Enhanced Constrained Predictive Control for Applications to Autonomous Vehicles and Missions

DTIC Science & Technology

2016-10-18

AFRL /RVSV 3550 Aberdeen Ave, SE 11. SPONSOR/MONITOR’S REPORT Kirtland AFB, NM 87117-5776 NUMBER(S) AFRL -RV-PS-TR-2016-0122 12. DISTRIBUTION...Suite 0944 Ft Belvoir, VA 22060-6218 1 cy AFRL /RVIL Kirtland AFB, NM 87117-5776 2 cys Official Record Copy AFRL /RVSV/Richard S. Erwin 1 cy ... AFRL -RV-PS- AFRL -RV-PS- TR-2016-0122 TR-2016-0122 ENHANCED CONSTRAINED PREDICTIVE CONTROL FOR APPLICATIONS TO AUTONOMOUS VEHICLES

Application of higher harmonic blade feathering for helicopter vibration reduction

NASA Technical Reports Server (NTRS)

Powers, R. W.

1978-01-01

Higher harmonic blade feathering for helicopter vibration reduction is considered. Recent wind tunnel tests confirmed the effectiveness of higher harmonic control in reducing articulated rotor vibratory hub loads. Several predictive analyses developed in support of the NASA program were shown to be capable of calculating single harmonic control inputs required to minimize a single 4P hub response. In addition, a multiple-input, multiple-output harmonic control predictive analysis was developed. All techniques developed thus far obtain a solution by extracting empirical transfer functions from sampled data. Algorithm data sampling and processing requirements are minimal to encourage adaptive control system application of such techniques in a flight environment.

Avionic Architecture for Model Predictive Control Application in Mars Sample & Return Rendezvous Scenario

NASA Astrophysics Data System (ADS)

Saponara, M.; Tramutola, A.; Creten, P.; Hardy, J.; Philippe, C.

2013-08-01

Optimization-based control techniques such as Model Predictive Control (MPC) are considered extremely attractive for space rendezvous, proximity operations and capture applications that require high level of autonomy, optimal path planning and dynamic safety margins. Such control techniques require high-performance computational needs for solving large optimization problems. The development and implementation in a flight representative avionic architecture of a MPC based Guidance, Navigation and Control system has been investigated in the ESA R&T study “On-line Reconfiguration Control System and Avionics Architecture” (ORCSAT) of the Aurora programme. The paper presents the baseline HW and SW avionic architectures, and verification test results obtained with a customised RASTA spacecraft avionics development platform from Aeroflex Gaisler.

A review of geographic information system and remote sensing with applications to the epidemiology and control of schistosomiasis in China.

PubMed

Yang, Guo-Jing; Vounatsou, Penelope; Zhou, Xiao-Nong; Utzinger, Jürg; Tanner, Marcel

2005-01-01

Geographic information system (GIS) and remote sensing (RS) technologies offer new opportunities for rapid assessment of endemic areas, provision of reliable estimates of populations at risk, prediction of disease distributions in areas that lack baseline data and are difficult to access, and guidance of intervention strategies, so that scarce resources can be allocated in a cost-effective manner. Here, we focus on the epidemiology and control of schistosomiasis in China and review GIS and RS applications to date. These include mapping prevalence and intensity data of Schistosoma japonicum at a large scale, and identifying and predicting suitable habitats for Oncomelania hupensis, the intermediate host snail of S. japonicum, at a small scale. Other prominent applications have been the prediction of infection risk due to ecological transformations, particularly those induced by floods and water resource developments, and the potential impact of climate change. We also discuss the limitations of the previous work, and outline potential new applications of GIS and RS techniques, namely quantitative GIS, WebGIS, and utilization of emerging satellite information, as they hold promise to further enhance infection risk mapping and disease prediction. Finally, we stress current research needs to overcome some of the remaining challenges of GIS and RS applications for schistosomiasis, so that further and sustained progress can be made to control this disease in China and elsewhere.

