics Data System (ADS)

Jeraj, Robert; Wu, Chuan; Mackie, Thomas R.

2003-09-01

Two of the errors common in the inverse treatment planning optimization have been investigated. The first error is the optimizer convergence error, which appears because of non-perfect convergence to the global or local solution, usually caused by a non-zero stopping criterion. The second error is the local minima error, which occurs when the objective function is not convex and/or the feasible solution space is not convex. The magnitude of the errors, their relative importance in comparison to other errors as well as their clinical significance in terms of tumour control probability (TCP) and normal tissue complication probability (NTCP) were investigated. Two inherently different optimizers, a stochastic simulated annealing and deterministic gradient method were compared on a clinical example. It was found that for typical optimization the optimizer convergence errors are rather small, especially compared to other convergence errors, e.g., convergence errors due to inaccuracy of the current dose calculation algorithms. This indicates that stopping criteria could often be relaxed leading into optimization speed-ups. The local minima errors were also found to be relatively small and typically in the range of the dose calculation convergence errors. Even for the cases where significantly higher objective function scores were obtained the local minima errors were not significantly higher. Clinical evaluation of the optimizer convergence error showed good correlation between the convergence of the clinical TCP or NTCP measures and convergence of the physical dose distribution. On the other hand, the local minima errors resulted in significantly different TCP or NTCP values (up to a factor of 2) indicating clinical importance of the local minima produced by physical optimization.

Optimizer convergence and local minima errors and their clinical importance.

PubMed

Jeraj, Robert; Wu, Chuan; Mackie, Thomas R

2003-09-07

Two of the errors common in the inverse treatment planning optimization have been investigated. The first error is the optimizer convergence error, which appears because of non-perfect convergence to the global or local solution, usually caused by a non-zero stopping criterion. The second error is the local minima error, which occurs when the objective function is not convex and/or the feasible solution space is not convex. The magnitude of the errors, their relative importance in comparison to other errors as well as their clinical significance in terms of tumour control probability (TCP) and normal tissue complication probability (NTCP) were investigated. Two inherently different optimizers, a stochastic simulated annealing and deterministic gradient method were compared on a clinical example. It was found that for typical optimization the optimizer convergence errors are rather small, especially compared to other convergence errors, e.g., convergence errors due to inaccuracy of the current dose calculation algorithms. This indicates that stopping criteria could often be relaxed leading into optimization speed-ups. The local minima errors were also found to be relatively small and typically in the range of the dose calculation convergence errors. Even for the cases where significantly higher objective function scores were obtained the local minima errors were not significantly higher. Clinical evaluation of the optimizer convergence error showed good correlation between the convergence of the clinical TCP or NTCP measures and convergence of the physical dose distribution. On the other hand, the local minima errors resulted in significantly different TCP or NTCP values (up to a factor of 2) indicating clinical importance of the local minima produced by physical optimization.

Light stops and observation of supersymmetry at LHC run II

NASA Astrophysics Data System (ADS)

Kaufman, Bryan; Nath, Pran; Nelson, Brent D.; Spisak, Andrew B.

2015-11-01

Light stops consistent with the Higgs boson mass of ˜126 GeV are investigated within the framework of minimal supergravity. It is shown that models with light stops which are also consistent with the thermal relic density constraints require stop coannihilation with the neutralino LSP. The analysis shows that the residual set of parameter points with light stops satisfying both the Higgs mass and the relic density constraints lie within a series of thin strips in the m0-m1 /2 plane for different values of A0/m0. Consequently, this region of minimal supergravity parameter space makes a number of very precise predictions. It is found that light stops of mass down to 400 GeV or lower can exist consistent with all constraints. A signal analysis for this class of models at LHC run II is carried out and the dominant signals for their detection identified. Also computed is the minimum integrated luminosity for 5 σ discovery of the models analyzed. If supersymmetry is realized in this manner, the stop masses can be as low as 400 GeV or lower, and the mass gap between the lightest neutralino and lightest stop will be approximately 30-40 GeV. We have optimized the ATLAS signal regions specifically for stop searches in the parameter space and find that a stop with mass ˜375 GeV can be discovered with as little as ˜60 fb-1 of integrated luminosity at run II of the LHC; the integrated luminosity needed for discovery could be further reduced with more efficient signature analyses. The direct detection of dark matter in this class of models is also discussed. It is found that dark matter cross sections lie close to, but above, coherent neutrino scattering and would require multiton detectors such as LZ to see a signal of dark matter for this class of models.

SU-G-TeP2-13: Patient-Specific Reduction of Range Uncertainties in Proton Therapy by Proton Radiography with a Multi-Layer Ionization Chamber

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

Deffet, S; Macq, B; Farace, P

2016-06-15

Purpose: The conversion from Hounsfield units (HU) to stopping powers is a major source of range uncertainty in proton therapy (PT). Our contribution shows how proton radiographs (PR) acquired with a multi-layer ionization chamber in a PT center can be used for accurate patient positioning and subsequently for patient-specific optimization of the conversion from HU to stopping powers. Methods: A multi-layer ionization chamber was used to measure the integral depth-dose (IDD) of 220 MeV pencil beam spots passing through several anthropomorphic phantoms. The whole area of interest was imaged by repositioning the couch and by acquiring a 45×45 mm{sup 2}more » frame for each position. A rigid registration algorithm was implemented to correct the positioning error between the proton radiographs and the planning CT. After registration, the stopping power map obtained from the planning CT with the calibration curve of the treatment planning system was used together with the water equivalent thickness gained from two proton radiographs to generate a phantom-specific stopping power map. Results: Our results show that it is possible to make a registration with submillimeter accuracy from proton radiography obtained by sending beamlets separated by more than 1 mm. This was made possible by the complex shape of the IDD due to the presence of lateral heterogeneities along the path of the beam. Submillimeter positioning was still possible with a 5 mm spot spacing. Phantom specific stopping power maps obtained by minimizing the range error were cross-verified by the acquisition of an additional proton radiography where the phantom was positioned in a random but known manner. Conclusion: Our results indicate that a CT-PR registration algorithm together with range-error based optimization can be used to produce a patient-specific stopping power map. Sylvain Deffet reports financial funding of its PhD thesis by Ion Beam Applications (IBA) during the confines of the study and outside the submitted work. Francois Vander Stappen reports being employed by Ion Beam Applications (IBA) during the confines of the study and outside the submitted work.« less

TU-FG-BRB-04: A New Optimization Method for Pre-Treatment Patient-Specific Stopping-Power by Combining Proton Radiography and X-Ray CT

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

Collins-Fekete, C; Centre Hospitalier University de Quebec, Quebec, QC; Mass General Hospital

Purpose: The relative stopping power (RSP) uncertainty is the largest contributor to the range uncertainty in proton therapy. The purpose of this work is to develop a robust and systematic method that yields accurate patient specific RSPs by combining pre-treatment X-ray CT and daily proton radiography. Methods: The method is formulated as a penalized least squares optimization (PLSO) problem min(|Ax-B|). The matrix A represents the cumulative path-length crossed in each material computed by calculating proton trajectories through the X-ray CT. The material RSPs are denoted by x and B is the pRad, expressed as water equivalent thickness. The equation ismore » solved using a convex-conic optimizer. Geant4 simulations were made to assess the feasibility of the method. RSP extracted from the Geant4 materials were used as a reference and the clinical HU-RSP curve as a comparison. The PLSO was first tested on a Gammex RMI-467 phantom. Then, anthropomorphic phantoms of the head, pelvis and lung were studied and resulting RSPs were evaluated. A pencil beam was generated in each phantom to evaluate the proton range accuracy achievable by using the optimized RSPs. Finally, experimental data of a pediatric head phantom (CIRS) were acquired using a recently completed experimental pCT scanner. Results: Numerical simulations showed precise RSP (<0.75%) for Gammex materials except low-density lung (LN-300) (1.2%). Accurate RSP have been obtained for the head (µ=−0.10%, 1.5σ=1.12%), lung (µ=−0.33, 1.5σ=1.02%) and pelvis anthropomorphic phantoms (µ=0.12, 1.5σ=0,99%). The range precision has been improved with an average R80 difference to the reference (µ±1.5σ) of −0.20±0.35%, −0.47±0.92% and −0.06±0.17% in the head, lung and pelvis phantoms respectively, compared to the 3.5% clinical margin. Experimental HU-RSP curve have been produced on the CIRS pediatric head. Conclusion: The proposed PLSO with prior knowledge X-ray CT shows promising potential (R80 σ<1.0% over all sites) to decrease the range uncertainty.« less

[Impact of social disadvantages and time perspective on smoking cessation].

PubMed

Merson, Frédéric; Perriot, Jean

2012-02-01

Smoking addiction and tobacco dependence are related to social deprivation and time perspective. The objective of this study was to understand how these factors influenced the results of smoking cessation in order to optimize the care of this population. We included 200 patients from our outpatient clinic from March 1, 2009 to June 30, 2010. This study focused on the impact of social disadvantages and time perspective on smoking cessation. Time perspective was measured with the short version of the Zimbardo Time Perspective Inventory, social disadvantages with Epices scale. Information on each individual's characteristics, smoking addiction, and smoking cessation was collected. One hundred and ninety-two patients (of whom 45% were socially disadvantaged) participated. Socially disadvantaged people tend to lean towards dimensions "Past Negative" (P<0.0001), "Present Fatalistic" (P<0.0001) and are less likely to foresee themselves in the future (P<0.0002) compared with the rest of the population. Their decision to stop smoking reveals they are more motivated for financial reasons (P<0.0001) and their attempts more often end in failure (P=0.006). In addition, they have, more frequently, anxiodepressive problems (P<0.0001) and a higher level of nicotine dependence (P<0.0001). The results highlight the importance of taking into account the social disadvantages and time perspective in helping these addicted patients to stop smoking. Copyright © 2011. Published by Elsevier Masson SAS.

Practical approximations to quantify the impact of time windows and delivery sizes on VMT multi-stop tours.

DOT National Transportation Integrated Search

2009-04-01

This paper studies approximations to the average length of Vehicle Routing Problems (VRP). The approximations are valuable for strategic and : planning analysis of transportation and logistics problems. The research focus is on VRP with varying numbe...

Accelerated gradient methods for the x-ray imaging of solar flares

NASA Astrophysics Data System (ADS)

Bonettini, S.; Prato, M.

2014-05-01

In this paper we present new optimization strategies for the reconstruction of x-ray images of solar flares by means of the data collected by the Reuven Ramaty high energy solar spectroscopic imager. The imaging concept of the satellite is based on rotating modulation collimator instruments, which allow the use of both Fourier imaging approaches and reconstruction techniques based on the straightforward inversion of the modulated count profiles. Although in the last decade, greater attention has been devoted to the former strategies due to their very limited computational cost, here we consider the latter model and investigate the effectiveness of different accelerated gradient methods for the solution of the corresponding constrained minimization problem. Moreover, regularization is introduced through either an early stopping of the iterative procedure, or a Tikhonov term added to the discrepancy function by means of a discrepancy principle accounting for the Poisson nature of the noise affecting the data.

Inactivated poliovirus vaccine and the final stages of poliovirus eradication.

PubMed

Hovi, T

2001-03-21

The use of the inactivated poliovirus vaccine (IPV) will increase before and probably also after the global eradication of the wild type poliovirus. Before eradication, the switch from the use of oral poliovirus vaccine (OPV) to IPV has been due to the better safety record of IPV. Introduction of IPV in the regular immunisation schedules is made easier by the development of several combination vaccines, including IPV. Maternal antibodies and young age, often considered problematic for early initiation of IPV schedules, did not compromise optimal maintenance of seropositivity during infancy or long-term persisting antibody levels in our studies. OPV-derived, potentially pathogenic and transmissible poliovirus strains, excreted by some individuals for years, may present a problem for a blunt stopping of all polio immunisations after eradication. Our recent results suggest that locally excreted IgA might have a role in the elimination of poliovirus infection in the intestinal tissues.

Energy Conservation: Heating Navy Hangars

DTIC Science & Technology

1984-07-01

temperature, IF Tf Inside air temperature 1 foot above the floor, OF T. Inside design temperature, IF To Hot water temperature setpoint , OF TON Chiller ...systems capable of optimizing energy usage base-wide. An add-on to an existing large scale EMCS is probably the first preference, followed by single...the building comfort conditions are met during hours of building occupancy. 2. Optimized Start/Stop turns on equipment at the latest possible time and

Database Management in Design Optimization.

DTIC Science & Technology

1983-10-30

processing program(s) engaged in the task of preparing input data for the (finite-element) analysis and optimization phases primary storage the main...and extraction of data from the database for further processing . It can be divided into two phases: a) The process of selection and identification of ...user wishes to stop the reading or the writing process . The meaning of END depends on the method specified for retrieving data: a) Row-wise - then

Cognitive Impairment in Chronic Alcoholics: Some Cause for Optimism.

ERIC Educational Resources Information Center

Goldman, Mark S.

1983-01-01

It appears that, although the cognitive functioning of many alcoholics remains impaired even after drinking has stopped, considerable recovery can occur. New findings now suggest the possibility of reducing cognitive dysfunction and enhancing alcoholism treatment outcomes. (CMG)

Motion Cueing Algorithm Development: Initial Investigation and Redesign of the Algorithms

NASA Technical Reports Server (NTRS)

Telban, Robert J.; Wu, Weimin; Cardullo, Frank M.; Houck, Jacob A. (Technical Monitor)

2000-01-01

In this project four motion cueing algorithms were initially investigated. The classical algorithm generated results with large distortion and delay and low magnitude. The NASA adaptive algorithm proved to be well tuned with satisfactory performance, while the UTIAS adaptive algorithm produced less desirable results. Modifications were made to the adaptive algorithms to reduce the magnitude of undesirable spikes. The optimal algorithm was found to have the potential for improved performance with further redesign. The center of simulator rotation was redefined. More terms were added to the cost function to enable more tuning flexibility. A new design approach using a Fortran/Matlab/Simulink setup was employed. A new semicircular canals model was incorporated in the algorithm. With these changes results show the optimal algorithm has some advantages over the NASA adaptive algorithm. Two general problems observed in the initial investigation required solutions. A nonlinear gain algorithm was developed that scales the aircraft inputs by a third-order polynomial, maximizing the motion cues while remaining within the operational limits of the motion system. A braking algorithm was developed to bring the simulator to a full stop at its motion limit and later release the brake to follow the cueing algorithm output.

Development and psychometric properties of the Suicidality: Treatment Occurring in Paediatrics (STOP) Suicidality Assessment Scale (STOP-SAS) in children and adolescents.

PubMed

Flamarique, I; Santosh, P; Zuddas, A; Arango, C; Purper-Ouakil, D; Hoekstra, P J; Coghill, D; Schulze, U; Dittmann, R W; Buitelaar, J K; Lievesley, K; Frongia, R; Llorente, C; Méndez, I; Sala, R; Fiori, F; Castro-Fornieles, J

2016-12-13

To create a self-reported, internet-based questionnaire for the assessment of suicide risk in children and adolescents. As part of the EU project 'Suicidality: Treatment Occurring in Paediatrics' (STOP project), we developed web-based Patient Reported Outcome Measures (PROMs) for children and adolescents and for proxy reports by parents and clinicians in order to assess suicidality. Based on a literature review, expert panels and focus groups of patients, we developed the items of the STOP Suicidality Assessment Scale (STOP-SAS) in Spanish and English, translated it into four more languages, and optimized it for web-based presentation using the HealthTracker TM platform. Of the total 19 questions developed for the STOP-SAS, four questions that assess low-level suicidality were identified as screening questions (three of them for use with children, and all four for use with adolescents, parents and clinicians). A total of 395 adolescents, 110 children, 637 parents and 716 clinicians completed the questionnaire using the HealthTracker TM , allowing us to evaluate the internal consistency and convergent validity of the STOP-SAS with the clinician-rated Columbia Suicide Severity Rating Scale (C-SSRS). Validity was also assessed with the receiver operating characteristic (ROC) area of the STOP-SAS with the C-SSRS. The STOP-SAS comprises 19 items in its adolescent, parent, and clinician versions, and 14 items in its children's version. Good internal consistency was found for adolescents (Cronbach's alpha: 0.965), children (Cronbach's alpha: 0.922), parents (Cronbach's alpha: 0.951) and clinicians (Cronbach's alpha: 0.955) versions. A strong correlation was found between the STOP-SAS and the C-SSRS for adolescents (r:0.670), parents (r:0.548), clinicians (r:0.863) and children (r:0.654). The ROC area was good for clinicians' (0.917), adolescents' (0.834) and parents' (0.756) versions but only fair (0.683) for children's version. The STOP-SAS is a comprehensive, web-based PROM developed on the HealthTracker TM platform, and co-designed for use by adolescents, children, parents and clinicians. It allows the evaluation of aspects of suicidality and shows good reliability and validity.

So You Need Action!

ERIC Educational Resources Information Center

Snyder, Sarah

A booklet for limited English speakers on dealing with consumer problems provides information on talking to businesses, getting someone on your side, going to the law, and stopping problems before they start. Cartoons, questions about the message in cartoons and narrative passages, checklists on things to consider, and the phonetic pronunciation…

Assignment Choice, Effort, and Assignment Completion: Does Work Ethic Predict Those Who Choose Higher-Effort Assignments?

ERIC Educational Resources Information Center

Parkhurst, John T.; Fleisher, Matthew S.; Skinner, Christopher H.; Woehr, David J.; Hawthorn-Embree, Meredith L.

2011-01-01

After completing the Multidimensional Work-Ethic Profile (MWEP), 98 college students were given a 20-problem math computation assignment and instructed to stop working on the assignment after completing 10 problems. Next, they were allowed to choose to finish either the partially completed assignment that had 10 problems remaining or a new…

Substance abuse in pregnant women. Experiences from a special child welfare clinic in Norway

PubMed Central

Hjerkinn, Bjørg; Lindbæk, Morten; Rosvold, Elin Olaug

2007-01-01

Background Substance abuse during pregnancy may harm the foetus and can cause neonatal abstinence syndrome. Exposure to alcohol and other substances can influence the child for the rest of its life. A special child welfare clinic was set up in 1994 in Kristiansand, Norway, targeting pregnant women with substance abuse problems in the county of Vest-Agder. Pregnancy is not an indication for opioid replacement therapy in Norway, and one of the clinic's aims was to support the drug dependent women through their pregnancy without any replacements. The object of this paper is to describe concurrent health and social problems, as well as the predictors for stopping drug abuse, in the clinic's user group. Methods Retrospective cohort study. Data was gathered from the medical records of all 102 women seen in the clinic in the period between 1992 and 2002. The study includes 59 out of 60 women that were followed until their children were two years old or placed in alternative care, and a comparison group of twice the size. Both groups were presented with a questionnaire concerning both the pregnancy and health and socio-economic issues. Results Four (4.5 percent) of the women that completed their pregnancies did not manage to reduce their substance abuse. All the others reduced their substance abuse considerably. The odds ratio for stopping substance abuse within the first trimester was significantly associated with stopping smoking (O.R. 9.7) or being victims of rape (O.R. 5.3). Conclusion A low cost and low threshold initiative organised as a child welfare clinic may support women with substance abuse problems in their efforts to stop or reduce their substance abuse during pregnancy. PMID:17996120

Improvement and Emergence of Insulin Restriction in Women With Type 1 Diabetes

PubMed Central

Goebel-Fabbri, Ann E.; Anderson, Barbara J.; Fikkan, Janna; Franko, Debra L.; Pearson, Kimberly; Weinger, Katie

2011-01-01

OBJECTIVE To determine the distinguishing characteristics of women who report stopping insulin restriction at 11 years of follow-up from those continuing to endorse insulin restriction as well as those characteristics differing in patients who continue to use insulin appropriately from new insulin restrictors. RESEARCH DESIGN AND METHODS This is an 11-year follow-up study of 207 women with type 1 diabetes. Insulin restriction, diabetes self-care behaviors, diabetes-specific distress, and psychiatric and eating disorder symptoms were assessed using self-report surveys. RESULTS Of the original sample, 57% participated in the follow-up study. Mean age was 44 ± 12 years, diabetes duration was 28 ± 11 years, and A1C was 7.9 ± 1.3%. At follow-up, 20 of 60 baseline insulin restrictors had stopped restriction. Women who stopped reported improved diabetes self-care and distress, fewer problems with diabetes self-management, and lower levels of psychologic distress and eating disorder symptoms. Logistic regression indicated that lower levels of fear of weight gain with improved blood glucose and fewer problems with diabetes self-management predicted stopping restriction. At follow-up, 34 women (23%) reported new restriction, and a larger proportion of new insulin restrictors, relative to nonrestrictors, endorsed fear of weight gain with improved blood glucose. CONCLUSIONS Findings indicate that fear of weight gain associated with improved blood glucose and problems with diabetes self-care are core issues related to both the emergence and resolution of insulin restriction. Greater attention to these concerns may help treatment teams to better meet the unique treatment needs of women struggling with insulin restriction. PMID:21266653

Statistical learning and adaptive decision-making underlie human response time variability in inhibitory control.

PubMed

Ma, Ning; Yu, Angela J

2015-01-01

Response time (RT) is an oft-reported behavioral measure in psychological and neurocognitive experiments, but the high level of observed trial-to-trial variability in this measure has often limited its usefulness. Here, we combine computational modeling and psychophysics to examine the hypothesis that fluctuations in this noisy measure reflect dynamic computations in human statistical learning and corresponding cognitive adjustments. We present data from the stop-signal task (SST), in which subjects respond to a go stimulus on each trial, unless instructed not to by a subsequent, infrequently presented stop signal. We model across-trial learning of stop signal frequency, P(stop), and stop-signal onset time, SSD (stop-signal delay), with a Bayesian hidden Markov model, and within-trial decision-making with an optimal stochastic control model. The combined model predicts that RT should increase with both expected P(stop) and SSD. The human behavioral data (n = 20) bear out this prediction, showing P(stop) and SSD both to be significant, independent predictors of RT, with P(stop) being a more prominent predictor in 75% of the subjects, and SSD being more prominent in the remaining 25%. The results demonstrate that humans indeed readily internalize environmental statistics and adjust their cognitive/behavioral strategy accordingly, and that subtle patterns in RT variability can serve as a valuable tool for validating models of statistical learning and decision-making. More broadly, the modeling tools presented in this work can be generalized to a large body of behavioral paradigms, in order to extract insights about cognitive and neural processing from apparently quite noisy behavioral measures. We also discuss how this behaviorally validated model can then be used to conduct model-based analysis of neural data, in order to help identify specific brain areas for representing and encoding key computational quantities in learning and decision-making.

Stigma-Stop: A Serious Game against the Stigma toward Mental Health in Educational Settings

PubMed Central

Cangas, Adolfo J.; Navarro, Noelia; Parra, José M. A.; Ojeda, Juan J.; Cangas, Diego; Piedra, Jose A.; Gallego, Jose

2017-01-01

This paper presents the results from the application of a serious game called Stigma-Stop among a group of high school students with the aim of reducing the stigma toward mental illnesses. The video game features characters with various mental disorders (schizophrenia, depression, bipolar disorder, and panic disorder with agoraphobia) and provides information about these problems. Additionally, the game asks players about whether they have ever felt the same as the characters, if they believe the characters are psychologically well, and if they think they could help these individuals. Similarly, a variety of reactions are provided for players to choose from when they encounter the characters with these problems. A total of 552 students between the ages of 14 and 18 participated in the study, and they were randomly assigned to either the experimental group, which used Stigma-Stop, or the control group, which utilized a video game completely unrelated to mental health. Both video games were used for similar lengths of time. Following the application of Stigma-Stop, a statistically significant decrease was obtained in levels of stigma toward schizophrenia, both in terms of stereotypes and, to a greater extent, its potential dangerousness. However, this was not the case in the control group. Results thus demonstrate the video game’s usefulness toward eradicating erroneous notions about serious mental disorders like schizophrenia. PMID:28878702

Stigma-Stop: A Serious Game against the Stigma toward Mental Health in Educational Settings.

PubMed

Cangas, Adolfo J; Navarro, Noelia; Parra, José M A; Ojeda, Juan J; Cangas, Diego; Piedra, Jose A; Gallego, Jose

2017-01-01

This paper presents the results from the application of a serious game called Stigma-Stop among a group of high school students with the aim of reducing the stigma toward mental illnesses. The video game features characters with various mental disorders (schizophrenia, depression, bipolar disorder, and panic disorder with agoraphobia) and provides information about these problems. Additionally, the game asks players about whether they have ever felt the same as the characters, if they believe the characters are psychologically well, and if they think they could help these individuals. Similarly, a variety of reactions are provided for players to choose from when they encounter the characters with these problems. A total of 552 students between the ages of 14 and 18 participated in the study, and they were randomly assigned to either the experimental group, which used Stigma-Stop, or the control group, which utilized a video game completely unrelated to mental health. Both video games were used for similar lengths of time. Following the application of Stigma-Stop, a statistically significant decrease was obtained in levels of stigma toward schizophrenia, both in terms of stereotypes and, to a greater extent, its potential dangerousness. However, this was not the case in the control group. Results thus demonstrate the video game's usefulness toward eradicating erroneous notions about serious mental disorders like schizophrenia.

Teaching Database Design with Constraint-Based Tutors

ERIC Educational Resources Information Center

Mitrovic, Antonija; Suraweera, Pramuditha

2016-01-01

Design tasks are difficult to teach, due to large, unstructured solution spaces, underspecified problems, non-existent problem solving algorithms and stopping criteria. In this paper, we comment on our approach to develop KERMIT, a constraint-based tutor that taught database design. In later work, we re-implemented KERMIT as EER-Tutor, and…

Optimal loop placement and models for length - based vehicle classification and stop - and - go traffic.

DOT National Transportation Integrated Search

2011-01-01

Inductive loops are widely used nationwide for traffic monitoring as a data source for a variety of : needs in generating traffic information for operation and planning analysis, validations of travel : demand models, freight studies, pavement design...

Enterprise Analysis of Strategic Airlift to Obtain Competitive Advantage Through Fuel Efficiency

DTIC Science & Technology

2014-09-18

Single Dimension Value Function SFC Specific Fuel Consumption TRANSCAP Transportation System Capability TSP Travelling Salesman Problem VFT...the value posed by limiting intermediate nodes and en route stops. According to Flood (1955), the Travelling Salesman Problem (TSP) was first...B. (1954). The Problem of Routing Aircraft, a Mathematical Solution. (No. P-561). RAND CORP SANTA MONICA CALIF. Flood, M. M. (1956). The Traveling

An efficient, scalable, and adaptable framework for solving generic systems of level-set PDEs

PubMed Central

Mosaliganti, Kishore R.; Gelas, Arnaud; Megason, Sean G.

2013-01-01

In the last decade, level-set methods have been actively developed for applications in image registration, segmentation, tracking, and reconstruction. However, the development of a wide variety of level-set PDEs and their numerical discretization schemes, coupled with hybrid combinations of PDE terms, stopping criteria, and reinitialization strategies, has created a software logistics problem. In the absence of an integrative design, current toolkits support only specific types of level-set implementations which restrict future algorithm development since extensions require significant code duplication and effort. In the new NIH/NLM Insight Toolkit (ITK) v4 architecture, we implemented a level-set software design that is flexible to different numerical (continuous, discrete, and sparse) and grid representations (point, mesh, and image-based). Given that a generic PDE is a summation of different terms, we used a set of linked containers to which level-set terms can be added or deleted at any point in the evolution process. This container-based approach allows the user to explore and customize terms in the level-set equation at compile-time in a flexible manner. The framework is optimized so that repeated computations of common intensity functions (e.g., gradient and Hessians) across multiple terms is eliminated. The framework further enables the evolution of multiple level-sets for multi-object segmentation and processing of large datasets. For doing so, we restrict level-set domains to subsets of the image domain and use multithreading strategies to process groups of subdomains or level-set functions. Users can also select from a variety of reinitialization policies and stopping criteria. Finally, we developed a visualization framework that shows the evolution of a level-set in real-time to help guide algorithm development and parameter optimization. We demonstrate the power of our new framework using confocal microscopy images of cells in a developing zebrafish embryo. PMID:24501592

An efficient, scalable, and adaptable framework for solving generic systems of level-set PDEs.

PubMed

Mosaliganti, Kishore R; Gelas, Arnaud; Megason, Sean G

2013-01-01

In the last decade, level-set methods have been actively developed for applications in image registration, segmentation, tracking, and reconstruction. However, the development of a wide variety of level-set PDEs and their numerical discretization schemes, coupled with hybrid combinations of PDE terms, stopping criteria, and reinitialization strategies, has created a software logistics problem. In the absence of an integrative design, current toolkits support only specific types of level-set implementations which restrict future algorithm development since extensions require significant code duplication and effort. In the new NIH/NLM Insight Toolkit (ITK) v4 architecture, we implemented a level-set software design that is flexible to different numerical (continuous, discrete, and sparse) and grid representations (point, mesh, and image-based). Given that a generic PDE is a summation of different terms, we used a set of linked containers to which level-set terms can be added or deleted at any point in the evolution process. This container-based approach allows the user to explore and customize terms in the level-set equation at compile-time in a flexible manner. The framework is optimized so that repeated computations of common intensity functions (e.g., gradient and Hessians) across multiple terms is eliminated. The framework further enables the evolution of multiple level-sets for multi-object segmentation and processing of large datasets. For doing so, we restrict level-set domains to subsets of the image domain and use multithreading strategies to process groups of subdomains or level-set functions. Users can also select from a variety of reinitialization policies and stopping criteria. Finally, we developed a visualization framework that shows the evolution of a level-set in real-time to help guide algorithm development and parameter optimization. We demonstrate the power of our new framework using confocal microscopy images of cells in a developing zebrafish embryo.

Feedback brake distribution control for minimum pitch

NASA Astrophysics Data System (ADS)

Tavernini, Davide; Velenis, Efstathios; Longo, Stefano

2017-06-01

The distribution of brake forces between front and rear axles of a vehicle is typically specified such that the same level of brake force coefficient is imposed at both front and rear wheels. This condition is known as 'ideal' distribution and it is required to deliver the maximum vehicle deceleration and minimum braking distance. For subcritical braking conditions, the deceleration demand may be delivered by different distributions between front and rear braking forces. In this research we show how to obtain the optimal distribution which minimises the pitch angle of a vehicle and hence enhances driver subjective feel during braking. A vehicle model including suspension geometry features is adopted. The problem of the minimum pitch brake distribution for a varying deceleration level demand is solved by means of a model predictive control (MPC) technique. To address the problem of the undesirable pitch rebound caused by a full-stop of the vehicle, a second controller is designed and implemented independently from the braking distribution in use. An extended Kalman filter is designed for state estimation and implemented in a high fidelity environment together with the MPC strategy. The proposed solution is compared with the reference 'ideal' distribution as well as another previous feed-forward solution.

On the Use of Stagewise Regression in Random Balance Screening Experiments.

DTIC Science & Technology

1983-05-01

each F-test at the same sig- nificance level, a . We tested for significance at the following eight a levels : .05, .40 (.05) . These same a levels were...observed significance levels associated with the SFT method agree closely with the various a levels employed. The observed sig- nificance levels...associated with the SR method, however, are significantly larger than the a levels that define the stopping rules. This problem is lWe stop at the stage where

Coming safely to a stop: a review of platelet activity after cessation of antiplatelet drugs.

PubMed

Ford, Isobel

2015-08-01

The platelet P2Y12 antagonists are widely used, usually in combination with aspirin, to prevent atherothrombotic events in patients with acute coronary syndromes during percutaneous coronary intervention and after placement of arterial stents. Inhibition by clopidogrel or prasugrel lasts for the lifetime of the affected platelets and platelet haemostatic function gradually recovers after stopping the drug, as new unaffected platelets are formed. The optimal durations for dual antiplatelet therapy are prescribed by clinical guidelines. Continuation beyond the recommended duration is associated with an increased mortality, mainly associated with major bleeding. Fear of a 'rebound' of prothrombotic platelet activity on stopping the drug has provoked much discussion and many studies. However, review of the available literature reveals no evidence for production of hyper-reactive platelets after cessation of clopidogrel in patients who are stable. Any increase in acute coronary and other vascular events after stopping seems most likely therefore to be due to premature discontinuation or disruption of treatment while thrombotic risk is still high. No difference in rebound was found with the newer P2Y12 inhibitors, although ticagrelor and prasugrel are more potent platelet inhibitors than clopidogrel. Recent randomized controlled trials confirm it is safe to stop the thienopyridine and continue with aspirin alone in most patients after the duration of treatment recommended by the guidelines. Decisions on when to stop therapy in individuals, however, remain challenging and there is a growing rationale for platelet testing to assist clinical judgement in certain situations such as patients stopping dual antiplatelet therapy before surgery or in individuals at highest bleeding or thrombotic risk.

Reach of the high-energy LHC for gluinos and top squarks in SUSY models with light Higgsinos

NASA Astrophysics Data System (ADS)

Baer, Howard; Barger, Vernon; Gainer, James S.; Serce, Hasan; Tata, Xerxes

2017-12-01

We examine the top squark (stop) and gluino reach of the proposed 33 TeV energy upgrade of the Large Hadron Collider (LHC33) in the Minimal Supersymmetric Standard Model (MSSM) with light Higgsinos and relatively heavy electroweak gauginos. In our analysis, we assume that stops decay to Higgsinos via t˜1→t Z˜1, t˜1→t Z˜2, and t˜1→b W˜1 with branching fractions in the ratio 1 ∶1 ∶2 (expected if the decay occurs dominantly via the superpotential Yukawa coupling), while gluinos decay via g ˜→t t˜1 or via three-body decays to third-generation quarks plus Higgsinos. These decay patterns are motivated by models of natural supersymmetry where Higgsinos are expected to be close in mass to mZ, but gluinos may be as heavy as 5-6 TeV, and stops may have masses up to ˜3 TeV . We devise cuts to optimize the signals from stop and gluino pair production at LHC33. We find that experiments at LHC33 should be able to discover stops with >5 σ significance if mt˜1<2.3 (2.8) [3.2] TeV for an integrated luminosity of 0.3 (1) [3 ] ab-1 . The corresponding reach for gluinos extends to 5 (5.5) [6] TeV. These results imply that experiments at LHC33 should be able to discover at least one of the stop or gluino pair signals even with an integrated luminosity of 0.3 ab-1 for natural supersymmetry models with no worse than 3% electroweak fine-tuning and quite likely both gluinos and stops for an integrated luminosity of 3 ab-1 .

Determining Optimal Location and Numbers of Sample Transects for Characterization of UXO Sites

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

BILISOLY, ROGER L.; MCKENNA, SEAN A.

2003-01-01

Previous work on sample design has been focused on constructing designs for samples taken at point locations. Significantly less work has been done on sample design for data collected along transects. A review of approaches to point and transect sampling design shows that transects can be considered as a sequential set of point samples. Any two sampling designs can be compared through using each one to predict the value of the quantity being measured on a fixed reference grid. The quality of a design is quantified in two ways: computing either the sum or the product of the eigenvalues ofmore » the variance matrix of the prediction error. An important aspect of this analysis is that the reduction of the mean prediction error variance (MPEV) can be calculated for any proposed sample design, including one with straight and/or meandering transects, prior to taking those samples. This reduction in variance can be used as a ''stopping rule'' to determine when enough transect sampling has been completed on the site. Two approaches for the optimization of the transect locations are presented. The first minimizes the sum of the eigenvalues of the predictive error, and the second minimizes the product of these eigenvalues. Simulated annealing is used to identify transect locations that meet either of these objectives. This algorithm is applied to a hypothetical site to determine the optimal locations of two iterations of meandering transects given a previously existing straight transect. The MPEV calculation is also used on both a hypothetical site and on data collected at the Isleta Pueblo to evaluate its potential as a stopping rule. Results show that three or four rounds of systematic sampling with straight parallel transects covering 30 percent or less of the site, can reduce the initial MPEV by as much as 90 percent. The amount of reduction in MPEV can be used as a stopping rule, but the relationship between MPEV and the results of excavation versus no-further-action decisions is site specific and cannot be calculated prior to the sampling. It may be advantageous to use the reduction in MPEV as a stopping rule for systematic sampling across the site that can then be followed by focused sampling in areas identified has having UXO during the systematic sampling. The techniques presented here provide answers to the questions of ''Where to sample?'' and ''When to stop?'' and are capable of running in near real time to support iterative site characterization campaigns.« less

An exploration of the relationship between postnatal distress and maternal role attainment, breast feeding problems and breast feeding cessation in Australia.

PubMed

Cooke, Margaret; Schmied, Virginia; Sheehan, Athena

2007-03-01

To explore the relationships between maternal distress, breast feeding cessation, breast feeding problems and breast feeding maternal role attainment. Longitudinal cohort study. Three urban hospitals within Sydney, Australia. 449 women were invited to participate in the study, with an 81% response rate. Self-report questionnaires were used to collect the data in pregnancy (28-36 weeks) and 2 weeks and 3 months after birth. The Edinburgh Postnatal Depression Scale (EPDS) was used to measure postnatal distress, and the Maternal Role Attainment subscale (MRA) of the Maternal Breast Feeding Evaluation Scale (MBFES) was used to measure breast feeding maternal role attainment. Women with high MRA were less likely to stop breast feeding (even when they had breast feeding problems) than women with low MRA. Antenatal EPDS and anxiety scores were not related to breast feeding cessation or breast feeding problems when analysed alone. As hypothesised, the relationship between breast feeding cessation and postnatal distress (EPDS scores) varied according to MRA level. Women who were categorised as high MRA and no longer breast feeding had higher EPDS scores and were more likely to be categorised as distressed (36%) than women who had low MRA (<12%) or women who had high MRA and continued to breast feed (7%). There is a complex relationship between maternal identity, stopping breast feeding earlier than desired, and psychological distress. Women with strong beliefs about the importance of breast feeding to their maternal role may benefit from psychological assessment and support should they decide to stop breast feeding earlier.

Predictors of Graduation of Readmitted "At Risk" College Students

ERIC Educational Resources Information Center

Berkovitz, Roslyn A.; O'Quin, Karen

2007-01-01

We conducted an archival study of at-risk students who had "stopped out" of college for many reasons (academic dismissal, financial problems, personal problems, etc.) and who later were accepted to return to school. Approximately 27% of the accepted students chose not to return. Those who returned had higher grade point averages, had completed…

Partial differential equations constrained combinatorial optimization on an adiabatic quantum computer

NASA Astrophysics Data System (ADS)

Chandra, Rishabh

Partial differential equation-constrained combinatorial optimization (PDECCO) problems are a mixture of continuous and discrete optimization problems. PDECCO problems have discrete controls, but since the partial differential equations (PDE) are continuous, the optimization space is continuous as well. Such problems have several applications, such as gas/water network optimization, traffic optimization, micro-chip cooling optimization, etc. Currently, no efficient classical algorithm which guarantees a global minimum for PDECCO problems exists. A new mapping has been developed that transforms PDECCO problem, which only have linear PDEs as constraints, into quadratic unconstrained binary optimization (QUBO) problems that can be solved using an adiabatic quantum optimizer (AQO). The mapping is efficient, it scales polynomially with the size of the PDECCO problem, requires only one PDE solve to form the QUBO problem, and if the QUBO problem is solved correctly and efficiently on an AQO, guarantees a global optimal solution for the original PDECCO problem.

Sustainable Mobility Initiative | Transportation Research | NREL

Science.gov Websites

optimize mobility and significantly reduce related energy consumption. This concept of an intelligent measures to explore these technologies' effects on transportation energy use, emissions, and overall system . Efficient driving with smoother starts, stops, and accelerations to reduce energy consumption and

SU-C-204-02: Improved Patient-Specific Optimization of the Stopping Power Calibration for Proton Therapy Planning Using a Single Proton Radiography

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

Rinaldi, I; Ludwig Maximilian University, Garching, DE; Heidelberg University Hospital, Heidelberg, DE

2015-06-15

Purpose: We present an improved method to calculate patient-specific calibration curves to convert X-ray computed tomography (CT) Hounsfield Unit (HU) to relative stopping powers (RSP) for proton therapy treatment planning. Methods: By optimizing the HU-RSP calibration curve, the difference between a proton radiographic image and a digitally reconstructed X-ray radiography (DRR) is minimized. The feasibility of this approach has previously been demonstrated. This scenario assumes that all discrepancies between proton radiography and DRR originate from uncertainties in the HU-RSP curve. In reality, external factors cause imperfections in the proton radiography, such as misalignment compared to the DRR and unfaithful representationmore » of geometric structures (“blurring”). We analyze these effects based on synthetic datasets of anthropomorphic phantoms and suggest an extended optimization scheme which explicitly accounts for these effects. Performance of the method is been tested for various simulated irradiation parameters. The ultimate purpose of the optimization is to minimize uncertainties in the HU-RSP calibration curve. We therefore suggest and perform a thorough statistical treatment to quantify the accuracy of the optimized HU-RSP curve. Results: We demonstrate that without extending the optimization scheme, spatial blurring (equivalent to FWHM=3mm convolution) in the proton radiographies can cause up to 10% deviation between the optimized and the ground truth HU-RSP calibration curve. Instead, results obtained with our extended method reach 1% or better correspondence. We have further calculated gamma index maps for different acceptance levels. With DTA=0.5mm and RD=0.5%, a passing ratio of 100% is obtained with the extended method, while an optimization neglecting effects of spatial blurring only reach ∼90%. Conclusion: Our contribution underlines the potential of a single proton radiography to generate a patient-specific calibration curve and to improve dose delivery by optimizing the HU-RSP calibration curve as long as all sources of systematic incongruence are properly modeled.« less

Self-harm

MedlinePlus

... have trouble stopping. Examples of self-harm include Cutting yourself (such as using a razor blade, knife, ... them a sense of relief. Some people use cutting as a means to cope with a problem. ...

About Stressful Situations

MedlinePlus

... Coping Skills (cont.) 2. Commit to a Positive Attitude A positive attitude helps stop you from being dragged down by unhappy feelings. A positive attitude also boosts the problem solving that a stressful ...

Testing calibration routines for LISFLOOD, a distributed hydrological model

NASA Astrophysics Data System (ADS)

Pannemans, B.