Prediction and control of chaotic processes using nonlinear adaptive networks

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

Jones, R.D.; Barnes, C.W.; Flake, G.W.

1990-01-01

We present the theory of nonlinear adaptive networks and discuss a few applications. In particular, we review the theory of feedforward backpropagation networks. We then present the theory of the Connectionist Normalized Linear Spline network in both its feedforward and iterated modes. Also, we briefly discuss the theory of stochastic cellular automata. We then discuss applications to chaotic time series, tidal prediction in Venice lagoon, finite differencing, sonar transient detection, control of nonlinear processes, control of a negative ion source, balancing a double inverted pendulum and design advice for free electron lasers and laser fusion targets.

Deadbeat Predictive Controllers

NASA Technical Reports Server (NTRS)

Juang, Jer-Nan; Phan, Minh

1997-01-01

Several new computational algorithms are presented to compute the deadbeat predictive control law. The first algorithm makes use of a multi-step-ahead output prediction to compute the control law without explicitly calculating the controllability matrix. The system identification must be performed first and then the predictive control law is designed. The second algorithm uses the input and output data directly to compute the feedback law. It combines the system identification and the predictive control law into one formulation. The third algorithm uses an observable-canonical form realization to design the predictive controller. The relationship between all three algorithms is established through the use of the state-space representation. All algorithms are applicable to multi-input, multi-output systems with disturbance inputs. In addition to the feedback terms, feed forward terms may also be added for disturbance inputs if they are measurable. Although the feedforward terms do not influence the stability of the closed-loop feedback law, they enhance the performance of the controlled system.

Predicting tree mortality following gypsy moth defoliation

Treesearch

D.E. Fosbroke; R.R. Hicks; K.W. Gottschalk

1991-01-01

Appropriate application of gypsy moth control strategies requires an accurate prediction of the distribution and intensity of tree mortality prior to defoliation. This prior information is necessary to better target investments in control activities where they are needed. This poster lays the groundwork for developing hazard-rating systems for forests of the...

Toward a Model-Based Predictive Controller Design in Brain–Computer Interfaces

PubMed Central

Kamrunnahar, M.; Dias, N. S.; Schiff, S. J.

2013-01-01

A first step in designing a robust and optimal model-based predictive controller (MPC) for brain–computer interface (BCI) applications is presented in this article. An MPC has the potential to achieve improved BCI performance compared to the performance achieved by current ad hoc, nonmodel-based filter applications. The parameters in designing the controller were extracted as model-based features from motor imagery task-related human scalp electroencephalography. Although the parameters can be generated from any model-linear or non-linear, we here adopted a simple autoregressive model that has well-established applications in BCI task discriminations. It was shown that the parameters generated for the controller design can as well be used for motor imagery task discriminations with performance (with 8–23% task discrimination errors) comparable to the discrimination performance of the commonly used features such as frequency specific band powers and the AR model parameters directly used. An optimal MPC has significant implications for high performance BCI applications. PMID:21267657

Toward a model-based predictive controller design in brain-computer interfaces.

PubMed

Kamrunnahar, M; Dias, N S; Schiff, S J

2011-05-01

A first step in designing a robust and optimal model-based predictive controller (MPC) for brain-computer interface (BCI) applications is presented in this article. An MPC has the potential to achieve improved BCI performance compared to the performance achieved by current ad hoc, nonmodel-based filter applications. The parameters in designing the controller were extracted as model-based features from motor imagery task-related human scalp electroencephalography. Although the parameters can be generated from any model-linear or non-linear, we here adopted a simple autoregressive model that has well-established applications in BCI task discriminations. It was shown that the parameters generated for the controller design can as well be used for motor imagery task discriminations with performance (with 8-23% task discrimination errors) comparable to the discrimination performance of the commonly used features such as frequency specific band powers and the AR model parameters directly used. An optimal MPC has significant implications for high performance BCI applications.