2009-04-01

Traditionally hydrological models are considered as difficult to calibrate: their highly non-linearity results in rugged and rough response surfaces were calibration algorithms easily get stuck in local minima. For the calibration of distributed hydrological models two extra factors play an important role: on the one hand they are often costly on computation, thus restricting the feasible number of model runs; on the other hand their distributed nature smooths the response surface, thus facilitating the search for a global minimum. Lisflood is a distributed hydrological model currently used for the European Flood Alert System - EFAS (Van der Knijff et al, 2008). Its upcoming recalibration over more then 200 catchments, each with an average runtime of 2-3 minutes, proved a perfect occasion to put several existing calibration algorithms to the test. The tested routines are Downhill Simplex (DHS, Nelder and Mead, 1965), SCEUA (Duan et Al. 1993), SCEM (Vrugt et al., 2003) and AMALGAM (Vrugt et al., 2008), and they were evaluated on their capability to efficiently converge onto the global minimum and on the spread in the found solutions in repeated runs. The routines were let loose on a simple hyperbolic function, on a Lisflood catchment using model output as observation, and on two Lisflood catchments using real observations (one on the river Inn in the Alps, the other along the downstream stretch of the Elbe). On the mathematical problem and on the catchment with synthetic observations DHS proved to be the fastest and the most efficient in finding a solution. SCEUA and AMALGAM are a slower, but while SCEUA keeps converging on the exact solution, AMALGAM slows down after about 600 runs. For the Lisflood models with real-time observations AMALGAM (hybrid algorithm that combines several other algorithms, we used CMA, PSO and GA) came as fastest out of the tests, and giving comparable results in consecutive runs. However, some more work is needed to tweak the stopping criteria. SCEUA is a bit slower, but has very transparent stopping rules. Both have closed in on the minima after about 600 runs. DHS equals only SCEUA on convergence speed. The stopping criteria we applied so far are too strict, causing it to stop too early. SCEM converges 5-6 times slower. This is a high price for the parameter uncertainty analysis that is simultaneously done. The ease with which all algorithms find the same optimum suggests that we are dealing with a smooth and relatively simple response surface. This leaves room for other deterministic calibration algorithms being smarter than DHS in sliding downhill. PEST seems promising but sofar we haven't managed to get it running with LISFLOOD. • Duan, Q.; Gupta, V. & Sorooshian, S., 1993, Shuffled complex evolution approach for effective and efficient global minimization, J Optim Theory Appl, Kluwer Academic Publishers-Plenum Publishers, 76, 501-521 • Nelder, J. & Mead, R., 1965, A simplex method for function minimization, Comput. J., 7, 308-313 • Van Der Knijff, J. M.; Younis, J. & De Roo, A. P. J., 2008, LISFLOOD: a GIS-based distributed model for river basin scale water balance and flood simulation, International Journal of Geographical Information Science, • Vrugt, J.; Gupta, H.; Bouten, W. & Sorooshian, S., 2003, A Shuffled Complex Evolution Metropolis algorithm for optimization and uncertainty assessment of hydrologic model parameters, Water Resour. Res., 39 • Vrugt, J.; Robinson, B. & Hyman, J., 2008, Self-Adaptive Multimethod Search for Global Optimization in Real-Parameter Spaces, IEEE Trans Evol Comput, IEEE,

Thought stopping and supportive therapy can reduce postpartum blues and anxiety parents of premature babies.

PubMed

Laela, Sri; Anna Keliat, Budi; Mustikasari

2018-02-01

The parents of premature baby tend to be at risk undergoing postpartum blues and anxiety. It is due to many problems faced by postpartum mother of premature baby. This research is aim to identifying influence of thought stopping and supportive therapy of postpartum blues and anxiety parents of premature babies. This is quantitative with quasi-experiment with control group pretest-posttest design and consecutive sampling method. Sample in this research are 62 postpartum mothers of premature babies in perinatal NICU (neonatal intensive care unit). The results show that there is significant decrease of postpartum blues and anxiety (p value = 0.000) in the group that was treated by using nursing intervention, thought stopping and supportive therapy and greater significant decrease than the group that was only treated by nursing intervention. Thought stopping and supportive therapy are able to decrease postpartum blues and anxiety parents of premature babies. Copyright © 2018 Elsevier España, S.L.U. All rights reserved.

Problem Periods

MedlinePlus

... ovary syndrome. Read our information on PCOS for teens , and see your doctor if you think you may have PCOS. Major weight loss. Girls who have anorexia will often stop having periods. When to see ...

Propranolol (Infantile Hemangioma)

MedlinePlus

... or has had asthma or other breathing problems, pheochromocytoma (a tumor on a small gland near the ... color sweating irritability decreased appetite low body temperature unusual sleepiness breathing stops for short periods of time ...

Parkinson disease - discharge

MedlinePlus

... medicines can lead to risky behaviors such as gambling. Make sure you follow instructions. DO NOT stop ... out of your bed or chair Problems with thinking of becoming confused Pain that is becoming worse ...

Pregnancy - health risks

MedlinePlus

... drugs, stop drinking alcohol, and limit caffeine and coffee. Talk to your health care provider about any ... problems with the unborn baby. Smoking, alcohol, and marijuana use have also been shown to lower sperm ...

Models of inhibitory control

PubMed Central

Logan, Gordon D.

2017-01-01

We survey models of response inhibition having different degrees of mathematical, computational and neurobiological specificity and generality. The independent race model accounts for performance of the stop-signal or countermanding task in terms of a race between GO and STOP processes with stochastic finishing times. This model affords insights into neurophysiological mechanisms that are reviewed by other authors in this volume. The formal link between the abstract GO and STOP processes and instantiating neural processes is articulated through interactive race models consisting of stochastic accumulator GO and STOP units. This class of model provides quantitative accounts of countermanding performance and replicates the dynamics of neural activity producing that performance. The interactive race can be instantiated in a network of biophysically plausible spiking excitatory and inhibitory units. Other models seek to account for interactions between units in frontal cortex, basal ganglia and superior colliculus. The strengths, weaknesses and relationships of the different models will be considered. We will conclude with a brief survey of alternative modelling approaches and a summary of problems to be addressed including accounting for differences across effectors, species, individuals, task conditions and clinical deficits. This article is part of the themed issue ‘Movement suppression: brain mechanisms for stopping and stillness’. PMID:28242727

Management of multiple sclerosis: the role of coping self-efficacy and self-esteem.

PubMed

Mikula, Pavol; Nagyova, Iveta; Vitkova, Marianna; Szilasiova, Jarmila

2018-02-07

Patients with multiple sclerosis (MS) engage in various coping behaviours in order to manage their disease. The aim of this study is to find out if the self-esteem of patients is associated with coping strategies - problem-focused (e.g. making a plan of action when confronted with a problem); emotion focused (e.g. get emotional support from community); and focused on stopping unpleasant emotions and thoughts (e.g. keeping oneself from feeling sad), and if it can enhance or hinder coping efforts in the disease management. We collected data from 155 consecutive MS patients who completed the Coping Self-Efficacy Scale (CSE) and the Rosenberg Self-esteem Scale (RSE). Explained variance for problem-focused coping, emotion-focused coping, and coping focused on stopping unpleasant emotions and thoughts was 33, 24, and 31%, respectively. Self-esteem seems to be associated with coping strategies indicating that feelings of self-worth are linked with the ability to handle difficult life situations and can be helpful in chronic disease management.

Ovarian Disorders

MedlinePlus

... a pregnancy can occur. Ovaries also make the female hormones estrogen and progesterone. When a woman goes through menopause, her ovaries stop making those hormones and releasing eggs. Problems with the ovaries include Ovarian cancer Ovarian ...

Collective Deceleration: Toward a Compact Beam Dump

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

Wu, H.-C.; /Munich, Max Planck Inst. Quantenopt.; Tajima, T.

With the increasing development of laser accelerators, the electron energy is already beyond GeV and even higher in near future. Conventional beam dump based on ionization or radiation loss mechanism is cumbersome and costly, also has radiological hazards. We revisit the stopping power of high-energy charged particles in matter and discuss the associated problem of beam dump from the point of view of collective deceleration. The collective stopping length in an ionized gas can be several orders of magnitude shorter than the Bethe-Bloch and multiple electromagnetic cascades stopping length in solid. At the mean time, the tenuous density of themore » gas makes the radioactivation negligible. Such a compact and non-radioactivating beam dump works well for short and dense bunches, which is typically generated from laser wakefield accelerator.« less

Material elemental decomposition in dual and multi-energy CT via a sparsity-dictionary approach for proton stopping power ratio calculation.

PubMed

Shen, Chenyang; Li, Bin; Chen, Liyuan; Yang, Ming; Lou, Yifei; Jia, Xun

2018-04-01

Accurate calculation of proton stopping power ratio (SPR) relative to water is crucial to proton therapy treatment planning, since SPR affects prediction of beam range. Current standard practice derives SPR using a single CT scan. Recent studies showed that dual-energy CT (DECT) offers advantages to accurately determine SPR. One method to further improve accuracy is to incorporate prior knowledge on human tissue composition through a dictionary approach. In addition, it is also suggested that using CT images with multiple (more than two) energy channels, i.e., multi-energy CT (MECT), can further improve accuracy. In this paper, we proposed a sparse dictionary-based method to convert CT numbers of DECT or MECT to elemental composition (EC) and relative electron density (rED) for SPR computation. A dictionary was constructed to include materials generated based on human tissues of known compositions. For a voxel with CT numbers of different energy channels, its EC and rED are determined subject to a constraint that the resulting EC is a linear non-negative combination of only a few tissues in the dictionary. We formulated this as a non-convex optimization problem. A novel algorithm was designed to solve the problem. The proposed method has a unified structure to handle both DECT and MECT with different number of channels. We tested our method in both simulation and experimental studies. Average errors of SPR in experimental studies were 0.70% in DECT, 0.53% in MECT with three energy channels, and 0.45% in MECT with four channels. We also studied the impact of parameter values and established appropriate parameter values for our method. The proposed method can accurately calculate SPR using DECT and MECT. The results suggest that using more energy channels may improve the SPR estimation accuracy. © 2018 American Association of Physicists in Medicine.

Hybrid optimal scheduling for intermittent androgen suppression of prostate cancer

NASA Astrophysics Data System (ADS)

Hirata, Yoshito; di Bernardo, Mario; Bruchovsky, Nicholas; Aihara, Kazuyuki

2010-12-01

We propose a method for achieving an optimal protocol of intermittent androgen suppression for the treatment of prostate cancer. Since the model that reproduces the dynamical behavior of the surrogate tumor marker, prostate specific antigen, is piecewise linear, we can obtain an analytical solution for the model. Based on this, we derive conditions for either stopping or delaying recurrent disease. The solution also provides a design principle for the most favorable schedule of treatment that minimizes the rate of expansion of the malignant cell population.

Stopping hormone replacement therapy: were women ill advised?

PubMed

Cumming, Grant P; Currie, Heather D; Panay, Nick; Moncur, Rik; Lee, Amanda J

2011-09-01

To survey women who stopped hormone replacement therapy (HRT) after 2002, including those who later restarted. A questionnaire on the UK-based menopause website www.menopausematters.co.uk evaluating how women are influenced by HRT advice. Main outcome measures Answers to questions regarding stopping/restarting HRT in response to the advice in the early 2000s and advice given today. A total of 1100 responses were obtained. Of those who made the decision to stop HRT themselves, 56.4% (n = 425/754) said that they were influenced by the media. In those who would potentially most benefit from HRT, 72.8% (n = 220/302) stopped without medical advice. Overall, women aged under 50 years were significantly more likely to stop HRT themselves than women over 50 (P < 0.001). In women in whom symptoms returned, 37.5% (n = 362/966) said these affected their ability to work, 45.1% (n = 436) had problems with decision-making, 53.6% (n = 518) admitted to relationships being negatively affected and 29.2% (n = 286) said that symptoms affected their social relationships. Overall 46.5% of women (n = 485/1044) would not have stopped HRT given the current understanding of risk. Compared with women over 50, significantly more women under the age of 50 said that they would not have previously stopped their HRT based on their current understanding of risk (P < 0.001). The negative impact of published research and its reporting from the early 2000s are being mitigated by current press coverage. Media reports appear to influence the younger woman more than the older woman. Health professionals and media must learn the lessons from the past.

Kids at Hope: All Children Are Capable of Success--No Exceptions!

ERIC Educational Resources Information Center

Tipps, Christine R.

2006-01-01

How has our society typically responded to the challenging problems facing youths? Communities have, more often than not, focused resources on prevention programs that have attempted to stop youths from taking drugs, joining gangs, getting pregnant, and dropping out of school, among other things. A problem is identified, and the response is to…

When to stop managing or surveying cryptic threatened species

PubMed Central

Chadès, Iadine; McDonald-Madden, Eve; McCarthy, Michael A.; Wintle, Brendan; Linkie, Matthew; Possingham, Hugh P.

2008-01-01

Threatened species become increasingly difficult to detect as their populations decline. Managers of such cryptic threatened species face several dilemmas: if they are not sure the species is present, should they continue to manage for that species or invest the limited resources in surveying? We find optimal solutions to this problem using a Partially Observable Markov Decision Process and rules of thumb derived from an analytical approximation. We discover that managing a protected area for a cryptic threatened species can be optimal even if we are not sure the species is present. The more threatened and valuable the species is, relative to the costs of management, the more likely we are to manage this species without determining its continued persistence by using surveys. If a species remains unseen, our belief in the persistence of the species declines to a point where the optimal strategy is to shift resources from saving the species to surveying for it. Finally, when surveys lead to a sufficiently low belief that the species is extant, we surrender resources to other conservation actions. We illustrate our findings with a case study using parameters based on the critically endangered Sumatran tiger (Panthera tigris sumatrae), and we generate rules of thumb on how to allocate conservation effort for any cryptic species. Using Partially Observable Markov Decision Processes in conservation science, we determine the conditions under which it is better to abandon management for that species because our belief that it continues to exist is too low. PMID:18779594

Smart sensing to drive real-time loads scheduling algorithm in a domotic architecture

NASA Astrophysics Data System (ADS)

Santamaria, Amilcare Francesco; Raimondo, Pierfrancesco; De Rango, Floriano; Vaccaro, Andrea

2014-05-01

Nowadays the focus on power consumption represent a very important factor regarding the reduction of power consumption with correlated costs and the environmental sustainability problems. Automatic control load based on power consumption and use cycle represents the optimal solution to costs restraint. The purpose of these systems is to modulate the power request of electricity avoiding an unorganized work of the loads, using intelligent techniques to manage them based on real time scheduling algorithms. The goal is to coordinate a set of electrical loads to optimize energy costs and consumptions based on the stipulated contract terms. The proposed algorithm use two new main notions: priority driven loads and smart scheduling loads. The priority driven loads can be turned off (stand by) according to a priority policy established by the user if the consumption exceed a defined threshold, on the contrary smart scheduling loads are scheduled in a particular way to don't stop their Life Cycle (LC) safeguarding the devices functions or allowing the user to freely use the devices without the risk of exceeding the power threshold. The algorithm, using these two kind of notions and taking into account user requirements, manages loads activation and deactivation allowing the completion their operation cycle without exceeding the consumption threshold in an off-peak time range according to the electricity fare. This kind of logic is inspired by industrial lean manufacturing which focus is to minimize any kind of power waste optimizing the available resources.

When to stop managing or surveying cryptic threatened species.

PubMed

Chadès, Iadine; McDonald-Madden, Eve; McCarthy, Michael A; Wintle, Brendan; Linkie, Matthew; Possingham, Hugh P

2008-09-16

Threatened species become increasingly difficult to detect as their populations decline. Managers of such cryptic threatened species face several dilemmas: if they are not sure the species is present, should they continue to manage for that species or invest the limited resources in surveying? We find optimal solutions to this problem using a Partially Observable Markov Decision Process and rules of thumb derived from an analytical approximation. We discover that managing a protected area for a cryptic threatened species can be optimal even if we are not sure the species is present. The more threatened and valuable the species is, relative to the costs of management, the more likely we are to manage this species without determining its continued persistence by using surveys. If a species remains unseen, our belief in the persistence of the species declines to a point where the optimal strategy is to shift resources from saving the species to surveying for it. Finally, when surveys lead to a sufficiently low belief that the species is extant, we surrender resources to other conservation actions. We illustrate our findings with a case study using parameters based on the critically endangered Sumatran tiger (Panthera tigris sumatrae), and we generate rules of thumb on how to allocate conservation effort for any cryptic species. Using Partially Observable Markov Decision Processes in conservation science, we determine the conditions under which it is better to abandon management for that species because our belief that it continues to exist is too low.

Sudden Cardiac Arrest

MedlinePlus

... SCA. Physical stress, which can cause the heart’s electrical system to stop working. In people who already ... the heart’s structure may cause problems with its electrical system, increasing the risk of arrhythmias. What are ...

Preventing Stroke Deaths

MedlinePlus

... Kit Read the MMWR Science Clips Preventing Stroke Deaths Progress Stalled Language: English (US) Español (Spanish) Recommend ... states. 80% of strokes are preventable. Problem Stroke deaths have stopped declining. Strokes are common and preventable. ...

Answering Questions About Underage Drinking

MedlinePlus

... Legal Drinking Age Dangers of Teen Drinking Alcohol Laws by State Stopping Teens’ Easy Access to Alcohol ... drinking is not a serious problem? Despite the law, the statistics, and the science, some people still ...

Image denoising by a direct variational minimization

NASA Astrophysics Data System (ADS)

Janev, Marko; Atanacković, Teodor; Pilipović, Stevan; Obradović, Radovan

2011-12-01

In this article we introduce a novel method for the image de-noising which combines a mathematically well-posdenes of the variational modeling with the efficiency of a patch-based approach in the field of image processing. It based on a direct minimization of an energy functional containing a minimal surface regularizer that uses fractional gradient. The minimization is obtained on every predefined patch of the image, independently. By doing so, we avoid the use of an artificial time PDE model with its inherent problems of finding optimal stopping time, as well as the optimal time step. Moreover, we control the level of image smoothing on each patch (and thus on the whole image) by adapting the Lagrange multiplier using the information on the level of discontinuities on a particular patch, which we obtain by pre-processing. In order to reduce the average number of vectors in the approximation generator and still to obtain the minimal degradation, we combine a Ritz variational method for the actual minimization on a patch, and a complementary fractional variational principle. Thus, the proposed method becomes computationally feasible and applicable for practical purposes. We confirm our claims with experimental results, by comparing the proposed method with a couple of PDE-based methods, where we get significantly better denoising results specially on the oscillatory regions.

The Montana Wild Virus Hunt | NIH MedlinePlus the Magazine

MedlinePlus

... you respect (i.e., mentors), striking a productive balance between healthy skepticism and blind optimism (i.e., know when to walk away). Pursue your research with vigor and never stop asking questions. Find Out More National Institute of General Medical Sciences Summer 2017 Issue: Volume 12 Number ...

Justice: A Problem for Military Ethics during Irregular War

DTIC Science & Technology

2008-05-22

monograph directly addresses the problem posed when considering the question ‘Who says what right is?’ or ‘Justice according to whom?’ The relative...nature of the term ‘justice’ creates a problem for military ethics, particularly when soldiers try to determine what actions are morally acceptable... What can stop this slide into strict formalism, where law eclipses ethics? The research conducted for this monograph has led the author to believe

Dual-scale topology optoelectronic processor.

PubMed

Marsden, G C; Krishnamoorthy, A V; Esener, S C; Lee, S H

1991-12-15

The dual-scale topology optoelectronic processor (D-STOP) is a parallel optoelectronic architecture for matrix algebraic processing. The architecture can be used for matrix-vector multiplication and two types of vector outer product. The computations are performed electronically, which allows multiplication and summation concepts in linear algebra to be generalized to various nonlinear or symbolic operations. This generalization permits the application of D-STOP to many computational problems. The architecture uses a minimum number of optical transmitters, which thereby reduces fabrication requirements while maintaining area-efficient electronics. The necessary optical interconnections are space invariant, minimizing space-bandwidth requirements.

Types of hormone therapy

MedlinePlus

Menopause symptoms include: Hot flashes Night sweats Sleep problems Vaginal dryness Anxiety Moodiness Less interest in sex After menopause, your body stops making estrogen and progesterone. HT can treat menopause symptoms that bother you. HT does ...

The Forced Marriage of Minors: A Neglected Form of Child Abuse.

PubMed

Kopelman, Loretta M

2016-03-01

The forced marriage of minors is child abuse, consequently duties exist to stop them. Yet over 14 million forced marriages of minors occur annually in developing countries. The American Bar Association (ABA) concludes that the problem in the US is significant, widespread but largely ignored, and that few US laws protect minors from forced marriages. Although their best chance of rescue often involves visits to health care providers, US providers show little awareness of this growing problem. Strategies discussed to stop forced marriages include recommendations from the UN, the ABA, and the UK. The author anticipates and responds to criticisms that first, no duty to intervene exists without better laws and practice guidelines; and second, that such marriages are not child abuse in traditions where parental rights or familism allegedly justify them. © 2016 American Society of Law, Medicine & Ethics.

Multiple-vehicle collision induced by a sudden stop in traffic flow

NASA Astrophysics Data System (ADS)

Sugiyama, Naoki; Nagatani, Takashi

2012-04-01

We study the dynamic process of the multiple-vehicle collision when a vehicle stops suddenly in a traffic flow. We apply the optimal-velocity model to the vehicular motion. If a vehicle does not decelerate successfully, it crashes into the vehicle ahead with a residual speed. The collision criterion is presented by vi(t)/Δxi(t)→∞ if Δxi(t)→0 where vi(t) and Δxi(t) are the speed and headway of vehicle i at time t. The number of crumpled vehicles depends on the initial velocity, the sensitivity, and the initial headway. We derive the region map (or phase diagram) for the multiple-vehicle collision.

On the Minimum Induced Drag of Wings

NASA Technical Reports Server (NTRS)

Bowers, Albion H.

2010-01-01

Of all the types of drag, induced drag is associated with the creation and generation of lift over wings. Induced drag is directly driven by the span load that the aircraft is flying at. The tools by which to calculate and predict induced drag we use were created by Ludwig Prandtl in 1903. Within a decade after Prandtl created a tool for calculating induced drag, Prandtl and his students had optimized the problem to solve the minimum induced drag for a wing of a given span, formalized and written about in 1920. This solution is quoted in textbooks extensively today. Prandtl did not stop with this first solution, and came to a dramatically different solution in 1932. Subsequent development of this 1932 solution solves several aeronautics design difficulties simultaneously, including maximum performance, minimum structure, minimum drag loss due to control input, and solution to adverse yaw without a vertical tail. This presentation lists that solution by Prandtl, and the refinements by Horten, Jones, Kline, Viswanathan, and Whitcomb

On the Minimum Induced Drag of Wings -or- Thinking Outside the Box

NASA Technical Reports Server (NTRS)

Bowers, Albion H.

2011-01-01

Of all the types of drag, induced drag is associated with the creation and generation of lift over wings. Induced drag is directly driven by the span load that the aircraft is flying at. The tools by which to calculate and predict induced drag we use were created by Ludwig Prandtl in 1903. Within a decade after Prandtl created a tool for calculating induced drag, Prandtl and his students had optimized the problem to solve the minimum induced drag for a wing of a given span, formalized and written about in 1920. This solution is quoted in textbooks extensively today. Prandtl did not stop with this first solution, and came to a dramatically different solution in 1932. Subsequent development of this 1932 solution solves several aeronautics design difficulties simultaneously, including maximum performance, minimum structure, minimum drag loss due to control input, and solution to adverse yaw without a vertical tail. This presentation lists that solution by Prandtl, and the refinements by Horten, Jones, Kline, Viswanathan, and Whitcomb.

On the Minimum Induced Drag of Wings

NASA Technical Reports Server (NTRS)

Bowers, Albion H.

2011-01-01

Of all the types of drag, induced drag is associated with the creation and generation of lift over wings. Induced drag is directly driven by the span load that the aircraft is flying at. The tools by which to calculate and predict induced drag we use were created by Ludwig Prandtl in 1903. Within a decade after Prandtl created a tool for calculating induced drag, Prandtl and his students had optimized the problem to solve the minimum induced drag for a wing of a given span, formalized and written about in 1920. This solution is quoted in textbooks extensively today. Prandtl did not stop with this first solution, and came to a dramatically different solution in 1932. Subsequent development of this 1932 solution solves several aeronautics design difficulties simultaneously, including maximum performance, minimum structure, minimum drag loss due to control input, and solution to adverse yaw without a vertical tail. This presentation lists that solution by Prandtl, and the refinements by Horten, Jones, Kline, Viswanathan, and Whitcomb.

Dyes for displays

NASA Astrophysics Data System (ADS)

Claussen, U.

1984-01-01

The improvement of contrast and visibility of LCD by two different means was undertaken. The two methods are: (1) development of fluorescent dyes to increase the visibility of fluorescent activated displays (FLAD); and (2) development of dichroic dyes to increase the contrast of displays. This work was done in close cooperation with the electronic industry, where the newly synthesized dyes were tested. The targets for the chemical synthesis were selected with the help of computer model calculations. A marketable range of dyes was developed. Since the interest of the electronic industries concerning FLAD was low, the investigations were stopped. Dichroic dyes, especially black mixtures with good light fastness, order parameter, and solubility in nematic phases were developed. The application of these dyes is restricted to indoor use because of an increase of viscosity below -10 C. Applications on a technical scale, e.g., for the automotive industry, will be possible if the displays work at temperatures down to -40 C. This problem requires a complex optimization of the dye/nematic phase system.

Self-reported illness among Boston-area international travelers: A prospective study

PubMed Central

Chen, Lin H.; Han, Pauline V.; Wilson, Mary E.; Stoney, Rhett J.; Jentes, Emily S.; Benoit, Christine; Ooi, Winnie W.; Barnett, Elizabeth D.; Hamer, Davidson H.

2017-01-01

Summary Background The Boston Area Travel Medicine Network surveyed travelers on travel-related health problems. Methods Travelers were recruited 2009–2011 during pre-travel consultation at three clinics. The investigation included pre-travel data, weekly during-travel diaries, and a post-travel questionnaire. We analyzed demographics, trip characteristics, health problems experienced, and assessed the relationship between influenza vaccination, influenza prevention advice, and respiratory symptoms. Results Of 987 enrolled travelers, 628 (64%) completed all surveys, of which 400 (64%) reported health problems during and/or after travel; median trip duration was 12 days. Diarrhea affected the most people during travel (172) while runny/stuffy nose affected the most people after travel (95). Of those with health problems during travel, 25% stopped or altered plans; 1% were hospitalized. After travel, 21% stopped planned activities, 23% sought physician or other health advice; one traveler was hospitalized. Travelers who received influenza vaccination and influenza prevention advice had lower rates of respiratory symptoms than those that received influenza prevention advice alone (18% vs 28%, P = 0.03). Conclusions A large proportion of Boston-area travelers reported health problems despite pre-travel consultation, resulting in inconveniences. The combination of influenza prevention advice and influenza immunization was associated with fewer respiratory symptoms than those who received influenza prevention advice alone. PMID:27687076

Self-reported illness among Boston-area international travelers: A prospective study.

PubMed

Chen, Lin H; Han, Pauline V; Wilson, Mary E; Stoney, Rhett J; Jentes, Emily S; Benoit, Christine; Ooi, Winnie W; Barnett, Elizabeth D; Hamer, Davidson H

The Boston Area Travel Medicine Network surveyed travelers on travel-related health problems. Travelers were recruited 2009-2011 during pre-travel consultation at three clinics. The investigation included pre-travel data, weekly during-travel diaries, and a post-travel questionnaire. We analyzed demographics, trip characteristics, health problems experienced, and assessed the relationship between influenza vaccination, influenza prevention advice, and respiratory symptoms. Of 987 enrolled travelers, 628 (64%) completed all surveys, of which 400 (64%) reported health problems during and/or after travel; median trip duration was 12 days. Diarrhea affected the most people during travel (172) while runny/stuffy nose affected the most people after travel (95). Of those with health problems during travel, 25% stopped or altered plans; 1% were hospitalized. After travel, 21% stopped planned activities, 23% sought physician or other health advice; one traveler was hospitalized. Travelers who received influenza vaccination and influenza prevention advice had lower rates of respiratory symptoms than those that received influenza prevention advice alone (18% vs 28%, P = 0.03). A large proportion of Boston-area travelers reported health problems despite pre-travel consultation, resulting in inconveniences. The combination of influenza prevention advice and influenza immunization was associated with fewer respiratory symptoms than those who received influenza prevention advice alone. Copyright © 2016 Elsevier Ltd. All rights reserved.

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

Gaitsgory, Vladimir, E-mail: vladimir.gaitsgory@mq.edu.au; Rossomakhine, Sergey, E-mail: serguei.rossomakhine@flinders.edu.au

The paper aims at the development of an apparatus for analysis and construction of near optimal solutions of singularly perturbed (SP) optimal controls problems (that is, problems of optimal control of SP systems) considered on the infinite time horizon. We mostly focus on problems with time discounting criteria but a possibility of the extension of results to periodic optimization problems is discussed as well. Our consideration is based on earlier results on averaging of SP control systems and on linear programming formulations of optimal control problems. The idea that we exploit is to first asymptotically approximate a given problem ofmore » optimal control of the SP system by a certain averaged optimal control problem, then reformulate this averaged problem as an infinite-dimensional linear programming (LP) problem, and then approximate the latter by semi-infinite LP problems. We show that the optimal solution of these semi-infinite LP problems and their duals (that can be found with the help of a modification of an available LP software) allow one to construct near optimal controls of the SP system. We demonstrate the construction with two numerical examples.« less

A Bayesian Hybrid Adaptive Randomisation Design for Clinical Trials with Survival Outcomes.

PubMed

Moatti, M; Chevret, S; Zohar, S; Rosenberger, W F

2016-01-01

Response-adaptive randomisation designs have been proposed to improve the efficiency of phase III randomised clinical trials and improve the outcomes of the clinical trial population. In the setting of failure time outcomes, Zhang and Rosenberger (2007) developed a response-adaptive randomisation approach that targets an optimal allocation, based on a fixed sample size. The aim of this research is to propose a response-adaptive randomisation procedure for survival trials with an interim monitoring plan, based on the following optimal criterion: for fixed variance of the estimated log hazard ratio, what allocation minimizes the expected hazard of failure? We demonstrate the utility of the design by redesigning a clinical trial on multiple myeloma. To handle continuous monitoring of data, we propose a Bayesian response-adaptive randomisation procedure, where the log hazard ratio is the effect measure of interest. Combining the prior with the normal likelihood, the mean posterior estimate of the log hazard ratio allows derivation of the optimal target allocation. We perform a simulation study to assess and compare the performance of this proposed Bayesian hybrid adaptive design to those of fixed, sequential or adaptive - either frequentist or fully Bayesian - designs. Non informative normal priors of the log hazard ratio were used, as well as mixture of enthusiastic and skeptical priors. Stopping rules based on the posterior distribution of the log hazard ratio were computed. The method is then illustrated by redesigning a phase III randomised clinical trial of chemotherapy in patients with multiple myeloma, with mixture of normal priors elicited from experts. As expected, there was a reduction in the proportion of observed deaths in the adaptive vs. non-adaptive designs; this reduction was maximized using a Bayes mixture prior, with no clear-cut improvement by using a fully Bayesian procedure. The use of stopping rules allows a slight decrease in the observed proportion of deaths under the alternate hypothesis compared with the adaptive designs with no stopping rules. Such Bayesian hybrid adaptive survival trials may be promising alternatives to traditional designs, reducing the duration of survival trials, as well as optimizing the ethical concerns for patients enrolled in the trial.

How to Stop Dealing with the Same Types of Problems Day after Day, Part 2

ERIC Educational Resources Information Center

Martin, Gary

2005-01-01

Gaining expertise in leadership requires time, commitment, an adequate knowledge base, and a working plan for learning and growth. Without a plan for learning, only tacit or "how-to" expertise is developed. Leaders often know how to solve the problems facing them, but fail to analyze and act on the underlying causes. This results in administrators…

How to Stop Dealing with the Same Types of Problems Day after Day, Part 1

ERIC Educational Resources Information Center

Martin, Gary

2005-01-01

Gaining expertise in leadership requires time, commitment, an adequate knowledge base, and a working plan for learning and growth. Without a plan for learning, only tacit or "how-to" expertise is developed. Leaders often know how to solve the problems facing them, but they fail to analyze and act on the underlying causes. This results in…

Alcohol use disorder

MedlinePlus

... help you stop drinking completely. These programs usually offer: Education about alcohol use and its effects Counseling and therapy to discuss how to control your thoughts and behaviors Physical ... programs offer housing options for people with alcohol problems. Depending ...

Stop Thief!

ERIC Educational Resources Information Center

American School and University, 1984

1984-01-01

A large urban school board has solved the security problem for electronically stored student records by refusing to file them on a dialup system and by requiring a notarized affidavit of custody before release to a parent or guardian. (TE)

Performance of Grey Wolf Optimizer on large scale problems

NASA Astrophysics Data System (ADS)

Gupta, Shubham; Deep, Kusum

2017-01-01

For solving nonlinear continuous problems of optimization numerous nature inspired optimization techniques are being proposed in literature which can be implemented to solve real life problems wherein the conventional techniques cannot be applied. Grey Wolf Optimizer is one of such technique which is gaining popularity since the last two years. The objective of this paper is to investigate the performance of Grey Wolf Optimization Algorithm on large scale optimization problems. The Algorithm is implemented on 5 common scalable problems appearing in literature namely Sphere, Rosenbrock, Rastrigin, Ackley and Griewank Functions. The dimensions of these problems are varied from 50 to 1000. The results indicate that Grey Wolf Optimizer is a powerful nature inspired Optimization Algorithm for large scale problems, except Rosenbrock which is a unimodal function.

Early cessation of breastfeeding amongst women in South Africa: an area needing urgent attention to improve child health

PubMed Central

2012-01-01

Background Breastfeeding is a critical component of interventions to reduce child mortality. Exclusive breastfeeding practice is extremely low in South Africa and there has been no improvement in this over the past ten years largely due to fears of HIV transmission. Early cessation of breastfeeding has been found to have negative effects on child morbidity and survival in several studies in Africa. This paper reports on determinants of early breastfeeding cessation among women in South Africa. Methods This is a sub group analysis of a community-based cluster-randomized trial (PROMISE EBF) promoting exclusive breastfeeding in three South African sites (Paarl in the Western Cape Province, and Umlazi and Rietvlei in KwaZulu-Natal) between 2006 and 2008 (ClinicalTrials.gov no: NCT00397150). Infant feeding recall of 22 food and fluid items was collected at 3, 6, 12 and 24 weeks postpartum. Women’s experiences of breast health problems were also collected at the same time points. 999 women who ever breastfed were included in the analysis. Univariable and multivariable logistic regression analysis adjusting for site, arm and cluster, was performed to determine predictors of stopping breastfeeding by 12 weeks postpartum. Results By 12 weeks postpartum, 20% of HIV-negative women and 40% of HIV-positive women had stopped all breastfeeding. About a third of women introduced other fluids, most commonly formula milk, within the first 3 days after birth. Antenatal intention not to breastfeed and being undecided about how to feed were most strongly associated with stopping breastfeeding by 12 weeks (Adjusted odds ratio, AOR 5.6, 95% CI 3.4 – 9.5 and AOR 4.1, 95% CI 1.6 – 10.8, respectively). Also important was self-reported breast health problems associated with a 3-fold risk of stopping breastfeeding (AOR 3.1, 95%CI 1.7 – 5.7) and the mother having her own income doubled the risk of stopping breastfeeding (AOR 1.9, 95% CI 1.3 – 2.8). Conclusion Early cessation of breastfeeding is common amongst both HIV-negative and positive women in South Africa. There is an urgent need to improve antenatal breastfeeding counselling taking into account the challenges faced by working women as well as early postnatal lactation support to prevent breast health problems. PMID:22827969

Single-step CE for miniaturized and easy-to-use system.

PubMed

Ono, Koichi; Kaneda, Shohei; Fujii, Teruo

2013-03-01

We developed a novel single-step capillary electrophoresis (SSCE) scheme for miniaturized and easy to use system by using a microchannel chip, which was made from the hydrophilic material polymethyl methacrylate (PMMA), equipped with a capillary stop valve. Taking the surface tension property of liquids into consideration, the capillary effect was used to introduce liquids and control capillary stop valves in a partial barrier structure in the wall of the microchannel. Through the combined action of stop valves and air vents, both sample plug formation for electrophoresis and sample injection into a separation channel were successfully performed in a single step. To optimize SSCE, different stop valve structures were evaluated using actual microchannel chips and the finite element method with the level set method. A partial barrier structure at the bottom of the channel functioned efficiently as a stop valve. The stability of stop valve was confirmed by a shock test, which was performed by dropping the microchannel chip to a floor. Sample plug deformation could be reduced by minimizing the size of the side partial barrier. By dissolving hydroxyl ethyl cellulose and using it as the sample solution, the EOF and adsorption of the sample into the PMMA microchannel were successfully reduced. Using this method, a 100-bp DNA ladder was concentrated; good separation was observed within 1 min. At a separation length of 5 mm, the signal was approximately 20-fold higher than a signal of original sample solution by field-amplified sample stacking effect. All operations, including liquid introduction and sample separation, can be completed within 2 min by using the SSCE scheme. © 2013 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

A numerical simulation approach to studying anterior cruciate ligament strains and internal forces among young recreational women performing valgus inducing stop-jump activities.

PubMed

Kar, Julia; Quesada, Peter M

2012-08-01

Anterior cruciate ligament (ACL) injuries are commonly incurred by recreational and professional women athletes during non-contact jumping maneuvers in sports like basketball and volleyball, where incidences of ACL injury is more frequent to females compared to males. What remains a numerical challenge is in vivo calculation of ACL strain and internal force. This study investigated effects of increasing stop-jump height on neuromuscular and bio-mechanical properties of knee and ACL, when performed by young female recreational athletes. The underlying hypothesis is increasing stop-jump (platform) height increases knee valgus angles and external moments which also increases ACL strain and internal force. Using numerical analysis tools comprised of Inverse Kinematics, Computed Muscle Control and Forward Dynamics, a novel approach is presented for computing ACL strain and internal force based on (1) knee joint kinematics and (2) optimization of muscle activation, with ACL insertion into musculoskeletal model. Results showed increases in knee valgus external moments and angles with increasing stop-jump height. Increase in stop-jump height from 30 to 50 cm lead to increase in average peak valgus external moment from 40.5 ± 3.2 to 43.2 ± 3.7 Nm which was co-incidental with increase in average peak ACL strain, from 9.3 ± 3.1 to 13.7 ± 1.1%, and average peak ACL internal force, from 1056.1 ± 71.4 to 1165.4 ± 123.8 N for the right side with comparable increases in the left. In effect this study demonstrates a technique for estimating dynamic changes to knee and ACL variables by conducting musculoskeletal simulation on motion analysis data, collected from actual stop-jump tasks performed by young recreational women athletes.

Feed Forward Neural Network and Optimal Control Problem with Control and State Constraints

NASA Astrophysics Data System (ADS)

Kmet', Tibor; Kmet'ová, Mária

2009-09-01

A feed forward neural network based optimal control synthesis is presented for solving optimal control problems with control and state constraints. The paper extends adaptive critic neural network architecture proposed by [5] to the optimal control problems with control and state constraints. The optimal control problem is transcribed into a nonlinear programming problem which is implemented with adaptive critic neural network. The proposed simulation method is illustrated by the optimal control problem of nitrogen transformation cycle model. Results show that adaptive critic based systematic approach holds promise for obtaining the optimal control with control and state constraints.

The NOAA OneStop System: From Well-Curated Metadata to Data Discovery

NASA Astrophysics Data System (ADS)

McQuinn, E.; Jakositz, A.; Caldwell, A.; Delk, Z.; Neufeld, D.; Shapiro, J.; Partee, R.; Milan, A.

2017-12-01

The NOAA OneStop project is a pathfinder in the realm of enabling users to search for, discover, and access NOAA data. As the project continues along its path to maturity, it has become evident that three areas are of utmost importance to its success in the Earth science community: ensuring quality metadata, building a robust and scalable backend architecture, and keeping the user interface simple to use. Why is this the case? Because, simply put, we are dealing with all aspects of a Big Data problem: large volumes of disparate data needing to be quickly and easily processed and retrieved. In this presentation we discuss the three key aspects of OneStop architecture and how development in each area must be done through cross-team collaboration in order to succeed. We cover aspects of the web-based user interface and OneStop API and how metadata curators and software engineers have worked together to continually iterate on an ever-improving data discovery tool meant to be used by a variety of users searching across a broad assortment of data types.

Pilot survey of subway and bus stop noise levels.

PubMed

Gershon, Robyn R M; Neitzel, Richard; Barrera, Marissa A; Akram, Muhammad

2006-09-01

Excessive noise exposure is a serious global urban health problem, adversely affecting millions of people. One often cited source of urban noise is mass transit, particularly subway systems. As a first step in determining risk within this context, we recently conducted an environmental survey of noise levels of the New York City transit system. Over 90 noise measurements were made using a sound level meter. Average and maximum noise levels were measured on subway platforms, and maximum levels were measured inside subway cars and at several bus stops for comparison purposes. The average noise level measured on the subway platforms was 86 +/- 4 dBA (decibel-A weighting). Maximum levels of 106, 112, and 89 dBA were measured on subway platforms, inside subway cars, and at bus stops, respectively. These results indicate that noise levels in subway and bus stop environments have the potential to exceed recommended exposure guidelines from the World Health Organization (WHO) and U.S. Environmental Protection Agency (EPA), given sufficient exposure duration. Risk reduction strategies following the standard hierarchy of control measures should be applied, where feasible, to reduce subway noise exposure.

From the Orbital Implementation of the Kinetic Theory to the Polarization Propagator Method in the Study of Energy Deposition Problems

NASA Astrophysics Data System (ADS)

Cabrera-Trujillo, R.; Cruz, S. A.; Soullard, J.

The energy deposited by swift atomic-ion projectiles when colliding with a given target material has been a topic of special scientific interest for the last century due to the variety of applications of ion beams in modern materials technology as well as in medical physics. In this work, we summarize our contributions in this field as a consequence of fruitful discussions and enlightening ideas put forward by one of the main protagonists in stopping power theory during the last three decades: Jens Oddershede. Our review, mainly motivated by Jens' work, evolves from the extension of the orbital implementation of the kinetic theory of stopping through the orbital local plasma approximation, its use in studies of orbital and total mean excitation energies for the study of atomic and molecular stopping until the advances on generalized oscillator strength and sum rules in the study of stopping cross sections. Finally, as a tribute to Jens' work on the orbital implementation of the kinetic theory of stopping, in this work we present new results on the use of the Thomas-Fermi-Dirac-Weizsäcker density functional for the calculation of orbital and total atomic mean excitation energies. The results are applied to free-atoms and and extension is done to confined atoms - taking Si as an example - whereby target pressure effects on stopping are derived. Hence, evidence of the far-yield of Jens' ideas is given.