Aircraft Trajectories Computation-Prediction-Control (La Trajectoire de l’Avion Calcul-Prediction-Controle). Volume 2

DTIC Science & Technology

1990-05-01

faire atterrir las a~ronefs sans recourir de faqon systimatique aux attentes habituelles; un de leurs coll~gues ayant contribu6 At la recherche de la...applicable to or usable for the management of the flows of aircraft and the control of individual flights, the integration of control phases over...February 1976. AIR TRAFFIC MANAGEMENT : Civil/Military Systems and Technologies Guidance and Control Symposium, Copenhagen, Denmark, 9-12 October 1979. AGARD

An Improved Formulation of Hybrid Model Predictive Control With Application to Production-Inventory Systems.

PubMed

Nandola, Naresh N; Rivera, Daniel E

2013-01-01

We consider an improved model predictive control (MPC) formulation for linear hybrid systems described by mixed logical dynamical (MLD) models. The algorithm relies on a multiple-degree-of-freedom parametrization that enables the user to adjust the speed of setpoint tracking, measured disturbance rejection and unmeasured disturbance rejection independently in the closed-loop system. Consequently, controller tuning is more flexible and intuitive than relying on objective function weights (such as move suppression) traditionally used in MPC schemes. The controller formulation is motivated by the needs of non-traditional control applications that are suitably described by hybrid production-inventory systems. Two applications are considered in this paper: adaptive, time-varying interventions in behavioral health, and inventory management in supply chains under conditions of limited capacity. In the adaptive intervention application, a hypothetical intervention inspired by the Fast Track program, a real-life preventive intervention for reducing conduct disorder in at-risk children, is examined. In the inventory management application, the ability of the algorithm to judiciously alter production capacity under conditions of varying demand is presented. These case studies demonstrate that MPC for hybrid systems can be tuned for desired performance under demanding conditions involving noise and uncertainty.

An Improved Formulation of Hybrid Model Predictive Control With Application to Production-Inventory Systems

PubMed Central

Nandola, Naresh N.; Rivera, Daniel E.

2013-01-01

We consider an improved model predictive control (MPC) formulation for linear hybrid systems described by mixed logical dynamical (MLD) models. The algorithm relies on a multiple-degree-of-freedom parametrization that enables the user to adjust the speed of setpoint tracking, measured disturbance rejection and unmeasured disturbance rejection independently in the closed-loop system. Consequently, controller tuning is more flexible and intuitive than relying on objective function weights (such as move suppression) traditionally used in MPC schemes. The controller formulation is motivated by the needs of non-traditional control applications that are suitably described by hybrid production-inventory systems. Two applications are considered in this paper: adaptive, time-varying interventions in behavioral health, and inventory management in supply chains under conditions of limited capacity. In the adaptive intervention application, a hypothetical intervention inspired by the Fast Track program, a real-life preventive intervention for reducing conduct disorder in at-risk children, is examined. In the inventory management application, the ability of the algorithm to judiciously alter production capacity under conditions of varying demand is presented. These case studies demonstrate that MPC for hybrid systems can be tuned for desired performance under demanding conditions involving noise and uncertainty. PMID:24348004

Introduction to Computational Methods for Stability and Control (COMSAC)

NASA Technical Reports Server (NTRS)

Hall, Robert M.; Fremaux, C. Michael; Chambers, Joseph R.

2004-01-01

This Symposium is intended to bring together the often distinct cultures of the Stability and Control (S&C) community and the Computational Fluid Dynamics (CFD) community. The COMSAC program is itself a new effort by NASA Langley to accelerate the application of high end CFD methodologies to the demanding job of predicting stability and control characteristics of aircraft. This talk is intended to set the stage for needing a program like COMSAC. It is not intended to give details of the program itself. The topics include: 1) S&C Challenges; 2) Aero prediction methodology; 3) CFD applications; 4) NASA COMSAC planning; 5) Objectives of symposium; and 6) Closing remarks.

An Efficient Silent Data Corruption Detection Method with Error-Feedback Control and Even Sampling for HPC Applications

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

Di, Sheng; Berrocal, Eduardo; Cappello, Franck

The silent data corruption (SDC) problem is attracting more and more attentions because it is expected to have a great impact on exascale HPC applications. SDC faults are hazardous in that they pass unnoticed by hardware and can lead to wrong computation results. In this work, we formulate SDC detection as a runtime one-step-ahead prediction method, leveraging multiple linear prediction methods in order to improve the detection results. The contributions are twofold: (1) we propose an error feedback control model that can reduce the prediction errors for different linear prediction methods, and (2) we propose a spatial-data-based even-sampling method tomore » minimize the detection overheads (including memory and computation cost). We implement our algorithms in the fault tolerance interface, a fault tolerance library with multiple checkpoint levels, such that users can conveniently protect their HPC applications against both SDC errors and fail-stop errors. We evaluate our approach by using large-scale traces from well-known, large-scale HPC applications, as well as by running those HPC applications on a real cluster environment. Experiments show that our error feedback control model can improve detection sensitivity by 34-189% for bit-flip memory errors injected with the bit positions in the range [20,30], without any degradation on detection accuracy. Furthermore, memory size can be reduced by 33% with our spatial-data even-sampling method, with only a slight and graceful degradation in the detection sensitivity.« less

Cell fate reprogramming by control of intracellular network dynamics

NASA Astrophysics Data System (ADS)

Zanudo, Jorge G. T.; Albert, Reka

Identifying control strategies for biological networks is paramount for practical applications that involve reprogramming a cell's fate, such as disease therapeutics and stem cell reprogramming. Although the topic of controlling the dynamics of a system has a long history in control theory, most of this work is not directly applicable to intracellular networks. Here we present a network control method that integrates the structural and functional information available for intracellular networks to predict control targets. Formulated in a logical dynamic scheme, our control method takes advantage of certain function-dependent network components and their relation to steady states in order to identify control targets, which are guaranteed to drive any initial state to the target state with 100% effectiveness and need to be applied only transiently for the system to reach and stay in the desired state. We illustrate our method's potential to find intervention targets for cancer treatment and cell differentiation by applying it to a leukemia signaling network and to the network controlling the differentiation of T cells. We find that the predicted control targets are effective in a broad dynamic framework. Moreover, several of the predicted interventions are supported by experiments. This work was supported by NSF Grant PHY 1205840.

Diagnostic inaccuracy of smartphone applications for melanoma detection.

PubMed

Wolf, Joel A; Moreau, Jacqueline F; Akilov, Oleg; Patton, Timothy; English, Joseph C; Ho, Jonhan; Ferris, Laura K

2013-04-01

To measure the performance of smartphone applications that evaluate photographs of skin lesions and provide the user with feedback about the likelihood of malignancy. Case-control diagnostic accuracy study. Academic dermatology department. PARTICIPANTS AND MATERIALS: Digital clinical images of pigmented cutaneous lesions (60 melanoma and 128 benign control lesions) with a histologic diagnosis rendered by a board-certified dermatopathologist, obtained before biopsy from patients undergoing lesion removal as a part of routine care. Sensitivity, specificity, and positive and negative predictive values of 4 smartphone applications designed to aid nonclinician users in determining whether their skin lesion is benign or malignant. Sensitivity of the 4 tested applications ranged from 6.8% to 98.1%; specificity, 30.4% to 93.7%; positive predictive value, 33.3% to 42.1%; and negative predictive value, 65.4% to 97.0%. The highest sensitivity for melanoma diagnosis was observed for an application that sends the image directly to a board-certified dermatologist for analysis; the lowest, for applications that use automated algorithms to analyze images. The performance of smartphone applications in assessing melanoma risk is highly variable, and 3 of 4 smartphone applications incorrectly classified 30% or more of melanomas as unconcerning. Reliance on these applications, which are not subject to regulatory oversight, in lieu of medical consultation can delay the diagnosis of melanoma and harm users.

Effects of external loads on balance control during upright stance: experimental results and model-based predictions.