Tribological composition optimization of chromium-carbide-based solid lubricant coatings for foil gas bearings at temperatures to 650 C

NASA Technical Reports Server (NTRS)

Dellacorte, Christopher

1988-01-01

The determination of the tribilogically optimum composition of chromium-carbide-based solid lubricant coatings using a foil gas bearing test apparatus is described. The coatings contain a wear resistant chromium carbide `base stock' with the lubricant additives silver and BaF2-CaF2 eutectic. The coating composition is optimized for air-lubricated foil gas bearings at temperatures ranging from 25 to 650 C. The various compositions were prepared by powder blending, then plasma sprayed onto Inconel 718 test journals and diamond ground to the desired coating thickness and surface finish. The journals were operated against preoxidized Ni-Cr alloy foils, and the test bearings were subjected to repeated start-stop cycles under a bearing unit of 14 kPa. Sliding contact between the coated journal and the smooth foil occurs during bearing start-up before lift-off or hydrodynamic lubrication by the air film and during bearing coast-down. The bearings were tested for 9000 start-stop cycles or until specimen reached a predetermined failure level.

COPS: Large-scale nonlinearly constrained optimization problems

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

Bondarenko, A.S.; Bortz, D.M.; More, J.J.

2000-02-10

The authors have started the development of COPS, a collection of large-scale nonlinearly Constrained Optimization Problems. The primary purpose of this collection is to provide difficult test cases for optimization software. Problems in the current version of the collection come from fluid dynamics, population dynamics, optimal design, and optimal control. For each problem they provide a short description of the problem, notes on the formulation of the problem, and results of computational experiments with general optimization solvers. They currently have results for DONLP2, LANCELOT, MINOS, SNOPT, and LOQO.

Experimental and numerical studies on the treatment of wet astronaut trash by forced-convection drying

NASA Astrophysics Data System (ADS)

Arquiza, J. M. R. Apollo; Morrow, Robert; Remiker, Ross; Hunter, Jean B.

2017-09-01

During long-term space missions, astronauts generate wet trash, including food containers with uneaten portions, moist hygiene wipes and wet paper towels. This waste produces two problems: the loss of water and the generation of odors and health hazards by microbial growth. These problems are solved by a closed-loop, forced-convection, heat-pump drying system which stops microbial activity by both pasteurization and desiccation, and recovers water in a gravity-independent porous media condensing heat exchanger. A transient, pseudo-homogeneous continuum model for the drying of wet ersatz trash was formulated for this system. The model is based on the conservation equations for energy and moisture applied to the air and solid phases and includes the unique trash characteristic of having both dry and wet solids. Experimentally determined heat and mass transfer coefficients, together with the moisture sorption equilibrium relationship for the wet material are used in the model. The resulting system of differential equations is solved by the finite-volume method as implemented by the commercial software COMSOL. Model simulations agreed well with experimental data under certain conditions. The validated model will be used in the optimization of the entire closed-loop system consisting of fan, air heater, dryer vessel, heat-pump condenser, and heat-recovery modules.

Lactose intolerance

MedlinePlus

... age 5. This is the age when our bodies may stop making lactase. In African Americans, the problem can occur as early as age 2. The condition is very common among adults with Asian, African, or Native American heritage. It is less ...

Quitting Smoking

MedlinePlus

... half of the people who don't quit smoking will die of smoking-related problems. Quitting smoking is important for your health. Soon after you ... they succeed. There are many ways to quit smoking. Some people stop "cold turkey." Others benefit from ...

Oral Rehabilitation With Orthognathic Surgery After Dental Implant Placement for Class III Malocclusion With Skeletal Asymmetry and Posterior Bite Collapse.

PubMed

Ohba, Seigo; Nakatani, Yuya; Kawasaki, Takako; Tajima, Nobutaka; Tobita, Takayoshi; Yoshida, Noriaki; Sawase, Takashi; Asahina, Izumi

2015-08-01

Increasing numbers of older patients are seeking orthognathic surgery to treat jaw deformity. However, orthodontic and orthognathic surgical treatment is difficult in cases without occlusal vertical stop. A 55-year-old man presented with Class III malocclusion and mandibular protrusion including esthetic problems and posterior bite collapse. He underwent dental implant treatment to reconstruct an occlusal vertical stop before orthognathic surgery. His occlusal function and esthetic problems improved after surgery, and his skeletal and occlusal stability has been maintained for 6 years. Dental implant placement at appropriate positions could help to determine the position of the proximal segment at orthognathic surgery and could shorten the time required to restore esthetic and occlusal function. This case demonstrates how skeletal and dental stability can be maintained long after surgery in a patient with jaw deformity and posterior bite collapse.

Selective decision-making deficits in at-risk gamblers

PubMed Central

Grant, Jon Edgar; Chamberlain, Samuel Robin; Schreiber, Liana Renne Nelson; Odlaug, Brian Lawrence; Kim, Suck Won

2011-01-01

Despite reasonable knowledge of pathological gambling (PG), little is known of its cognitive antecedents. We evaluated decision-making and impulsivity characteristics in people at risk of developing PG using neuropsychological tests. Non-treatment seeking volunteers (18-29 years) who gamble ≥5 times/year were recruited from the general community, and split into two groups: those “at risk” of developing PG (n=74) and those social, non-problem gamblers (n=112). Participants undertook the Cambridge Gamble and Stop-signal tasks and were assessed with the Mini-International Neuropsychiatric Interview and the Yale Brown Obsessive Compulsive Scale Modified for Pathological Gambling. On the Cambridge Gamble task, the at- risk subjects gambled more points overall, were more likely to go bankrupt, and made more irrational decisions under situations of relative risk ambiguity. On the Stop-signal task, at- risk gamblers did not differ from the social, non-problem gamblers in terms of motor impulse control (stop-signal reaction times). Findings suggest that selective cognitive dysfunction may already be present in terms of decision-making in at-risk gamblers, even before psychopathology arises. These findings implicate selective decision-making deficits and dysfunction of orbitofronto-limbic circuitry in the chain of pathogenesis between social, non-problematic and pathological gambling. PMID:21715016

Optimization of PSA screening policies: a comparison of the patient and societal perspectives.

PubMed

Zhang, Jingyu; Denton, Brian T; Balasubramanian, Hari; Shah, Nilay D; Inman, Brant A

2012-01-01

To estimate the benefit of PSA-based screening for prostate cancer from the patient and societal perspectives. A partially observable Markov decision process model was used to optimize PSA screening decisions. Age-specific prostate cancer incidence rates and the mortality rates from prostate cancer and competing causes were considered. The model trades off the potential benefit of early detection with the cost of screening and loss of patient quality of life due to screening and treatment. PSA testing and biopsy decisions are made based on the patient's probability of having prostate cancer. Probabilities are inferred based on the patient's complete PSA history using Bayesian updating. The results of all PSA tests and biopsies done in Olmsted County, Minnesota, from 1993 to 2005 (11,872 men and 50,589 PSA test results). Patients' perspective: to maximize expected quality-adjusted life years (QALYs); societal perspective: to maximize the expected monetary value based on societal willingness to pay for QALYs and the cost of PSA testing, prostate biopsies, and treatment. From the patient perspective, the optimal policy recommends stopping PSA testing and biopsy at age 76. From the societal perspective, the stopping age is 71. The expected incremental benefit of optimal screening over the traditional guideline of annual PSA screening with threshold 4.0 ng/mL for biopsy is estimated to be 0.165 QALYs per person from the patient perspective and 0.161 QALYs per person from the societal perspective. PSA screening based on traditional guidelines is found to be worse than no screening at all. PSA testing done with traditional guidelines underperforms and therefore underestimates the potential benefit of screening. Optimal screening guidelines differ significantly depending on the perspective of the decision maker.

Generalized bipartite quantum state discrimination problems with sequential measurements

NASA Astrophysics Data System (ADS)

Nakahira, Kenji; Kato, Kentaro; Usuda, Tsuyoshi Sasaki

2018-02-01

We investigate an optimization problem of finding quantum sequential measurements, which forms a wide class of state discrimination problems with the restriction that only local operations and one-way classical communication are allowed. Sequential measurements from Alice to Bob on a bipartite system are considered. Using the fact that the optimization problem can be formulated as a problem with only Alice's measurement and is convex programming, we derive its dual problem and necessary and sufficient conditions for an optimal solution. Our results are applicable to various practical optimization criteria, including the Bayes criterion, the Neyman-Pearson criterion, and the minimax criterion. In the setting of the problem of finding an optimal global measurement, its dual problem and necessary and sufficient conditions for an optimal solution have been widely used to obtain analytical and numerical expressions for optimal solutions. Similarly, our results are useful to obtain analytical and numerical expressions for optimal sequential measurements. Examples in which our results can be used to obtain an analytical expression for an optimal sequential measurement are provided.

An RCT into the effects of neurofeedback on neurocognitive functioning compared to stimulant medication and physical activity in children with ADHD.

PubMed

Geladé, Katleen; Bink, Marleen; Janssen, Tieme W P; van Mourik, Rosa; Maras, Athanasios; Oosterlaan, Jaap

2017-04-01

Neurofeedback (NFB) is a potential alternative treatment for children with ADHD that aims to optimize brain activity. Whereas most studies into NFB have investigated behavioral effects, less attention has been paid to the effects on neurocognitive functioning. The present randomized controlled trial (RCT) compared neurocognitive effects of NFB to (1) optimally titrated methylphenidate (MPH) and (2) a semi-active control intervention, physical activity (PA), to control for non-specific effects. Using a multicentre three-way parallel group RCT design, children with ADHD, aged 7-13, were randomly allocated to NFB (n = 39), MPH (n = 36) or PA (n = 37) over a period of 10-12 weeks. NFB comprised theta/beta training at CZ. The PA intervention was matched in frequency and duration to NFB. MPH was titrated using a double-blind placebo controlled procedure to determine the optimal dose. Neurocognitive functioning was assessed using parameters derived from the auditory oddball-, stop-signal- and visual spatial working memory task. Data collection took place between September 2010 and March 2014. Intention-to-treat analyses showed improved attention for MPH compared to NFB and PA, as reflected by decreased response speed during the oddball task [η p 2  = 0.21, p < 0.001], as well as improved inhibition, impulsivity and attention, as reflected by faster stop signal reaction times, lower commission and omission error rates during the stop-signal task (range η p 2  = 0.09-0.18, p values <0.008). Working memory improved over time, irrespective of received treatment (η p 2  = 0.17, p < 0.001). Overall, stimulant medication showed superior effects over NFB to improve neurocognitive functioning. Hence, the findings do not support theta/beta training applied as a stand-alone treatment in children with ADHD.

A Cascade Optimization Strategy for Solution of Difficult Multidisciplinary Design Problems

NASA Technical Reports Server (NTRS)

Patnaik, Surya N.; Coroneos, Rula M.; Hopkins, Dale A.; Berke, Laszlo

1996-01-01

A research project to comparatively evaluate 10 nonlinear optimization algorithms was recently completed. A conclusion was that no single optimizer could successfully solve all 40 problems in the test bed, even though most optimizers successfully solved at least one-third of the problems. We realized that improved search directions and step lengths, available in the 10 optimizers compared, were not likely to alleviate the convergence difficulties. For the solution of those difficult problems we have devised an alternative approach called cascade optimization strategy. The cascade strategy uses several optimizers, one followed by another in a specified sequence, to solve a problem. A pseudorandom scheme perturbs design variables between the optimizers. The cascade strategy has been tested successfully in the design of supersonic and subsonic aircraft configurations and air-breathing engines for high-speed civil transport applications. These problems could not be successfully solved by an individual optimizer. The cascade optimization strategy, however, generated feasible optimum solutions for both aircraft and engine problems. This paper presents the cascade strategy and solutions to a number of these problems.

Reproducibility in a multiprocessor system

DOEpatents

Bellofatto, Ralph A; Chen, Dong; Coteus, Paul W; Eisley, Noel A; Gara, Alan; Gooding, Thomas M; Haring, Rudolf A; Heidelberger, Philip; Kopcsay, Gerard V; Liebsch, Thomas A; Ohmacht, Martin; Reed, Don D; Senger, Robert M; Steinmacher-Burow, Burkhard; Sugawara, Yutaka

2013-11-26

Fixing a problem is usually greatly aided if the problem is reproducible. To ensure reproducibility of a multiprocessor system, the following aspects are proposed; a deterministic system start state, a single system clock, phase alignment of clocks in the system, system-wide synchronization events, reproducible execution of system components, deterministic chip interfaces, zero-impact communication with the system, precise stop of the system and a scan of the system state.

Environmental tobacco smoke exposure and children's health.

PubMed

Polanska, Kinga; Hanke, Wojciech; Ronchetti, Roberto; van den Hazel, Peter; Zuurbier, Moniek; Koppe, Janna G; Bartonova, Alena

2006-10-01

Almost half of the child population is involuntarily exposed to environmental tobacco smoke (ETS). The ETS exposure gives rise to an excessive risk of several diseases in infancy and childhood, including sudden infant death syndrome, upper and lower respiratory infections, asthma and middle ear diseases. It is also linked to cancer, and behavioural problems and neurocognitive deficits in children. Protecting children from ETS exposure is a complex and important issue. The best improvement in children's health is to be gained when parents stop smoking or, when that is not possible, they stop smoking in their children's environment. Paediatricians, because of their authority, and their frequent and regular contact with parents, play a leading role in protecting children from ETS exposure. An ideal approach to help parents to stop smoking seems to be initial minimal-contact advice provided by their paediatrician with feedback and supplemental printed materials, leading to greater intensity and duration of follow-up home visits.

Optimization of CMOS image sensor utilizing variable temporal multisampling partial transfer technique to achieve full-frame high dynamic range with superior low light and stop motion capability

NASA Astrophysics Data System (ADS)

Kabir, Salman; Smith, Craig; Armstrong, Frank; Barnard, Gerrit; Schneider, Alex; Guidash, Michael; Vogelsang, Thomas; Endsley, Jay

2018-03-01

Differential binary pixel technology is a threshold-based timing, readout, and image reconstruction method that utilizes the subframe partial charge transfer technique in a standard four-transistor (4T) pixel CMOS image sensor to achieve a high dynamic range video with stop motion. This technology improves low light signal-to-noise ratio (SNR) by up to 21 dB. The method is verified in silicon using a Taiwan Semiconductor Manufacturing Company's 65 nm 1.1 μm pixel technology 1 megapixel test chip array and is compared with a traditional 4 × oversampling technique using full charge transfer to show low light SNR superiority of the presented technology.

An ITK framework for deterministic global optimization for medical image registration

NASA Astrophysics Data System (ADS)

Dru, Florence; Wachowiak, Mark P.; Peters, Terry M.

2006-03-01

Similarity metric optimization is an essential step in intensity-based rigid and nonrigid medical image registration. For clinical applications, such as image guidance of minimally invasive procedures, registration accuracy and efficiency are prime considerations. In addition, clinical utility is enhanced when registration is integrated into image analysis and visualization frameworks, such as the popular Insight Toolkit (ITK). ITK is an open source software environment increasingly used to aid the development, testing, and integration of new imaging algorithms. In this paper, we present a new ITK-based implementation of the DIRECT (Dividing Rectangles) deterministic global optimization algorithm for medical image registration. Previously, it has been shown that DIRECT improves the capture range and accuracy for rigid registration. Our ITK class also contains enhancements over the original DIRECT algorithm by improving stopping criteria, adaptively adjusting a locality parameter, and by incorporating Powell's method for local refinement. 3D-3D registration experiments with ground-truth brain volumes and clinical cardiac volumes show that combining DIRECT with Powell's method improves registration accuracy over Powell's method used alone, is less sensitive to initial misorientation errors, and, with the new stopping criteria, facilitates adequate exploration of the search space without expending expensive iterations on non-improving function evaluations. Finally, in this framework, a new parallel implementation for computing mutual information is presented, resulting in near-linear speedup with two processors.

Algorithms for bilevel optimization

NASA Technical Reports Server (NTRS)

Alexandrov, Natalia; Dennis, J. E., Jr.

1994-01-01

General multilevel nonlinear optimization problems arise in design of complex systems and can be used as a means of regularization for multi-criteria optimization problems. Here, for clarity in displaying our ideas, we restrict ourselves to general bi-level optimization problems, and we present two solution approaches. Both approaches use a trust-region globalization strategy, and they can be easily extended to handle the general multilevel problem. We make no convexity assumptions, but we do assume that the problem has a nondegenerate feasible set. We consider necessary optimality conditions for the bi-level problem formulations and discuss results that can be extended to obtain multilevel optimization formulations with constraints at each level.

Near-Optimal Guidance Method for Maximizing the Reachable Domain of Gliding Aircraft

NASA Astrophysics Data System (ADS)

Tsuchiya, Takeshi

This paper proposes a guidance method for gliding aircraft by using onboard computers to calculate a near-optimal trajectory in real-time, and thereby expanding the reachable domain. The results are applicable to advanced aircraft and future space transportation systems that require high safety. The calculation load of the optimal control problem that is used to maximize the reachable domain is too large for current computers to calculate in real-time. Thus the optimal control problem is divided into two problems: a gliding distance maximization problem in which the aircraft motion is limited to a vertical plane, and an optimal turning flight problem in a horizontal direction. First, the former problem is solved using a shooting method. It can be solved easily because its scale is smaller than that of the original problem, and because some of the features of the optimal solution are obtained in the first part of this paper. Next, in the latter problem, the optimal bank angle is computed from the solution of the former; this is an analytical computation, rather than an iterative computation. Finally, the reachable domain obtained from the proposed near-optimal guidance method is compared with that obtained from the original optimal control problem.

Direct Method Transcription for a Human-Class Translunar Injection Trajectory Optimization

NASA Technical Reports Server (NTRS)

Witzberger, Kevin E.; Zeiler, Tom

2012-01-01

This paper presents a new trajectory optimization software package developed in the framework of a low-to-high fidelity 3 degrees-of-freedom (DOF)/6-DOF vehicle simulation program named Mission Analysis Simulation Tool in Fortran (MASTIF) and its application to a translunar trajectory optimization problem. The functionality of the developed optimization package is implemented as a new "mode" in generalized settings to make it applicable for a general trajectory optimization problem. In doing so, a direct optimization method using collocation is employed for solving the problem. Trajectory optimization problems in MASTIF are transcribed to a constrained nonlinear programming (NLP) problem and solved with SNOPT, a commercially available NLP solver. A detailed description of the optimization software developed is provided as well as the transcription specifics for the translunar injection (TLI) problem. The analysis includes a 3-DOF trajectory TLI optimization and a 3-DOF vehicle TLI simulation using closed-loop guidance.

Better Field Instruction by Using Jigsaw Groups

NASA Astrophysics Data System (ADS)

Sammons, J. I.; Murray, D. P.

2006-12-01

Do any of these sound familiar? Most of my students do well at field stops, but there are always the few at the back. I'd like to guest speak at the local High School, but the students have too little background. I wish I could spark the interest of my introductory classes. Jigsaw is the solution to these problems. This easy-to-apply technique puts students in the driver's seat. They make the inferences-they own the discovery. You'll see that "A-ha!" as though it were a first time event. Jigsaw brings new excitement to familiar activities for every student in your class, even that guy in the back. Best of all, the technique does not depend on the style or force of personality of the instructor. It is easy to learn and suitable for use by Teaching Assistants. Here's how it works: 1. Identify the critical concepts necessary for a full understanding of the field stop or activity. 2. Divide your class into Expert Groups. The members of each Expert Group will master one of these critical concepts. 3.Dissolve the Expert Groups. Divide your class into new Jigsaw Groups to address the field stop or activity. Each Jigsaw Group includes members from each Expert Group. Like pieces of a puzzle, each Jigsaw Group member brings a critical piece to the problem. This talk will demonstrate Jigsaw Groups in action at a field stop. You'll see the crucial identification of critical concepts, small lab explorations carried out by the Expert Groups to master their assigned concepts, and Jigsaw Groups working a complex geological feature. You'll learn how to trouble-shoot less-than-successful first attempts and you'll leave with a step-by-step template that will allow you to adapt your existing activities to Jigsaw technique.

Highway extraction from high resolution aerial photography using a geometric active contour model

NASA Astrophysics Data System (ADS)

Niu, Xutong

Highway extraction and vehicle detection are two of the most important steps in traffic-flow analysis from multi-frame aerial photographs. The traditional method of deriving traffic flow trajectories relies on manual vehicle counting from a sequence of aerial photographs, which is tedious and time-consuming. This research presents a new framework for semi-automatic highway extraction. The basis of the new framework is an improved geometric active contour (GAC) model. This novel model seeks to minimize an objective function that transforms a problem of propagation of regular curves into an optimization problem. The implementation of curve propagation is based on level set theory. By using an implicit representation of a two-dimensional curve, a level set approach can be used to deal with topological changes naturally, and the output is unaffected by different initial positions of the curve. However, the original GAC model, on which the new model is based, only incorporates boundary information into the curve propagation process. An error-producing phenomenon called leakage is inevitable wherever there is an uncertain weak edge. In this research, region-based information is added as a constraint into the original GAC model, thereby, giving this proposed method the ability of integrating both boundary and region-based information during the curve propagation. Adding the region-based constraint eliminates the leakage problem. This dissertation applies the proposed augmented GAC model to the problem of highway extraction from high-resolution aerial photography. First, an optimized stopping criterion is designed and used in the implementation of the GAC model. It effectively saves processing time and computations. Second, a seed point propagation framework is designed and implemented. This framework incorporates highway extraction, tracking, and linking into one procedure. A seed point is usually placed at an end node of highway segments close to the boundary of the image or at a position where possible blocking may occur, such as at an overpass bridge or near vehicle crowds. These seed points can be automatically propagated throughout the entire highway network. During the process, road center points are also extracted, which introduces a search direction for solving possible blocking problems. This new framework has been successfully applied to highway network extraction from a large orthophoto mosaic. In the process, vehicles on the highway extracted from mosaic were detected with an 83% success rate.

Addressing dilemma zone issues with control solutions : final report.

DOT National Transportation Integrated Search

2017-04-01

Rural, high-speed signalized intersections are associated with vehicle crashes attributable to problems in dilemma zones : (DZs). DZs are areas where at the onset of yellow, some drivers may decide to proceed and some may decide to stop. This : disag...

Multidisciplinary Optimization of a Transport Aircraft Wing using Particle Swarm Optimization

NASA Technical Reports Server (NTRS)

Sobieszczanski-Sobieski, Jaroslaw; Venter, Gerhard

2002-01-01

The purpose of this paper is to demonstrate the application of particle swarm optimization to a realistic multidisciplinary optimization test problem. The paper's new contributions to multidisciplinary optimization is the application of a new algorithm for dealing with the unique challenges associated with multidisciplinary optimization problems, and recommendations as to the utility of the algorithm in future multidisciplinary optimization applications. The selected example is a bi-level optimization problem that demonstrates severe numerical noise and has a combination of continuous and truly discrete design variables. The use of traditional gradient-based optimization algorithms is thus not practical. The numerical results presented indicate that the particle swarm optimization algorithm is able to reliably find the optimum design for the problem presented here. The algorithm is capable of dealing with the unique challenges posed by multidisciplinary optimization as well as the numerical noise and truly discrete variables present in the current example problem.

Optimal recombination in genetic algorithms for flowshop scheduling problems

NASA Astrophysics Data System (ADS)

Kovalenko, Julia

2016-10-01

The optimal recombination problem consists in finding the best possible offspring as a result of a recombination operator in a genetic algorithm, given two parent solutions. We prove NP-hardness of the optimal recombination for various variants of the flowshop scheduling problem with makespan criterion and criterion of maximum lateness. An algorithm for solving the optimal recombination problem for permutation flowshop problems is built, using enumeration of prefect matchings in a special bipartite graph. The algorithm is adopted for the classical flowshop scheduling problem and for the no-wait flowshop problem. It is shown that the optimal recombination problem for the permutation flowshop scheduling problem is solvable in polynomial time for almost all pairs of parent solutions as the number of jobs tends to infinity.

An efficient and accurate solution methodology for bilevel multi-objective programming problems using a hybrid evolutionary-local-search algorithm.

PubMed

Deb, Kalyanmoy; Sinha, Ankur

2010-01-01

Bilevel optimization problems involve two optimization tasks (upper and lower level), in which every feasible upper level solution must correspond to an optimal solution to a lower level optimization problem. These problems commonly appear in many practical problem solving tasks including optimal control, process optimization, game-playing strategy developments, transportation problems, and others. However, they are commonly converted into a single level optimization problem by using an approximate solution procedure to replace the lower level optimization task. Although there exist a number of theoretical, numerical, and evolutionary optimization studies involving single-objective bilevel programming problems, not many studies look at the context of multiple conflicting objectives in each level of a bilevel programming problem. In this paper, we address certain intricate issues related to solving multi-objective bilevel programming problems, present challenging test problems, and propose a viable and hybrid evolutionary-cum-local-search based algorithm as a solution methodology. The hybrid approach performs better than a number of existing methodologies and scales well up to 40-variable difficult test problems used in this study. The population sizing and termination criteria are made self-adaptive, so that no additional parameters need to be supplied by the user. The study indicates a clear niche of evolutionary algorithms in solving such difficult problems of practical importance compared to their usual solution by a computationally expensive nested procedure. The study opens up many issues related to multi-objective bilevel programming and hopefully this study will motivate EMO and other researchers to pay more attention to this important and difficult problem solving activity.

Measurement and Reliability of Response Inhibition

PubMed Central

Congdon, Eliza; Mumford, Jeanette A.; Cohen, Jessica R.; Galvan, Adriana; Canli, Turhan; Poldrack, Russell A.

2012-01-01

Response inhibition plays a critical role in adaptive functioning and can be assessed with the Stop-signal task, which requires participants to suppress prepotent motor responses. Evidence suggests that this ability to inhibit a prepotent motor response (reflected as Stop-signal reaction time (SSRT)) is a quantitative and heritable measure of interindividual variation in brain function. Although attention has been given to the optimal method of SSRT estimation, and initial evidence exists in support of its reliability, there is still variability in how Stop-signal task data are treated across samples. In order to examine this issue, we pooled data across three separate studies and examined the influence of multiple SSRT calculation methods and outlier calling on reliability (using Intra-class correlation). Our results suggest that an approach which uses the average of all available sessions, all trials of each session, and excludes outliers based on predetermined lenient criteria yields reliable SSRT estimates, while not excluding too many participants. Our findings further support the reliability of SSRT, which is commonly used as an index of inhibitory control, and provide support for its continued use as a neurocognitive phenotype. PMID:22363308

The control system of a 2kW@20K helium refrigerator

NASA Astrophysics Data System (ADS)

Pan, W.; Wu, J. H.; Li, Qing; Liu, L. Q.; Li, Qiang

2017-12-01

The automatic control of a helium refrigerator includes three aspects, that is, one-button start and stop control, safety protection control, and cooling capacity control. The 2kW@20K helium refrigerator’s control system uses the SIEMENS PLC S7-300 and its related programming and configuration software Step7 and the industrial monitoring software WinCC, to realize the dynamic control of its process, the real-time monitoring of its data, the safety interlock control, and the optimal control of its cooling capacity. At first, this paper describes the control architecture of the whole system in detail, including communication configuration and equipment introduction; and then introduces the sequence control strategy of the dynamic processes, including the start and stop control mode of the machine and the safety interlock control strategy of the machine; finally tells the precise control strategy of the machine’s cooling capacity. Eventually, the whole system achieves the target of one-button starting and stopping, automatic fault protection and stable running to the target cooling capacity, and help finished the cold helium pressurization test of aerospace products.

Optimation of Operation System Integration between Main and Feeder Public Transport (Case Study: Trans Jakarta-Kopaja Bus Services)

NASA Astrophysics Data System (ADS)

Miharja, M.; Priadi, Y. N.

2018-05-01

Promoting a better public transport is a key strategy to cope with urban transport problems which are mostly caused by a huge private vehicle usage. A better public transport service quality not only focuses on one type of public transport mode, but also concerns on inter modes service integration. Fragmented inter mode public transport service leads to a longer trip chain as well as average travel time which would result in its failure to compete with a private vehicle. This paper examines the optimation process of operation system integration between Trans Jakarta Bus as the main public transport mode and Kopaja Bus as feeder public transport service in Jakarta. Using scoring-interview method combined with standard parameters in operation system integration, this paper identifies the key factors that determine the success of the two public transport operation system integrations. The study found that some key integration parameters, such as the cancellation of “system setoran”, passenger get in-get out at official stop points, and systematic payment, positively contribute to a better service integration. However, some parameters such as fine system, time and changing point reliability, and information system reliability are among those which need improvement. These findings are very useful for the authority to set the right strategy to improve operation system integration between Trans Jakarta and Kopaja Bus services.

Pilot Survey of Subway and Bus Stop Noise Levels

PubMed Central

Neitzel, Richard; Barrera, Marissa A.; Akram, Muhammad

2006-01-01

Excessive noise exposure is a serious global urban health problem, adversely affecting millions of people. One often cited source of urban noise is mass transit, particularly subway systems. As a first step in determining risk within this context, we recently conducted an environmental survey of noise levels of the New York City transit system. Over 90 noise measurements were made using a sound level meter. Average and maximum noise levels were measured on subway platforms, and maximum levels were measured inside subway cars and at several bus stops for comparison purposes. The average noise level measured on the subway platforms was 86 ± 4 dBA (decibel-A weighting). Maximum levels of 106, 112, and 89 dBA were measured on subway platforms, inside subway cars, and at bus stops, respectively. These results indicate that noise levels in subway and bus stop environments have the potential to exceed recommended exposure guidelines from the World Health Organization (WHO) and U.S. Environmental Protection Agency (EPA), given sufficient exposure duration. Risk reduction strategies following the standard hierarchy of control measures should be applied, where feasible, to reduce subway noise exposure. PMID:16802179

The Role of Multiple Neuromodulators in Reinforcement Learning That Is Based on Competition between Eligibility Traces.

PubMed

Huertas, Marco A; Schwettmann, Sarah E; Shouval, Harel Z

2016-01-01

The ability to maximize reward and avoid punishment is essential for animal survival. Reinforcement learning (RL) refers to the algorithms used by biological or artificial systems to learn how to maximize reward or avoid negative outcomes based on past experiences. While RL is also important in machine learning, the types of mechanistic constraints encountered by biological machinery might be different than those for artificial systems. Two major problems encountered by RL are how to relate a stimulus with a reinforcing signal that is delayed in time (temporal credit assignment), and how to stop learning once the target behaviors are attained (stopping rule). To address the first problem synaptic eligibility traces were introduced, bridging the temporal gap between a stimulus and its reward. Although, these were mere theoretical constructs, recent experiments have provided evidence of their existence. These experiments also reveal that the presence of specific neuromodulators converts the traces into changes in synaptic efficacy. A mechanistic implementation of the stopping rule usually assumes the inhibition of the reward nucleus; however, recent experimental results have shown that learning terminates at the appropriate network state even in setups where the reward nucleus cannot be inhibited. In an effort to describe a learning rule that solves the temporal credit assignment problem and implements a biologically plausible stopping rule, we proposed a model based on two separate synaptic eligibility traces, one for long-term potentiation (LTP) and one for long-term depression (LTD), each obeying different dynamics and having different effective magnitudes. The model has been shown to successfully generate stable learning in recurrent networks. Although, the model assumes the presence of a single neuromodulator, evidence indicates that there are different neuromodulators for expressing the different traces. What could be the role of different neuromodulators for expressing the LTP and LTD traces? Here we expand on our previous model to include several neuromodulators, and illustrate through various examples how different these contribute to learning reward-timing within a wide set of training paradigms and propose further roles that multiple neuromodulators can play in encoding additional information of the rewarding signal.

Finite dimensional approximation of a class of constrained nonlinear optimal control problems

NASA Technical Reports Server (NTRS)

Gunzburger, Max D.; Hou, L. S.

1994-01-01

An abstract framework for the analysis and approximation of a class of nonlinear optimal control and optimization problems is constructed. Nonlinearities occur in both the objective functional and in the constraints. The framework includes an abstract nonlinear optimization problem posed on infinite dimensional spaces, and approximate problem posed on finite dimensional spaces, together with a number of hypotheses concerning the two problems. The framework is used to show that optimal solutions exist, to show that Lagrange multipliers may be used to enforce the constraints, to derive an optimality system from which optimal states and controls may be deduced, and to derive existence results and error estimates for solutions of the approximate problem. The abstract framework and the results derived from that framework are then applied to three concrete control or optimization problems and their approximation by finite element methods. The first involves the von Karman plate equations of nonlinear elasticity, the second, the Ginzburg-Landau equations of superconductivity, and the third, the Navier-Stokes equations for incompressible, viscous flows.

LDRD Final Report: Global Optimization for Engineering Science Problems

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

HART,WILLIAM E.

1999-12-01

For a wide variety of scientific and engineering problems the desired solution corresponds to an optimal set of objective function parameters, where the objective function measures a solution's quality. The main goal of the LDRD ''Global Optimization for Engineering Science Problems'' was the development of new robust and efficient optimization algorithms that can be used to find globally optimal solutions to complex optimization problems. This SAND report summarizes the technical accomplishments of this LDRD, discusses lessons learned and describes open research issues.

SMART Application: One stop services bridging the gap between doctor and patients

NASA Astrophysics Data System (ADS)

Wiweko, Budi; Agung, P. G.; Narasati, Shabrina

2017-02-01

In this study, we describe the SMART IVF services that has been developed into android-based application as "SMART Application". In this application, we can find one stop services in IVF. This application is expected to help patients to plan effectively for IVF procedure, full access to their IVF information helps them ease off a lot of stress and anxiety in this very delicate and stressful phase in their lives and help the doctor to plan for the best intervention of patients who face infertility problems using Assisted Reproductive Technology (ART). SMART application will be compatible with all major mobile operating systems.

Control strategies for planetary rover motion and manipulator control

NASA Technical Reports Server (NTRS)

Trautwein, W.

1973-01-01

An unusual insect-like vehicle designed for planetary surface exploration is made the occasion for a discussion of control concepts in path selection, hazard detection, obstacle negotiation, and soil sampling. A control scheme which actively articulates the pitching motion between a single-loop front module and a dual loop rear module leads to near optimal behavior in soft soil; at the same time the vehicle's front module acts as a reliable tactile forward probe with a detection range much longer than the stopping distance. Some optimal control strategies are discussed, and the photos of a working scale model are displayed.

Optimal design for slip deceleration control in anti-lock braking system

NASA Astrophysics Data System (ADS)

Mishra, Sheelam; Kumar, Pankaj; Rahman, Mohd. Saifur

2018-05-01

ABS (Anti-lock Braking System) is the most advanced braking system implemented in modern cars to avoid the slipping or skidding of the vehicle on the road. Moreover, it reduces the stopping distance of the vehicle because it avoids the locking of the wheel during braking. It enables the driver to steer the vehicle during braking. But every system has its downsides and likewise ABS too, it is not efficient during normal braking or snowy conditions. Our aim is to overcome these downsides and optimize Anti-lock Braking System to make it even better.

Audible monitor for electroplating

NASA Technical Reports Server (NTRS)

Burowick, E. A.

1979-01-01

"No buzzer" indicates early problem in electroplating when parts are properly immersed into electropolating bath. Buzzer sounds when current flows through part; however, if current is cut, buzzer stops warning that parts must be removed and refinished thus preventing unnecessary waste of electrical energy and labor.

The "Shopping" Behavior of Parents of Mentally Retarded Children: The Professional Person's Role

ERIC Educational Resources Information Center

Anderson, Kathryn A.

1971-01-01

Discussed is the role of the professional in preventing or stopping diagnostic and therapeutic shopping (repeated visits to the same or different professionals without resolution of a resolvable problem), with emphasis on the initial informing interview. (KW)

Research on NC laser combined cutting optimization model of sheet metal parts

NASA Astrophysics Data System (ADS)

Wu, Z. Y.; Zhang, Y. L.; Li, L.; Wu, L. H.; Liu, N. B.

2017-09-01

The optimization problem for NC laser combined cutting of sheet metal parts was taken as the research object in this paper. The problem included two contents: combined packing optimization and combined cutting path optimization. In the problem of combined packing optimization, the method of “genetic algorithm + gravity center NFP + geometric transformation” was used to optimize the packing of sheet metal parts. In the problem of combined cutting path optimization, the mathematical model of cutting path optimization was established based on the parts cutting constraint rules of internal contour priority and cross cutting. The model played an important role in the optimization calculation of NC laser combined cutting.

Quadratic constrained mixed discrete optimization with an adiabatic quantum optimizer

NASA Astrophysics Data System (ADS)

Chandra, Rishabh; Jacobson, N. Tobias; Moussa, Jonathan E.; Frankel, Steven H.; Kais, Sabre

2014-07-01

We extend the family of problems that may be implemented on an adiabatic quantum optimizer (AQO). When a quadratic optimization problem has at least one set of discrete controls and the constraints are linear, we call this a quadratic constrained mixed discrete optimization (QCMDO) problem. QCMDO problems are NP-hard, and no efficient classical algorithm for their solution is known. Included in the class of QCMDO problems are combinatorial optimization problems constrained by a linear partial differential equation (PDE) or system of linear PDEs. An essential complication commonly encountered in solving this type of problem is that the linear constraint may introduce many intermediate continuous variables into the optimization while the computational cost grows exponentially with problem size. We resolve this difficulty by developing a constructive mapping from QCMDO to quadratic unconstrained binary optimization (QUBO) such that the size of the QUBO problem depends only on the number of discrete control variables. With a suitable embedding, taking into account the physical constraints of the realizable coupling graph, the resulting QUBO problem can be implemented on an existing AQO. The mapping itself is efficient, scaling cubically with the number of continuous variables in the general case and linearly in the PDE case if an efficient preconditioner is available.

An Enhanced Memetic Algorithm for Single-Objective Bilevel Optimization Problems.

PubMed

Islam, Md Monjurul; Singh, Hemant Kumar; Ray, Tapabrata; Sinha, Ankur

2017-01-01

Bilevel optimization, as the name reflects, deals with optimization at two interconnected hierarchical levels. The aim is to identify the optimum of an upper-level  leader problem, subject to the optimality of a lower-level follower problem. Several problems from the domain of engineering, logistics, economics, and transportation have an inherent nested structure which requires them to be modeled as bilevel optimization problems. Increasing size and complexity of such problems has prompted active theoretical and practical interest in the design of efficient algorithms for bilevel optimization. Given the nested nature of bilevel problems, the computational effort (number of function evaluations) required to solve them is often quite high. In this article, we explore the use of a Memetic Algorithm (MA) to solve bilevel optimization problems. While MAs have been quite successful in solving single-level optimization problems, there have been relatively few studies exploring their potential for solving bilevel optimization problems. MAs essentially attempt to combine advantages of global and local search strategies to identify optimum solutions with low computational cost (function evaluations). The approach introduced in this article is a nested Bilevel Memetic Algorithm (BLMA). At both upper and lower levels, either a global or a local search method is used during different phases of the search. The performance of BLMA is presented on twenty-five standard test problems and two real-life applications. The results are compared with other established algorithms to demonstrate the efficacy of the proposed approach.

To the North Coast of Devon: Collaborative Navigation While Exploring Unfamiliar Terrain

NASA Technical Reports Server (NTRS)

Clancey, William J.; Lee, Pascal; Cockell, Charles S.; Braham, Stephen; Shafto, Mike

2006-01-01

Navigation-knowing where one is and finding a safe route-is a fundamental aspect of all exploration. In unfamiliar terrain, one may use maps and instruments such as a compass or binoculars to assist, and people often collaborate in finding their way. This paper analyzes a group of people driving a humvee from a base camp to the north coast of Devon Island in the High Canadian Arctic. A complete audio recording and video during most stops allows a quantitative and semantic analysis of the conversations when the team stopped to take bearings and replan a route. Over a period of 2 hours, the humvee stopped 20 times, with an average duration of 3.15 min/pause and 3.85 min moving forward. The team failed to reach its goal due to difficult terrain causing mechanical problems. The analysis attempts to explain these facts by considering a variety of complicating factors, especially the navigation problem of relating maps and the world to locate the humvee and to plan a route. The analysis reveals patterns in topic structure and turn-taking, supporting the view that the collaboration was efficient, but the tools and information were inadequate for the task. This work is relevant for planning and training for planetary surface missions, as well as developing computer systems that could aid navigation.

Optimal Price Decision Problem for Simultaneous Multi-article Auction and Its Optimal Price Searching Method by Particle Swarm Optimization

NASA Astrophysics Data System (ADS)

Masuda, Kazuaki; Aiyoshi, Eitaro

We propose a method for solving optimal price decision problems for simultaneous multi-article auctions. An auction problem, originally formulated as a combinatorial problem, determines both every seller's whether or not to sell his/her article and every buyer's which article(s) to buy, so that the total utility of buyers and sellers will be maximized. Due to the duality theory, we transform it equivalently into a dual problem in which Lagrange multipliers are interpreted as articles' transaction price. As the dual problem is a continuous optimization problem with respect to the multipliers (i.e., the transaction prices), we propose a numerical method to solve it by applying heuristic global search methods. In this paper, Particle Swarm Optimization (PSO) is used to solve the dual problem, and experimental results are presented to show the validity of the proposed method.

Techniques for shuttle trajectory optimization

NASA Technical Reports Server (NTRS)

Edge, E. R.; Shieh, C. J.; Powers, W. F.

1973-01-01

The application of recently developed function-space Davidon-type techniques to the shuttle ascent trajectory optimization problem is discussed along with an investigation of the recently developed PRAXIS algorithm for parameter optimization. At the outset of this analysis, the major deficiency of the function-space algorithms was their potential storage problems. Since most previous analyses of the methods were with relatively low-dimension problems, no storage problems were encountered. However, in shuttle trajectory optimization, storage is a problem, and this problem was handled efficiently. Topics discussed include: the shuttle ascent model and the development of the particular optimization equations; the function-space algorithms; the operation of the algorithm and typical simulations; variable final-time problem considerations; and a modification of Powell's algorithm.