PubMed

Qu, Xingda; Nussbaum, Maury A

2009-01-01

The purpose of this study was to identify the effects of external loads on balance control during upright stance, and to examine the ability of a new balance control model to predict these effects. External loads were applied to 12 young, healthy participants, and effects on balance control were characterized by center-of-pressure (COP) based measures. Several loading conditions were studied, involving combinations of load mass (10% and 20% of individual body mass) and height (at or 15% of stature above the whole-body COM). A balance control model based on an optimal control strategy was used to predict COP time series. It was assumed that a given individual would adopt the same neural optimal control mechanisms, identified in a no-load condition, under diverse external loading conditions. With the application of external loads, COP mean velocity in the anterior-posterior direction and RMS distance in the medial-lateral direction increased 8.1% and 10.4%, respectively. Predicted COP mean velocity and RMS distance in the anterior-posterior direction also increased with external loading, by 11.1% and 2.9%, respectively. Both experimental COP data and model-based predictions provided the same general conclusion, that application of larger external loads and loads more superior to the whole body center of mass lead to less effective postural control and perhaps a greater risk of loss of balance or falls. Thus, it can be concluded that the assumption about consistency in control mechanisms was partially supported, and it is the mechanical changes induced by external loads that primarily affect balance control.

An improved predictive functional control method with application to PMSM systems

NASA Astrophysics Data System (ADS)

Li, Shihua; Liu, Huixian; Fu, Wenshu

2017-01-01

In common design of prediction model-based control method, usually disturbances are not considered in the prediction model as well as the control design. For the control systems with large amplitude or strong disturbances, it is difficult to precisely predict the future outputs according to the conventional prediction model, and thus the desired optimal closed-loop performance will be degraded to some extent. To this end, an improved predictive functional control (PFC) method is developed in this paper by embedding disturbance information into the system model. Here, a composite prediction model is thus obtained by embedding the estimated value of disturbances, where disturbance observer (DOB) is employed to estimate the lumped disturbances. So the influence of disturbances on system is taken into account in optimisation procedure. Finally, considering the speed control problem for permanent magnet synchronous motor (PMSM) servo system, a control scheme based on the improved PFC method is designed to ensure an optimal closed-loop performance even in the presence of disturbances. Simulation and experimental results based on a hardware platform are provided to confirm the effectiveness of the proposed algorithm.

Internal health locus of control predicts willingness to track health behaviors online and with smartphone applications.

PubMed

Bennett, Brooke L; Goldstein, Carly M; Gathright, Emily C; Hughes, Joel W; Latner, Janet D

2017-12-01

Given rising technology use across all demographic groups, digital interventions offer a potential strategy for increasing access to health information and care. Research is lacking on identifying individual differences that impact willingness to use digital interventions, which may affect patient engagement. Health locus of control, the amount of control an individual believes they have over their own health, may predict willingness to use mobile health (mHealth) applications ('apps') and online trackers. A cross-sectional study (n = 276) was conducted to assess college students' health locus of control beliefs and willingness to use health apps and online trackers. Internal and powerful other health locus of control beliefs predicted willingness to use health apps and online trackers while chance health locus of control beliefs did not. Individuals with internal and powerful other health locus of control beliefs are more willing than those with chance health locus of control beliefs to utilize a form of technology to monitor or change health behaviors. Health locus of control is an easy-to-assess patient characteristic providers can measure to identify which patients are more likely to utilize mHealth apps and online trackers.

Predictive optimal control of sewer networks using CORAL tool: application to Riera Blanca catchment in Barcelona.