Preliminary Investigation of Longitudinal Differences in TEC and Scintillation at Transition Latitudes

DTIC Science & Technology

1991-04-04

AIR. j NO ABSOLUTE TEC. C: NEW SATELITE WINDOWS INSERTED. j - IAPEDRIVE PROBLEM. D: SOME DATA ON CHART NOT RECORDED ON TAPE. H = NPIB INTERFASE...PROBLEM. E: SOME DATA BROKEN UP. V 2 FLOPPY DISK/DRIVE PROBLEM. F: TAPE CHANGE. W - WRONG SATELITE WINDOWS. TOTAL HOURS OF ACTIVITY LEVEL 1:300 P - POWER...0 1 0 31 1 COMMENT’S: ADDITIONAL COMMENT’S. A: TAPE STOP * L1/L2 SCINTILLATION. B: GPS SYSTEM OFF THE AIR. O= N ABSOLUTE TEC. C: NEW SATELITE WINDOWS

Public Health Stops at the School House Door

PubMed Central

Paulson, Jerome A.; Barnett, Claire L.

2016-01-01

Summary: In the United States, all children of appropriate age are required to attend school, and many parents send their children to child care. Many school and day care buildings have been found to have environmental health problems that impact children’s health and diminish their ability to learn. No federal agency has the capacity or authority to identify, track, or remediate these problems. A recent meeting, coordinated by Healthy Schools Network, Inc., has developed a set of recommendations to begin to deal with the issue of environmental health problems in schools. PMID:27689395

The returns and risks of investment portfolio in stock market crashes

NASA Astrophysics Data System (ADS)

Li, Jiang-Cheng; Long, Chao; Chen, Xiao-Dan

2015-06-01

The returns and risks of investment portfolio in stock market crashes are investigated by considering a theoretical model, based on a modified Heston model with a cubic nonlinearity, proposed by Spagnolo and Valenti. Through numerically simulating probability density function of returns and the mean escape time of the model, the results indicate that: (i) the maximum stability of returns is associated with the maximum dispersion of investment portfolio and an optimal stop-loss position; (ii) the maximum risks are related with a worst dispersion of investment portfolio and the risks of investment portfolio are enhanced by increasing stop-loss position. In addition, the good agreements between the theoretical result and real market data are found in the behaviors of the probability density function and the mean escape time.

High precision AlGaAsSb ridge-waveguide etching by in situ reflectance monitored ICP-RIE

NASA Astrophysics Data System (ADS)

Tran, N. T.; Breivik, Magnus; Patra, S. K.; Fimland, Bjørn-Ove

2014-05-01

GaSb-based semiconductor diode lasers are promising candidates for light sources working in the mid-infrared wavelength region of 2-5 μm. Using edge emitting lasers with ridge-waveguide structure, light emission with good beam quality can be achieved. Fabrication of the ridge waveguide requires precise etch stop control for optimal laser performance. Simulation results are presented that show the effect of increased confinement in the waveguide when the etch depth is well-defined. In situ reflectance monitoring with a 675 nm-wavelength laser was used to determine the etch stop with high accuracy. Based on the simulations of laser reflectance from a proposed sample, the etching process can be controlled to provide an endpoint depth precision within +/- 10 nm.

On l(1): Optimal decentralized performance

NASA Technical Reports Server (NTRS)

Sourlas, Dennis; Manousiouthakis, Vasilios

1993-01-01

In this paper, the Manousiouthakis parametrization of all decentralized stabilizing controllers is employed in mathematically formulating the l(sup 1) optimal decentralized controller synthesis problem. The resulting optimization problem is infinite dimensional and therefore not directly amenable to computations. It is shown that finite dimensional optimization problems that have value arbitrarily close to the infinite dimensional one can be constructed. Based on this result, an algorithm that solves the l(sup 1) decentralized performance problems is presented. A global optimization approach to the solution of the infinite dimensional approximating problems is also discussed.

Execution of Multidisciplinary Design Optimization Approaches on Common Test Problems

NASA Technical Reports Server (NTRS)

Balling, R. J.; Wilkinson, C. A.

1997-01-01

A class of synthetic problems for testing multidisciplinary design optimization (MDO) approaches is presented. These test problems are easy to reproduce because all functions are given as closed-form mathematical expressions. They are constructed in such a way that the optimal value of all variables and the objective is unity. The test problems involve three disciplines and allow the user to specify the number of design variables, state variables, coupling functions, design constraints, controlling design constraints, and the strength of coupling. Several MDO approaches were executed on two sample synthetic test problems. These approaches included single-level optimization approaches, collaborative optimization approaches, and concurrent subspace optimization approaches. Execution results are presented, and the robustness and efficiency of these approaches an evaluated for these sample problems.

Time-domain finite elements in optimal control with application to launch-vehicle guidance. PhD. Thesis

NASA Technical Reports Server (NTRS)

Bless, Robert R.

1991-01-01

A time-domain finite element method is developed for optimal control problems. The theory derived is general enough to handle a large class of problems including optimal control problems that are continuous in the states and controls, problems with discontinuities in the states and/or system equations, problems with control inequality constraints, problems with state inequality constraints, or problems involving any combination of the above. The theory is developed in such a way that no numerical quadrature is necessary regardless of the degree of nonlinearity in the equations. Also, the same shape functions may be employed for every problem because all strong boundary conditions are transformed into natural or weak boundary conditions. In addition, the resulting nonlinear algebraic equations are very sparse. Use of sparse matrix solvers allows for the rapid and accurate solution of very difficult optimization problems. The formulation is applied to launch-vehicle trajectory optimization problems, and results show that real-time optimal guidance is realizable with this method. Finally, a general problem solving environment is created for solving a large class of optimal control problems. The algorithm uses both FORTRAN and a symbolic computation program to solve problems with a minimum of user interaction. The use of symbolic computation eliminates the need for user-written subroutines which greatly reduces the setup time for solving problems.

Evaluations of the Combat Ready Clamp to Control Bleeding in Human Cadavers, Manikins, Swine Femoral Artery Hemorrhage Model and Swine Carcasses

DTIC Science & Technology

2012-06-01

some advantages over alternative live tissue models when a mechanical device is employed to reduce arterial flow rates. Authentic human anatomy is...vessels to reduce and stop blood flow require authentic human anatomy for optimal testing. Cadaver I was approximately 60 year old male with a total

TU-FG-BRB-03: Basis Vector Model Based Method for Proton Stopping Power Estimation From Experimental Dual Energy CT Data

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

Zhang, S; Politte, D; O’Sullivan, J

2016-06-15

Purpose: This work aims at reducing the uncertainty in proton stopping power (SP) estimation by a novel combination of a linear, separable basis vector model (BVM) for stopping power calculation (Med Phys 43:600) and a statistical, model-based dual-energy CT (DECT) image reconstruction algorithm (TMI 35:685). The method was applied to experimental data. Methods: BVM assumes the photon attenuation coefficients, electron densities, and mean excitation energies (I-values) of unknown materials can be approximated by a combination of the corresponding quantities of two reference materials. The DECT projection data for a phantom with 5 different known materials was collected on a Philipsmore » Brilliance scanner using two scans at 90 kVp and 140 kVp. The line integral alternating minimization (LIAM) algorithm was used to recover the two BVM coefficient images using the measured source spectra. The proton stopping powers are then estimated from the Bethe-Bloch equation using electron densities and I-values derived from the BVM coefficients. The proton stopping powers and proton ranges for the phantom materials estimated via our BVM based DECT method are compared to ICRU reference values and a post-processing DECT analysis (Yang PMB 55:1343) applied to vendorreconstructed images using the Torikoshi parametric fit model (tPFM). Results: For the phantom materials, the average stopping power estimations for 175 MeV protons derived from our method are within 1% of the ICRU reference values (except for Teflon with a 1.48% error), with an average standard deviation of 0.46% over pixels. The resultant proton ranges agree with the reference values within 2 mm. Conclusion: Our principled DECT iterative reconstruction algorithm, incorporating optimal beam hardening and scatter corrections, in conjunction with a simple linear BVM model, achieves more accurate and robust proton stopping power maps than the post-processing, nonlinear tPFM based DECT analysis applied to conventional reconstructions of low and high energy scans. Funding Support: NIH R01CA 75371; NCI grant R01 CA 149305.« less

Employer's Guide: A Time for Action on Sexual Harassment in the Workplace = Guide de L'Employeur: Les Enjeux du Harcelement Sexuel au Travail.

ERIC Educational Resources Information Center

Ontario Women's Directorate, Toronto.

Harassment, like other forms of violence against women, is not a new problem. It is not a problem that will just go away, but it can be stopped. This guide is designed for use by organizations and employers to help them develop policies and implement programs in their workplace that address workplace sexual harassment. It focuses on Canadian…

An Empirical Comparison of Seven Iterative and Evolutionary Function Optimization Heuristics

NASA Technical Reports Server (NTRS)

Baluja, Shumeet

1995-01-01

This report is a repository of the results obtained from a large scale empirical comparison of seven iterative and evolution-based optimization heuristics. Twenty-seven static optimization problems, spanning six sets of problem classes which are commonly explored in genetic algorithm literature, are examined. The problem sets include job-shop scheduling, traveling salesman, knapsack, binpacking, neural network weight optimization, and standard numerical optimization. The search spaces in these problems range from 2368 to 22040. The results indicate that using genetic algorithms for the optimization of static functions does not yield a benefit, in terms of the final answer obtained, over simpler optimization heuristics. Descriptions of the algorithms tested and the encodings of the problems are described in detail for reproducibility.

Driver performance on approach to crossbuck and STOP sign equipped crossings

DOT National Transportation Integrated Search

2014-07-01

In order to improve safe driving behavior at grade crossings, it is important to understand driver actions at or on approach to those areas. Thus, in order to gain a better understanding of the problem, the Federal Railroad Administration (FRA) Offic...

Multiobjective optimization of temporal processes.

PubMed

Song, Zhe; Kusiak, Andrew

2010-06-01

This paper presents a dynamic predictive-optimization framework of a nonlinear temporal process. Data-mining (DM) and evolutionary strategy algorithms are integrated in the framework for solving the optimization model. DM algorithms learn dynamic equations from the process data. An evolutionary strategy algorithm is then applied to solve the optimization problem guided by the knowledge extracted by the DM algorithm. The concept presented in this paper is illustrated with the data from a power plant, where the goal is to maximize the boiler efficiency and minimize the limestone consumption. This multiobjective optimization problem can be either transformed into a single-objective optimization problem through preference aggregation approaches or into a Pareto-optimal optimization problem. The computational results have shown the effectiveness of the proposed optimization framework.

Charging conditions research to increase the initial projected velocity at different initial charge temperatures

NASA Astrophysics Data System (ADS)

Ishchenko, Aleksandr; Burkin, Viktor; Kasimov, Vladimir; Samorokova, Nina; Zykova, Angelica; Diachkovskii, Alexei

2017-11-01

The problems of the defense industry occupy the most important place in the constantly developing modern world. The daily development of defense technology does not stop, nor do studies on internal ballistics. The scientists of the whole world are faced with the task of managing the main characteristics of a ballistic experiment. The main characteristics of the ballistic experiment are the maximum pressure in the combustion chamber Pmax and the projected velocity at the time of barrel leaving UM. During the work the combustion law of the new high-energy fuel was determined in a ballistic experiment for different initial temperatures. This combustion law was used for a parametric study of depending Pmax and UM from a powder charge mass and a traveling charge was carried out. The optimal conditions for loading were obtained for improving the initial velocity at pressures up to 600 MPa for different initial temperatures. In this paper, one of the most promising schemes of throwing is considered, as well as a method for increasing the muzzle velocity of a projected element to 3317 m/s.

The Ebola Spatial Care Path™: Accelerating point-of-care diagnosis, decision making, and community resilience in outbreaks.

PubMed

Kost, Gerald J; Ferguson, William J; Hoe, Jackie; Truong, Anh-Thu; Banpavichit, Arirat; Kongpila, Surin

2015-01-01

To present a vision where point-of-care testing (POCT) accelerates an Ebola Spatial Care Path™ (SCP) and future molecular diagnostics enable facilitated-access self-testing (FAST POC); to design an alternate care facility (ACF) for the SCP; to innovate an Ebola diagnostic center (DC); and to propel rapid POCT to the frontline to create resilience that stops future outbreaks. PubMed, literature, and web searches. Centers for Disease Control and Prevention (CDC), Food and Drug Administration (FDA), Medicine Without Frontiers, and World Health Organization (WHO) document analyses. Investigations in China, the Philippines, Thailand, and the United States. Review of SE Asia, US, and West Africa isolation-treatment centers. Innovation of a SCP, ACF, and DC suitable for American and other communities. The authors designed an ACF and DC to integrate SCP principles for urgent Ebola care. FDA emergency use authorizations for Ebola molecular diagnostics were discovered, but no portable, handheld, or self-contained molecular POC instruments are yet available, although feasible. The WHO initiated design criteria and an acceptance protocol for testing. Financial investment in POCT will downsize Ebola outbreaks. POCT is facilitating global health. Now, global health problems are elevating POCT to new levels of importance for accelerating diagnosis and evidence-based decision making during disease outbreaks. Authorities concur that rapid diagnosis has potential to stop disease spread. With embedded POCT, strategic SCPs planned by communities fulfill CDC recommendations. POC devices should consolidate multiplex test clusters supporting patients with Ebola in isolation. The ultimate future solution is FAST POC. New technologies offer minimally significant risks. Diagnostic centers in ACFs and transportable formats also will optimize Ebola SCPs.

Social Emotional Optimization Algorithm for Nonlinear Constrained Optimization Problems

NASA Astrophysics Data System (ADS)

Xu, Yuechun; Cui, Zhihua; Zeng, Jianchao

Nonlinear programming problem is one important branch in operational research, and has been successfully applied to various real-life problems. In this paper, a new approach called Social emotional optimization algorithm (SEOA) is used to solve this problem which is a new swarm intelligent technique by simulating the human behavior guided by emotion. Simulation results show that the social emotional optimization algorithm proposed in this paper is effective and efficiency for the nonlinear constrained programming problems.

Clinical and immunologic follow-up of patients who stop venom immunotherapy.

PubMed

Keating, M U; Kagey-Sobotka, A; Hamilton, R G; Yunginger, J W

1991-09-01

We prospectively studied 51 self-selected Hymenoptera sting-sensitive patients to determine (1) whether a minimal or optimal duration for venom immunotherapy (VIT) exists and (2) whether clinical or immunologic parameters exist that are predictive of clinical immunity after VIT was stopped. After 2 to 10 years of VIT, all patients had deliberate sting challenges (DSCs) from live insects. If DSCs were tolerated, patients voluntarily stopped VIT and returned annually for repeat venom skin tests (VSTs) and DSCs. In most patients, it was possible to monitor VST and venom-specific antibody (Ab) levels before and after VIT was stopped. One-year after VIT, VST and venom-specific IgE and IgG Ab level results were variable; 49 patients tolerated DSC, whereas two patients exhibited generalized reactions. These two patients had pre-VIT histories of grade IV field-sting reactions and had received VIT for 2 years and 4 years, respectively. The short-term (1 year) risk of recurrence of clinical allergy to stings after VIT was higher in patients who had experienced grade IV field-sting reactions before VIT versus patients experiencing grade I to III reactions before VIT (2/15, 13% versus 0/36, 0%) and higher in patients who had received VIT for less than 5 years versus patients who received VIT for 5 or more years (2/20, 10% versus 0/31, 0%). We suggest that VIT should be continued for 5 years in patients with pre-VIT field-sting reactions of grade IV severity. VST and venom-specific Ab results do not reliably predict the outcome of DSC or the subsequent clinical course in individual patients stopping VIT.

Evolutionary optimization methods for accelerator design

NASA Astrophysics Data System (ADS)

Poklonskiy, Alexey A.

Many problems from the fields of accelerator physics and beam theory can be formulated as optimization problems and, as such, solved using optimization methods. Despite growing efficiency of the optimization methods, the adoption of modern optimization techniques in these fields is rather limited. Evolutionary Algorithms (EAs) form a relatively new and actively developed optimization methods family. They possess many attractive features such as: ease of the implementation, modest requirements on the objective function, a good tolerance to noise, robustness, and the ability to perform a global search efficiently. In this work we study the application of EAs to problems from accelerator physics and beam theory. We review the most commonly used methods of unconstrained optimization and describe the GATool, evolutionary algorithm and the software package, used in this work, in detail. Then we use a set of test problems to assess its performance in terms of computational resources, quality of the obtained result, and the tradeoff between them. We justify the choice of GATool as a heuristic method to generate cutoff values for the COSY-GO rigorous global optimization package for the COSY Infinity scientific computing package. We design the model of their mutual interaction and demonstrate that the quality of the result obtained by GATool increases as the information about the search domain is refined, which supports the usefulness of this model. We Giscuss GATool's performance on the problems suffering from static and dynamic noise and study useful strategies of GATool parameter tuning for these and other difficult problems. We review the challenges of constrained optimization with EAs and methods commonly used to overcome them. We describe REPA, a new constrained optimization method based on repairing, in exquisite detail, including the properties of its two repairing techniques: REFIND and REPROPT. We assess REPROPT's performance on the standard constrained optimization test problems for EA with a variety of different configurations and suggest optimal default parameter values based on the results. Then we study the performance of the REPA method on the same set of test problems and compare the obtained results with those of several commonly used constrained optimization methods with EA. Based on the obtained results, particularly on the outstanding performance of REPA on test problem that presents significant difficulty for other reviewed EAs, we conclude that the proposed method is useful and competitive. We discuss REPA parameter tuning for difficult problems and critically review some of the problems from the de-facto standard test problem set for the constrained optimization with EA. In order to demonstrate the practical usefulness of the developed method, we study several problems of accelerator design and demonstrate how they can be solved with EAs. These problems include a simple accelerator design problem (design a quadrupole triplet to be stigmatically imaging, find all possible solutions), a complex real-life accelerator design problem (an optimization of the front end section for the future neutrino factory), and a problem of the normal form defect function optimization which is used to rigorously estimate the stability of the beam dynamics in circular accelerators. The positive results we obtained suggest that the application of EAs to problems from accelerator theory can be very beneficial and has large potential. The developed optimization scenarios and tools can be used to approach similar problems.

A weak Hamiltonian finite element method for optimal control problems

NASA Technical Reports Server (NTRS)

Hodges, Dewey H.; Bless, Robert R.

1989-01-01

A temporal finite element method based on a mixed form of the Hamiltonian weak principle is developed for dynamics and optimal control problems. The mixed form of Hamilton's weak principle contains both displacements and momenta as primary variables that are expanded in terms of nodal values and simple polynomial shape functions. Unlike other forms of Hamilton's principle, however, time derivatives of the momenta and displacements do not appear therein; instead, only the virtual momenta and virtual displacements are differentiated with respect to time. Based on the duality that is observed to exist between the mixed form of Hamilton's weak principle and variational principles governing classical optimal control problems, a temporal finite element formulation of the latter can be developed in a rather straightforward manner. Several well-known problems in dynamics and optimal control are illustrated. The example dynamics problem involves a time-marching problem. As optimal control examples, elementary trajectory optimization problems are treated.

A weak Hamiltonian finite element method for optimal control problems

NASA Technical Reports Server (NTRS)

Hodges, Dewey H.; Bless, Robert R.

1990-01-01

A temporal finite element method based on a mixed form of the Hamiltonian weak principle is developed for dynamics and optimal control problems. The mixed form of Hamilton's weak principle contains both displacements and momenta as primary variables that are expanded in terms of nodal values and simple polynomial shape functions. Unlike other forms of Hamilton's principle, however, time derivatives of the momenta and displacements do not appear therein; instead, only the virtual momenta and virtual displacements are differentiated with respect to time. Based on the duality that is observed to exist between the mixed form of Hamilton's weak principle and variational principles governing classical optimal control problems, a temporal finite element formulation of the latter can be developed in a rather straightforward manner. Several well-known problems in dynamics and optimal control are illustrated. The example dynamics problem involves a time-marching problem. As optimal control examples, elementary trajectory optimization problems are treated.

Weak Hamiltonian finite element method for optimal control problems

NASA Technical Reports Server (NTRS)

Hodges, Dewey H.; Bless, Robert R.

1991-01-01

A temporal finite element method based on a mixed form of the Hamiltonian weak principle is developed for dynamics and optimal control problems. The mixed form of Hamilton's weak principle contains both displacements and momenta as primary variables that are expanded in terms of nodal values and simple polynomial shape functions. Unlike other forms of Hamilton's principle, however, time derivatives of the momenta and displacements do not appear therein; instead, only the virtual momenta and virtual displacements are differentiated with respect to time. Based on the duality that is observed to exist between the mixed form of Hamilton's weak principle and variational principles governing classical optimal control problems, a temporal finite element formulation of the latter can be developed in a rather straightforward manner. Several well-known problems in dynamics and optimal control are illustrated. The example dynamics problem involves a time-marching problem. As optimal control examples, elementary trajectory optimization problems are treated.

Causes Of Low Efficiency Of Combined Ventilation System In Coal Mines In Resolving The Problem Of Air Leaks (Inflows) Between Levels And Surface

NASA Astrophysics Data System (ADS)

Popov, Valeriy; Filatov, Yuriy; Lee, Hee; Golik, Anatoliy

2017-11-01

The paper discusses the problem of the underground mining safety control. The long-term air intake to coal accumulations is reviewed as one of the reasons of endogenous fires during mining. The methods of combating air leaks (inflows) in order to prevent endogenous fires are analyzed. The calculations showing the discrepancy between the design calculations for the mine ventilation, disregarding a number of mining-andgeological and mining-engineering factors, and the actual conditions of mining are given. It is proved that the conversion of operating mines to combined (pressure and exhaust) ventilation system in order to reduce the endogenous fire hazard of underground mining is unreasonable due to impossibility of providing an optimal distribution of aerodynamic pressure in mines. The conversion does not exclude the entry of air into potentially hazardous zones of endogenous fires. The essence of the combined application of positive and negative control methods for the distribution of air pressure is revealed. It consists of air doors installation in easily ventilated airways and installation of pressure equalization chambers equipped with auxiliary fans near the stoppings, working sections and in parallel airways.The effectiveness of the combined application of negative and positive control methods for the air pressure distribution in order to reduce endogenous fire hazard of mining operations is proved.

Risk analysis of heat recovery steam generator with semi quantitative risk based inspection API 581

NASA Astrophysics Data System (ADS)

Prayogo, Galang Sandy; Haryadi, Gunawan Dwi; Ismail, Rifky; Kim, Seon Jin

2016-04-01

Corrosion is a major problem that most often occurs in the power plant. Heat recovery steam generator (HRSG) is an equipment that has a high risk to the power plant. The impact of corrosion damage causing HRSG power plant stops operating. Furthermore, it could be threaten the safety of employees. The Risk Based Inspection (RBI) guidelines by the American Petroleum Institute (API) 58 has been used to risk analysis in the HRSG 1. By using this methodology, the risk that caused by unexpected failure as a function of the probability and consequence of failure can be estimated. This paper presented a case study relating to the risk analysis in the HRSG, starting with a summary of the basic principles and procedures of risk assessment and applying corrosion RBI for process industries. The risk level of each HRSG equipment were analyzed: HP superheater has a medium high risk (4C), HP evaporator has a medium-high risk (4C), and the HP economizer has a medium risk (3C). The results of the risk assessment using semi-quantitative method of standard API 581 based on the existing equipment at medium risk. In the fact, there is no critical problem in the equipment components. Damage mechanisms were prominent throughout the equipment is thinning mechanism. The evaluation of the risk approach was done with the aim of reducing risk by optimizing the risk assessment activities.

Dental patients' perceptions and motivation in smoking cessation activities.

PubMed

Andersson, Pia; Johannsen, Annsofi

2016-01-01

The aim of the present study was to investigate smokers' perceptions of and motivation for smoking cessation activities in dentistry. MATERIALS AND METHODS PATIENTS: who smoked were consecutively recruited from general as well as specialist dental care clinics in Sweden. After a dental visit the patients completed a questionnaire about self-perceived oral health, smoking habits, motivation, reasons to quit and not to quit smoking, support to quit, smoking cessation activities and questions about smoking asked by dentists and dental hygienists. The sample consisted of 167 adult patients (≥ 20 years) who smoked daily. During the last 6 months, 81% of the patients had experienced oral health problems. The most common complaints were discolourations of the teeth, periodontal problems and dry mouth (38%, 36% and 33%, respectively). Improved general health was a major reason to quit smoking (89%). It was also stated that it was important to avoid oral health problems. 71% of the patients preferred to quit by themselves and 16% wanted support from dentistry. High motivation to quit smoking was reported by 20%. Occurrence of periodontitis during the last 6 months was significantly associated with being highly motivated to stop smoking (OR = 3.0, 95% CI = 1.03-8.55). This study revealed that, although it was important to quit smoking to avoid oral health problems, the patients were not aware that tobacco cessation activities can be performed in dentistry. Periodontal problems seem to be the most motivating factor among the patients who were highly motivated to stop smoking.

Optimality conditions for the numerical solution of optimization problems with PDE constraints :

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

Aguilo Valentin, Miguel Alejandro; Ridzal, Denis

2014-03-01

A theoretical framework for the numerical solution of partial di erential equation (PDE) constrained optimization problems is presented in this report. This theoretical framework embodies the fundamental infrastructure required to e ciently implement and solve this class of problems. Detail derivations of the optimality conditions required to accurately solve several parameter identi cation and optimal control problems are also provided in this report. This will allow the reader to further understand how the theoretical abstraction presented in this report translates to the application.

FRANOPP: Framework for analysis and optimization problems user's guide

NASA Technical Reports Server (NTRS)

Riley, K. M.

1981-01-01

Framework for analysis and optimization problems (FRANOPP) is a software aid for the study and solution of design (optimization) problems which provides the driving program and plotting capability for a user generated programming system. In addition to FRANOPP, the programming system also contains the optimization code CONMIN, and two user supplied codes, one for analysis and one for output. With FRANOPP the user is provided with five options for studying a design problem. Three of the options utilize the plot capability and present an indepth study of the design problem. The study can be focused on a history of the optimization process or on the interaction of variables within the design problem.

Entropy evolution of moving mirrors and the information loss problem

NASA Astrophysics Data System (ADS)

Chen, Pisin; Yeom, Dong-han

2017-07-01

We investigate the entanglement entropy and the information flow of two-dimensional moving mirrors. Here we point out that various mirror trajectories can help to mimic different candidate resolutions to the information loss paradox following the semiclassical quantum field theory: (i) a suddenly stopping mirror corresponds to the assertion that all information is attached to the last burst, (ii) a slowly stopping mirror corresponds to the assertion that thermal Hawking radiation carries information, and (iii) a long propagating mirror corresponds to the remnant scenario. Based on such analogy, we find that the last burst of a black hole cannot contain enough information, while slowly emitting radiation can restore unitarity. For all cases, there is an apparent inconsistency between the picture based on quantum entanglements and that based on the semiclassical quantum field theory. Based on the quantum entanglement theory, a stopping mirror will generate a firewall-like violent emission which is in conflict with notions based on the semiclassical quantum field theory.

Evaluation of Genetic Algorithm Concepts Using Model Problems. Part 2; Multi-Objective Optimization

NASA Technical Reports Server (NTRS)

Holst, Terry L.; Pulliam, Thomas H.

2003-01-01

A genetic algorithm approach suitable for solving multi-objective optimization problems is described and evaluated using a series of simple model problems. Several new features including a binning selection algorithm and a gene-space transformation procedure are included. The genetic algorithm is suitable for finding pareto optimal solutions in search spaces that are defined by any number of genes and that contain any number of local extrema. Results indicate that the genetic algorithm optimization approach is flexible in application and extremely reliable, providing optimal results for all optimization problems attempted. The binning algorithm generally provides pareto front quality enhancements and moderate convergence efficiency improvements for most of the model problems. The gene-space transformation procedure provides a large convergence efficiency enhancement for problems with non-convoluted pareto fronts and a degradation in efficiency for problems with convoluted pareto fronts. The most difficult problems --multi-mode search spaces with a large number of genes and convoluted pareto fronts-- require a large number of function evaluations for GA convergence, but always converge.

Wireless Sensor Network Optimization: Multi-Objective Paradigm.

PubMed

Iqbal, Muhammad; Naeem, Muhammad; Anpalagan, Alagan; Ahmed, Ashfaq; Azam, Muhammad

2015-07-20

Optimization problems relating to wireless sensor network planning, design, deployment and operation often give rise to multi-objective optimization formulations where multiple desirable objectives compete with each other and the decision maker has to select one of the tradeoff solutions. These multiple objectives may or may not conflict with each other. Keeping in view the nature of the application, the sensing scenario and input/output of the problem, the type of optimization problem changes. To address different nature of optimization problems relating to wireless sensor network design, deployment, operation, planing and placement, there exist a plethora of optimization solution types. We review and analyze different desirable objectives to show whether they conflict with each other, support each other or they are design dependent. We also present a generic multi-objective optimization problem relating to wireless sensor network which consists of input variables, required output, objectives and constraints. A list of constraints is also presented to give an overview of different constraints which are considered while formulating the optimization problems in wireless sensor networks. Keeping in view the multi facet coverage of this article relating to multi-objective optimization, this will open up new avenues of research in the area of multi-objective optimization relating to wireless sensor networks.

Uncertainty Aware Structural Topology Optimization Via a Stochastic Reduced Order Model Approach

NASA Technical Reports Server (NTRS)

Aguilo, Miguel A.; Warner, James E.

2017-01-01

This work presents a stochastic reduced order modeling strategy for the quantification and propagation of uncertainties in topology optimization. Uncertainty aware optimization problems can be computationally complex due to the substantial number of model evaluations that are necessary to accurately quantify and propagate uncertainties. This computational complexity is greatly magnified if a high-fidelity, physics-based numerical model is used for the topology optimization calculations. Stochastic reduced order model (SROM) methods are applied here to effectively 1) alleviate the prohibitive computational cost associated with an uncertainty aware topology optimization problem; and 2) quantify and propagate the inherent uncertainties due to design imperfections. A generic SROM framework that transforms the uncertainty aware, stochastic topology optimization problem into a deterministic optimization problem that relies only on independent calls to a deterministic numerical model is presented. This approach facilitates the use of existing optimization and modeling tools to accurately solve the uncertainty aware topology optimization problems in a fraction of the computational demand required by Monte Carlo methods. Finally, an example in structural topology optimization is presented to demonstrate the effectiveness of the proposed uncertainty aware structural topology optimization approach.

A Kind of Nonlinear Programming Problem Based on Mixed Fuzzy Relation Equations Constraints

NASA Astrophysics Data System (ADS)

Li, Jinquan; Feng, Shuang; Mi, Honghai

In this work, a kind of nonlinear programming problem with non-differential objective function and under the constraints expressed by a system of mixed fuzzy relation equations is investigated. First, some properties of this kind of optimization problem are obtained. Then, a polynomial-time algorithm for this kind of optimization problem is proposed based on these properties. Furthermore, we show that this algorithm is optimal for the considered optimization problem in this paper. Finally, numerical examples are provided to illustrate our algorithms.

One-Stop Shop

ERIC Educational Resources Information Center

Protheroe, Nancy

2010-01-01

Full-service community schools do more than educate; they partner with the community to provide the supports and services that students and families need through one comprehensive, coordinated effort. By offering services on-site, full-service schools can help eliminate some barriers that families face such as problems with transportation, lack of…

Plagiarism in Academia

ERIC Educational Resources Information Center

Shahabuddin, Syed

2009-01-01

Plagiarism sometimes creates legal and ethical problems for students and faculty. It can have serious consequences. Fortunately, there are ways to stop plagiarism. There are many tools available to detect plagiarism, e.g. using software for detecting submitted articles. Also, there are many ways to punish a plagiarist, e.g. banning plagiarists…

The Demanding Job of Resident Assistant: Has It Grown Too Big for Students?

ERIC Educational Resources Information Center

Dodge, Susan

1990-01-01

More student resident assistants are dealing with such difficult problems as alcoholism, suicide, homophobia, racism, date rape, and stress. Some institutions have decided to stop using students to supervise dormitories, while others are working to make resident assistants more qualified. (MLW)

SAFE: Stopping AIDS through Functional Education.

ERIC Educational Resources Information Center

Hylton, Judith

This functional curriculum is intended to teach people with developmental disabilities or other learning problems how to prevent infection with HIV/AIDS (Human Immunodeficiency Virus/Acquired Immune Deficiency Syndrome). The entire curriculum includes six video segments, four illustrated brochures, 28 slides and illustrations, as well as a guide…

Supercritical tests of a self-optimizing, variable-Camber wind tunnel model

NASA Technical Reports Server (NTRS)

Levinsky, E. S.; Palko, R. L.

1979-01-01

A testing procedure was used in a 16-foot Transonic Propulsion Wind Tunnel which leads to optimum wing airfoil sections without stopping the tunnel for model changes. Being experimental, the optimum shapes obtained incorporate various three-dimensional and nonlinear viscous and transonic effects not included in analytical optimization methods. The method is a closed-loop, computer-controlled, interactive procedure and employs a Self-Optimizing Flexible Technology wing semispan model that conformally adapts the airfoil section at two spanwise control stations to maximize or minimize various prescribed merit functions subject to both equality and inequality constraints. The model, which employed twelve independent hydraulic actuator systems and flexible skins, was also used for conventional testing. Although six of seven optimizations attempted were at least partially convergent, further improvements in model skin smoothness and hydraulic reliability are required to make the technique fully operational.

Optimization of simultaneous tritium–radiocarbon internal gas proportional counting

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

Bonicalzi, R. M.; Aalseth, C. E.; Day, A. R.

Specific environmental applications can benefit from dual tritium and radiocarbon measurements in a single compound. Assuming typical environmental levels, it is often the low tritium activity relative to the higher radiocarbon activity that limits the dual measurement. In this paper, we explore the parameter space for a combined tritium and radiocarbon measurement using a methane sample mixed with an argon fill gas in low-background proportional counters of a specific design. We present an optimized methane percentage, detector fill pressure, and analysis energy windows to maximize measurement sensitivity while minimizing count time. The final optimized method uses a 9-atm fill ofmore » P35 (35% methane, 65% argon), and a tritium analysis window from 1.5 to 10.3 keV, which stops short of the tritium beta decay endpoint energy of 18.6 keV. This method optimizes tritium counting efficiency while minimizing radiocarbon beta decay interference.« less

On the unity of children’s phonological error patterns: Distinguishing symptoms from the problem

PubMed Central

Dinnsen, Daniel A.

2012-01-01

This article compares the claims of rule- and constraint-based accounts of three seemingly distinct error patterns, namely, Deaffrication, Consonant Harmony and Assibilation, in the sound system of a child with a phonological delay. It is argued that these error patterns are not separate problems, but rather are symptoms of a larger conspiracy to avoid word-initial coronal stops. The clinical implications of these findings are also considered. PMID:21787147

Treatment preferences of patients with binge eating disorder.

PubMed

Brody, Michelle L; Masheb, Robin M; Grilo, Carlos M

2005-05-01

The current study examined the treatment preferences of obese patients with binge eating disorder (BED). Participants were 103 consecutive patients with BED who responded to advertisements for treatment studies looking for persons who wanted to "stop binge eating and lose weight." In addition to completing comprehensive assessment batteries, participants were provided descriptions of cognitive-behavioral therapy (CBT) and behavioral weight loss therapy (BWL) after which they were asked to choose and rate their preferred treatment. Sixty-three percent of participants stated they preferred CBT. Treatment preferences were not associated with (1) histories of obesity, dieting, binge eating, or weight cycling, (2) current obesity or eating disorder features, or (3) psychological features such as depression or self-esteem levels. In contrast, participants' stated treatment preferences were aligned with their perception of their primary problem (eating disorder vs. obesity) and their primary goals for treatment (stop binge eating vs. lose weight). The patients who preferred CBT based their treatment selection more on their problem perception than on their primary treatment goal, whereas the patients who preferred BWL selected treatment based more on their primary treatment goal (weight loss) than on their problem perception. Obese patients with BED express treatment preferences that are not associated with variability in their clinical characteristics but are aligned with their perception of their primary problem and with their primary goals for treatment. Copyright 2005 by Wiley Periodicals, Inc

Fast Optimization for Aircraft Descent and Approach Trajectory

NASA Technical Reports Server (NTRS)

Luchinsky, Dmitry G.; Schuet, Stefan; Brenton, J.; Timucin, Dogan; Smith, David; Kaneshige, John

2017-01-01

We address problem of on-line scheduling of the aircraft descent and approach trajectory. We formulate a general multiphase optimal control problem for optimization of the descent trajectory and review available methods of its solution. We develop a fast algorithm for solution of this problem using two key components: (i) fast inference of the dynamical and control variables of the descending trajectory from the low dimensional flight profile data and (ii) efficient local search for the resulting reduced dimensionality non-linear optimization problem. We compare the performance of the proposed algorithm with numerical solution obtained using optimal control toolbox General Pseudospectral Optimal Control Software. We present results of the solution of the scheduling problem for aircraft descent using novel fast algorithm and discuss its future applications.

Research on cutting path optimization of sheet metal parts based on ant colony algorithm

NASA Astrophysics Data System (ADS)

Wu, Z. Y.; Ling, H.; Li, L.; Wu, L. H.; Liu, N. B.

2017-09-01

In view of the disadvantages of the current cutting path optimization methods of sheet metal parts, a new method based on ant colony algorithm was proposed in this paper. The cutting path optimization problem of sheet metal parts was taken as the research object. The essence and optimization goal of the optimization problem were presented. The traditional serial cutting constraint rule was improved. The cutting constraint rule with cross cutting was proposed. The contour lines of parts were discretized and the mathematical model of cutting path optimization was established. Thus the problem was converted into the selection problem of contour lines of parts. Ant colony algorithm was used to solve the problem. The principle and steps of the algorithm were analyzed.

Optimizing cinefilm.

PubMed

Kato, W; Wong, M

1975-01-01

A system for improving the quality of cinefilm and for maintaining quality control is described. Objective criteria for contrast, resolution, and grain structure were established to measure the effects of varying X-ray dose, f-stop, development temperature, and selection of film and developer. We found that all variables nust be adjusted to maximize the viewing quality and that similar denisty curves can be achieved, independently of the choice of film and developer.

Large-scale structural optimization

NASA Technical Reports Server (NTRS)

Sobieszczanski-Sobieski, J.

1983-01-01

Problems encountered by aerospace designers in attempting to optimize whole aircraft are discussed, along with possible solutions. Large scale optimization, as opposed to component-by-component optimization, is hindered by computational costs, software inflexibility, concentration on a single, rather than trade-off, design methodology and the incompatibility of large-scale optimization with single program, single computer methods. The software problem can be approached by placing the full analysis outside of the optimization loop. Full analysis is then performed only periodically. Problem-dependent software can be removed from the generic code using a systems programming technique, and then embody the definitions of design variables, objective function and design constraints. Trade-off algorithms can be used at the design points to obtain quantitative answers. Finally, decomposing the large-scale problem into independent subproblems allows systematic optimization of the problems by an organization of people and machines.

Application of the gravity search algorithm to multi-reservoir operation optimization

NASA Astrophysics Data System (ADS)

Bozorg-Haddad, Omid; Janbaz, Mahdieh; Loáiciga, Hugo A.

2016-12-01

Complexities in river discharge, variable rainfall regime, and drought severity merit the use of advanced optimization tools in multi-reservoir operation. The gravity search algorithm (GSA) is an evolutionary optimization algorithm based on the law of gravity and mass interactions. This paper explores the GSA's efficacy for solving benchmark functions, single reservoir, and four-reservoir operation optimization problems. The GSA's solutions are compared with those of the well-known genetic algorithm (GA) in three optimization problems. The results show that the GSA's results are closer to the optimal solutions than the GA's results in minimizing the benchmark functions. The average values of the objective function equal 1.218 and 1.746 with the GSA and GA, respectively, in solving the single-reservoir hydropower operation problem. The global solution equals 1.213 for this same problem. The GSA converged to 99.97% of the global solution in its average-performing history, while the GA converged to 97% of the global solution of the four-reservoir problem. Requiring fewer parameters for algorithmic implementation and reaching the optimal solution in fewer number of functional evaluations are additional advantages of the GSA over the GA. The results of the three optimization problems demonstrate a superior performance of the GSA for optimizing general mathematical problems and the operation of reservoir systems.

Discrete particle swarm optimization to solve multi-objective limited-wait hybrid flow shop scheduling problem

NASA Astrophysics Data System (ADS)

Santosa, B.; Siswanto, N.; Fiqihesa

2018-04-01

This paper proposes a discrete Particle Swam Optimization (PSO) to solve limited-wait hybrid flowshop scheduing problem with multi objectives. Flow shop schedulimg represents the condition when several machines are arranged in series and each job must be processed at each machine with same sequence. The objective functions are minimizing completion time (makespan), total tardiness time, and total machine idle time. Flow shop scheduling model always grows to cope with the real production system accurately. Since flow shop scheduling is a NP-Hard problem then the most suitable method to solve is metaheuristics. One of metaheuristics algorithm is Particle Swarm Optimization (PSO), an algorithm which is based on the behavior of a swarm. Originally, PSO was intended to solve continuous optimization problems. Since flow shop scheduling is a discrete optimization problem, then, we need to modify PSO to fit the problem. The modification is done by using probability transition matrix mechanism. While to handle multi objectives problem, we use Pareto Optimal (MPSO). The results of MPSO is better than the PSO because the MPSO solution set produced higher probability to find the optimal solution. Besides the MPSO solution set is closer to the optimal solution

Constraint Optimization Literature Review

DTIC Science & Technology

2015-11-01

COPs. 15. SUBJECT TERMS high-performance computing, mobile ad hoc network, optimization, constraint, satisfaction 16. SECURITY CLASSIFICATION OF: 17...Optimization Problems 1 2.1 Constraint Satisfaction Problems 1 2.2 Constraint Optimization Problems 3 3. Constraint Optimization Algorithms 9 3.1...Constraint Satisfaction Algorithms 9 3.1.1 Brute-Force search 9 3.1.2 Constraint Propagation 10 3.1.3 Depth-First Search 13 3.1.4 Local Search 18

Optimizing topological cascade resilience based on the structure of terrorist networks.