PubMed

Puig, V; Cembrano, G; Romera, J; Quevedo, J; Aznar, B; Ramón, G; Cabot, J

2009-01-01

This paper deals with the global control of the Riera Blanca catchment in the Barcelona sewer network using a predictive optimal control approach. This catchment has been modelled using a conceptual modelling approach based on decomposing the catchments in subcatchments and representing them as virtual tanks. This conceptual modelling approach allows real-time model calibration and control of the sewer network. The global control problem of the Riera Blanca catchment is solved using a optimal/predictive control algorithm. To implement the predictive optimal control of the Riera Blanca catchment, a software tool named CORAL is used. The on-line control is simulated by interfacing CORAL with a high fidelity simulator of sewer networks (MOUSE). CORAL interchanges readings from the limnimeters and gate commands with MOUSE as if it was connected with the real SCADA system. Finally, the global control results obtained using the predictive optimal control are presented and compared against the results obtained using current local control system. The results obtained using the global control are very satisfactory compared to those obtained using the local control.

Self-Tuning of Design Variables for Generalized Predictive Control

NASA Technical Reports Server (NTRS)

Lin, Chaung; Juang, Jer-Nan

2000-01-01

Three techniques are introduced to determine the order and control weighting for the design of a generalized predictive controller. These techniques are based on the application of fuzzy logic, genetic algorithms, and simulated annealing to conduct an optimal search on specific performance indexes or objective functions. Fuzzy logic is found to be feasible for real-time and on-line implementation due to its smooth and quick convergence. On the other hand, genetic algorithms and simulated annealing are applicable for initial estimation of the model order and control weighting, and final fine-tuning within a small region of the solution space, Several numerical simulations for a multiple-input and multiple-output system are given to illustrate the techniques developed in this paper.

Model Predictive Flight Control System with Full State Observer using H∞ Method

NASA Astrophysics Data System (ADS)

Sanwale, Jitu; Singh, Dhan Jeet

2018-03-01

This paper presents the application of the model predictive approach to design a flight control system (FCS) for longitudinal dynamics of a fixed wing aircraft. Longitudinal dynamics is derived for a conventional aircraft. Open loop aircraft response analysis is carried out. Simulation studies are illustrated to prove the efficacy of the proposed model predictive controller using H ∞ state observer. The estimation criterion used in the {H}_{∞} observer design is to minimize the worst possible effects of the modelling errors and additive noise on the parameter estimation.

Quality Control Analysis of Selected Aspects of Programs Administered by the Bureau of Student Financial Assistance. Task 1 and Quality Control Sample; Error-Prone Modeling Analysis Plan.

ERIC Educational Resources Information Center

Saavedra, Pedro; And Others

Parameters and procedures for developing an error-prone model (EPM) to predict financial aid applicants who are likely to misreport on Basic Educational Opportunity Grant (BEOG) applications are introduced. Specifications to adapt these general parameters to secondary data analysis of the Validation, Edits, and Applications Processing Systems…

Quality by control: Towards model predictive control of mammalian cell culture bioprocesses.

PubMed

Sommeregger, Wolfgang; Sissolak, Bernhard; Kandra, Kulwant; von Stosch, Moritz; Mayer, Martin; Striedner, Gerald

2017-07-01

The industrial production of complex biopharmaceuticals using recombinant mammalian cell lines is still mainly built on a quality by testing approach, which is represented by fixed process conditions and extensive testing of the end-product. In 2004 the FDA launched the process analytical technology initiative, aiming to guide the industry towards advanced process monitoring and better understanding of how critical process parameters affect the critical quality attributes. Implementation of process analytical technology into the bio-production process enables moving from the quality by testing to a more flexible quality by design approach. The application of advanced sensor systems in combination with mathematical modelling techniques offers enhanced process understanding, allows on-line prediction of critical quality attributes and subsequently real-time product quality control. In this review opportunities and unsolved issues on the road to a successful quality by design and dynamic control implementation are discussed. A major focus is directed on the preconditions for the application of model predictive control for mammalian cell culture bioprocesses. Design of experiments providing information about the process dynamics upon parameter change, dynamic process models, on-line process state predictions and powerful software environments seem to be a prerequisite for quality by control realization. © 2017 The Authors. Biotechnology Journal published by WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

A model for prediction of STOVL ejector dynamics

NASA Technical Reports Server (NTRS)

Drummond, Colin K.

1989-01-01

A semi-empirical control-volume approach to ejector modeling for transient performance prediction is presented. This new approach is motivated by the need for a predictive real-time ejector sub-system simulation for Short Take-Off Verticle Landing (STOVL) integrated flight and propulsion controls design applications. Emphasis is placed on discussion of the approximate characterization of the mixing process central to thrust augmenting ejector operation. The proposed ejector model suggests transient flow predictions are possible with a model based on steady-flow data. A practical test case is presented to illustrate model calibration.

Applications of artificial neural networks (ANNs) in food science.

PubMed

Huang, Yiqun; Kangas, Lars J; Rasco, Barbara A

2007-01-01

Artificial neural networks (ANNs) have been applied in almost every aspect of food science over the past two decades, although most applications are in the development stage. ANNs are useful tools for food safety and quality analyses, which include modeling of microbial growth and from this predicting food safety, interpreting spectroscopic data, and predicting physical, chemical, functional and sensory properties of various food products during processing and distribution. ANNs hold a great deal of promise for modeling complex tasks in process control and simulation and in applications of machine perception including machine vision and electronic nose for food safety and quality control. This review discusses the basic theory of the ANN technology and its applications in food science, providing food scientists and the research community an overview of the current research and future trend of the applications of ANN technology in the field.

Assessment of quantitative structure-activity relationship of toxicity prediction models for Korean chemical substance control legislation

PubMed Central

Kim, Kwang-Yon; Shin, Seong Eun; No, Kyoung Tai

2015-01-01

Objectives For successful adoption of legislation controlling registration and assessment of chemical substances, it is important to obtain sufficient toxicological experimental evidence and other related information. It is also essential to obtain a sufficient number of predicted risk and toxicity results. Particularly, methods used in predicting toxicities of chemical substances during acquisition of required data, ultimately become an economic method for future dealings with new substances. Although the need for such methods is gradually increasing, the-required information about reliability and applicability range has not been systematically provided. Methods There are various representative environmental and human toxicity models based on quantitative structure-activity relationships (QSAR). Here, we secured the 10 representative QSAR-based prediction models and its information that can make predictions about substances that are expected to be regulated. We used models that predict and confirm usability of the information expected to be collected and submitted according to the legislation. After collecting and evaluating each predictive model and relevant data, we prepared methods quantifying the scientific validity and reliability, which are essential conditions for using predictive models. Results We calculated predicted values for the models. Furthermore, we deduced and compared adequacies of the models using the Alternative non-testing method assessed for Registration, Evaluation, Authorization, and Restriction of Chemicals Substances scoring system, and deduced the applicability domains for each model. Additionally, we calculated and compared inclusion rates of substances expected to be regulated, to confirm the applicability. Conclusions We evaluated and compared the data, adequacy, and applicability of our selected QSAR-based toxicity prediction models, and included them in a database. Based on this data, we aimed to construct a system that can be used with predicted toxicity results. Furthermore, by presenting the suitability of individual predicted results, we aimed to provide a foundation that could be used in actual assessments and regulations. PMID:26206368

Nonlinear model predictive control of a wave energy converter based on differential flatness parameterisation

NASA Astrophysics Data System (ADS)

Li, Guang

2017-01-01

This paper presents a fast constrained optimization approach, which is tailored for nonlinear model predictive control of wave energy converters (WEC). The advantage of this approach relies on its exploitation of the differential flatness of the WEC model. This can reduce the dimension of the resulting nonlinear programming problem (NLP) derived from the continuous constrained optimal control of WEC using pseudospectral method. The alleviation of computational burden using this approach helps to promote an economic implementation of nonlinear model predictive control strategy for WEC control problems. The method is applicable to nonlinear WEC models, nonconvex objective functions and nonlinear constraints, which are commonly encountered in WEC control problems. Numerical simulations demonstrate the efficacy of this approach.