PubMed

Gutfraind, Alexander

2010-11-10

Complex socioeconomic networks such as information, finance and even terrorist networks need resilience to cascades--to prevent the failure of a single node from causing a far-reaching domino effect. We show that terrorist and guerrilla networks are uniquely cascade-resilient while maintaining high efficiency, but they become more vulnerable beyond a certain threshold. We also introduce an optimization method for constructing networks with high passive cascade resilience. The optimal networks are found to be based on cells, where each cell has a star topology. Counterintuitively, we find that there are conditions where networks should not be modified to stop cascades because doing so would come at a disproportionate loss of efficiency. Implementation of these findings can lead to more cascade-resilient networks in many diverse areas.

A Possible Role for End-Stopped V1 Neurons in the Perception of Motion: A Computational Model

PubMed Central

Zarei Eskikand, Parvin; Kameneva, Tatiana; Ibbotson, Michael R.; Burkitt, Anthony N.; Grayden, David B.

2016-01-01

We present a model of the early stages of processing in the visual cortex, in particular V1 and MT, to investigate the potential role of end-stopped V1 neurons in solving the aperture problem. A hierarchical network is used in which the incoming motion signals provided by complex V1 neurons and end-stopped V1 neurons proceed to MT neurons at the next stage. MT neurons are categorized into two types based on their function: integration and segmentation. The role of integration neurons is to propagate unambiguous motion signals arriving from those V1 neurons that emphasize object terminators (e.g. corners). Segmentation neurons detect the discontinuities in the input stimulus to control the activity of integration neurons. Although the activity of the complex V1 neurons at the terminators of the object accurately represents the direction of the motion, their level of activity is less than the activity of the neurons along the edges. Therefore, a model incorporating end-stopped neurons is essential to suppress ambiguous motion signals along the edges of the stimulus. It is shown that the unambiguous motion signals at terminators propagate over the rest of the object to achieve an accurate representation of motion. PMID:27741307

Comparison of Optimal Design Methods in Inverse Problems

PubMed Central

Banks, H. T.; Holm, Kathleen; Kappel, Franz

2011-01-01

Typical optimal design methods for inverse or parameter estimation problems are designed to choose optimal sampling distributions through minimization of a specific cost function related to the resulting error in parameter estimates. It is hoped that the inverse problem will produce parameter estimates with increased accuracy using data collected according to the optimal sampling distribution. Here we formulate the classical optimal design problem in the context of general optimization problems over distributions of sampling times. We present a new Prohorov metric based theoretical framework that permits one to treat succinctly and rigorously any optimal design criteria based on the Fisher Information Matrix (FIM). A fundamental approximation theory is also included in this framework. A new optimal design, SE-optimal design (standard error optimal design), is then introduced in the context of this framework. We compare this new design criteria with the more traditional D-optimal and E-optimal designs. The optimal sampling distributions from each design are used to compute and compare standard errors; the standard errors for parameters are computed using asymptotic theory or bootstrapping and the optimal mesh. We use three examples to illustrate ideas: the Verhulst-Pearl logistic population model [13], the standard harmonic oscillator model [13] and a popular glucose regulation model [16, 19, 29]. PMID:21857762

Buses of Cuernavaca—an agent-based model for universal random matrix behavior minimizing mutual information

NASA Astrophysics Data System (ADS)

Warchoł, Piotr

2018-06-01

The public transportation system of Cuernavaca, Mexico, exhibits random matrix theory statistics. In particular, the fluctuation of times between the arrival of buses on a given bus stop, follows the Wigner surmise for the Gaussian unitary ensemble. To model this, we propose an agent-based approach in which each bus driver tries to optimize his arrival time to the next stop with respect to an estimated arrival time of his predecessor. We choose a particular form of the associated utility function and recover the appropriate distribution in numerical experiments for a certain value of the only parameter of the model. We then investigate whether this value of the parameter is otherwise distinguished within an information theoretic approach and give numerical evidence that indeed it is associated with a minimum of averaged pairwise mutual information.

Influence of forces acting on side of machine on precision machining of large diameter holes

NASA Astrophysics Data System (ADS)

Fedorenko, M. A.; Bondarenko, J. A.; Sanina, T. M.

2018-03-01

One of the most important factors that increase efficiency, durability and reliability of rotating units is precision installation, preventive maintenance work, timely replacing of a failed or worn components and assemblies. These works should be carried out in the operation of the equipment, as the downtime in many cases leads to large financial losses. Stop of one unit of an industrial enterprise can interrupt the technological chain of production, resulting in a possible stop of the entire equipment. Improving the efficiency and optimization of the repair process increases accuracy of installation work when installing equipment, conducting restoration under operating conditions relevant for enterprises of different industries because it eliminates dismantling the equipment, sending it to maintenance, the expectation of equipment return, the new installation with the required quality and accuracy of repair.

[Correction of acute psychotic states in schizophrenia by rispolept solution per os].

PubMed

Panteleeva, G P; Korenev, A N; Barkhatova, A N

2004-01-01

To stop acute psychotic states during the first episode or relapses of schizophrenia, 37 patients were treated with rispolept solution per os during 2 weeks. A procedure of a fast transition to optimal daily doses of the drug after 1 day of treatment (searching period) with a following stabilization of mean daily doses (5.02-5.7 mg) at the stage of 14 day treatment course was used. Positive therapeutic effect by PANSS total score reduction, along with minor side-effects, were found in 91.9% patients. Stopping effect of rispolept on acute psychotic states, emerging from day 1 of the treatment, and general antipsychotic and therapeutic action, beginning from day 2-3 and increasing to day 14, were stated out. Efficacy of the drug in syndromes differing by psychopathological structure is emphasized.

Multiobjective optimization approach: thermal food processing.

PubMed

Abakarov, A; Sushkov, Y; Almonacid, S; Simpson, R

2009-01-01

The objective of this study was to utilize a multiobjective optimization technique for the thermal sterilization of packaged foods. The multiobjective optimization approach used in this study is based on the optimization of well-known aggregating functions by an adaptive random search algorithm. The applicability of the proposed approach was illustrated by solving widely used multiobjective test problems taken from the literature. The numerical results obtained for the multiobjective test problems and for the thermal processing problem show that the proposed approach can be effectively used for solving multiobjective optimization problems arising in the food engineering field.

Selective inhibition of a multicomponent response can be achieved without cost

PubMed Central

Westrick, Zachary; Ivry, Richard B.

2014-01-01

Behavioral flexibility frequently requires the ability to modify an on-going action. In some situations, optimal performance requires modifying some components of an on-going action without interrupting other components of that action. This form of control has been studied with the selective stop-signal task, in which participants are instructed to abort only one movement of a multicomponent response. Previous studies have shown a transient disruption of the nonaborted component, suggesting limitations in our ability to use selective inhibition. This cost has been attributed to a structural limitation associated with the recruitment of a cortico-basal ganglia pathway that allows for the rapid inhibition of action but operates in a relatively generic manner. Using a model-based approach, we demonstrate that, with a modest amount of training and highly compatible stimulus-response mappings, people can perform a selective-stop task without any cost on the nonaborted component. Prior reports of behavioral costs in selective-stop tasks reflect, at least in part, a sampling bias in the method commonly used to estimate such costs. These results suggest that inhibition can be selectively controlled and present a challenge for models of inhibitory control that posit the operation of generic processes. PMID:25339712

Replica analysis for the duality of the portfolio optimization problem

NASA Astrophysics Data System (ADS)

Shinzato, Takashi

2016-11-01

In the present paper, the primal-dual problem consisting of the investment risk minimization problem and the expected return maximization problem in the mean-variance model is discussed using replica analysis. As a natural extension of the investment risk minimization problem under only a budget constraint that we analyzed in a previous study, we herein consider a primal-dual problem in which the investment risk minimization problem with budget and expected return constraints is regarded as the primal problem, and the expected return maximization problem with budget and investment risk constraints is regarded as the dual problem. With respect to these optimal problems, we analyze a quenched disordered system involving both of these optimization problems using the approach developed in statistical mechanical informatics and confirm that both optimal portfolios can possess the primal-dual structure. Finally, the results of numerical simulations are shown to validate the effectiveness of the proposed method.

Replica analysis for the duality of the portfolio optimization problem.

PubMed

Shinzato, Takashi

2016-11-01

In the present paper, the primal-dual problem consisting of the investment risk minimization problem and the expected return maximization problem in the mean-variance model is discussed using replica analysis. As a natural extension of the investment risk minimization problem under only a budget constraint that we analyzed in a previous study, we herein consider a primal-dual problem in which the investment risk minimization problem with budget and expected return constraints is regarded as the primal problem, and the expected return maximization problem with budget and investment risk constraints is regarded as the dual problem. With respect to these optimal problems, we analyze a quenched disordered system involving both of these optimization problems using the approach developed in statistical mechanical informatics and confirm that both optimal portfolios can possess the primal-dual structure. Finally, the results of numerical simulations are shown to validate the effectiveness of the proposed method.

Fine tuning of optical signals in nanoporous anodic alumina photonic crystals by apodized sinusoidal pulse anodisation.

PubMed

Santos, Abel; Law, Cheryl Suwen; Chin Lei, Dominique Wong; Pereira, Taj; Losic, Dusan

2016-11-03

In this study, we present an advanced nanofabrication approach to produce gradient-index photonic crystal structures based on nanoporous anodic alumina. An apodization strategy is for the first time applied to a sinusoidal pulse anodisation process in order to engineer the photonic stop band of nanoporous anodic alumina (NAA) in depth. Four apodization functions are explored, including linear positive, linear negative, logarithmic positive and logarithmic negative, with the aim of finely tuning the characteristic photonic stop band of these photonic crystal structures. We systematically analyse the effect of the amplitude difference (from 0.105 to 0.840 mA cm -2 ), the pore widening time (from 0 to 6 min), the anodisation period (from 650 to 950 s) and the anodisation time (from 15 to 30 h) on the quality and the position of the characteristic photonic stop band and the interferometric colour of these photonic crystal structures using the aforementioned apodization functions. Our results reveal that a logarithmic negative apodisation function is the most optimal approach to obtain unprecedented well-resolved and narrow photonic stop bands across the UV-visible-NIR spectrum of NAA-based gradient-index photonic crystals. Our study establishes a fully comprehensive rationale towards the development of unique NAA-based photonic crystal structures with finely engineered optical properties for advanced photonic devices such as ultra-sensitive optical sensors, selective optical filters and all-optical platforms for quantum computing.

Drinking Problems of Native American and White Youth.

ERIC Educational Resources Information Center

Forslund, Morris A.

1979-01-01

Found that American Indian youths tend to experience more serious consequences of drinking than do White youths from the same area with regard to feeling high, getting drunk, passing out, suffering loss of memory, being stopped by police, having automobile accidents, and getting into trouble with parents. (Author/BEF)

Structural-Thermal-Optical Program (STOP)

NASA Technical Reports Server (NTRS)

Lee, H. P.

1972-01-01

A structural thermal optical computer program is developed which uses a finite element approach and applies the Ritz method for solving heat transfer problems. Temperatures are represented at the vertices of each element and the displacements which yield deformations at any point of the heated surface are interpolated through grid points.

Safety in the Chemical Laboratory: Flood Control.

ERIC Educational Resources Information Center

Pollard, Bruce D.

1983-01-01

Describes events leading to a flood in the Wehr Chemistry Laboratory at Marquette University, discussing steps taken to minimize damage upon discovery. Analyzes the problem of flooding in the chemical laboratory and outlines seven steps of flood control: prevention; minimization; early detection; stopping the flood; evaluation; clean-up; and…

Responding to Bullying: What Works?

ERIC Educational Resources Information Center

Craig, Wendy; Pepler, Debra; Blais, Julie

2007-01-01

Children who are bullied are often told to "solve the problems themselves"; however, when bullying is repeated over time, it becomes increasingly difficult for victimized children to stop the torment because of their relative lack of power. We examine the ways in which children respond to bullying and their evaluations of the…

Stop, Think, Proceed: Solving Problems in the Real World

ERIC Educational Resources Information Center

Isbell, Jackie S.; Jolivette, Kristine

2011-01-01

Prevalence reports indicate approximately half of all children diagnosed with autism spectrum disorder (ASD) have a mild form of the disorder such as high-functioning autism, Asperger syndrome, or pervasive developmental disorder--not otherwise specified. These disorders are referred to collectively as high-functioning autism spectrum disorders…

Positive Perspectives on the Profession: Reframing through Appreciative Inquiry

ERIC Educational Resources Information Center

Fiorentino, Leah Holland

2012-01-01

Change theories and Organization Development strategies have long followed the problem-solving approach of looking at organizations, identifying the weaknesses and introducing interventions to "stop doing the wrong things." In its simplest form, this approach has been successful in a variety of situations and has a popular following. Consultants…

Green School Checklist: Environmental Actions for Schools To Consider.

ERIC Educational Resources Information Center

Illinois Environmental Protection Agency, Springfield.

This checklist offers tips and resources to help schools identify opportunities to "green" their buildings and operations, focusing on common-sense improvements that schools can make in their daily operations to minimize or stop potential health and environmental problems before they start. The first section discusses the benefits of a…

Possibilities of Cooperation with Eastern Europe.

ERIC Educational Resources Information Center

Horvath, Attila

This paper presents possible methods of cooperation in the area of U.S. educational exchange with Hungary and other Eastern Bloc countries. Specific problems are featured, and information is provided about legal, political, and economic issues and concerns. The paper stresses the need to stop thinking of these countries as politically homogeneous…

How I Manage Shin Splints.

PubMed

Andrish, J; Work, J A

1990-12-01

Shin splints are a common problem for athletes whose sports involve a repeated, jarring impact to the leg. Often they are due to a change in activity level. Stopping the activity until the pain subsides, and then gradually working back up to the desired level is generally the best treatment and protection against recurrence.

Studies on the flight medical aspects of the German Lufthansa non-stop route from Frankfurt to Rio de Janeiro, part 1

NASA Technical Reports Server (NTRS)

Wegmann, H. M.; Klein, K. E.; Goeters, K. M.; Samel, A.

1982-01-01

The problem of crew size for regularly scheduled flights between Frankfurt and Rio de Janeiro is discussed. Factors affecting crew performance are examined, comparisons are drawn to regulations of other countries and crew questionnaires and tests are presented.

Going Back to School: Participation Motives and Experiences of Older Adults in an Undergraduate Classroom.

ERIC Educational Resources Information Center

Scala, Marisa A.

1996-01-01

Interviews with 191 older adults attending college (131 females, 60 males) revealed that gender, educational attainment, employment status, and degree-seeking behavior were important sources of differences in motivation for participating. Personal or family health problems were most frequently cited for stopping attendance. (SK)

Overload and Boredom: When the Humanities Turn to Noise.

ERIC Educational Resources Information Center

Walter, James A.

This paper argues that the current debate over humanities curricula has failed to articulate a vision for humanities education because it has turned on a liberal/conservative axis. It also contends that educators must stop debating elite versus democratic values or traditional versus contemporary problems in humanities education, and start…

E-Portfolios: Making Things E-asy

ERIC Educational Resources Information Center

Waters, John K.

2007-01-01

With test scores dipping, dropout rates spiking, and disciplinary problems multiplying, student motivation was in short supply at Hope High School in East Providence, Rhode Island, when, in 2002, the state commissioner of education stepped in to stop the slide. After months of planning, the state reorganized the school into three smaller,…

Pulling out All the Stops

ERIC Educational Resources Information Center

Sezer, Renan

2010-01-01

This article discusses how an active learning environment was created in a community college class and a high school mathematics class using the same approach. In both settings the NCTM and AMATYC Standards, such as problem solving, communication, use of technology and alternate assessment, were fully embraced. The goal was to have students take…

The Schrodinger Eigenvalue March

ERIC Educational Resources Information Center

Tannous, C.; Langlois, J.

2011-01-01

A simple numerical method for the determination of Schrodinger equation eigenvalues is introduced. It is based on a marching process that starts from an arbitrary point, proceeds in two opposite directions simultaneously and stops after a tolerance criterion is met. The method is applied to solving several 1D potential problems including symmetric…

Cognitive Education in Four Canadian Prisons.

ERIC Educational Resources Information Center

Volpe, Richard; And Others

1985-01-01

This article reports the evaluation of a cognitive education course designed for inmates in Canadian federal penitentiaries. Reports from school instructors indicate that participating inmates showed improvement in their ability to communicate and discuss ideas and were more able to stop and think before acting on a problem. (Author/CT)

The coral reefs optimization algorithm: a novel metaheuristic for efficiently solving optimization problems.

PubMed

Salcedo-Sanz, S; Del Ser, J; Landa-Torres, I; Gil-López, S; Portilla-Figueras, J A

2014-01-01

This paper presents a novel bioinspired algorithm to tackle complex optimization problems: the coral reefs optimization (CRO) algorithm. The CRO algorithm artificially simulates a coral reef, where different corals (namely, solutions to the optimization problem considered) grow and reproduce in coral colonies, fighting by choking out other corals for space in the reef. This fight for space, along with the specific characteristics of the corals' reproduction, produces a robust metaheuristic algorithm shown to be powerful for solving hard optimization problems. In this research the CRO algorithm is tested in several continuous and discrete benchmark problems, as well as in practical application scenarios (i.e., optimum mobile network deployment and off-shore wind farm design). The obtained results confirm the excellent performance of the proposed algorithm and open line of research for further application of the algorithm to real-world problems.

The Coral Reefs Optimization Algorithm: A Novel Metaheuristic for Efficiently Solving Optimization Problems

PubMed Central

Salcedo-Sanz, S.; Del Ser, J.; Landa-Torres, I.; Gil-López, S.; Portilla-Figueras, J. A.

2014-01-01

This paper presents a novel bioinspired algorithm to tackle complex optimization problems: the coral reefs optimization (CRO) algorithm. The CRO algorithm artificially simulates a coral reef, where different corals (namely, solutions to the optimization problem considered) grow and reproduce in coral colonies, fighting by choking out other corals for space in the reef. This fight for space, along with the specific characteristics of the corals' reproduction, produces a robust metaheuristic algorithm shown to be powerful for solving hard optimization problems. In this research the CRO algorithm is tested in several continuous and discrete benchmark problems, as well as in practical application scenarios (i.e., optimum mobile network deployment and off-shore wind farm design). The obtained results confirm the excellent performance of the proposed algorithm and open line of research for further application of the algorithm to real-world problems. PMID:25147860

Quantum Heterogeneous Computing for Satellite Positioning Optimization

NASA Astrophysics Data System (ADS)

Bass, G.; Kumar, V.; Dulny, J., III

2016-12-01

Hard optimization problems occur in many fields of academic study and practical situations. We present results in which quantum heterogeneous computing is used to solve a real-world optimization problem: satellite positioning. Optimization problems like this can scale very rapidly with problem size, and become unsolvable with traditional brute-force methods. Typically, such problems have been approximately solved with heuristic approaches; however, these methods can take a long time to calculate and are not guaranteed to find optimal solutions. Quantum computing offers the possibility of producing significant speed-up and improved solution quality. There are now commercially available quantum annealing (QA) devices that are designed to solve difficult optimization problems. These devices have 1000+ quantum bits, but they have significant hardware size and connectivity limitations. We present a novel heterogeneous computing stack that combines QA and classical machine learning and allows the use of QA on problems larger than the quantum hardware could solve in isolation. We begin by analyzing the satellite positioning problem with a heuristic solver, the genetic algorithm. The classical computer's comparatively large available memory can explore the full problem space and converge to a solution relatively close to the true optimum. The QA device can then evolve directly to the optimal solution within this more limited space. Preliminary experiments, using the Quantum Monte Carlo (QMC) algorithm to simulate QA hardware, have produced promising results. Working with problem instances with known global minima, we find a solution within 8% in a matter of seconds, and within 5% in a few minutes. Future studies include replacing QMC with commercially available quantum hardware and exploring more problem sets and model parameters. Our results have important implications for how heterogeneous quantum computing can be used to solve difficult optimization problems in any field.

An Integrated Procedure for the Structural Design of a Composite Rotor-Hydrofoil of a Water Current Turbine (WCT)

NASA Astrophysics Data System (ADS)

Oller Aramayo, S. A.; Nallim, L. G.; Oller, S.

2013-12-01

This paper shows an integrated structural design optimization of a composite rotor-hydrofoil of a water current turbine by means the finite elements method (FEM), using a Serial/Parallel mixing theory (Rastellini et al. Comput. Struct. 86:879-896, 2008, Martinez et al., 2007, Martinez and Oller Arch. Comput. Methods. 16(4):357-397, 2009, Martinez et al. Compos. Part B Eng. 42(2011):134-144, 2010) coupled with a fluid-dynamic formulation and multi-objective optimization algorithm (Gen and Cheng 1997, Lee et al. Compos. Struct. 99:181-192, 2013, Lee et al. Compos. Struct. 94(3):1087-1096, 2012). The composite hydrofoil of the turbine rotor has been design using a reinforced laminate composites, taking into account the optimization of the carbon fiber orientation to obtain the maximum strength and lower rotational-inertia. Also, these results have been compared with a steel hydrofoil remarking the different performance on both structures. The mechanical and geometrical parameters involved in the design of this fiber-reinforced composite material are the fiber orientation, number of layers, stacking sequence and laminate thickness. Water pressure in the rotor of the turbine is obtained from a coupled fluid-dynamic simulation (CFD), whose detail can be found in the reference Oller et al. (2012). The main purpose of this paper is to achieve a very low inertia rotor minimizing the start-stop effect, because it is applied in axial water flow turbine currently in design by the authors, in which is important to take the maximum advantage of the kinetic energy. The FEM simulation codes are engineered by CIMNE (International Center for Numerical Method in Engineering, Barcelona, Spain), COMPack for the solids problem application, KRATOS for fluid dynamic application and RMOP for the structural optimization. To validate the procedure here presented, many turbine rotors made of composite materials are analyzed and three of them are compared with the steel one.

Wireless Sensor Network Optimization: Multi-Objective Paradigm

PubMed Central

Iqbal, Muhammad; Naeem, Muhammad; Anpalagan, Alagan; Ahmed, Ashfaq; Azam, Muhammad

2015-01-01

Optimization problems relating to wireless sensor network planning, design, deployment and operation often give rise to multi-objective optimization formulations where multiple desirable objectives compete with each other and the decision maker has to select one of the tradeoff solutions. These multiple objectives may or may not conflict with each other. Keeping in view the nature of the application, the sensing scenario and input/output of the problem, the type of optimization problem changes. To address different nature of optimization problems relating to wireless sensor network design, deployment, operation, planing and placement, there exist a plethora of optimization solution types. We review and analyze different desirable objectives to show whether they conflict with each other, support each other or they are design dependent. We also present a generic multi-objective optimization problem relating to wireless sensor network which consists of input variables, required output, objectives and constraints. A list of constraints is also presented to give an overview of different constraints which are considered while formulating the optimization problems in wireless sensor networks. Keeping in view the multi facet coverage of this article relating to multi-objective optimization, this will open up new avenues of research in the area of multi-objective optimization relating to wireless sensor networks. PMID:26205271

Cost component analysis.

PubMed

Lörincz, András; Póczos, Barnabás

2003-06-01

In optimizations the dimension of the problem may severely, sometimes exponentially increase optimization time. Parametric function approximatiors (FAPPs) have been suggested to overcome this problem. Here, a novel FAPP, cost component analysis (CCA) is described. In CCA, the search space is resampled according to the Boltzmann distribution generated by the energy landscape. That is, CCA converts the optimization problem to density estimation. Structure of the induced density is searched by independent component analysis (ICA). The advantage of CCA is that each independent ICA component can be optimized separately. In turn, (i) CCA intends to partition the original problem into subproblems and (ii) separating (partitioning) the original optimization problem into subproblems may serve interpretation. Most importantly, (iii) CCA may give rise to high gains in optimization time. Numerical simulations illustrate the working of the algorithm.

The design of multirate digital control systems

NASA Technical Reports Server (NTRS)

Berg, M. C.

1986-01-01

The successive loop closures synthesis method is the only method for multirate (MR) synthesis in common use. A new method for MR synthesis is introduced which requires a gradient-search solution to a constrained optimization problem. Some advantages of this method are that the control laws for all control loops are synthesized simultaneously, taking full advantage of all cross-coupling effects, and that simple, low-order compensator structures are easily accomodated. The algorithm and associated computer program for solving the constrained optimization problem are described. The successive loop closures , optimal control, and constrained optimization synthesis methods are applied to two example design problems. A series of compensator pairs are synthesized for each example problem. The succesive loop closure, optimal control, and constrained optimization synthesis methods are compared, in the context of the two design problems.

The optimal location of piezoelectric actuators and sensors for vibration control of plates

NASA Astrophysics Data System (ADS)

Kumar, K. Ramesh; Narayanan, S.

2007-12-01

This paper considers the optimal placement of collocated piezoelectric actuator-sensor pairs on a thin plate using a model-based linear quadratic regulator (LQR) controller. LQR performance is taken as objective for finding the optimal location of sensor-actuator pairs. The problem is formulated using the finite element method (FEM) as multi-input-multi-output (MIMO) model control. The discrete optimal sensor and actuator location problem is formulated in the framework of a zero-one optimization problem. A genetic algorithm (GA) is used to solve the zero-one optimization problem. Different classical control strategies like direct proportional feedback, constant-gain negative velocity feedback and the LQR optimal control scheme are applied to study the control effectiveness.

Exploring the quantum speed limit with computer games

NASA Astrophysics Data System (ADS)

Sørensen, Jens Jakob W. H.; Pedersen, Mads Kock; Munch, Michael; Haikka, Pinja; Jensen, Jesper Halkjær; Planke, Tilo; Andreasen, Morten Ginnerup; Gajdacz, Miroslav; Mølmer, Klaus; Lieberoth, Andreas; Sherson, Jacob F.

2016-04-01

Humans routinely solve problems of immense computational complexity by intuitively forming simple, low-dimensional heuristic strategies. Citizen science (or crowd sourcing) is a way of exploiting this ability by presenting scientific research problems to non-experts. ‘Gamification’—the application of game elements in a non-game context—is an effective tool with which to enable citizen scientists to provide solutions to research problems. The citizen science games Foldit, EteRNA and EyeWire have been used successfully to study protein and RNA folding and neuron mapping, but so far gamification has not been applied to problems in quantum physics. Here we report on Quantum Moves, an online platform gamifying optimization problems in quantum physics. We show that human players are able to find solutions to difficult problems associated with the task of quantum computing. Players succeed where purely numerical optimization fails, and analyses of their solutions provide insights into the problem of optimization of a more profound and general nature. Using player strategies, we have thus developed a few-parameter heuristic optimization method that efficiently outperforms the most prominent established numerical methods. The numerical complexity associated with time-optimal solutions increases for shorter process durations. To understand this better, we produced a low-dimensional rendering of the optimization landscape. This rendering reveals why traditional optimization methods fail near the quantum speed limit (that is, the shortest process duration with perfect fidelity). Combined analyses of optimization landscapes and heuristic solution strategies may benefit wider classes of optimization problems in quantum physics and beyond.

Exploring the quantum speed limit with computer games.

PubMed

Sørensen, Jens Jakob W H; Pedersen, Mads Kock; Munch, Michael; Haikka, Pinja; Jensen, Jesper Halkjær; Planke, Tilo; Andreasen, Morten Ginnerup; Gajdacz, Miroslav; Mølmer, Klaus; Lieberoth, Andreas; Sherson, Jacob F

2016-04-14

Humans routinely solve problems of immense computational complexity by intuitively forming simple, low-dimensional heuristic strategies. Citizen science (or crowd sourcing) is a way of exploiting this ability by presenting scientific research problems to non-experts. 'Gamification'--the application of game elements in a non-game context--is an effective tool with which to enable citizen scientists to provide solutions to research problems. The citizen science games Foldit, EteRNA and EyeWire have been used successfully to study protein and RNA folding and neuron mapping, but so far gamification has not been applied to problems in quantum physics. Here we report on Quantum Moves, an online platform gamifying optimization problems in quantum physics. We show that human players are able to find solutions to difficult problems associated with the task of quantum computing. Players succeed where purely numerical optimization fails, and analyses of their solutions provide insights into the problem of optimization of a more profound and general nature. Using player strategies, we have thus developed a few-parameter heuristic optimization method that efficiently outperforms the most prominent established numerical methods. The numerical complexity associated with time-optimal solutions increases for shorter process durations. To understand this better, we produced a low-dimensional rendering of the optimization landscape. This rendering reveals why traditional optimization methods fail near the quantum speed limit (that is, the shortest process duration with perfect fidelity). Combined analyses of optimization landscapes and heuristic solution strategies may benefit wider classes of optimization problems in quantum physics and beyond.

Numerical optimization methods for controlled systems with parameters

NASA Astrophysics Data System (ADS)

Tyatyushkin, A. I.

2017-10-01

First- and second-order numerical methods for optimizing controlled dynamical systems with parameters are discussed. In unconstrained-parameter problems, the control parameters are optimized by applying the conjugate gradient method. A more accurate numerical solution in these problems is produced by Newton's method based on a second-order functional increment formula. Next, a general optimal control problem with state constraints and parameters involved on the righthand sides of the controlled system and in the initial conditions is considered. This complicated problem is reduced to a mathematical programming one, followed by the search for optimal parameter values and control functions by applying a multimethod algorithm. The performance of the proposed technique is demonstrated by solving application problems.

Data Understanding Applied to Optimization

NASA Technical Reports Server (NTRS)

Buntine, Wray; Shilman, Michael

1998-01-01

The goal of this research is to explore and develop software for supporting visualization and data analysis of search and optimization. Optimization is an ever-present problem in science. The theory of NP-completeness implies that the problems can only be resolved by increasingly smarter problem specific knowledge, possibly for use in some general purpose algorithms. Visualization and data analysis offers an opportunity to accelerate our understanding of key computational bottlenecks in optimization and to automatically tune aspects of the computation for specific problems. We will prototype systems to demonstrate how data understanding can be successfully applied to problems characteristic of NASA's key science optimization tasks, such as central tasks for parallel processing, spacecraft scheduling, and data transmission from a remote satellite.

Multiobjective Optimization Using a Pareto Differential Evolution Approach

NASA Technical Reports Server (NTRS)

Madavan, Nateri K.; Biegel, Bryan A. (Technical Monitor)

2002-01-01

Differential Evolution is a simple, fast, and robust evolutionary algorithm that has proven effective in determining the global optimum for several difficult single-objective optimization problems. In this paper, the Differential Evolution algorithm is extended to multiobjective optimization problems by using a Pareto-based approach. The algorithm performs well when applied to several test optimization problems from the literature.

On a distinctive feature of problems of calculating time-average characteristics of nuclear reactor optimal control sets

NASA Astrophysics Data System (ADS)

Trifonenkov, A. V.; Trifonenkov, V. P.

2017-01-01

This article deals with a feature of problems of calculating time-average characteristics of nuclear reactor optimal control sets. The operation of a nuclear reactor during threatened period is considered. The optimal control search problem is analysed. The xenon poisoning causes limitations on the variety of statements of the problem of calculating time-average characteristics of a set of optimal reactor power off controls. The level of xenon poisoning is limited. There is a problem of choosing an appropriate segment of the time axis to ensure that optimal control problem is consistent. Two procedures of estimation of the duration of this segment are considered. Two estimations as functions of the xenon limitation were plot. Boundaries of the interval of averaging are defined more precisely.

Robust optimization modelling with applications to industry and environmental problems

NASA Astrophysics Data System (ADS)

Chaerani, Diah; Dewanto, Stanley P.; Lesmana, Eman

2017-10-01

Robust Optimization (RO) modeling is one of the existing methodology for handling data uncertainty in optimization problem. The main challenge in this RO methodology is how and when we can reformulate the robust counterpart of uncertain problems as a computationally tractable optimization problem or at least approximate the robust counterpart by a tractable problem. Due to its definition the robust counterpart highly depends on how we choose the uncertainty set. As a consequence we can meet this challenge only if this set is chosen in a suitable way. The development on RO grows fast, since 2004, a new approach of RO called Adjustable Robust Optimization (ARO) is introduced to handle uncertain problems when the decision variables must be decided as a ”wait and see” decision variables. Different than the classic Robust Optimization (RO) that models decision variables as ”here and now”. In ARO, the uncertain problems can be considered as a multistage decision problem, thus decision variables involved are now become the wait and see decision variables. In this paper we present the applications of both RO and ARO. We present briefly all results to strengthen the importance of RO and ARO in many real life problems.

A Matrix-Free Algorithm for Multidisciplinary Design Optimization

NASA Astrophysics Data System (ADS)

Lambe, Andrew Borean

Multidisciplinary design optimization (MDO) is an approach to engineering design that exploits the coupling between components or knowledge disciplines in a complex system to improve the final product. In aircraft design, MDO methods can be used to simultaneously design the outer shape of the aircraft and the internal structure, taking into account the complex interaction between the aerodynamic forces and the structural flexibility. Efficient strategies are needed to solve such design optimization problems and guarantee convergence to an optimal design. This work begins with a comprehensive review of MDO problem formulations and solution algorithms. First, a fundamental MDO problem formulation is defined from which other formulations may be obtained through simple transformations. Using these fundamental problem formulations, decomposition methods from the literature are reviewed and classified. All MDO methods are presented in a unified mathematical notation to facilitate greater understanding. In addition, a novel set of diagrams, called extended design structure matrices, are used to simultaneously visualize both data communication and process flow between the many software components of each method. For aerostructural design optimization, modern decomposition-based MDO methods cannot efficiently handle the tight coupling between the aerodynamic and structural states. This fact motivates the exploration of methods that can reduce the computational cost. A particular structure in the direct and adjoint methods for gradient computation motivates the idea of a matrix-free optimization method. A simple matrix-free optimizer is developed based on the augmented Lagrangian algorithm. This new matrix-free optimizer is tested on two structural optimization problems and one aerostructural optimization problem. The results indicate that the matrix-free optimizer is able to efficiently solve structural and multidisciplinary design problems with thousands of variables and constraints. On the aerostructural test problem formulated with thousands of constraints, the matrix-free optimizer is estimated to reduce the total computational time by up to 90% compared to conventional optimizers.

A Matrix-Free Algorithm for Multidisciplinary Design Optimization

NASA Astrophysics Data System (ADS)

Lambe, Andrew Borean

Multidisciplinary design optimization (MDO) is an approach to engineering design that exploits the coupling between components or knowledge disciplines in a complex system to improve the final product. In aircraft design, MDO methods can be used to simultaneously design the outer shape of the aircraft and the internal structure, taking into account the complex interaction between the aerodynamic forces and the structural flexibility. Efficient strategies are needed to solve such design optimization problems and guarantee convergence to an optimal design. This work begins with a comprehensive review of MDO problem formulations and solution algorithms. First, a fundamental MDO problem formulation is defined from which other formulations may be obtained through simple transformations. Using these fundamental problem formulations, decomposition methods from the literature are reviewed and classified. All MDO methods are presented in a unified mathematical notation to facilitate greater understanding. In addition, a novel set of diagrams, called extended design structure matrices, are used to simultaneously visualize both data communication and process flow between the many software components of each method. For aerostructural design optimization, modern decomposition-based MDO methods cannot efficiently handle the tight coupling between the aerodynamic and structural states. This fact motivates the exploration of methods that can reduce the computational cost. A particular structure in the direct and adjoint methods for gradient computation. motivates the idea of a matrix-free optimization method. A simple matrix-free optimizer is developed based on the augmented Lagrangian algorithm. This new matrix-free optimizer is tested on two structural optimization problems and one aerostructural optimization problem. The results indicate that the matrix-free optimizer is able to efficiently solve structural and multidisciplinary design problems with thousands of variables and constraints. On the aerostructural test problem formulated with thousands of constraints, the matrix-free optimizer is estimated to reduce the total computational time by up to 90% compared to conventional optimizers.

A sequential linear optimization approach for controller design

NASA Technical Reports Server (NTRS)

Horta, L. G.; Juang, J.-N.; Junkins, J. L.

1985-01-01

A linear optimization approach with a simple real arithmetic algorithm is presented for reliable controller design and vibration suppression of flexible structures. Using first order sensitivity of the system eigenvalues with respect to the design parameters in conjunction with a continuation procedure, the method converts a nonlinear optimization problem into a maximization problem with linear inequality constraints. The method of linear programming is then applied to solve the converted linear optimization problem. The general efficiency of the linear programming approach allows the method to handle structural optimization problems with a large number of inequality constraints on the design vector. The method is demonstrated using a truss beam finite element model for the optimal sizing and placement of active/passive-structural members for damping augmentation. Results using both the sequential linear optimization approach and nonlinear optimization are presented and compared. The insensitivity to initial conditions of the linear optimization approach is also demonstrated.

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

Kolda, Christopher

In this talk, I review recent work on using a generalization of the Next-to-Minimal Supersymmetric Standard Model (NMSSM), called the Singlet-extended Minimal Supersymmetric Standard Model (SMSSM), to raise the mass of the Standard Model-like Higgs boson without requiring extremely heavy top squarks or large stop mixing. In so doing, this model solves the little hierarchy problem of the minimal model (MSSM), at the expense of leaving the {mu}-problem of the MSSM unresolved. This talk is based on work published in Refs. [1, 2, 3].

Design and multi-physics optimization of rotary MRF brakes

NASA Astrophysics Data System (ADS)

Topcu, Okan; Taşcıoğlu, Yiğit; Konukseven, Erhan İlhan

2018-03-01

Particle swarm optimization (PSO) is a popular method to solve the optimization problems. However, calculations for each particle will be excessive when the number of particles and complexity of the problem increases. As a result, the execution speed will be too slow to achieve the optimized solution. Thus, this paper proposes an automated design and optimization method for rotary MRF brakes and similar multi-physics problems. A modified PSO algorithm is developed for solving multi-physics engineering optimization problems. The difference between the proposed method and the conventional PSO is to split up the original single population into several subpopulations according to the division of labor. The distribution of tasks and the transfer of information to the next party have been inspired by behaviors of a hunting party. Simulation results show that the proposed modified PSO algorithm can overcome the problem of heavy computational burden of multi-physics problems while improving the accuracy. Wire type, MR fluid type, magnetic core material, and ideal current inputs have been determined by the optimization process. To the best of the authors' knowledge, this multi-physics approach is novel for optimizing rotary MRF brakes and the developed PSO algorithm is capable of solving other multi-physics engineering optimization problems. The proposed method has showed both better performance compared to the conventional PSO and also has provided small, lightweight, high impedance rotary MRF brake designs.

Grid artifact reduction for direct digital radiography detectors based on rotated stationary grids with homomorphic filtering

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

Kim, Dong Sik; Lee, Sanggyun

2013-06-15

Purpose: Grid artifacts are caused when using the antiscatter grid in obtaining digital x-ray images. In this paper, research on grid artifact reduction techniques is conducted especially for the direct detectors, which are based on amorphous selenium. Methods: In order to analyze and reduce the grid artifacts, the authors consider a multiplicative grid image model and propose a homomorphic filtering technique. For minimal damage due to filters, which are used to suppress the grid artifacts, rotated grids with respect to the sampling direction are employed, and min-max optimization problems for searching optimal grid frequencies and angles for given sampling frequenciesmore » are established. The authors then propose algorithms for the grid artifact reduction based on the band-stop filters as well as low-pass filters. Results: The proposed algorithms are experimentally tested for digital x-ray images, which are obtained from direct detectors with the rotated grids, and are compared with other algorithms. It is shown that the proposed algorithms can successfully reduce the grid artifacts for direct detectors. Conclusions: By employing the homomorphic filtering technique, the authors can considerably suppress the strong grid artifacts with relatively narrow-bandwidth filters compared to the normal filtering case. Using rotated grids also significantly reduces the ringing artifact. Furthermore, for specific grid frequencies and angles, the authors can use simple homomorphic low-pass filters in the spatial domain, and thus alleviate the grid artifacts with very low implementation complexity.« less

Algorithmic Perspectives on Problem Formulations in MDO

NASA Technical Reports Server (NTRS)

Alexandrov, Natalia M.; Lewis, Robert Michael

2000-01-01

This work is concerned with an approach to formulating the multidisciplinary optimization (MDO) problem that reflects an algorithmic perspective on MDO problem solution. The algorithmic perspective focuses on formulating the problem in light of the abilities and inabilities of optimization algorithms, so that the resulting nonlinear programming problem can be solved reliably and efficiently by conventional optimization techniques. We propose a modular approach to formulating MDO problems that takes advantage of the problem structure, maximizes the autonomy of implementation, and allows for multiple easily interchangeable problem statements to be used depending on the available resources and the characteristics of the application problem.

Optimization of pencil beam f-theta lens for high-accuracy metrology

NASA Astrophysics Data System (ADS)

Peng, Chuanqian; He, Yumei; Wang, Jie

2018-01-01

Pencil beam deflectometric profilers are common instruments for high-accuracy surface slope metrology of x-ray mirrors in synchrotron facilities. An f-theta optical system is a key optical component of the deflectometric profilers and is used to perform the linear angle-to-position conversion. Traditional optimization procedures of the f-theta systems are not directly related to the angle-to-position conversion relation and are performed with stops of large size and a fixed working distance, which means they may not be suitable for the design of f-theta systems working with a small-sized pencil beam within a working distance range for ultra-high-accuracy metrology. If an f-theta system is not well-designed, aberrations of the f-theta system will introduce many systematic errors into the measurement. A least-squares' fitting procedure was used to optimize the configuration parameters of an f-theta system. Simulations using ZEMAX software showed that the optimized f-theta system significantly suppressed the angle-to-position conversion errors caused by aberrations. Any pencil-beam f-theta optical system can be optimized with the help of this optimization method.

A general optimality criteria algorithm for a class of engineering optimization problems

NASA Astrophysics Data System (ADS)

Belegundu, Ashok D.

2015-05-01

An optimality criteria (OC)-based algorithm for optimization of a general class of nonlinear programming (NLP) problems is presented. The algorithm is only applicable to problems where the objective and constraint functions satisfy certain monotonicity properties. For multiply constrained problems which satisfy these assumptions, the algorithm is attractive compared with existing NLP methods as well as prevalent OC methods, as the latter involve computationally expensive active set and step-size control strategies. The fixed point algorithm presented here is applicable not only to structural optimization problems but also to certain problems as occur in resource allocation and inventory models. Convergence aspects are discussed. The fixed point update or resizing formula is given physical significance, which brings out a strength and trim feature. The number of function evaluations remains independent of the number of variables, allowing the efficient solution of problems with large number of variables.

Convex optimization problem prototyping for image reconstruction in computed tomography with the Chambolle-Pock algorithm

PubMed Central

Sidky, Emil Y.; Jørgensen, Jakob H.; Pan, Xiaochuan

2012-01-01

The primal-dual optimization algorithm developed in Chambolle and Pock (CP), 2011 is applied to various convex optimization problems of interest in computed tomography (CT) image reconstruction. This algorithm allows for rapid prototyping of optimization problems for the purpose of designing iterative image reconstruction algorithms for CT. The primal-dual algorithm is briefly summarized in the article, and its potential for prototyping is demonstrated by explicitly deriving CP algorithm instances for many optimization problems relevant to CT. An example application modeling breast CT with low-intensity X-ray illumination is presented. PMID:22538474

Wind Farm Turbine Type and Placement Optimization

NASA Astrophysics Data System (ADS)

Graf, Peter; Dykes, Katherine; Scott, George; Fields, Jason; Lunacek, Monte; Quick, Julian; Rethore, Pierre-Elouan

2016-09-01

The layout of turbines in a wind farm is already a challenging nonlinear, nonconvex, nonlinearly constrained continuous global optimization problem. Here we begin to address the next generation of wind farm optimization problems by adding the complexity that there is more than one turbine type to choose from. The optimization becomes a nonlinear constrained mixed integer problem, which is a very difficult class of problems to solve. This document briefly summarizes the algorithm and code we have developed, the code validation steps we have performed, and the initial results for multi-turbine type and placement optimization (TTP_OPT) we have run.

Wind farm turbine type and placement optimization

DOE PAGES

Graf, Peter; Dykes, Katherine; Scott, George; ...

2016-10-03

The layout of turbines in a wind farm is already a challenging nonlinear, nonconvex, nonlinearly constrained continuous global optimization problem. Here we begin to address the next generation of wind farm optimization problems by adding the complexity that there is more than one turbine type to choose from. The optimization becomes a nonlinear constrained mixed integer problem, which is a very difficult class of problems to solve. Furthermore, this document briefly summarizes the algorithm and code we have developed, the code validation steps we have performed, and the initial results for multi-turbine type and placement optimization (TTP_OPT) we have run.

Gravity inversion of a fault by Particle swarm optimization (PSO).

PubMed

Toushmalani, Reza

2013-01-01

Particle swarm optimization is a heuristic global optimization method and also an optimization algorithm, which is based on swarm intelligence. It comes from the research on the bird and fish flock movement behavior. In this paper we introduce and use this method in gravity inverse problem. We discuss the solution for the inverse problem of determining the shape of a fault whose gravity anomaly is known. Application of the proposed algorithm to this problem has proven its capability to deal with difficult optimization problems. The technique proved to work efficiently when tested to a number of models.

Post-Optimality Analysis In Aerospace Vehicle Design

NASA Technical Reports Server (NTRS)

Braun, Robert D.; Kroo, Ilan M.; Gage, Peter J.

1993-01-01

This analysis pertains to the applicability of optimal sensitivity information to aerospace vehicle design. An optimal sensitivity (or post-optimality) analysis refers to computations performed once the initial optimization problem is solved. These computations may be used to characterize the design space about the present solution and infer changes in this solution as a result of constraint or parameter variations, without reoptimizing the entire system. The present analysis demonstrates that post-optimality information generated through first-order computations can be used to accurately predict the effect of constraint and parameter perturbations on the optimal solution. This assessment is based on the solution of an aircraft design problem in which the post-optimality estimates are shown to be within a few percent of the true solution over the practical range of constraint and parameter variations. Through solution of a reusable, single-stage-to-orbit, launch vehicle design problem, this optimal sensitivity information is also shown to improve the efficiency of the design process, For a hierarchically decomposed problem, this computational efficiency is realized by estimating the main-problem objective gradient through optimal sep&ivity calculations, By reducing the need for finite differentiation of a re-optimized subproblem, a significant decrease in the number of objective function evaluations required to reach the optimal solution is obtained.

Analysis of a Two-Dimensional Thermal Cloaking Problem on the Basis of Optimization

NASA Astrophysics Data System (ADS)

Alekseev, G. V.

2018-04-01

For a two-dimensional model of thermal scattering, inverse problems arising in the development of tools for cloaking material bodies on the basis of a mixed thermal cloaking strategy are considered. By applying the optimization approach, these problems are reduced to optimization ones in which the role of controls is played by variable parameters of the medium occupying the cloaking shell and by the heat flux through a boundary segment of the basic domain. The solvability of the direct and optimization problems is proved, and an optimality system is derived. Based on its analysis, sufficient conditions on the input data are established that ensure the uniqueness and stability of optimal solutions.

Solving mixed integer nonlinear programming problems using spiral dynamics optimization algorithm

NASA Astrophysics Data System (ADS)

Kania, Adhe; Sidarto, Kuntjoro Adji

2016-02-01

Many engineering and practical problem can be modeled by mixed integer nonlinear programming. This paper proposes to solve the problem with modified spiral dynamics inspired optimization method of Tamura and Yasuda. Four test cases have been examined, including problem in engineering and sport. This method succeeds in obtaining the optimal result in all test cases.

ANTECEDENT VERSUS CONSEQUENT EVENTS AS PREDICTORS OF PROBLEM BEHAVIOR

PubMed Central

Camp, Erin M; Iwata, Brian A; Hammond, Jennifer L; Bloom, Sarah E

2009-01-01

Comparisons of results from descriptive and functional analyses of problem behavior generally have shown poor correspondence. Most descriptive analyses have focused on relations between consequent events and behavior, and it has been noted that attention is a common consequence for problem behavior even though it may not be a functional reinforcer. Because attention may be prescribed simply as a means of stopping serious problem behavior, it is possible that naturally occurring antecedent events (establishing operations) might be better predictors of problem behavior than consequences. We conducted descriptive and functional analyses of the problem behaviors of 7 participants. Conditional probabilities based on combined antecedent and consequent events showed correspondence with the functional analysis data for 4 of the 7 participants, but antecedent events were no better than consequent events in identifying the function of problem behavior. PMID:19949538

Research on Radiation Effects in Support of the Defense Nuclear Agency

DTIC Science & Technology

1993-01-01

relationships between pertinent parameters,------------ n. which can guide device design and optimization, aid the inter - CColleclor pretation of results from...Handbook for Stopping Cross Sections for of the parasiti ( npn-structure is the most effective measure to Energetic Ions in all Elements, Vol. 5, Pergamon... inter - actions between collector current, electric field distribution, 35 2262 and avalanche multiplication in the collector depletion region N are

Therapy for Duchenne muscular dystrophy: renewed optimism from genetic approaches.

PubMed

Fairclough, Rebecca J; Wood, Matthew J; Davies, Kay E

2013-06-01

Duchenne muscular dystrophy (DMD) is a devastating progressive disease for which there is currently no effective treatment except palliative therapy. There are several promising genetic approaches, including viral delivery of the missing dystrophin gene, read-through of translation stop codons, exon skipping to restore the reading frame and increased expression of the compensatory utrophin gene. The lessons learned from these approaches will be applicable to many other disorders.

Cohort profile: Seek and treat for the optimal prevention of HIV/AIDS in British Columbia (STOP HIV/AIDS BC).

PubMed

Heath, Kate; Samji, Hasina; Nosyk, Bohdan; Colley, Guillaume; Gilbert, Mark; Hogg, Robert S; Montaner, Julio Sg

2014-08-01

The Seek and Treat for Optimal Prevention of HIV/AIDS (STOP HIV/AIDS) cohort is a census of all identified HIV-positive individuals in the province of British Columbia. It was formed through the linkage of nine provincial treatment, surveillance and administrative databases. This open cohort allows for bidirectional analyses from 1996 onward and is refreshed annually. Extensive data collection for cohort members includes demographic information, detailed clinical and laboratory data, complete prescription drug use including antiretroviral agents, and information on health service utilization encompassing inpatient and outpatient care, addictions treatment and palliative care. This cohort provides an unprecedented opportunity to evaluate, over an extended time period, patterns and determinants of key outcomes including engagement in the cascade of HIV care from diagnosis to treatment to viral suppression as well as monitoring trends in medical costs, health outcomes and other key healthcare delivery indicators at a population level with wide-ranging, high-quality data. The overall purpose of these activities is to enable the development and implementation of strategically targeted interventions to improve access to testing, care and treatment for all HIV-positive individuals living in British Columbia. © The Author 2014; all rights reserved. Published by Oxford University Press on behalf of the International Epidemiological Association.

Nash equilibrium and multi criterion aerodynamic optimization

NASA Astrophysics Data System (ADS)

Tang, Zhili; Zhang, Lianhe

2016-06-01

Game theory and its particular Nash Equilibrium (NE) are gaining importance in solving Multi Criterion Optimization (MCO) in engineering problems over the past decade. The solution of a MCO problem can be viewed as a NE under the concept of competitive games. This paper surveyed/proposed four efficient algorithms for calculating a NE of a MCO problem. Existence and equivalence of the solution are analyzed and proved in the paper based on fixed point theorem. Specific virtual symmetric Nash game is also presented to set up an optimization strategy for single objective optimization problems. Two numerical examples are presented to verify proposed algorithms. One is mathematical functions' optimization to illustrate detailed numerical procedures of algorithms, the other is aerodynamic drag reduction of civil transport wing fuselage configuration by using virtual game. The successful application validates efficiency of algorithms in solving complex aerodynamic optimization problem.

Exact solution of large asymmetric traveling salesman problems.

PubMed

Miller, D L; Pekny, J F

1991-02-15

The traveling salesman problem is one of a class of difficult problems in combinatorial optimization that is representative of a large number of important scientific and engineering problems. A survey is given of recent applications and methods for solving large problems. In addition, an algorithm for the exact solution of the asymmetric traveling salesman problem is presented along with computational results for several classes of problems. The results show that the algorithm performs remarkably well for some classes of problems, determining an optimal solution even for problems with large numbers of cities, yet for other classes, even small problems thwart determination of a provably optimal solution.

Review: Optimization methods for groundwater modeling and management

NASA Astrophysics Data System (ADS)

Yeh, William W.-G.

2015-09-01

Optimization methods have been used in groundwater modeling as well as for the planning and management of groundwater systems. This paper reviews and evaluates the various optimization methods that have been used for solving the inverse problem of parameter identification (estimation), experimental design, and groundwater planning and management. Various model selection criteria are discussed, as well as criteria used for model discrimination. The inverse problem of parameter identification concerns the optimal determination of model parameters using water-level observations. In general, the optimal experimental design seeks to find sampling strategies for the purpose of estimating the unknown model parameters. A typical objective of optimal conjunctive-use planning of surface water and groundwater is to minimize the operational costs of meeting water demand. The optimization methods include mathematical programming techniques such as linear programming, quadratic programming, dynamic programming, stochastic programming, nonlinear programming, and the global search algorithms such as genetic algorithms, simulated annealing, and tabu search. Emphasis is placed on groundwater flow problems as opposed to contaminant transport problems. A typical two-dimensional groundwater flow problem is used to explain the basic formulations and algorithms that have been used to solve the formulated optimization problems.

A new chaotic multi-verse optimization algorithm for solving engineering optimization problems

NASA Astrophysics Data System (ADS)

Sayed, Gehad Ismail; Darwish, Ashraf; Hassanien, Aboul Ella

2018-03-01

Multi-verse optimization algorithm (MVO) is one of the recent meta-heuristic optimization algorithms. The main inspiration of this algorithm came from multi-verse theory in physics. However, MVO like most optimization algorithms suffers from low convergence rate and entrapment in local optima. In this paper, a new chaotic multi-verse optimization algorithm (CMVO) is proposed to overcome these problems. The proposed CMVO is applied on 13 benchmark functions and 7 well-known design problems in the engineering and mechanical field; namely, three-bar trust, speed reduce design, pressure vessel problem, spring design, welded beam, rolling element-bearing and multiple disc clutch brake. In the current study, a modified feasible-based mechanism is employed to handle constraints. In this mechanism, four rules were used to handle the specific constraint problem through maintaining a balance between feasible and infeasible solutions. Moreover, 10 well-known chaotic maps are used to improve the performance of MVO. The experimental results showed that CMVO outperforms other meta-heuristic optimization algorithms on most of the optimization problems. Also, the results reveal that sine chaotic map is the most appropriate map to significantly boost MVO's performance.

Optimal control of a harmonic oscillator: Economic interpretations

NASA Astrophysics Data System (ADS)

Janová, Jitka; Hampel, David

2013-10-01

Optimal control is a popular technique for modelling and solving the dynamic decision problems in economics. A standard interpretation of the criteria function and Lagrange multipliers in the profit maximization problem is well known. On a particular example, we aim to a deeper understanding of the possible economic interpretations of further mathematical and solution features of the optimal control problem: we focus on the solution of the optimal control problem for harmonic oscillator serving as a model for Phillips business cycle. We discuss the economic interpretations of arising mathematical objects with respect to well known reasoning for these in other problems.

The effectiveness of the Stop Now and Plan (SNAP) program for boys at risk for violence and delinquency.

PubMed

Burke, Jeffrey D; Loeber, Rolf

2015-02-01

Among the available treatments for disruptive behavior problems, a need remains for additional service options to reduce antisocial behavior and prevent further development along delinquent and violent pathways. The Stop Now and Plan (SNAP) Program is an intervention for antisocial behavior among boys between 6 and 11. This paper describes a randomized controlled treatment effectiveness study of SNAP versus standard behavioral health services. The treatment program was delivered to youth with aggressive, rule-breaking, or antisocial behavior in excess of clinical criterion levels. Outcomes were measured at 3, 9, and 15 months from baseline. Youth in the SNAP condition showed significantly greater reduction in aggression, conduct problems, and overall externalizing behavior, as well as counts of oppositional defiant disorder and attention deficit hyperactivity disorder symptoms. Additional benefits for SNAP were observed on measures of depression and anxiety. Further analyses indicated that the SNAP program was more effective among those with a higher severity of initial behavioral problems. At 1 year follow-up, treatment benefits for SNAP were maintained on some outcome measures (aggression, ADHD and ODD, depression and anxiety) but not others. Although overall juvenile justice system contact was not significantly different, youth in SNAP had significantly fewer charges against them relative to those standard services. The SNAP Program, when contrasted with standard services alone, was associated with greater, clinically meaningful, reductions in targeted behaviors. It may be particularly effective for youth with more severe behavioral problems and may result in improvements in internalizing problems as well.

Stopping randomized trials early for benefit: a protocol of the Study Of Trial Policy Of Interim Truncation-2 (STOPIT-2)

PubMed Central

Briel, Matthias; Lane, Melanie; Montori, Victor M; Bassler, Dirk; Glasziou, Paul; Malaga, German; Akl, Elie A; Ferreira-Gonzalez, Ignacio; Alonso-Coello, Pablo; Urrutia, Gerard; Kunz, Regina; Culebro, Carolina Ruiz; da Silva, Suzana Alves; Flynn, David N; Elamin, Mohamed B; Strahm, Brigitte; Murad, M Hassan; Djulbegovic, Benjamin; Adhikari, Neill KJ; Mills, Edward J; Gwadry-Sridhar, Femida; Kirpalani, Haresh; Soares, Heloisa P; Elnour, Nisrin O Abu; You, John J; Karanicolas, Paul J; Bucher, Heiner C; Lampropulos, Julianna F; Nordmann, Alain J; Burns, Karen EA; Mulla, Sohail M; Raatz, Heike; Sood, Amit; Kaur, Jagdeep; Bankhead, Clare R; Mullan, Rebecca J; Nerenberg, Kara A; Vandvik, Per Olav; Coto-Yglesias, Fernando; Schünemann, Holger; Tuche, Fabio; Chrispim, Pedro Paulo M; Cook, Deborah J; Lutz, Kristina; Ribic, Christine M; Vale, Noah; Erwin, Patricia J; Perera, Rafael; Zhou, Qi; Heels-Ansdell, Diane; Ramsay, Tim; Walter, Stephen D; Guyatt, Gordon H

2009-01-01

Background Randomized clinical trials (RCTs) stopped early for benefit often receive great attention and affect clinical practice, but pose interpretational challenges for clinicians, researchers, and policy makers. Because the decision to stop the trial may arise from catching the treatment effect at a random high, truncated RCTs (tRCTs) may overestimate the true treatment effect. The Study Of Trial Policy Of Interim Truncation (STOPIT-1), which systematically reviewed the epidemiology and reporting quality of tRCTs, found that such trials are becoming more common, but that reporting of stopping rules and decisions were often deficient. Most importantly, treatment effects were often implausibly large and inversely related to the number of the events accrued. The aim of STOPIT-2 is to determine the magnitude and determinants of possible bias introduced by stopping RCTs early for benefit. Methods/Design We will use sensitive strategies to search for systematic reviews addressing the same clinical question as each of the tRCTs identified in STOPIT-1 and in a subsequent literature search. We will check all RCTs included in each systematic review to determine their similarity to the index tRCT in terms of participants, interventions, and outcome definition, and conduct new meta-analyses addressing the outcome that led to early termination of the tRCT. For each pair of tRCT and systematic review of corresponding non-tRCTs we will estimate the ratio of relative risks, and hence estimate the degree of bias. We will use hierarchical multivariable regression to determine the factors associated with the magnitude of this ratio. Factors explored will include the presence and quality of a stopping rule, the methodological quality of the trials, and the number of total events that had occurred at the time of truncation. Finally, we will evaluate whether Bayesian methods using conservative informative priors to "regress to the mean" overoptimistic tRCTs can correct observed biases. Discussion A better understanding of the extent to which tRCTs exaggerate treatment effects and of the factors associated with the magnitude of this bias can optimize trial design and data monitoring charters, and may aid in the interpretation of the results from trials stopped early for benefit. PMID:19580665

"Talk with me": perspectives on services for men with problem gambling and housing instability.

PubMed

Guilcher, Sara J T; Hamilton-Wright, Sarah; Skinner, Wayne; Woodhall-Melnik, Julia; Ferentzy, Peter; Wendaferew, Aklilu; Hwang, Stephen W; Matheson, Flora I

2016-08-02

Problem gambling and homelessness are recognized as important public health concerns that significantly impact individuals, their friends and families, communities and broader society. We aimed to explore the experiences with health and social services of men who had histories of problem gambling and housing instability in Toronto, Ontario. We used a community-based participatory approach with a multi-service agency serving low-income individuals. We conducted qualitative interviews with men (n = 30) who had experienced problem gambling and housing instability. Our interviews employed open-ended questions to elicit men's perceptions of services related to housing instability, problem gambling and other comorbid conditions (e.g., mental illness, substance use). We reviewed relevant themes related to experiences with services (e.g., Use of and feedback on: health and social services, housing services, justice/legal aid services, substance use services, gambling services; stigma; goals; triggers; physical health; coping strategies; finances; relationships; barriers to services and recommendations for services). The concept of person-centred engagement was identified as a main overarching theme, and seemed to be lacking in most of the men's experiences of services. Person-centred engagement for these men entailed empowerment and autonomy; empathy, compassion and sincerity; respectful communication; and tailored and holistic life plans. While there was a strong emphasis placed on independence, the men identified the importance of positive therapeutic relationships as being critical aspects of the recovery process. Based on our analyses, several recommendations were identified: 1) Increasing general awareness of services for problem gambling; 2) Delivering integrated services in a one-stop-shop; 3) Addressing mental health with psychotherapy and pharmacotherapy; 4) Providing timely access to prevention and recovery services; and 5) Enhancing life skills with peer support. Our study highlighted that most of the men we interviewed were not having their health and social needs met. Services need to address the intersection of problem gambling, housing instability, and other comorbidities. Ensuring services are grounded in person-centred engagement appears to be critical for optimal service delivery.

Singular perturbation analysis of AOTV-related trajectory optimization problems

NASA Technical Reports Server (NTRS)

Calise, Anthony J.; Bae, Gyoung H.

1990-01-01

The problem of real time guidance and optimal control of Aeroassisted Orbit Transfer Vehicles (AOTV's) was addressed using singular perturbation theory as an underlying method of analysis. Trajectories were optimized with the objective of minimum energy expenditure in the atmospheric phase of the maneuver. Two major problem areas were addressed: optimal reentry, and synergetic plane change with aeroglide. For the reentry problem, several reduced order models were analyzed with the objective of optimal changes in heading with minimum energy loss. It was demonstrated that a further model order reduction to a single state model is possible through the application of singular perturbation theory. The optimal solution for the reduced problem defines an optimal altitude profile dependent on the current energy level of the vehicle. A separate boundary layer analysis is used to account for altitude and flight path angle dynamics, and to obtain lift and bank angle control solutions. By considering alternative approximations to solve the boundary layer problem, three guidance laws were derived, each having an analytic feedback form. The guidance laws were evaluated using a Maneuvering Reentry Research Vehicle model and all three laws were found to be near optimal. For the problem of synergetic plane change with aeroglide, a difficult terminal boundary layer control problem arises which to date is found to be analytically intractable. Thus a predictive/corrective solution was developed to satisfy the terminal constraints on altitude and flight path angle. A composite guidance solution was obtained by combining the optimal reentry solution with the predictive/corrective guidance method. Numerical comparisons with the corresponding optimal trajectory solutions show that the resulting performance is very close to optimal. An attempt was made to obtain numerically optimized trajectories for the case where heating rate is constrained. A first order state variable inequality constraint was imposed on the full order AOTV point mass equations of motion, using a simple aerodynamic heating rate model.

Conceptual Comparison of Population Based Metaheuristics for Engineering Problems

PubMed Central

Green, Paul

2015-01-01

Metaheuristic algorithms are well-known optimization tools which have been employed for solving a wide range of optimization problems. Several extensions of differential evolution have been adopted in solving constrained and nonconstrained multiobjective optimization problems, but in this study, the third version of generalized differential evolution (GDE) is used for solving practical engineering problems. GDE3 metaheuristic modifies the selection process of the basic differential evolution and extends DE/rand/1/bin strategy in solving practical applications. The performance of the metaheuristic is investigated through engineering design optimization problems and the results are reported. The comparison of the numerical results with those of other metaheuristic techniques demonstrates the promising performance of the algorithm as a robust optimization tool for practical purposes. PMID:25874265

Conceptual comparison of population based metaheuristics for engineering problems.

PubMed

Adekanmbi, Oluwole; Green, Paul

2015-01-01

Metaheuristic algorithms are well-known optimization tools which have been employed for solving a wide range of optimization problems. Several extensions of differential evolution have been adopted in solving constrained and nonconstrained multiobjective optimization problems, but in this study, the third version of generalized differential evolution (GDE) is used for solving practical engineering problems. GDE3 metaheuristic modifies the selection process of the basic differential evolution and extends DE/rand/1/bin strategy in solving practical applications. The performance of the metaheuristic is investigated through engineering design optimization problems and the results are reported. The comparison of the numerical results with those of other metaheuristic techniques demonstrates the promising performance of the algorithm as a robust optimization tool for practical purposes.

Efficiency of quantum vs. classical annealing in nonconvex learning problems

PubMed Central

Zecchina, Riccardo

2018-01-01

Quantum annealers aim at solving nonconvex optimization problems by exploiting cooperative tunneling effects to escape local minima. The underlying idea consists of designing a classical energy function whose ground states are the sought optimal solutions of the original optimization problem and add a controllable quantum transverse field to generate tunneling processes. A key challenge is to identify classes of nonconvex optimization problems for which quantum annealing remains efficient while thermal annealing fails. We show that this happens for a wide class of problems which are central to machine learning. Their energy landscapes are dominated by local minima that cause exponential slowdown of classical thermal annealers while simulated quantum annealing converges efficiently to rare dense regions of optimal solutions. PMID:29382764

Direct Multiple Shooting Optimization with Variable Problem Parameters

NASA Technical Reports Server (NTRS)

Whitley, Ryan J.; Ocampo, Cesar A.

2009-01-01

Taking advantage of a novel approach to the design of the orbital transfer optimization problem and advanced non-linear programming algorithms, several optimal transfer trajectories are found for problems with and without known analytic solutions. This method treats the fixed known gravitational constants as optimization variables in order to reduce the need for an advanced initial guess. Complex periodic orbits are targeted with very simple guesses and the ability to find optimal transfers in spite of these bad guesses is successfully demonstrated. Impulsive transfers are considered for orbits in both the 2-body frame as well as the circular restricted three-body problem (CRTBP). The results with this new approach demonstrate the potential for increasing robustness for all types of orbit transfer problems.

The pseudo-Boolean optimization approach to form the N-version software structure

NASA Astrophysics Data System (ADS)

Kovalev, I. V.; Kovalev, D. I.; Zelenkov, P. V.; Voroshilova, A. A.

2015-10-01

The problem of developing an optimal structure of N-version software system presents a kind of very complex optimization problem. This causes the use of deterministic optimization methods inappropriate for solving the stated problem. In this view, exploiting heuristic strategies looks more rational. In the field of pseudo-Boolean optimization theory, the so called method of varied probabilities (MVP) has been developed to solve problems with a large dimensionality. Some additional modifications of MVP have been made to solve the problem of N-version systems design. Those algorithms take into account the discovered specific features of the objective function. The practical experiments have shown the advantage of using these algorithm modifications because of reducing a search space.

Optimal control of LQR for discrete time-varying systems with input delays

NASA Astrophysics Data System (ADS)

Yin, Yue-Zhu; Yang, Zhong-Lian; Yin, Zhi-Xiang; Xu, Feng

2018-04-01

In this work, we consider the optimal control problem of linear quadratic regulation for discrete time-variant systems with single input and multiple input delays. An innovative and simple method to derive the optimal controller is given. The studied problem is first equivalently converted into a problem subject to a constraint condition. Last, with the established duality, the problem is transformed into a static mathematical optimisation problem without input delays. The optimal control input solution to minimise performance index function is derived by solving this optimisation problem with two methods. A numerical simulation example is carried out and its results show that our two approaches are both feasible and very effective.

Exact solution for an optimal impermeable parachute problem

NASA Astrophysics Data System (ADS)

Lupu, Mircea; Scheiber, Ernest

2002-10-01

In the paper there are solved direct and inverse boundary problems and analytical solutions are obtained for optimization problems in the case of some nonlinear integral operators. It is modeled the plane potential flow of an inviscid, incompressible and nonlimited fluid jet, witch encounters a symmetrical, curvilinear obstacle--the deflector of maximal drag. There are derived integral singular equations, for direct and inverse problems and the movement in the auxiliary canonical half-plane is obtained. Next, the optimization problem is solved in an analytical manner. The design of the optimal airfoil is performed and finally, numerical computations concerning the drag coefficient and other geometrical and aerodynamical parameters are carried out. This model corresponds to the Helmholtz impermeable parachute problem.

From nonlinear optimization to convex optimization through firefly algorithm and indirect approach with applications to CAD/CAM.

PubMed

Gálvez, Akemi; Iglesias, Andrés

2013-01-01

Fitting spline curves to data points is a very important issue in many applied fields. It is also challenging, because these curves typically depend on many continuous variables in a highly interrelated nonlinear way. In general, it is not possible to compute these parameters analytically, so the problem is formulated as a continuous nonlinear optimization problem, for which traditional optimization techniques usually fail. This paper presents a new bioinspired method to tackle this issue. In this method, optimization is performed through a combination of two techniques. Firstly, we apply the indirect approach to the knots, in which they are not initially the subject of optimization but precomputed with a coarse approximation scheme. Secondly, a powerful bioinspired metaheuristic technique, the firefly algorithm, is applied to optimization of data parameterization; then, the knot vector is refined by using De Boor's method, thus yielding a better approximation to the optimal knot vector. This scheme converts the original nonlinear continuous optimization problem into a convex optimization problem, solved by singular value decomposition. Our method is applied to some illustrative real-world examples from the CAD/CAM field. Our experimental results show that the proposed scheme can solve the original continuous nonlinear optimization problem very efficiently.

From Nonlinear Optimization to Convex Optimization through Firefly Algorithm and Indirect Approach with Applications to CAD/CAM

PubMed Central

Gálvez, Akemi; Iglesias, Andrés

2013-01-01

Fitting spline curves to data points is a very important issue in many applied fields. It is also challenging, because these curves typically depend on many continuous variables in a highly interrelated nonlinear way. In general, it is not possible to compute these parameters analytically, so the problem is formulated as a continuous nonlinear optimization problem, for which traditional optimization techniques usually fail. This paper presents a new bioinspired method to tackle this issue. In this method, optimization is performed through a combination of two techniques. Firstly, we apply the indirect approach to the knots, in which they are not initially the subject of optimization but precomputed with a coarse approximation scheme. Secondly, a powerful bioinspired metaheuristic technique, the firefly algorithm, is applied to optimization of data parameterization; then, the knot vector is refined by using De Boor's method, thus yielding a better approximation to the optimal knot vector. This scheme converts the original nonlinear continuous optimization problem into a convex optimization problem, solved by singular value decomposition. Our method is applied to some illustrative real-world examples from the CAD/CAM field. Our experimental results show that the proposed scheme can solve the original continuous nonlinear optimization problem very efficiently. PMID:24376380

Analytical and numerical analysis of inverse optimization problems: conditions of uniqueness and computational methods

PubMed Central

Zatsiorsky, Vladimir M.

2011-01-01

One of the key problems of motor control is the redundancy problem, in particular how the central nervous system (CNS) chooses an action out of infinitely many possible. A promising way to address this question is to assume that the choice is made based on optimization of a certain cost function. A number of cost functions have been proposed in the literature to explain performance in different motor tasks: from force sharing in grasping to path planning in walking. However, the problem of uniqueness of the cost function(s) was not addressed until recently. In this article, we analyze two methods of finding additive cost functions in inverse optimization problems with linear constraints, so-called linear-additive inverse optimization problems. These methods are based on the Uniqueness Theorem for inverse optimization problems that we proved recently (Terekhov et al., J Math Biol 61(3):423–453, 2010). Using synthetic data, we show that both methods allow for determining the cost function. We analyze the influence of noise on the both methods. Finally, we show how a violation of the conditions of the Uniqueness Theorem may lead to incorrect solutions of the inverse optimization problem. PMID:21311907

3D Pit Stop Printing

ERIC Educational Resources Information Center

Wright, Lael; Shaw, Daniel; Gaidds, Kimberly; Lyman, Gregory; Sorey, Timothy

2018-01-01

Although solving an engineering design project problem with limited resources or structural capabilities of materials can be part of the challenge, students making their own parts can support creativity. The authors of this article found an exciting solution: 3D printers are not only one of several tools for making but also facilitate a creative…

Embedded feature ranking for ensemble MLP classifiers.

PubMed

Windeatt, Terry; Duangsoithong, Rakkrit; Smith, Raymond

2011-06-01

A feature ranking scheme for multilayer perceptron (MLP) ensembles is proposed, along with a stopping criterion based upon the out-of-bootstrap estimate. To solve multi-class problems feature ranking is combined with modified error-correcting output coding. Experimental results on benchmark data demonstrate the versatility of the MLP base classifier in removing irrelevant features.

Operationalization of the Army National Guard: A Bridging Strategy to Stop the Cycle of Indecision

DTIC Science & Technology

2008-03-24

higher demand for forces. 11 This cycle of indecision is the heart of the problem that faces mobilizing ARNG formations. Indecision freezes action and...UNCLASSIFIED slides provided by ARNG Directorate of the National Guard Bureau. 18 Michael Ferriter and Jay Burdon, “The Success of Global Force

Some practical aspects of designing a large inventory

Treesearch

Kim Iles

2000-01-01

Designing a large multiresource inventory is horribly difficult, it is not work for faint hearts, and the 250,000,000-acre size of British Columbia is not a trivial problem. Completion of the details (as opposed to stopping the work) is a process prone to collapse. After that point, implementation is also likely to fail.

Speaking My Mind: Stop Reading Shakespeare!

ERIC Educational Resources Information Center

Spangler, Susan

2009-01-01

Reading skills are vital to student success, and those skills could be practiced with Shakespeare "if students are taught reading skills in the classroom." The problem is that many teachers of English do not consider themselves reading specialists and do not teach reading skills to their students. Fred L. Hamel notes that teachers in a recent…

Stopping the Bully: An Analysis of Texas House Bill 1942

ERIC Educational Resources Information Center

Kelly, Don R.

2016-01-01

Bullying is prevalent in our culture and can be recognizable through a competitive, capitalistic economy and a dominance hierarchy. Based on dominance, bullying continues to be a problem in our public schools as witnessed through nationally televised stories in Colorado (Columbine), Vermont (Ryan Halligan), and Missouri (Megan Meier), to name a…

Got It Wrong? Think Again. And Again.

ERIC Educational Resources Information Center

Miller, Donna L.

2013-01-01

Although the human mind resists confusion, this feeling of disequilibrium nurtures learning. Newkirk, the author quotes, says intelligence is not a matter of being smart--it is the capacity to view difficulty as an opportunity to stop, reassess, and employ strategies for making sense of problems. These same habits of mind define reflection, a…

Sexual Violence Prevention in Indiana: Toward Safer, Healthier Communities

ERIC Educational Resources Information Center

Cierniak, Katie; Heiman, Julia R.; Plucker, Jonathan A.

2012-01-01

For roughly three decades, policymakers have sought to reduce sexual violence by reliance on a criminal justice approach in which sexually violent acts are dealt with after they occur. Recognizing that prevention efforts could be more valuable, as they work to stop the problem before it begins, researchers have begun to implement a primary…

Secondary Physical Education Avoidance and Gender: Problems and Antidotes

ERIC Educational Resources Information Center

Ryan, Thomas; Poirier, Yves

2012-01-01

Our goal was to locate and evaluate the barriers that impact and cause females to avoid secondary elective physical education courses. We sought to find answers to stop the further decline of female enrolment in secondary physical education by looking into curricula, program and instructional variables. Anecdotal evidence informed this study which…

The Tension between Professors' and Students' Perceptions Regarding the Academic Environment.

ERIC Educational Resources Information Center

Hativa, Nira

This study was initiated in response to perceived behavior problems of undergraduate law school students at a research university in Israel. It was found that increasing numbers of students stopped attending classes on a regular basis, were not reading assigned materials, avoided participating in discussions, studied only superficially for exams,…

Bullying and Harassment: A Legal Guide for Educators

ERIC Educational Resources Information Center

Conn, Kathleen

2004-01-01

Any educator who wants to stop bullying and harassment needs to first understand the legal ins and outs of the problem. Here's a guide that provides the practical information needed to protect students and avoid litigation. Using actual court cases and school events that made major headlines, educator and attorney Kathleen Conn examines essentials…

Project STOP (Spectral Thermal Optimization Program)

NASA Technical Reports Server (NTRS)

Goldhammer, L. J.; Opjorden, R. W.; Goodelle, G. S.; Powe, J. S.

1977-01-01

The spectral thermal optimization of solar cell configurations for various solar panel applications is considered. The method of optimization depends upon varying the solar cell configuration's optical characteristics to minimize panel temperatures, maximize power output and decrease the power delta from beginning of life to end of life. Four areas of primary investigation are: (1) testing and evaluation of ultraviolet resistant coverslide adhesives, primarily FEP as an adhesive; (2) examination of solar cell absolute spectral response and corresponding cell manufacturing processes that affect it; (3) experimental work with solar cell manufacturing processes that vary cell reflectance (solar absorptance); and (4) experimental and theoretical studies with various coverslide filter designs, mainly a red rejection filter. The Hughes' solar array prediction program has been modified to aid in evaluating the effect of each of the above four areas on the output of a solar panel in orbit.

Helicopter Flight Procedures for Community Noise Reduction

NASA Technical Reports Server (NTRS)

Greenwood, Eric

2017-01-01

A computationally efficient, semiempirical noise model suitable for maneuvering flight noise prediction is used to evaluate the community noise impact of practical variations on several helicopter flight procedures typical of normal operations. Turns, "quick-stops," approaches, climbs, and combinations of these maneuvers are assessed. Relatively small variations in flight procedures are shown to cause significant changes to Sound Exposure Levels over a wide area. Guidelines are developed for helicopter pilots intended to provide effective strategies for reducing the negative effects of helicopter noise on the community. Finally, direct optimization of flight trajectories is conducted to identify low noise optimal flight procedures and quantify the magnitude of community noise reductions that can be obtained through tailored helicopter flight procedures. Physically realizable optimal turns and approaches are identified that achieve global noise reductions of as much as 10 dBA Sound Exposure Level.

Adaptive Constrained Optimal Control Design for Data-Based Nonlinear Discrete-Time Systems With Critic-Only Structure.

PubMed

Luo, Biao; Liu, Derong; Wu, Huai-Ning

2018-06-01

Reinforcement learning has proved to be a powerful tool to solve optimal control problems over the past few years. However, the data-based constrained optimal control problem of nonaffine nonlinear discrete-time systems has rarely been studied yet. To solve this problem, an adaptive optimal control approach is developed by using the value iteration-based Q-learning (VIQL) with the critic-only structure. Most of the existing constrained control methods require the use of a certain performance index and only suit for linear or affine nonlinear systems, which is unreasonable in practice. To overcome this problem, the system transformation is first introduced with the general performance index. Then, the constrained optimal control problem is converted to an unconstrained optimal control problem. By introducing the action-state value function, i.e., Q-function, the VIQL algorithm is proposed to learn the optimal Q-function of the data-based unconstrained optimal control problem. The convergence results of the VIQL algorithm are established with an easy-to-realize initial condition . To implement the VIQL algorithm, the critic-only structure is developed, where only one neural network is required to approximate the Q-function. The converged Q-function obtained from the critic-only VIQL method is employed to design the adaptive constrained optimal controller based on the gradient descent scheme. Finally, the effectiveness of the developed adaptive control method is tested on three examples with computer simulation.

Topology optimization of unsteady flow problems using the lattice Boltzmann method

NASA Astrophysics Data System (ADS)

Nørgaard, Sebastian; Sigmund, Ole; Lazarov, Boyan

2016-02-01

This article demonstrates and discusses topology optimization for unsteady incompressible fluid flows. The fluid flows are simulated using the lattice Boltzmann method, and a partial bounceback model is implemented to model the transition between fluid and solid phases in the optimization problems. The optimization problem is solved with a gradient based method, and the design sensitivities are computed by solving the discrete adjoint problem. For moderate Reynolds number flows, it is demonstrated that topology optimization can successfully account for unsteady effects such as vortex shedding and time-varying boundary conditions. Such effects are relevant in several engineering applications, i.e. fluid pumps and control valves.

Artificial bee colony algorithm for constrained possibilistic portfolio optimization problem

NASA Astrophysics Data System (ADS)

Chen, Wei

2015-07-01

In this paper, we discuss the portfolio optimization problem with real-world constraints under the assumption that the returns of risky assets are fuzzy numbers. A new possibilistic mean-semiabsolute deviation model is proposed, in which transaction costs, cardinality and quantity constraints are considered. Due to such constraints the proposed model becomes a mixed integer nonlinear programming problem and traditional optimization methods fail to find the optimal solution efficiently. Thus, a modified artificial bee colony (MABC) algorithm is developed to solve the corresponding optimization problem. Finally, a numerical example is given to illustrate the effectiveness of the proposed model and the corresponding algorithm.

Multiobjective Aerodynamic Shape Optimization Using Pareto Differential Evolution and Generalized Response Surface Metamodels

NASA Technical Reports Server (NTRS)

Madavan, Nateri K.

2004-01-01

Differential Evolution (DE) is a simple, fast, and robust evolutionary algorithm that has proven effective in determining the global optimum for several difficult single-objective optimization problems. The DE algorithm has been recently extended to multiobjective optimization problem by using a Pareto-based approach. In this paper, a Pareto DE algorithm is applied to multiobjective aerodynamic shape optimization problems that are characterized by computationally expensive objective function evaluations. To improve computational expensive the algorithm is coupled with generalized response surface meta-models based on artificial neural networks. Results are presented for some test optimization problems from the literature to demonstrate the capabilities of the method.

Parameter meta-optimization of metaheuristics of solving specific NP-hard facility location problem

NASA Astrophysics Data System (ADS)

Skakov, E. S.; Malysh, V. N.

2018-03-01

The aim of the work is to create an evolutionary method for optimizing the values of the control parameters of metaheuristics of solving the NP-hard facility location problem. A system analysis of the tuning process of optimization algorithms parameters is carried out. The problem of finding the parameters of a metaheuristic algorithm is formulated as a meta-optimization problem. Evolutionary metaheuristic has been chosen to perform the task of meta-optimization. Thus, the approach proposed in this work can be called “meta-metaheuristic”. Computational experiment proving the effectiveness of the procedure of tuning the control parameters of metaheuristics has been performed.

Energy spectrum of 50-250 MeV/nucleon iron nuclei inside the MIR space craft.

PubMed

Gunther, W; Leugner, D; Becker, E; Heinrich, W; Reitz, G

2002-10-01

Stacks of CR-39 plastic nuclear track detectors were mounted inside the MIR spacecraft during the EUROMIR95 space mission for a period of 6 months. This long exposure time resulted in a large number of tracks of HZE-particles in the detector foils. All trajectories of stopping iron nuclei could be reconstructed by optimizing the etching conditions so that an automatic track measurement using image analysis techniques was possible. We found 185 stopping iron nuclei and used the énergy-range relation to calculate their energies at the stack surface. The measured spectrum of iron nuclei inside the MIR station is compared to results of model predictions considering the effect of the solar modulation for the mission period, the geomagnetic shielding effect for the MIR orbit and the shielding by material of the spacecraft walls and its instrumentation. c2002 Elsevier Science Ltd. All rights reserved.

Integrated Modeling Activities for the James Webb Space Telescope: Structural-Thermal-Optical Analysis

NASA Technical Reports Server (NTRS)

Johnston, John D.; Howard, Joseph M.; Mosier, Gary E.; Parrish, Keith A.; McGinnis, Mark A.; Bluth, Marcel; Kim, Kevin; Ha, Kong Q.

2004-01-01

The James Web Space Telescope (JWST) is a large, infrared-optimized space telescope scheduled for launch in 2011. This is a continuation of a series of papers on modeling activities for JWST. The structural-thermal-optical, often referred to as STOP, analysis process is used to predict the effect of thermal distortion on optical performance. The benchmark STOP analysis for JWST assesses the effect of an observatory slew on wavefront error. Temperatures predicted using geometric and thermal math models are mapped to a structural finite element model in order to predict thermally induced deformations. Motions and deformations at optical surfaces are then input to optical models, and optical performance is predicted using either an optical ray trace or a linear optical analysis tool. In addition to baseline performance predictions, a process for performing sensitivity studies to assess modeling uncertainties is described.

A Globally Convergent Augmented Lagrangian Pattern Search Algorithm for Optimization with General Constraints and Simple Bounds

NASA Technical Reports Server (NTRS)

Lewis, Robert Michael; Torczon, Virginia

1998-01-01

We give a pattern search adaptation of an augmented Lagrangian method due to Conn, Gould, and Toint. The algorithm proceeds by successive bound constrained minimization of an augmented Lagrangian. In the pattern search adaptation we solve this subproblem approximately using a bound constrained pattern search method. The stopping criterion proposed by Conn, Gould, and Toint for the solution of this subproblem requires explicit knowledge of derivatives. Such information is presumed absent in pattern search methods; however, we show how we can replace this with a stopping criterion based on the pattern size in a way that preserves the convergence properties of the original algorithm. In this way we proceed by successive, inexact, bound constrained minimization without knowing exactly how inexact the minimization is. So far as we know, this is the first provably convergent direct search method for general nonlinear programming.

Optimal control problem for linear fractional-order systems, described by equations with Hadamard-type derivative

NASA Astrophysics Data System (ADS)

Postnov, Sergey

2017-11-01

Two kinds of optimal control problem are investigated for linear time-invariant fractional-order systems with lumped parameters which dynamics described by equations with Hadamard-type derivative: the problem of control with minimal norm and the problem of control with minimal time at given restriction on control norm. The problem setting with nonlocal initial conditions studied. Admissible controls allowed to be the p-integrable functions (p > 1) at half-interval. The optimal control problem studied by moment method. The correctness and solvability conditions for the corresponding moment problem are derived. For several special cases the optimal control problems stated are solved analytically. Some analogies pointed for results obtained with the results which are known for integer-order systems and fractional-order systems describing by equations with Caputo- and Riemann-Liouville-type derivatives.

Multi-step optimization strategy for fuel-optimal orbital transfer of low-thrust spacecraft

NASA Astrophysics Data System (ADS)

Rasotto, M.; Armellin, R.; Di Lizia, P.

2016-03-01

An effective method for the design of fuel-optimal transfers in two- and three-body dynamics is presented. The optimal control problem is formulated using calculus of variation and primer vector theory. This leads to a multi-point boundary value problem (MPBVP), characterized by complex inner constraints and a discontinuous thrust profile. The first issue is addressed by embedding the MPBVP in a parametric optimization problem, thus allowing a simplification of the set of transversality constraints. The second problem is solved by representing the discontinuous control function by a smooth function depending on a continuation parameter. The resulting trajectory optimization method can deal with different intermediate conditions, and no a priori knowledge of the control structure is required. Test cases in both the two- and three-body dynamics show the capability of the method in solving complex trajectory design problems.

Optimal perturbations for nonlinear systems using graph-based optimal transport

NASA Astrophysics Data System (ADS)

Grover, Piyush; Elamvazhuthi, Karthik

2018-06-01

We formulate and solve a class of finite-time transport and mixing problems in the set-oriented framework. The aim is to obtain optimal discrete-time perturbations in nonlinear dynamical systems to transport a specified initial measure on the phase space to a final measure in finite time. The measure is propagated under system dynamics in between the perturbations via the associated transfer operator. Each perturbation is described by a deterministic map in the measure space that implements a version of Monge-Kantorovich optimal transport with quadratic cost. Hence, the optimal solution minimizes a sum of quadratic costs on phase space transport due to the perturbations applied at specified times. The action of the transport map is approximated by a continuous pseudo-time flow on a graph, resulting in a tractable convex optimization problem. This problem is solved via state-of-the-art solvers to global optimality. We apply this algorithm to a problem of transport between measures supported on two disjoint almost-invariant sets in a chaotic fluid system, and to a finite-time optimal mixing problem by choosing the final measure to be uniform. In both cases, the optimal perturbations are found to exploit the phase space structures, such as lobe dynamics, leading to efficient global transport. As the time-horizon of the problem is increased, the optimal perturbations become increasingly localized. Hence, by combining the transfer operator approach with ideas from the theory of optimal mass transportation, we obtain a discrete-time graph-based algorithm for optimal transport and mixing in nonlinear systems.

Comparative Evaluation of Different Optimization Algorithms for Structural Design Applications

NASA Technical Reports Server (NTRS)

Patnaik, Surya N.; Coroneos, Rula M.; Guptill, James D.; Hopkins, Dale A.

1996-01-01

Non-linear programming algorithms play an important role in structural design optimization. Fortunately, several algorithms with computer codes are available. At NASA Lewis Research Centre, a project was initiated to assess the performance of eight different optimizers through the development of a computer code CometBoards. This paper summarizes the conclusions of that research. CometBoards was employed to solve sets of small, medium and large structural problems, using the eight different optimizers on a Cray-YMP8E/8128 computer. The reliability and efficiency of the optimizers were determined from the performance of these problems. For small problems, the performance of most of the optimizers could be considered adequate. For large problems, however, three optimizers (two sequential quadratic programming routines, DNCONG of IMSL and SQP of IDESIGN, along with Sequential Unconstrained Minimizations Technique SUMT) outperformed others. At optimum, most optimizers captured an identical number of active displacement and frequency constraints but the number of active stress constraints differed among the optimizers. This discrepancy can be attributed to singularity conditions in the optimization and the alleviation of this discrepancy can improve the efficiency of optimizers.

Performance Trend of Different Algorithms for Structural Design Optimization

NASA Technical Reports Server (NTRS)

Patnaik, Surya N.; Coroneos, Rula M.; Guptill, James D.; Hopkins, Dale A.

1996-01-01

Nonlinear programming algorithms play an important role in structural design optimization. Fortunately, several algorithms with computer codes are available. At NASA Lewis Research Center, a project was initiated to assess performance of different optimizers through the development of a computer code CometBoards. This paper summarizes the conclusions of that research. CometBoards was employed to solve sets of small, medium and large structural problems, using different optimizers on a Cray-YMP8E/8128 computer. The reliability and efficiency of the optimizers were determined from the performance of these problems. For small problems, the performance of most of the optimizers could be considered adequate. For large problems however, three optimizers (two sequential quadratic programming routines, DNCONG of IMSL and SQP of IDESIGN, along with the sequential unconstrained minimizations technique SUMT) outperformed others. At optimum, most optimizers captured an identical number of active displacement and frequency constraints but the number of active stress constraints differed among the optimizers. This discrepancy can be attributed to singularity conditions in the optimization and the alleviation of this discrepancy can improve the efficiency of optimizers.

Evolutionary Optimization of a Geometrically Refined Truss

NASA Technical Reports Server (NTRS)

Hull, P. V.; Tinker, M. L.; Dozier, G. V.

2007-01-01

Structural optimization is a field of research that has experienced noteworthy growth for many years. Researchers in this area have developed optimization tools to successfully design and model structures, typically minimizing mass while maintaining certain deflection and stress constraints. Numerous optimization studies have been performed to minimize mass, deflection, and stress on a benchmark cantilever truss problem. Predominantly traditional optimization theory is applied to this problem. The cross-sectional area of each member is optimized to minimize the aforementioned objectives. This Technical Publication (TP) presents a structural optimization technique that has been previously applied to compliant mechanism design. This technique demonstrates a method that combines topology optimization, geometric refinement, finite element analysis, and two forms of evolutionary computation: genetic algorithms and differential evolution to successfully optimize a benchmark structural optimization problem. A nontraditional solution to the benchmark problem is presented in this TP, specifically a geometrically refined topological solution. The design process begins with an alternate control mesh formulation, multilevel geometric smoothing operation, and an elastostatic structural analysis. The design process is wrapped in an evolutionary computing optimization toolset.

The expanded invasive weed optimization metaheuristic for solving continuous and discrete optimization problems.

PubMed

Josiński, Henryk; Kostrzewa, Daniel; Michalczuk, Agnieszka; Switoński, Adam

2014-01-01

This paper introduces an expanded version of the Invasive Weed Optimization algorithm (exIWO) distinguished by the hybrid strategy of the search space exploration proposed by the authors. The algorithm is evaluated by solving three well-known optimization problems: minimization of numerical functions, feature selection, and the Mona Lisa TSP Challenge as one of the instances of the traveling salesman problem. The achieved results are compared with analogous outcomes produced by other optimization methods reported in the literature.

Classical conditioning for preserving the effects of short melatonin treatment in children with delayed sleep: a pilot study.

PubMed

van Maanen, Annette; Meijer, Anne Marie; Smits, Marcel G; Oort, Frans J

2017-01-01

Melatonin treatment is effective in treating sleep onset problems in children with delayed melatonin onset, but effects usually disappear when treatment is discontinued. In this pilot study, we investigated whether classical conditioning might help in preserving treatment effects of melatonin in children with sleep onset problems, with and without comorbid attention deficit hyperactivity disorder (ADHD) or autism. After a baseline week, 16 children (mean age: 9.92 years, 31% ADHD/autism) received melatonin treatment for 3 weeks and then gradually discontinued the treatment. Classical conditioning was applied by having children drink organic lemonade while taking melatonin and by using a dim red light lamp that was turned on when children went to bed. Results were compared with a group of 41 children (mean age: 9.43 years, 34% ADHD/autism) who received melatonin without classical conditioning. Melatonin treatment was effective in advancing dim light melatonin onset and reducing sleep onset problems, and positive effects were found on health and behavior problems. After stopping melatonin, sleep returned to baseline levels. We found that for children without comorbidity in the experimental group, sleep latency and sleep start delayed less in the stop week, which suggests an effect of classical conditioning. However, classical conditioning seems counterproductive in children with ADHD or autism. Further research is needed to establish these results and to examine other ways to preserve melatonin treatment effects, for example, by applying morning light.

Particle swarm optimization - Genetic algorithm (PSOGA) on linear transportation problem

NASA Astrophysics Data System (ADS)

Rahmalia, Dinita

2017-08-01

Linear Transportation Problem (LTP) is the case of constrained optimization where we want to minimize cost subject to the balance of the number of supply and the number of demand. The exact method such as northwest corner, vogel, russel, minimal cost have been applied at approaching optimal solution. In this paper, we use heurisitic like Particle Swarm Optimization (PSO) for solving linear transportation problem at any size of decision variable. In addition, we combine mutation operator of Genetic Algorithm (GA) at PSO to improve optimal solution. This method is called Particle Swarm Optimization - Genetic Algorithm (PSOGA). The simulations show that PSOGA can improve optimal solution resulted by PSO.

Analytical and Computational Properties of Distributed Approaches to MDO

NASA Technical Reports Server (NTRS)

Alexandrov, Natalia M.; Lewis, Robert Michael

2000-01-01

Historical evolution of engineering disciplines and the complexity of the MDO problem suggest that disciplinary autonomy is a desirable goal in formulating and solving MDO problems. We examine the notion of disciplinary autonomy and discuss the analytical properties of three approaches to formulating and solving MDO problems that achieve varying degrees of autonomy by distributing the problem along disciplinary lines. Two of the approaches-Optimization by Linear Decomposition and Collaborative Optimization-are based on bi-level optimization and reflect what we call a structural perspective. The third approach, Distributed Analysis Optimization, is a single-level approach that arises from what we call an algorithmic perspective. The main conclusion of the paper is that disciplinary autonomy may come at a price: in the bi-level approaches, the system-level constraints introduced to relax the interdisciplinary coupling and enable disciplinary autonomy can cause analytical and computational difficulties for optimization algorithms. The single-level alternative we discuss affords a more limited degree of autonomy than that of the bi-level approaches, but without the computational difficulties of the bi-level methods. Key Words: Autonomy, bi-level optimization, distributed optimization, multidisciplinary optimization, multilevel optimization, nonlinear programming, problem integration, system synthesis

Simultaneous optimization of loading pattern and burnable poison placement for PWRs

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

Alim, F.; Ivanov, K.; Yilmaz, S.

2006-07-01

To solve in-core fuel management optimization problem, GARCO-PSU (Genetic Algorithm Reactor Core Optimization - Pennsylvania State Univ.) is developed. This code is applicable for all types and geometry of PWR core structures with unlimited number of fuel assembly (FA) types in the inventory. For this reason an innovative genetic algorithm is developed with modifying the classical representation of the genotype. In-core fuel management heuristic rules are introduced into GARCO. The core re-load design optimization has two parts, loading pattern (LP) optimization and burnable poison (BP) placement optimization. These parts depend on each other, but it is difficult to solve themore » combined problem due to its large size. Separating the problem into two parts provides a practical way to solve the problem. However, the result of this method does not reflect the real optimal solution. GARCO-PSU achieves to solve LP optimization and BP placement optimization simultaneously in an efficient manner. (authors)« less

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

Huang, Kuo -Ling; Mehrotra, Sanjay

We present a homogeneous algorithm equipped with a modified potential function for the monotone complementarity problem. We show that this potential function is reduced by at least a constant amount if a scaled Lipschitz condition (SLC) is satisfied. A practical algorithm based on this potential function is implemented in a software package named iOptimize. The implementation in iOptimize maintains global linear and polynomial time convergence properties, while achieving practical performance. It either successfully solves the problem, or concludes that the SLC is not satisfied. When compared with the mature software package MOSEK (barrier solver version 6.0.0.106), iOptimize solves convex quadraticmore » programming problems, convex quadratically constrained quadratic programming problems, and general convex programming problems in fewer iterations. Moreover, several problems for which MOSEK fails are solved to optimality. In addition, we also find that iOptimize detects infeasibility more reliably than the general nonlinear solvers Ipopt (version 3.9.2) and Knitro (version 8.0).« less

A noisy chaotic neural network for solving combinatorial optimization problems: stochastic chaotic simulated annealing.

PubMed

Wang, Lipo; Li, Sa; Tian, Fuyu; Fu, Xiuju

2004-10-01

Recently Chen and Aihara have demonstrated both experimentally and mathematically that their chaotic simulated annealing (CSA) has better search ability for solving combinatorial optimization problems compared to both the Hopfield-Tank approach and stochastic simulated annealing (SSA). However, CSA may not find a globally optimal solution no matter how slowly annealing is carried out, because the chaotic dynamics are completely deterministic. In contrast, SSA tends to settle down to a global optimum if the temperature is reduced sufficiently slowly. Here we combine the best features of both SSA and CSA, thereby proposing a new approach for solving optimization problems, i.e., stochastic chaotic simulated annealing, by using a noisy chaotic neural network. We show the effectiveness of this new approach with two difficult combinatorial optimization problems, i.e., a traveling salesman problem and a channel assignment problem for cellular mobile communications.

An Algorithm for the Mixed Transportation Network Design Problem

PubMed Central

Liu, Xinyu; Chen, Qun

2016-01-01

This paper proposes an optimization algorithm, the dimension-down iterative algorithm (DDIA), for solving a mixed transportation network design problem (MNDP), which is generally expressed as a mathematical programming with equilibrium constraint (MPEC). The upper level of the MNDP aims to optimize the network performance via both the expansion of the existing links and the addition of new candidate links, whereas the lower level is a traditional Wardrop user equilibrium (UE) problem. The idea of the proposed solution algorithm (DDIA) is to reduce the dimensions of the problem. A group of variables (discrete/continuous) is fixed to optimize another group of variables (continuous/discrete) alternately; then, the problem is transformed into solving a series of CNDPs (continuous network design problems) and DNDPs (discrete network design problems) repeatedly until the problem converges to the optimal solution. The advantage of the proposed algorithm is that its solution process is very simple and easy to apply. Numerical examples show that for the MNDP without budget constraint, the optimal solution can be found within a few iterations with DDIA. For the MNDP with budget constraint, however, the result depends on the selection of initial values, which leads to different optimal solutions (i.e., different local optimal solutions). Some thoughts are given on how to derive meaningful initial values, such as by considering the budgets of new and reconstruction projects separately. PMID:27626803

Optimal Control Problems with Switching Points. Ph.D. Thesis, 1990 Final Report

NASA Technical Reports Server (NTRS)

Seywald, Hans

1991-01-01

The main idea of this report is to give an overview of the problems and difficulties that arise in solving optimal control problems with switching points. A brief discussion of existing optimality conditions is given and a numerical approach for solving the multipoint boundary value problems associated with the first-order necessary conditions of optimal control is presented. Two real-life aerospace optimization problems are treated explicitly. These are altitude maximization for a sounding rocket (Goddard Problem) in the presence of a dynamic pressure limit, and range maximization for a supersonic aircraft flying in the vertical, also in the presence of a dynamic pressure limit. In the second problem singular control appears along arcs with active dynamic pressure limit, which in the context of optimal control, represents a first-order state inequality constraint. An extension of the Generalized Legendre-Clebsch Condition to the case of singular control along state/control constrained arcs is presented and is applied to the aircraft range maximization problem stated above. A contribution to the field of Jacobi Necessary Conditions is made by giving a new proof for the non-optimality of conjugate paths in the Accessory Minimum Problem. Because of its simple and explicit character, the new proof may provide the basis for an extension of Jacobi's Necessary Condition to the case of the trajectories with interior point constraints. Finally, the result that touch points cannot occur for first-order state inequality constraints is extended to the case of vector valued control functions.

Nonexpansiveness of a linearized augmented Lagrangian operator for hierarchical convex optimization

NASA Astrophysics Data System (ADS)

Yamagishi, Masao; Yamada, Isao

2017-04-01

Hierarchical convex optimization concerns two-stage optimization problems: the first stage problem is a convex optimization; the second stage problem is the minimization of a convex function over the solution set of the first stage problem. For the hierarchical convex optimization, the hybrid steepest descent method (HSDM) can be applied, where the solution set of the first stage problem must be expressed as the fixed point set of a certain nonexpansive operator. In this paper, we propose a nonexpansive operator that yields a computationally efficient update when it is plugged into the HSDM. The proposed operator is inspired by the update of the linearized augmented Lagrangian method. It is applicable to characterize the solution set of recent sophisticated convex optimization problems found in the context of inverse problems, where the sum of multiple proximable convex functions involving linear operators must be minimized to incorporate preferable properties into the minimizers. For such a problem formulation, there has not yet been reported any nonexpansive operator that yields an update free from the inversions of linear operators in cases where it is utilized in the HSDM. Unlike previously known nonexpansive operators, the proposed operator yields an inversion-free update in such cases. As an application of the proposed operator plugged into the HSDM, we also present, in the context of the so-called superiorization, an algorithmic solution to a convex optimization problem over the generalized convex feasible set where the intersection of the hard constraints is not necessarily simple.

TARCMO: Theory and Algorithms for Robust, Combinatorial, Multicriteria Optimization

DTIC Science & Technology

2016-11-28

objective 9 4.6 On The Recoverable Robust Traveling Salesman Problem . . . . . 11 4.7 A Bicriteria Approach to Robust Optimization...be found. 4.6 On The Recoverable Robust Traveling Salesman Problem The traveling salesman problem (TSP) is a well-known combinatorial optimiza- tion...procedure for the robust traveling salesman problem . While this iterative algorithms results in an optimal solution to the robust TSP, computation

A Mathematical Optimization Problem in Bioinformatics

ERIC Educational Resources Information Center

Heyer, Laurie J.

2008-01-01

This article describes the sequence alignment problem in bioinformatics. Through examples, we formulate sequence alignment as an optimization problem and show how to compute the optimal alignment with dynamic programming. The examples and sample exercises have been used by the author in a specialized course in bioinformatics, but could be adapted…

A Problem on Optimal Transportation

ERIC Educational Resources Information Center

Cechlarova, Katarina

2005-01-01

Mathematical optimization problems are not typical in the classical curriculum of mathematics. In this paper we show how several generalizations of an easy problem on optimal transportation were solved by gifted secondary school pupils in a correspondence mathematical seminar, how they can be used in university courses of linear programming and…

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

Graf, Peter; Dykes, Katherine; Scott, George

The layout of turbines in a wind farm is already a challenging nonlinear, nonconvex, nonlinearly constrained continuous global optimization problem. Here we begin to address the next generation of wind farm optimization problems by adding the complexity that there is more than one turbine type to choose from. The optimization becomes a nonlinear constrained mixed integer problem, which is a very difficult class of problems to solve. Furthermore, this document briefly summarizes the algorithm and code we have developed, the code validation steps we have performed, and the initial results for multi-turbine type and placement optimization (TTP_OPT) we have run.

A framework for modeling and optimizing dynamic systems under uncertainty

DOE PAGES

Nicholson, Bethany; Siirola, John

2017-11-11

Algebraic modeling languages (AMLs) have drastically simplified the implementation of algebraic optimization problems. However, there are still many classes of optimization problems that are not easily represented in most AMLs. These classes of problems are typically reformulated before implementation, which requires significant effort and time from the modeler and obscures the original problem structure or context. In this work we demonstrate how the Pyomo AML can be used to represent complex optimization problems using high-level modeling constructs. We focus on the operation of dynamic systems under uncertainty and demonstrate the combination of Pyomo extensions for dynamic optimization and stochastic programming.more » We use a dynamic semibatch reactor model and a large-scale bubbling fluidized bed adsorber model as test cases.« less

Computational alternatives to obtain time optimal jet engine control. M.S. Thesis

NASA Technical Reports Server (NTRS)

Basso, R. J.; Leake, R. J.

1976-01-01

Two computational methods to determine an open loop time optimal control sequence for a simple single spool turbojet engine are described by a set of nonlinear differential equations. Both methods are modifications of widely accepted algorithms which can solve fixed time unconstrained optimal control problems with a free right end. Constrained problems to be considered have fixed right ends and free time. Dynamic programming is defined on a standard problem and it yields a successive approximation solution to the time optimal problem of interest. A feedback control law is obtained and it is then used to determine the corresponding open loop control sequence. The Fletcher-Reeves conjugate gradient method has been selected for adaptation to solve a nonlinear optimal control problem with state variable and control constraints.

A framework for modeling and optimizing dynamic systems under uncertainty

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

Nicholson, Bethany; Siirola, John

Algebraic modeling languages (AMLs) have drastically simplified the implementation of algebraic optimization problems. However, there are still many classes of optimization problems that are not easily represented in most AMLs. These classes of problems are typically reformulated before implementation, which requires significant effort and time from the modeler and obscures the original problem structure or context. In this work we demonstrate how the Pyomo AML can be used to represent complex optimization problems using high-level modeling constructs. We focus on the operation of dynamic systems under uncertainty and demonstrate the combination of Pyomo extensions for dynamic optimization and stochastic programming.more » We use a dynamic semibatch reactor model and a large-scale bubbling fluidized bed adsorber model as test cases.« less

Distributed Method to Optimal Profile Descent

NASA Astrophysics Data System (ADS)

Kim, Geun I.

Current ground automation tools for Optimal Profile Descent (OPD) procedures utilize path stretching and speed profile change to maintain proper merging and spacing requirements at high traffic terminal area. However, low predictability of aircraft's vertical profile and path deviation during decent add uncertainty to computing estimated time of arrival, a key information that enables the ground control center to manage airspace traffic effectively. This paper uses an OPD procedure that is based on a constant flight path angle to increase the predictability of the vertical profile and defines an OPD optimization problem that uses both path stretching and speed profile change while largely maintaining the original OPD procedure. This problem minimizes the cumulative cost of performing OPD procedures for a group of aircraft by assigning a time cost function to each aircraft and a separation cost function to a pair of aircraft. The OPD optimization problem is then solved in a decentralized manner using dual decomposition techniques under inter-aircraft ADS-B mechanism. This method divides the optimization problem into more manageable sub-problems which are then distributed to the group of aircraft. Each aircraft solves its assigned sub-problem and communicate the solutions to other aircraft in an iterative process until an optimal solution is achieved thus decentralizing the computation of the optimization problem.

Applying the Toyota Production System: using a patient safety alert system to reduce error.

PubMed

Furman, Cathie; Caplan, Robert

2007-07-01

In 2002, Virginia Mason Medical Center (VMMC) adapted the Toyota Production System, also known as lean manufacturing. To translate the techniques of zero defects and stopping the line into health care, the Patient Safety Alert (PSA) system requires any employee who encounters a situation that is likely to harm a patient to make an immediate report and to cease any activity that could cause further harm (stopping the line). IMPLEMENTING THE PSA SYSTEM--STOPPING THE LINE: If any VMMC employee's practice or conduct is deemed capable of causing harm to a patient, a PSA can cause that person to be stopped from working until the problem is resolved. A policy statement, senior executive commitment, dedicated resources, a 24-hour hotline, and communication were all key features of implementation. As of December 2006, 6,112 PSA reports were received: 20% from managers, 8% from physicians, 44% from nurses, and 23% from nonclinical support personnel, for example. The number of reports received per month increased from an average of 3 in 2002 to 285 in 2006. Most reports were processed within 24 hours and were resolved within 2 to 3 weeks. Implementing the PSA system has drastically increased the number of safety concerns that are resolved at VMMC, while drastically reducing the time it takes to resolve them. Transparent discussion and feedback have helped promote staff acceptance and participation.

Accrual and drop out in a primary prevention randomised controlled trial: qualitative study.

PubMed

Eborall, Helen C; Stewart, Marlene C W; Cunningham-Burley, Sarah; Price, Jackie F; Fowkes, F Gerry R

2011-01-11

Recruitment and retention of participants are critical to the success of a randomised controlled trial. Gaining the views of potential trial participants who decline to enter a trial and of trial participants who stop the trial treatment is important and can help to improve study processes. Limited research on these issues has been conducted on healthy individuals recruited for prevention trials in the community. Semi-structured interviews with people who were eligible but had declined to participate in the Aspirin for Asymptomatic Atherosclerosis (AAA) trial (N = 11), and AAA trial participants who had stopped taking the trial medication (N = 11). A focus group with further participants who had stopped taking the trial medication (N = 6). (Total participants N = 28). Explanations for declining to participate could be divided into two groups: the first group were characterised by a lack of necessity to participate and a tendency to prioritise other largely mundane problems. The second group's concern was with a high level of perceived risk from participating.Explanations for stopping trial medication fell into four categories: side effects attributed to the trial medication; starting on aspirin or medication contraindicating to aspirin; experiencing an outcome event, and changing one's mind. These results indicate that when planning trials (especially in preventive medicine) particular attention should be given to designing appropriate recruitment materials and processes that fully inform potential recruits of the risks and benefits of participation. ISRCTN66587262.

Diageo's 'Stop Out of Control Drinking' Campaign in Ireland: An Analysis

PubMed Central

Petticrew, Mark; Fitzgerald, Niamh; Durand, Mary Alison; Knai, Cécile; Davoren, Martin; Perry, Ivan

2016-01-01

Background It has been argued that the alcohol industry uses corporate social responsibility activities to influence policy and undermine public health, and that every opportunity should be taken to scrutinise such activities. This study analyses a controversial Diageo-funded ‘responsible drinking’ campaign (“Stop out of Control Drinking”, or SOOCD) in Ireland. The study aims to identify how the campaign and its advisory board members frame and define (i) alcohol-related harms, and their causes, and (ii) possible solutions. Methods Documentary analysis of SOOCD campaign material. This includes newspaper articles (n = 9), media interviews (n = 11), Facebook posts (n = 92), and Tweets (n = 340) produced by the campaign and by board members. All material was coded inductively, and a thematic analysis undertaken, with codes aggregated into sub-themes. Results The SOOCD campaign utilises vague or self-defined concepts of ‘out of control’ and ‘moderate’ drinking, tending to present alcohol problems as behavioural rather than health issues. These are also unquantified with respect to actual drinking levels. It emphasises alcohol-related antisocial behaviour among young people, particularly young women. In discussing solutions to alcohol-related problems, it focuses on public opinion rather than on scientific evidence, and on educational approaches and information provision, misrepresenting these as effective. “Moderate drinking” is presented as a behavioural issue (“negative drinking behaviours”), rather than as a health issue. Conclusions The ‘Stop Out of Control Drinking’ campaign frames alcohol problems and solutions in ways unfavourable to public health, and closely reflects other Diageo Corporate Social Responsibility (CSR) activity, as well as alcohol and tobacco industry strategies more generally. This framing, and in particular the framing of alcohol harms as a behavioural issue, with the implication that consumption should be guided only by self-defined limits, may not have been recognised by all board members. It suggests a need for awareness-raising efforts among the public, third sector and policymakers about alcohol industry strategies. PMID:27636883

Diageo's 'Stop Out of Control Drinking' Campaign in Ireland: An Analysis.

PubMed

Petticrew, Mark; Fitzgerald, Niamh; Durand, Mary Alison; Knai, Cécile; Davoren, Martin; Perry, Ivan

2016-01-01

It has been argued that the alcohol industry uses corporate social responsibility activities to influence policy and undermine public health, and that every opportunity should be taken to scrutinise such activities. This study analyses a controversial Diageo-funded 'responsible drinking' campaign ("Stop out of Control Drinking", or SOOCD) in Ireland. The study aims to identify how the campaign and its advisory board members frame and define (i) alcohol-related harms, and their causes, and (ii) possible solutions. Documentary analysis of SOOCD campaign material. This includes newspaper articles (n = 9), media interviews (n = 11), Facebook posts (n = 92), and Tweets (n = 340) produced by the campaign and by board members. All material was coded inductively, and a thematic analysis undertaken, with codes aggregated into sub-themes. The SOOCD campaign utilises vague or self-defined concepts of 'out of control' and 'moderate' drinking, tending to present alcohol problems as behavioural rather than health issues. These are also unquantified with respect to actual drinking levels. It emphasises alcohol-related antisocial behaviour among young people, particularly young women. In discussing solutions to alcohol-related problems, it focuses on public opinion rather than on scientific evidence, and on educational approaches and information provision, misrepresenting these as effective. "Moderate drinking" is presented as a behavioural issue ("negative drinking behaviours"), rather than as a health issue. The 'Stop Out of Control Drinking' campaign frames alcohol problems and solutions in ways unfavourable to public health, and closely reflects other Diageo Corporate Social Responsibility (CSR) activity, as well as alcohol and tobacco industry strategies more generally. This framing, and in particular the framing of alcohol harms as a behavioural issue, with the implication that consumption should be guided only by self-defined limits, may not have been recognised by all board members. It suggests a need for awareness-raising efforts among the public, third sector and policymakers about alcohol industry strategies.

Long-term energy capture and the effects of optimizing wind turbine operating strategies

NASA Technical Reports Server (NTRS)

Miller, A. H.; Formica, W. J.

1982-01-01

Methods of increasing energy capture without affecting the turbine design were investigated. The emphasis was on optimizing the wind turbine operating strategy. The operating strategy embodies the startup and shutdown algorithm as well as the algorithm for determining when to yaw (rotate) the axis of the turbine more directly into the wind. Using data collected at a number of sites, the time-dependent simulation of a MOD-2 wind turbine using various, site-dependent operating strategies provided evidence that site-specific fine tuning can produce significant increases in long-term energy capture as well as reduce the number of start-stop cycles and yawing maneuvers, which may result in reduced fatigue and subsequent maintenance.

Assessing benefits, costs, and disparate racial impacts of confrontational proactive policing

PubMed Central

Manski, Charles F.; Nagin, Daniel S.

2017-01-01

Effective policing in a democratic society must balance the sometime conflicting objectives of public safety and community trust. This paper uses a formal model of optimal policing to explore how society might reasonably resolve the tension between these two objectives as well as evaluate disparate racial impacts. We do so by considering the social benefits and costs of confrontational types of proactive policing, such as stop, question, and frisk. Three features of the optimum that are particularly relevant to policy choices are explored: (i) the cost of enforcement against the innocent, (ii) the baseline level of crime rate without confrontational enforcement, and (iii) differences across demographic groups in the optimal rate of enforcement. PMID:28739928

Solution of monotone complementarity and general convex programming problems using a modified potential reduction interior point method

DOE PAGES

Huang, Kuo -Ling; Mehrotra, Sanjay

2016-11-08

We present a homogeneous algorithm equipped with a modified potential function for the monotone complementarity problem. We show that this potential function is reduced by at least a constant amount if a scaled Lipschitz condition (SLC) is satisfied. A practical algorithm based on this potential function is implemented in a software package named iOptimize. The implementation in iOptimize maintains global linear and polynomial time convergence properties, while achieving practical performance. It either successfully solves the problem, or concludes that the SLC is not satisfied. When compared with the mature software package MOSEK (barrier solver version 6.0.0.106), iOptimize solves convex quadraticmore » programming problems, convex quadratically constrained quadratic programming problems, and general convex programming problems in fewer iterations. Moreover, several problems for which MOSEK fails are solved to optimality. In addition, we also find that iOptimize detects infeasibility more reliably than the general nonlinear solvers Ipopt (version 3.9.2) and Knitro (version 8.0).« less

Dynamic programming and graph algorithms in computer vision.

PubMed

Felzenszwalb, Pedro F; Zabih, Ramin

2011-04-01

Optimization is a powerful paradigm for expressing and solving problems in a wide range of areas, and has been successfully applied to many vision problems. Discrete optimization techniques are especially interesting since, by carefully exploiting problem structure, they often provide nontrivial guarantees concerning solution quality. In this paper, we review dynamic programming and graph algorithms, and discuss representative examples of how these discrete optimization techniques have been applied to some classical vision problems. We focus on the low-level vision problem of stereo, the mid-level problem of interactive object segmentation, and the high-level problem of model-based recognition.

An optimization method for the problems of thermal cloaking of material bodies

NASA Astrophysics Data System (ADS)

Alekseev, G. V.; Levin, V. A.

2016-11-01

Inverse heat-transfer problems related to constructing special thermal devices such as cloaking shells, thermal-illusion or thermal-camouflage devices, and heat-flux concentrators are studied. The heatdiffusion equation with a variable heat-conductivity coefficient is used as the initial heat-transfer model. An optimization method is used to reduce the above inverse problems to the respective control problem. The solvability of the above control problem is proved, an optimality system that describes necessary extremum conditions is derived, and a numerical algorithm for solving the control problem is proposed.

System design optimization for a Mars-roving vehicle and perturbed-optimal solutions in nonlinear programming

NASA Technical Reports Server (NTRS)

Pavarini, C.

1974-01-01

Work in two somewhat distinct areas is presented. First, the optimal system design problem for a Mars-roving vehicle is attacked by creating static system models and a system evaluation function and optimizing via nonlinear programming techniques. The second area concerns the problem of perturbed-optimal solutions. Given an initial perturbation in an element of the solution to a nonlinear programming problem, a linear method is determined to approximate the optimal readjustments of the other elements of the solution. Then, the sensitivity of the Mars rover designs is described by application of this method.

Performance comparison of genetic algorithms and particle swarm optimization for model integer programming bus timetabling problem

NASA Astrophysics Data System (ADS)

Wihartiko, F. D.; Wijayanti, H.; Virgantari, F.

2018-03-01

Genetic Algorithm (GA) is a common algorithm used to solve optimization problems with artificial intelligence approach. Similarly, the Particle Swarm Optimization (PSO) algorithm. Both algorithms have different advantages and disadvantages when applied to the case of optimization of the Model Integer Programming for Bus Timetabling Problem (MIPBTP), where in the case of MIPBTP will be found the optimal number of trips confronted with various constraints. The comparison results show that the PSO algorithm is superior in terms of complexity, accuracy, iteration and program simplicity in finding the optimal solution.

Optimal Control of Evolution Mixed Variational Inclusions

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

Alduncin, Gonzalo, E-mail: alduncin@geofisica.unam.mx

2013-12-15

Optimal control problems of primal and dual evolution mixed variational inclusions, in reflexive Banach spaces, are studied. The solvability analysis of the mixed state systems is established via duality principles. The optimality analysis is performed in terms of perturbation conjugate duality methods, and proximation penalty-duality algorithms to mixed optimality conditions are further presented. Applications to nonlinear diffusion constrained problems as well as quasistatic elastoviscoplastic bilateral contact problems exemplify the theory.

Optimal control and optimal trajectories of regional macroeconomic dynamics based on the Pontryagin maximum principle

NASA Astrophysics Data System (ADS)

Bulgakov, V. K.; Strigunov, V. V.

2009-05-01

The Pontryagin maximum principle is used to prove a theorem concerning optimal control in regional macroeconomics. A boundary value problem for optimal trajectories of the state and adjoint variables is formulated, and optimal curves are analyzed. An algorithm is proposed for solving the boundary value problem of optimal control. The performance of the algorithm is demonstrated by computing an optimal control and the corresponding optimal trajectories.

Random Matrix Approach for Primal-Dual Portfolio Optimization Problems

NASA Astrophysics Data System (ADS)

Tada, Daichi; Yamamoto, Hisashi; Shinzato, Takashi

2017-12-01

In this paper, we revisit the portfolio optimization problems of the minimization/maximization of investment risk under constraints of budget and investment concentration (primal problem) and the maximization/minimization of investment concentration under constraints of budget and investment risk (dual problem) for the case that the variances of the return rates of the assets are identical. We analyze both optimization problems by the Lagrange multiplier method and the random matrix approach. Thereafter, we compare the results obtained from our proposed approach with the results obtained in previous work. Moreover, we use numerical experiments to validate the results obtained from the replica approach and the random matrix approach as methods for analyzing both the primal and dual portfolio optimization problems.

Evaluation of Genetic Algorithm Concepts using Model Problems. Part 1; Single-Objective Optimization

NASA Technical Reports Server (NTRS)

Holst, Terry L.; Pulliam, Thomas H.

2003-01-01

A genetic-algorithm-based optimization approach is described and evaluated using a simple hill-climbing model problem. The model problem utilized herein allows for the broad specification of a large number of search spaces including spaces with an arbitrary number of genes or decision variables and an arbitrary number hills or modes. In the present study, only single objective problems are considered. Results indicate that the genetic algorithm optimization approach is flexible in application and extremely reliable, providing optimal results for all problems attempted. The most difficult problems - those with large hyper-volumes and multi-mode search spaces containing a large number of genes - require a large number of function evaluations for GA convergence, but they always converge.

A time-domain decomposition iterative method for the solution of distributed linear quadratic optimal control problems

NASA Astrophysics Data System (ADS)

Heinkenschloss, Matthias

2005-01-01

We study a class of time-domain decomposition-based methods for the numerical solution of large-scale linear quadratic optimal control problems. Our methods are based on a multiple shooting reformulation of the linear quadratic optimal control problem as a discrete-time optimal control (DTOC) problem. The optimality conditions for this DTOC problem lead to a linear block tridiagonal system. The diagonal blocks are invertible and are related to the original linear quadratic optimal control problem restricted to smaller time-subintervals. This motivates the application of block Gauss-Seidel (GS)-type methods for the solution of the block tridiagonal systems. Numerical experiments show that the spectral radii of the block GS iteration matrices are larger than one for typical applications, but that the eigenvalues of the iteration matrices decay to zero fast. Hence, while the GS method is not expected to convergence for typical applications, it can be effective as a preconditioner for Krylov-subspace methods. This is confirmed by our numerical tests.A byproduct of this research is the insight that certain instantaneous control techniques can be viewed as the application of one step of the forward block GS method applied to the DTOC optimality system.

Direct Digital Control of HVAC (Heating, Ventilating, and Air Conditioning).

DTIC Science & Technology

1985-01-01

controller func- tions such as time-of-day, economizer cycles, reset, load shedding, chiller optimization , VAV fan synchronization, and optimum start/stop...control system such as that illustrated in Fig- urc 4. Data on setpoints , reset schedules, and event timing, such as that presented in Figure 6, are...program code (Figure 7). In addition to the control logic, setpoint and other data are readily available. Program logi:, setpoint and schedule data, and

Heterogeneous quantum computing for satellite constellation optimization: solving the weighted k-clique problem

NASA Astrophysics Data System (ADS)

Bass, Gideon; Tomlin, Casey; Kumar, Vaibhaw; Rihaczek, Pete; Dulny, Joseph, III

2018-04-01

NP-hard optimization problems scale very rapidly with problem size, becoming unsolvable with brute force methods, even with supercomputing resources. Typically, such problems have been approximated with heuristics. However, these methods still take a long time and are not guaranteed to find an optimal solution. Quantum computing offers the possibility of producing significant speed-up and improved solution quality. Current quantum annealing (QA) devices are designed to solve difficult optimization problems, but they are limited by hardware size and qubit connectivity restrictions. We present a novel heterogeneous computing stack that combines QA and classical machine learning, allowing the use of QA on problems larger than the hardware limits of the quantum device. These results represent experiments on a real-world problem represented by the weighted k-clique problem. Through this experiment, we provide insight into the state of quantum machine learning.

Decomposition method for zonal resource allocation problems in telecommunication networks

NASA Astrophysics Data System (ADS)

Konnov, I. V.; Kashuba, A. Yu

2016-11-01

We consider problems of optimal resource allocation in telecommunication networks. We first give an optimization formulation for the case where the network manager aims to distribute some homogeneous resource (bandwidth) among users of one region with quadratic charge and fee functions and present simple and efficient solution methods. Next, we consider a more general problem for a provider of a wireless communication network divided into zones (clusters) with common capacity constraints. We obtain a convex quadratic optimization problem involving capacity and balance constraints. By using the dual Lagrangian method with respect to the capacity constraint, we suggest to reduce the initial problem to a single-dimensional optimization problem, but calculation of the cost function value leads to independent solution of zonal problems, which coincide with the above single region problem. Some results of computational experiments confirm the applicability of the new methods.

Evolutionary computation in zoology and ecology.

PubMed

Boone, Randall B

2017-12-01

Evolutionary computational methods have adopted attributes of natural selection and evolution to solve problems in computer science, engineering, and other fields. The method is growing in use in zoology and ecology. Evolutionary principles may be merged with an agent-based modeling perspective to have individual animals or other agents compete. Four main categories are discussed: genetic algorithms, evolutionary programming, genetic programming, and evolutionary strategies. In evolutionary computation, a population is represented in a way that allows for an objective function to be assessed that is relevant to the problem of interest. The poorest performing members are removed from the population, and remaining members reproduce and may be mutated. The fitness of the members is again assessed, and the cycle continues until a stopping condition is met. Case studies include optimizing: egg shape given different clutch sizes, mate selection, migration of wildebeest, birds, and elk, vulture foraging behavior, algal bloom prediction, and species richness given energy constraints. Other case studies simulate the evolution of species and a means to project shifts in species ranges in response to a changing climate that includes competition and phenotypic plasticity. This introduction concludes by citing other uses of evolutionary computation and a review of the flexibility of the methods. For example, representing species' niche spaces subject to selective pressure allows studies on cladistics, the taxon cycle, neutral versus niche paradigms, fundamental versus realized niches, community structure and order of colonization, invasiveness, and responses to a changing climate.

Evolutionary computation in zoology and ecology

PubMed Central

2017-01-01

Abstract Evolutionary computational methods have adopted attributes of natural selection and evolution to solve problems in computer science, engineering, and other fields. The method is growing in use in zoology and ecology. Evolutionary principles may be merged with an agent-based modeling perspective to have individual animals or other agents compete. Four main categories are discussed: genetic algorithms, evolutionary programming, genetic programming, and evolutionary strategies. In evolutionary computation, a population is represented in a way that allows for an objective function to be assessed that is relevant to the problem of interest. The poorest performing members are removed from the population, and remaining members reproduce and may be mutated. The fitness of the members is again assessed, and the cycle continues until a stopping condition is met. Case studies include optimizing: egg shape given different clutch sizes, mate selection, migration of wildebeest, birds, and elk, vulture foraging behavior, algal bloom prediction, and species richness given energy constraints. Other case studies simulate the evolution of species and a means to project shifts in species ranges in response to a changing climate that includes competition and phenotypic plasticity. This introduction concludes by citing other uses of evolutionary computation and a review of the flexibility of the methods. For example, representing species’ niche spaces subject to selective pressure allows studies on cladistics, the taxon cycle, neutral versus niche paradigms, fundamental versus realized niches, community structure and order of colonization, invasiveness, and responses to a changing climate. PMID:29492029

Risk analysis of heat recovery steam generator with semi quantitative risk based inspection API 581

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

Prayogo, Galang Sandy, E-mail: gasandylang@live.com; Haryadi, Gunawan Dwi; Ismail, Rifky

Corrosion is a major problem that most often occurs in the power plant. Heat recovery steam generator (HRSG) is an equipment that has a high risk to the power plant. The impact of corrosion damage causing HRSG power plant stops operating. Furthermore, it could be threaten the safety of employees. The Risk Based Inspection (RBI) guidelines by the American Petroleum Institute (API) 58 has been used to risk analysis in the HRSG 1. By using this methodology, the risk that caused by unexpected failure as a function of the probability and consequence of failure can be estimated. This paper presentedmore » a case study relating to the risk analysis in the HRSG, starting with a summary of the basic principles and procedures of risk assessment and applying corrosion RBI for process industries. The risk level of each HRSG equipment were analyzed: HP superheater has a medium high risk (4C), HP evaporator has a medium-high risk (4C), and the HP economizer has a medium risk (3C). The results of the risk assessment using semi-quantitative method of standard API 581 based on the existing equipment at medium risk. In the fact, there is no critical problem in the equipment components. Damage mechanisms were prominent throughout the equipment is thinning mechanism. The evaluation of the risk approach was done with the aim of reducing risk by optimizing the risk assessment activities.« less

Portfolio optimization using fuzzy linear programming

NASA Astrophysics Data System (ADS)

Pandit, Purnima K.

2013-09-01

Portfolio Optimization (PO) is a problem in Finance, in which investor tries to maximize return and minimize risk by carefully choosing different assets. Expected return and risk are the most important parameters with regard to optimal portfolios. In the simple form PO can be modeled as quadratic programming problem which can be put into equivalent linear form. PO problems with the fuzzy parameters can be solved as multi-objective fuzzy linear programming problem. In this paper we give the solution to such problems with an illustrative example.

[Fight against tuberculosis in the world].

PubMed

El Kamel, A; Joobeur, S; Skhiri, N; Cheikh Mhamed, S; Mribah, H; Rouatbi, N

2015-01-01

Tuberculosis (TB) in a major health problem in the world. WHO and its partners especially, the stop TB partnership launched numerous strategies against TB especially in the 1990. Strategy DOTS (directly observed therapy short course) was launched in 1995. One main key was the direct supervision of drug intake by patients. Progress was achieved but it was insufficient. A new strategy called "Stop TB Strategy 2006-2015" was launched in 2006 in the context of Millennium Development Goals (MDG) elaborated by United Nations. The common goals were to halt and start to reverse the incidence of TB, reduce the prevalence and death rate by 50% compared to their level in 1990 by 2015 to eliminate TB as a public health problem by 2050. The end of 2010 marks the mid-point of the Global Plan and is an obvious time to update it and take into account actual progress with a focus on the 2015 to reach goals. So an updated Global Plan to stop TB 2011-2015, was launched. Expected progress and targets were defined for 2015, in diagnosis and treatment, in co-infection TB/HIV, in drug-resistant TB and achievements expected in new tests for diagnosis, new medications, new vaccines and new regimens with shorter duration of treatment. WHO and partners have started discussions to define the new post 2015 strategy to TB control and elimination. Risk factors (diabetes, malnutrition, tobacco smoke…) and socioeconomic factors, which are associated with TB, should be included in the new strategy to eliminate TB in 2050. Copyright © 2014 Elsevier Masson SAS. All rights reserved.

Prevalence of sleep complaints in Colombia at different altitudes.

PubMed

Ruiz, A J; Sepúlveda, Martín Alonso Rondón; Martínez, Patricia Hidalgo; Muñoz, Martín Cañón; Mendoza, Liliana Otero; Centanaro, Olga Patricia Panqueva; Carrasco, Luis Felipe Uriza; García, Juan Camilo Ospina

2016-01-01

To determine the prevalence of sleep complaints in adults in Colombia at different altitudes. Cross-sectional, population-based and observational study. Urban areas in three cities (Bogotá, Bucaramanga, Santa Marta) located between 15 and 2640 masl. Subjects Over 18 years old. Epworth sleepiness scale (ESS), Pittsburgh sleep quality index (PSQI), Berlin questionnaire, STOP-Bang questionnaire and diagnostic criteria for restless leg syndrome (IRLSSG). The overall prevalence of sleep complaints was 59.6% (CI 95%: 57.3; 61.8%). According to the Pittsburgh scale, 45.3% (CI 95%: 43.0; 47.5) required medical assistance. The Berlin questionnaire indicated that 19.0% (CI 95%: 17.3; 20.8%) had a high risk of sleep apnea (OSA) compared to 26.9% (CI 95%: 24.9; 29.0%) according to STOP-Bang. Among the subjects, 13.7% (CI 95%: 12.3; 15.3%) had excessive daytime sleepiness and 37.7% (CI 95%: 35.5; 39.8%) had a restless leg syndrome. When comparing cities, significant differences in the overall frequency of subjects requiring care were found between Santa Marta (higher frequency) and the other two cities. Differences in sleep problem frequency (Pittsburgh) were observed between Bogota (higher frequency) and Bucaramanga and also between Santa Marta (higher frequency) and the other two cities. The high risk of OSA (STOP-Bang) was different between Bogota (higher frequency) and Bucaramanga and also between Santa Marta (high frequency) and Bucaramanga. We observed a high prevalence of sleep complaints with significant differences among the cities, indicating a need to pay a greater attention to these problems.

Topology-changing shape optimization with the genetic algorithm

NASA Astrophysics Data System (ADS)

Lamberson, Steven E., Jr.

The goal is to take a traditional shape optimization problem statement and modify it slightly to allow for prescribed changes in topology. This modification enables greater flexibility in the choice of parameters for the topology optimization problem, while improving the direct physical relevance of the results. This modification involves changing the optimization problem statement from a nonlinear programming problem into a form of mixed-discrete nonlinear programing problem. The present work demonstrates one possible way of using the Genetic Algorithm (GA) to solve such a problem, including the use of "masking bits" and a new modification to the bit-string affinity (BSA) termination criterion specifically designed for problems with "masking bits." A simple ten-bar truss problem proves the utility of the modified BSA for this type of problem. A more complicated two dimensional bracket problem is solved using both the proposed approach and a more traditional topology optimization approach (Solid Isotropic Microstructure with Penalization or SIMP) to enable comparison. The proposed approach is able to solve problems with both local and global constraints, which is something traditional methods cannot do. The proposed approach has a significantly higher computational burden --- on the order of 100 times larger than SIMP, although the proposed approach is able to offset this with parallel computing.

Genetic algorithm parameters tuning for resource-constrained project scheduling problem

NASA Astrophysics Data System (ADS)

Tian, Xingke; Yuan, Shengrui

2018-04-01

Project Scheduling Problem (RCPSP) is a kind of important scheduling problem. To achieve a certain optimal goal such as the shortest duration, the smallest cost, the resource balance and so on, it is required to arrange the start and finish of all tasks under the condition of satisfying project timing constraints and resource constraints. In theory, the problem belongs to the NP-hard problem, and the model is abundant. Many combinatorial optimization problems are special cases of RCPSP, such as job shop scheduling, flow shop scheduling and so on. At present, the genetic algorithm (GA) has been used to deal with the classical RCPSP problem and achieved remarkable results. Vast scholars have also studied the improved genetic algorithm for the RCPSP problem, which makes it to solve the RCPSP problem more efficiently and accurately. However, for the selection of the main parameters of the genetic algorithm, there is no parameter optimization in these studies. Generally, we used the empirical method, but it cannot ensure to meet the optimal parameters. In this paper, the problem was carried out, which is the blind selection of parameters in the process of solving the RCPSP problem. We made sampling analysis, the establishment of proxy model and ultimately solved the optimal parameters.

A new approach to impulsive rendezvous near circular orbit

NASA Astrophysics Data System (ADS)

Carter, Thomas; Humi, Mayer

2012-04-01

A new approach is presented for the problem of planar optimal impulsive rendezvous of a spacecraft in an inertial frame near a circular orbit in a Newtonian gravitational field. The total characteristic velocity to be minimized is replaced by a related characteristic-value function and this related optimization problem can be solved in closed form. The solution of this problem is shown to approach the solution of the original problem in the limit as the boundary conditions approach those of a circular orbit. Using a form of primer-vector theory the problem is formulated in a way that leads to relatively easy calculation of the optimal velocity increments. A certain vector that can easily be calculated from the boundary conditions determines the number of impulses required for solution of the optimization problem and also is useful in the computation of these velocity increments. Necessary and sufficient conditions for boundary conditions to require exactly three nonsingular non-degenerate impulses for solution of the related optimal rendezvous problem, and a means of calculating these velocity increments are presented. A simple example of a three-impulse rendezvous problem is solved and the resulting trajectory is depicted. Optimal non-degenerate nonsingular two-impulse rendezvous for the related problem is found to consist of four categories of solutions depending on the four ways the primer vector locus intersects the unit circle. Necessary and sufficient conditions for each category of solutions are presented. The region of the boundary values that admit each category of solutions of the related problem are found, and in each case a closed-form solution of the optimal velocity increments is presented. Similar results are presented for the simpler optimal rendezvous that require only one-impulse. For brevity degenerate and singular solutions are not discussed in detail, but should be presented in a following study. Although this approach is thought to provide simpler computations than existing methods, its main contribution may be in establishing a new approach to the more general problem.

New evidence favoring multilevel decomposition and optimization

NASA Technical Reports Server (NTRS)

Padula, Sharon L.; Polignone, Debra A.

1990-01-01

The issue of the utility of multilevel decomposition and optimization remains controversial. To date, only the structural optimization community has actively developed and promoted multilevel optimization techniques. However, even this community acknowledges that multilevel optimization is ideally suited for a rather limited set of problems. It is warned that decomposition typically requires eliminating local variables by using global variables and that this in turn causes ill-conditioning of the multilevel optimization by adding equality constraints. The purpose is to suggest a new multilevel optimization technique. This technique uses behavior variables, in addition to design variables and constraints, to decompose the problem. The new technique removes the need for equality constraints, simplifies the decomposition of the design problem, simplifies the programming task, and improves the convergence speed of multilevel optimization compared to conventional optimization.

Primer-optimized results and trends for circular phasing and other circle-to-circle impulsive coplanar rendezvous

NASA Astrophysics Data System (ADS)

Sandrik, Suzannah

Optimal solutions to the impulsive circular phasing problem, a special class of orbital maneuver in which impulsive thrusts shift a vehicle's orbital position by a specified angle, are found using primer vector theory. The complexities of optimal circular phasing are identified and illustrated using specifically designed Matlab software tools. Information from these new visualizations is applied to explain discrepancies in locally optimal solutions found by previous researchers. Two non-phasing circle-to-circle impulsive rendezvous problems are also examined to show the applicability of the tools developed here to a broader class of problems and to show how optimizing these rendezvous problems differs from the circular phasing case.

On Born's Conjecture about Optimal Distribution of Charges for an Infinite Ionic Crystal

NASA Astrophysics Data System (ADS)

Bétermin, Laurent; Knüpfer, Hans

2018-04-01

We study the problem for the optimal charge distribution on the sites of a fixed Bravais lattice. In particular, we prove Born's conjecture about the optimality of the rock salt alternate distribution of charges on a cubic lattice (and more generally on a d-dimensional orthorhombic lattice). Furthermore, we study this problem on the two-dimensional triangular lattice and we prove the optimality of a two-component honeycomb distribution of charges. The results hold for a class of completely monotone interaction potentials which includes Coulomb-type interactions for d≥3 . In a more general setting, we derive a connection between the optimal charge problem and a minimization problem for the translated lattice theta function.

Multimodal optimization by using hybrid of artificial bee colony algorithm and BFGS algorithm

NASA Astrophysics Data System (ADS)

Anam, S.

2017-10-01

Optimization has become one of the important fields in Mathematics. Many problems in engineering and science can be formulated into optimization problems. They maybe have many local optima. The optimization problem with many local optima, known as multimodal optimization problem, is how to find the global solution. Several metaheuristic methods have been proposed to solve multimodal optimization problems such as Particle Swarm Optimization (PSO), Genetics Algorithm (GA), Artificial Bee Colony (ABC) algorithm, etc. The performance of the ABC algorithm is better than or similar to those of other population-based algorithms with the advantage of employing a fewer control parameters. The ABC algorithm also has the advantages of strong robustness, fast convergence and high flexibility. However, it has the disadvantages premature convergence in the later search period. The accuracy of the optimal value cannot meet the requirements sometimes. Broyden-Fletcher-Goldfarb-Shanno (BFGS) algorithm is a good iterative method for finding a local optimum. Compared with other local optimization methods, the BFGS algorithm is better. Based on the advantages of the ABC algorithm and the BFGS algorithm, this paper proposes a hybrid of the artificial bee colony algorithm and the BFGS algorithm to solve the multimodal optimization problem. The first step is that the ABC algorithm is run to find a point. In the second step is that the point obtained by the first step is used as an initial point of BFGS algorithm. The results show that the hybrid method can overcome from the basic ABC algorithm problems for almost all test function. However, if the shape of function is flat, the proposed method cannot work well.

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

Hart, William E.; Siirola, John Daniel

We describe new capabilities for modeling MPEC problems within the Pyomo modeling software. These capabilities include new modeling components that represent complementar- ity conditions, modeling transformations for re-expressing models with complementarity con- ditions in other forms, and meta-solvers that apply transformations and numeric optimization solvers to optimize MPEC problems. We illustrate the breadth of Pyomo's modeling capabil- ities for MPEC problems, and we describe how Pyomo's meta-solvers can perform local and global optimization of MPEC problems.

Genetic algorithms for multicriteria shape optimization of induction furnace

NASA Astrophysics Data System (ADS)

Kůs, Pavel; Mach, František; Karban, Pavel; Doležel, Ivo

2012-09-01

In this contribution we deal with a multi-criteria shape optimization of an induction furnace. We want to find shape parameters of the furnace in such a way, that two different criteria are optimized. Since they cannot be optimized simultaneously, instead of one optimum we find set of partially optimal designs, so called Pareto front. We compare two different approaches to the optimization, one using nonlinear conjugate gradient method and second using variation of genetic algorithm. As can be seen from the numerical results, genetic algorithm seems to be the right choice for this problem. Solution of direct problem (coupled problem consisting of magnetic and heat field) is done using our own code Agros2D. It uses finite elements of higher order leading to fast and accurate solution of relatively complicated coupled problem. It also provides advanced scripting support, allowing us to prepare parametric model of the furnace and simply incorporate various types of optimization algorithms.

A One-Layer Recurrent Neural Network for Real-Time Portfolio Optimization With Probability Criterion.

PubMed

Liu, Qingshan; Dang, Chuangyin; Huang, Tingwen

2013-02-01

This paper presents a decision-making model described by a recurrent neural network for dynamic portfolio optimization. The portfolio-optimization problem is first converted into a constrained fractional programming problem. Since the objective function in the programming problem is not convex, the traditional optimization techniques are no longer applicable for solving this problem. Fortunately, the objective function in the fractional programming is pseudoconvex on the feasible region. It leads to a one-layer recurrent neural network modeled by means of a discontinuous dynamic system. To ensure the optimal solutions for portfolio optimization, the convergence of the proposed neural network is analyzed and proved. In fact, the neural network guarantees to get the optimal solutions for portfolio-investment advice if some mild conditions are satisfied. A numerical example with simulation results substantiates the effectiveness and illustrates the characteristics of the proposed neural network.

Statistical Analysis of Readthrough Levels for Nonsense Mutations in Mammalian Cells Reveals a Major Determinant of Response to Gentamicin

PubMed Central

Floquet, Célia; Hatin, Isabelle; Rousset, Jean-Pierre; Bidou, Laure

2012-01-01

The efficiency of translation termination depends on the nature of the stop codon and the surrounding nucleotides. Some molecules, such as aminoglycoside antibiotics (gentamicin), decrease termination efficiency and are currently being evaluated for diseases caused by premature termination codons. However, the readthrough response to treatment is highly variable and little is known about the rules governing readthrough level and response to aminoglycosides. In this study, we carried out in-depth statistical analysis on a very large set of nonsense mutations to decipher the elements of nucleotide context responsible for modulating readthrough levels and gentamicin response. We quantified readthrough for 66 sequences containing a stop codon, in the presence and absence of gentamicin, in cultured mammalian cells. We demonstrated that the efficiency of readthrough after treatment is determined by the complex interplay between the stop codon and a larger sequence context. There was a strong positive correlation between basal and induced readthrough levels, and a weak negative correlation between basal readthrough level and gentamicin response (i.e. the factor of increase from basal to induced readthrough levels). The identity of the stop codon did not affect the response to gentamicin treatment. In agreement with a previous report, we confirm that the presence of a cytosine in +4 position promotes higher basal and gentamicin-induced readthrough than other nucleotides. We highlight for the first time that the presence of a uracil residue immediately upstream from the stop codon is a major determinant of the response to gentamicin. Moreover, this effect was mediated by the nucleotide itself, rather than by the amino-acid or tRNA corresponding to the −1 codon. Finally, we point out that a uracil at this position associated with a cytosine at +4 results in an optimal gentamicin-induced readthrough, which is the therapeutically relevant variable. PMID:22479203

Progression towards smoking cessation: Qualitative analysis of successful, unsuccessful, and never quitters

PubMed Central

Tombor, Ildiko; Vangeli, Eleni; West, Robert; Shahab, Lion

2018-01-01

ABSTRACT Background: Understanding how people transition between phases of not making a quit attempt to stopping smoking successfully is important in order to optimize interventions. This study aimed to explore differences in attitudes towards smoking and quitting among smokers and ex-smokers. Methods: Adult (age 18 and over) successful (n = 8), unsuccessful (n = 8) and never quitters (n = 7) were recruited through stop-smoking services in England. Semi-structured interviews were conducted and data were analysed using framework analysis. Results: Seven themes (starting to smoke, positive appraisal of smoking, responsibility for past/current smoking, negative effects of smoking, reasons to quit, process of quitting, and identity) were identified in all groups. Sub-group differences were explored and used to derive six typologies with descriptive characteristics: committed smokers, aware smokers, forced attempters, struggling attempters, pragmatic ex-smokers, and committed non-smokers. Using these typologies and the smallest number of differentiating factors between them (awareness of negative effects, motivation to stop and acceptance of responsibility), a parsimonious model of progression towards smoking cessation was developed. Conclusions: Awareness of negative effects, motivation and, crucially, a sense of commitment for taking responsibility to take actions towards behavior change may be important for whether smokers attempt to quit and progress to a successful quit attempt. PMID:29527597

Single Phase Dual-energy CT Angiography: One-stop-shop Tool for Evaluating Aneurysmal Subarachnoid Hemorrhage.

PubMed

Ni, Qian Qian; Tang, Chun Xiang; Zhao, Yan E; Zhou, Chang Sheng; Chen, Guo Zhong; Lu, Guang Ming; Zhang, Long Jiang

2016-05-25

Aneurysmal subarachnoid hemorrhages have extremely high case fatality in clinic. Early and rapid identifications of ruptured intracranial aneurysms seem to be especially important. Here we evaluate clinical value of single phase contrast-enhanced dual-energy CT angiograph (DE-CTA) as a one-stop-shop tool in detecting aneurysmal subarachnoid hemorrhage. One hundred and five patients who underwent true non-enhanced CT (TNCT), contrast-enhanced DE-CTA and digital subtraction angiography (DSA) were included. Image quality and detectability of intracranial hemorrhage were evaluated and compared between virtual non-enhanced CT (VNCT) images reconstructed from DE-CTA and TNCT. There was no statistical difference in image quality (P > 0.05) between VNCT and TNCT. The agreement of VNCT and TNCT in detecting intracranial hemorrhage reached 98.1% on a per-patient basis. With DSA as reference standard, sensitivity and specificity on a per-patient were 98.3% and 97.9% for DE-CTA in intracranial aneurysm detection. Effective dose of DE-CTA was reduced by 75.0% compared to conventional digital subtraction CTA. Thus, single phase contrast-enhanced DE-CTA is optimal reliable one-stop-shop tool for detecting intracranial hemorrhage with VNCT and intracranial aneurysms with DE-CTA with substantial radiation dose reduction compared with conventional digital subtraction CTA.

Single Phase Dual-energy CT Angiography: One-stop-shop Tool for Evaluating Aneurysmal Subarachnoid Hemorrhage

PubMed Central

Ni, Qian Qian; Tang, Chun Xiang; Zhao, Yan E; Zhou, Chang Sheng; Chen, Guo Zhong; Lu, Guang Ming; Zhang, Long Jiang

2016-01-01

Aneurysmal subarachnoid hemorrhages have extremely high case fatality in clinic. Early and rapid identifications of ruptured intracranial aneurysms seem to be especially important. Here we evaluate clinical value of single phase contrast-enhanced dual-energy CT angiograph (DE-CTA) as a one-stop-shop tool in detecting aneurysmal subarachnoid hemorrhage. One hundred and five patients who underwent true non-enhanced CT (TNCT), contrast-enhanced DE-CTA and digital subtraction angiography (DSA) were included. Image quality and detectability of intracranial hemorrhage were evaluated and compared between virtual non-enhanced CT (VNCT) images reconstructed from DE-CTA and TNCT. There was no statistical difference in image quality (P > 0.05) between VNCT and TNCT. The agreement of VNCT and TNCT in detecting intracranial hemorrhage reached 98.1% on a per-patient basis. With DSA as reference standard, sensitivity and specificity on a per-patient were 98.3% and 97.9% for DE-CTA in intracranial aneurysm detection. Effective dose of DE-CTA was reduced by 75.0% compared to conventional digital subtraction CTA. Thus, single phase contrast-enhanced DE-CTA is optimal reliable one-stop-shop tool for detecting intracranial hemorrhage with VNCT and intracranial aneurysms with DE-CTA with substantial radiation dose reduction compared with conventional digital subtraction CTA. PMID:27222163

Understanding the psychological precursors of young drivers' willingness to speed and text while driving.

PubMed

Preece, Carissa; Watson, Angela; Kaye, Sherrie-Anne; Fleiter, Judy

2018-08-01

This study applied the Prototype Willingness Model (PWM) to investigate the factors that may predict young drivers' (non-intentional) willingness to text while driving, text while stopped, and engage in high and low levels of speeding. In addition, the study sought to assess whether general optimism bias would predict young drivers' willingness to text and speed over and above the PWM. Licenced drivers (N = 183) aged 17-25 years (M = 19.84, SD = 2.30) in Queensland, Australia completed an online survey. Hierarchical multiple regressions revealed that the PWM was effective in explaining the variance in willingness to perform all four illegal driving behaviours. Particularly, young drivers who possessed favourable attitudes and a positive prototype perception towards these behaviours were more willing to engage in texting and speeding. In contrast to the study's predictions, optimistically biased beliefs decreased young drivers' willingness to text while stopped and engage in high and low levels of speeding. The findings of the study may help inform policy and educational campaigns to better target risky driving behaviours by considering the influence of attitudes, prototypes and the non-intentional pathway that may lead to engagement in texting while driving and stopped and engagement in high and low levels of speeding. Copyright © 2018 Elsevier Ltd. All rights reserved.

Optimization in First Semester Calculus: A Look at a Classic Problem

ERIC Educational Resources Information Center

LaRue, Renee; Infante, Nicole Engelke

2015-01-01

Optimization problems in first semester calculus have historically been a challenge for students. Focusing on the classic optimization problem of finding the minimum amount of fencing required to enclose a fixed area, we examine students' activity through the lens of Tall and Vinner's concept image and Carlson and Bloom's multidimensional…

Energy-Efficient Cognitive Radio Sensor Networks: Parametric and Convex Transformations

PubMed Central

Naeem, Muhammad; Illanko, Kandasamy; Karmokar, Ashok; Anpalagan, Alagan; Jaseemuddin, Muhammad

2013-01-01

Designing energy-efficient cognitive radio sensor networks is important to intelligently use battery energy and to maximize the sensor network life. In this paper, the problem of determining the power allocation that maximizes the energy-efficiency of cognitive radio-based wireless sensor networks is formed as a constrained optimization problem, where the objective function is the ratio of network throughput and the network power. The proposed constrained optimization problem belongs to a class of nonlinear fractional programming problems. Charnes-Cooper Transformation is used to transform the nonlinear fractional problem into an equivalent concave optimization problem. The structure of the power allocation policy for the transformed concave problem is found to be of a water-filling type. The problem is also transformed into a parametric form for which a ε-optimal iterative solution exists. The convergence of the iterative algorithms is proven, and numerical solutions are presented. The iterative solutions are compared with the optimal solution obtained from the transformed concave problem, and the effects of different system parameters (interference threshold level, the number of primary users and secondary sensor nodes) on the performance of the proposed algorithms are investigated. PMID:23966194

Using Animal Instincts to Design Efficient Biomedical Studies via Particle Swarm Optimization.

PubMed

Qiu, Jiaheng; Chen, Ray-Bing; Wang, Weichung; Wong, Weng Kee

2014-10-01

Particle swarm optimization (PSO) is an increasingly popular metaheuristic algorithm for solving complex optimization problems. Its popularity is due to its repeated successes in finding an optimum or a near optimal solution for problems in many applied disciplines. The algorithm makes no assumption of the function to be optimized and for biomedical experiments like those presented here, PSO typically finds the optimal solutions in a few seconds of CPU time on a garden-variety laptop. We apply PSO to find various types of optimal designs for several problems in the biological sciences and compare PSO performance relative to the differential evolution algorithm, another popular metaheuristic algorithm in the engineering literature.

Neutron yields from 155 MeV/nucleon carbon and helium stopping in aluminum

NASA Technical Reports Server (NTRS)

Heilbronn, L.; Cary, R. S.; Cronqvist, M.; Deak, F.; Frankel, K.; Galonsky, A.; Holabird, K.; Horvath, A.; Kiss, A.; Kruse, J.;

Alcohol-induced impairment of inhibitory control is linked to attenuated brain responses in right fronto-temporal cortex.

PubMed

Gan, Gabriela; Guevara, Alvaro; Marxen, Michael; Neumann, Maike; Jünger, Elisabeth; Kobiella, Andrea; Mennigen, Eva; Pilhatsch, Maximilian; Schwarz, Daniel; Zimmermann, Ulrich S; Smolka, Michael N

2014-11-01

A self-enhancing loop between impaired inhibitory control under alcohol and alcohol consumption has been proposed as a possible mechanism underlying dysfunctional drinking in susceptible people. However, the neural underpinnings of alcohol-induced impairment of inhibitory control are widely unknown. We measured inhibitory control in 50 young adults with a stop-signal task during functional magnetic resonance imaging. In a single-blind placebo-controlled cross-over design, all participants performed the stop-signal task once under alcohol with a breath alcohol concentration of .6 g/kg and once under placebo. In addition, alcohol consumption was assessed with a free-access alcohol self-administration paradigm in the same participants. Inhibitory control was robustly decreased under alcohol compared with placebo, indicated by longer stop-signal reaction times. On the neural level, impaired inhibitory control under alcohol was associated with attenuated brain responses in the right fronto-temporal portion of the inhibition network that supports the attentional capture of infrequent stop-signals and subsequent updating of action plans from response execution to inhibition. Furthermore, the extent of alcohol-induced impairment of inhibitory control predicted free-access alcohol consumption. We suggest that during inhibitory control alcohol affects cognitive processes preceding actual motor inhibition. Under alcohol, decreased brain responses in right fronto-temporal areas might slow down the attentional capture of infrequent stop-signals and subsequent updating of action plans, which leads to impaired inhibitory control. In turn, pronounced alcohol-induced impairment of inhibitory control might enhance alcohol consumption in young adults, which might promote future alcohol problems. Copyright © 2014 Society of Biological Psychiatry. Published by Elsevier Inc. All rights reserved.

Are smokers adequately informed about the health risks of smoking and medicinal nicotine?

PubMed

Cummings, K Michael; Hyland, Andrew; Giovino, Gary A; Hastrup, Janice L; Bauer, Joseph E; Bansal, Maansi A

2004-12-01

The present study assessed smokers' beliefs about the health risks of smoking and the benefits of smoking filtered and low-tar cigarettes, and their awareness of and interest in trying so-called reduced-risk tobacco products. Results were based on a nationally representative random-digit-dialed telephone survey of 1,046 adult (aged 18 years or older) current cigarette smokers. Data were gathered on demographic characteristics, tobacco use behaviors, awareness and use of nicotine medications, beliefs about the health risks of smoking, content of smoke and design features of cigarettes, and the safety and efficacy of nicotine medications. In addition, respondents were asked about their interest in and perceived ability to stop smoking and about their desire for more information about the health risks of smoking. Smokers were least knowledgeable about low-tar and filter cigarettes (65% of responses were incorrect or "don't know") and most knowledgeable about the health risks of smoking (39% of responses were incorrect or "don't know"). The smokers' characteristics most commonly associated with misinformation when all six indices were combined into a summary index were as follows: those aged 45 years or older, smokers of ultralight cigarettes, smokers who believe they will stop smoking before they experience a serious health problem caused by smoking, smokers who have never used a stop-smoking medication, and smokers with a lower education level. Those who believed they would stop smoking in the next year were more knowledgeable about smoking. Some 77% of respondents reported a desire for additional information from tobacco companies on the health dangers of smoking. The present findings demonstrate that smokers are misinformed about many aspects of the cigarettes they smoke and stop-smoking medications and that they want more information about ways to reduce their health risks.

Close games versus blowouts: Optimal challenge reinforces one's intrinsic motivation to win.

PubMed

Meng, Liang; Pei, Guanxiong; Zheng, Jiehui; Ma, Qingguo

2016-12-01

When immersed in intrinsically motivating activities, individuals actively seek optimal challenge, which generally brings the most satisfaction as they play hard and finally win. To better simulate real-life scenarios in the controlled laboratory setting, a two-player online StopWatch (SW) game was developed, whose format is similar to that of a badminton tournament. During the game, a male opponent played by a confederate ensured that the same-sex participant paired with him won both matches, one with a wide margin (the lack of challenge condition) and another with a narrow one (the optimal challenge condition). Electrophysiological data were recorded during the entire experiment. An enlarged Stimulus-preceding negativity (SPN) was observed in the optimal challenge condition, indicating a more concentrated anticipatory attention toward the feedback and a stronger intrinsic motivation during close games. Thus, this study provided original neural evidence for predictions of Self-determination theory (SDT) and Flow theory, and confirmed and emphasized the significant role of optimal challenge in promoting one's intrinsic motivation to win. Copyright © 2016 Elsevier B.V. All rights reserved.

Multiobjective optimization in a pseudometric objective space as applied to a general model of business activities

NASA Astrophysics Data System (ADS)

Khachaturov, R. V.

2016-09-01

It is shown that finding the equivalence set for solving multiobjective discrete optimization problems is advantageous over finding the set of Pareto optimal decisions. An example of a set of key parameters characterizing the economic efficiency of a commercial firm is proposed, and a mathematical model of its activities is constructed. In contrast to the classical problem of finding the maximum profit for any business, this study deals with a multiobjective optimization problem. A method for solving inverse multiobjective problems in a multidimensional pseudometric space is proposed for finding the best project of firm's activities. The solution of a particular problem of this type is presented.

Optimal orientation in flows: providing a benchmark for animal movement strategies.

PubMed

McLaren, James D; Shamoun-Baranes, Judy; Dokter, Adriaan M; Klaassen, Raymond H G; Bouten, Willem

2014-10-06

Animal movements in air and water can be strongly affected by experienced flow. While various flow-orientation strategies have been proposed and observed, their performance in variable flow conditions remains unclear. We apply control theory to establish a benchmark for time-minimizing (optimal) orientation. We then define optimal orientation for movement in steady flow patterns and, using dynamic wind data, for short-distance mass movements of thrushes (Turdus sp.) and 6000 km non-stop migratory flights by great snipes, Gallinago media. Relative to the optimal benchmark, we assess the efficiency (travel speed) and reliability (success rate) of three generic orientation strategies: full compensation for lateral drift, vector orientation (single-heading movement) and goal orientation (continually heading towards the goal). Optimal orientation is characterized by detours to regions of high flow support, especially when flow speeds approach and exceed the animal's self-propelled speed. In strong predictable flow (short distance thrush flights), vector orientation adjusted to flow on departure is nearly optimal, whereas for unpredictable flow (inter-continental snipe flights), only goal orientation was near-optimally reliable and efficient. Optimal orientation provides a benchmark for assessing efficiency of responses to complex flow conditions, thereby offering insight into adaptive flow-orientation across taxa in the light of flow strength, predictability and navigation capacity.

Optimal flexible sample size design with robust power.

PubMed

Zhang, Lanju; Cui, Lu; Yang, Bo

2016-08-30

It is well recognized that sample size determination is challenging because of the uncertainty on the treatment effect size. Several remedies are available in the literature. Group sequential designs start with a sample size based on a conservative (smaller) effect size and allow early stop at interim looks. Sample size re-estimation designs start with a sample size based on an optimistic (larger) effect size and allow sample size increase if the observed effect size is smaller than planned. Different opinions favoring one type over the other exist. We propose an optimal approach using an appropriate optimality criterion to select the best design among all the candidate designs. Our results show that (1) for the same type of designs, for example, group sequential designs, there is room for significant improvement through our optimization approach; (2) optimal promising zone designs appear to have no advantages over optimal group sequential designs; and (3) optimal designs with sample size re-estimation deliver the best adaptive performance. We conclude that to deal with the challenge of sample size determination due to effect size uncertainty, an optimal approach can help to select the best design that provides most robust power across the effect size range of interest. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

Optimal orientation in flows: providing a benchmark for animal movement strategies

PubMed Central

McLaren, James D.; Shamoun-Baranes, Judy; Dokter, Adriaan M.; Klaassen, Raymond H. G.; Bouten, Willem

2014-01-01

Animal movements in air and water can be strongly affected by experienced flow. While various flow-orientation strategies have been proposed and observed, their performance in variable flow conditions remains unclear. We apply control theory to establish a benchmark for time-minimizing (optimal) orientation. We then define optimal orientation for movement in steady flow patterns and, using dynamic wind data, for short-distance mass movements of thrushes (Turdus sp.) and 6000 km non-stop migratory flights by great snipes, Gallinago media. Relative to the optimal benchmark, we assess the efficiency (travel speed) and reliability (success rate) of three generic orientation strategies: full compensation for lateral drift, vector orientation (single-heading movement) and goal orientation (continually heading towards the goal). Optimal orientation is characterized by detours to regions of high flow support, especially when flow speeds approach and exceed the animal's self-propelled speed. In strong predictable flow (short distance thrush flights), vector orientation adjusted to flow on departure is nearly optimal, whereas for unpredictable flow (inter-continental snipe flights), only goal orientation was near-optimally reliable and efficient. Optimal orientation provides a benchmark for assessing efficiency of responses to complex flow conditions, thereby offering insight into adaptive flow-orientation across taxa in the light of flow strength, predictability and navigation capacity. PMID:25056213

The Sizing and Optimization Language, (SOL): Computer language for design problems

NASA Technical Reports Server (NTRS)

Lucas, Stephen H.; Scotti, Stephen J.

1988-01-01

The Sizing and Optimization Language, (SOL), a new high level, special purpose computer language was developed to expedite application of numerical optimization to design problems and to make the process less error prone. SOL utilizes the ADS optimization software and provides a clear, concise syntax for describing an optimization problem, the OPTIMIZE description, which closely parallels the mathematical description of the problem. SOL offers language statements which can be used to model a design mathematically, with subroutines or code logic, and with existing FORTRAN routines. In addition, SOL provides error checking and clear output of the optimization results. Because of these language features, SOL is best suited to model and optimize a design concept when the model consits of mathematical expressions written in SOL. For such cases, SOL's unique syntax and error checking can be fully utilized. SOL is presently available for DEC VAX/VMS systems. A SOL package is available which includes the SOL compiler, runtime library routines, and a SOL reference manual.

System safety management: A new discipline

NASA Technical Reports Server (NTRS)

Pope, W. C.

1971-01-01

The systems theory is discussed in relation to safety management. It is suggested that systems safety management, as a new discipline, holds great promise for reducing operating errors, conserving labor resources, avoiding operating costs due to mistakes, and for improving managerial techniques. It is pointed out that managerial failures or system breakdowns are the basic reasons for human errors and condition defects. In this respect, a recommendation is made that safety engineers stop visualizing the problem only with the individual (supervisor or employee) and see the problem from the systems point of view.

Optimal ballistically captured Earth-Moon transfers

NASA Astrophysics Data System (ADS)

Ricord Griesemer, Paul; Ocampo, Cesar; Cooley, D. S.

2012-07-01

The optimality of a low-energy Earth-Moon transfer terminating in ballistic capture is examined for the first time using primer vector theory. An optimal control problem is formed with the following free variables: the location, time, and magnitude of the transfer insertion burn, and the transfer time. A constraint is placed on the initial state of the spacecraft to bind it to a given initial orbit around a first body, and on the final state of the spacecraft to limit its Keplerian energy with respect to a second body. Optimal transfers in the system are shown to meet certain conditions placed on the primer vector and its time derivative. A two point boundary value problem containing these necessary conditions is created for use in targeting optimal transfers. The two point boundary value problem is then applied to the ballistic lunar capture problem, and an optimal trajectory is shown. Additionally, the problem is then modified to fix the time of transfer, allowing for optimal multi-impulse transfers. The tradeoff between transfer time and fuel cost is shown for Earth-Moon ballistic lunar capture transfers.

An approach for aerodynamic optimization of transonic fan blades

NASA Astrophysics Data System (ADS)

Khelghatibana, Maryam

Aerodynamic design optimization of transonic fan blades is a highly challenging problem due to the complexity of flow field inside the fan, the conflicting design requirements and the high-dimensional design space. In order to address all these challenges, an aerodynamic design optimization method is developed in this study. This method automates the design process by integrating a geometrical parameterization method, a CFD solver and numerical optimization methods that can be applied to both single and multi-point optimization design problems. A multi-level blade parameterization is employed to modify the blade geometry. Numerical analyses are performed by solving 3D RANS equations combined with SST turbulence model. Genetic algorithms and hybrid optimization methods are applied to solve the optimization problem. In order to verify the effectiveness and feasibility of the optimization method, a singlepoint optimization problem aiming to maximize design efficiency is formulated and applied to redesign a test case. However, transonic fan blade design is inherently a multi-faceted problem that deals with several objectives such as efficiency, stall margin, and choke margin. The proposed multi-point optimization method in the current study is formulated as a bi-objective problem to maximize design and near-stall efficiencies while maintaining the required design pressure ratio. Enhancing these objectives significantly deteriorate the choke margin, specifically at high rotational speeds. Therefore, another constraint is embedded in the optimization problem in order to prevent the reduction of choke margin at high speeds. Since capturing stall inception is numerically very expensive, stall margin has not been considered as an objective in the problem statement. However, improving near-stall efficiency results in a better performance at stall condition, which could enhance the stall margin. An investigation is therefore performed on the Pareto-optimal solutions to demonstrate the relation between near-stall efficiency and stall margin. The proposed method is applied to redesign NASA rotor 67 for single and multiple operating conditions. The single-point design optimization showed +0.28 points improvement of isentropic efficiency at design point, while the design pressure ratio and mass flow are, respectively, within 0.12% and 0.11% of the reference blade. Two cases of multi-point optimization are performed: First, the proposed multi-point optimization problem is relaxed by removing the choke margin constraint in order to demonstrate the relation between near-stall efficiency and stall margin. An investigation on the Pareto-optimal solutions of this optimization shows that the stall margin has been increased with improving near-stall efficiency. The second multi-point optimization case is performed with considering all the objectives and constraints. One selected optimized design on the Pareto front presents +0.41, +0.56 and +0.9 points improvement in near-peak efficiency, near-stall efficiency and stall margin, respectively. The design pressure ratio and mass flow are, respectively, within 0.3% and 0.26% of the reference blade. Moreover the optimized design maintains the required choking margin. Detailed aerodynamic analyses are performed to investigate the effect of shape optimization on shock occurrence, secondary flows, tip leakage and shock/tip-leakage interactions in both single and multi-point optimizations.

OPTIMIZING THROUGH CO-EVOLUTIONARY AVALANCHES

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

S. BOETTCHER; A. PERCUS

2000-08-01

We explore a new general-purpose heuristic for finding high-quality solutions to hard optimization problems. The method, called extremal optimization, is inspired by ''self-organized critically,'' a concept introduced to describe emergent complexity in many physical systems. In contrast to Genetic Algorithms which operate on an entire ''gene-pool'' of possible solutions, extremal optimization successively replaces extremely undesirable elements of a sub-optimal solution with new, random ones. Large fluctuations, called ''avalanches,'' ensue that efficiently explore many local optima. Drawing upon models used to simulate far-from-equilibrium dynamics, extremal optimization complements approximation methods inspired by equilibrium statistical physics, such as simulated annealing. With only onemore » adjustable parameter, its performance has proved competitive with more elaborate methods, especially near phase transitions. Those phase transitions are found in the parameter space of most optimization problems, and have recently been conjectured to be the origin of some of the hardest instances in computational complexity. We will demonstrate how extremal optimization can be implemented for a variety of combinatorial optimization problems. We believe that extremal optimization will be a useful tool in the investigation of phase transitions in combinatorial optimization problems, hence valuable in elucidating the origin of computational complexity.« less