Model Predictive Control techniques with application to photovoltaic, DC Microgrid, and a multi-sourced hybrid energy system

NASA Astrophysics Data System (ADS)

Shadmand, Mohammad Bagher

Renewable energy sources continue to gain popularity. However, two major limitations exist that prevent widespread adoption: availability and variability of the electricity generated and the cost of the equipment. The focus of this dissertation is Model Predictive Control (MPC) for optimal sized photovoltaic (PV), DC Microgrid, and multi-sourced hybrid energy systems. The main considered applications are: maximum power point tracking (MPPT) by MPC, droop predictive control of DC microgrid, MPC of grid-interaction inverter, MPC of a capacitor-less VAR compensator based on matrix converter (MC). This dissertation firstly investigates a multi-objective optimization technique for a hybrid distribution system. The variability of a high-penetration PV scenario is also studied when incorporated into the microgrid concept. Emerging (PV) technologies have enabled the creation of contoured and conformal PV surfaces; the effect of using non-planar PV modules on variability is also analyzed. The proposed predictive control to achieve maximum power point for isolated and grid-tied PV systems speeds up the control loop since it predicts error before the switching signal is applied to the converter. The low conversion efficiency of PV cells means we want to ensure always operating at maximum possible power point to make the system economical. Thus the proposed MPPT technique can capture more energy compared to the conventional MPPT techniques from same amount of installed solar panel. Because of the MPPT requirement, the output voltage of the converter may vary. Therefore a droop control is needed to feed multiple arrays of photovoltaic systems to a DC bus in microgrid community. Development of a droop control technique by means of predictive control is another application of this dissertation. Reactive power, denoted as Volt Ampere Reactive (VAR), has several undesirable consequences on AC power system network such as reduction in power transfer capability and increase in transmission loss if not controlled appropriately. Inductive loads which operate with lagging power factor consume VARs, thus load compensation techniques by capacitor bank employment locally supply VARs needed by the load. Capacitors are highly unreliable components due to their failure modes and aging inherent. Approximately 60% of power electronic devices failure such as voltage-source inverter based static synchronous compensator (STATCOM) is due to the use of aluminum electrolytic DC capacitors. Therefore, a capacitor-less VAR compensation is desired. This dissertation also investigates a STATCOM capacitor-less reactive power compensation that uses only inductors combined with predictive controlled matrix converter.

Machine learning and predictive data analytics enabling metrology and process control in IC fabrication

NASA Astrophysics Data System (ADS)

Rana, Narender; Zhang, Yunlin; Wall, Donald; Dirahoui, Bachir; Bailey, Todd C.

2015-03-01

Integrate circuit (IC) technology is going through multiple changes in terms of patterning techniques (multiple patterning, EUV and DSA), device architectures (FinFET, nanowire, graphene) and patterning scale (few nanometers). These changes require tight controls on processes and measurements to achieve the required device performance, and challenge the metrology and process control in terms of capability and quality. Multivariate data with complex nonlinear trends and correlations generally cannot be described well by mathematical or parametric models but can be relatively easily learned by computing machines and used to predict or extrapolate. This paper introduces the predictive metrology approach which has been applied to three different applications. Machine learning and predictive analytics have been leveraged to accurately predict dimensions of EUV resist patterns down to 18 nm half pitch leveraging resist shrinkage patterns. These patterns could not be directly and accurately measured due to metrology tool limitations. Machine learning has also been applied to predict the electrical performance early in the process pipeline for deep trench capacitance and metal line resistance. As the wafer goes through various processes its associated cost multiplies. It may take days to weeks to get the electrical performance readout. Predicting the electrical performance early on can be very valuable in enabling timely actionable decision such as rework, scrap, feedforward, feedback predicted information or information derived from prediction to improve or monitor processes. This paper provides a general overview of machine learning and advanced analytics application in the advanced semiconductor development and manufacturing.

Hinge Moment Coefficient Prediction Tool and Control Force Analysis of Extra-300 Aerobatic Aircraft

NASA Astrophysics Data System (ADS)

Nurohman, Chandra; Arifianto, Ony; Barecasco, Agra

2018-04-01

This paper presents the development of tool that is applicable to predict hinge moment coefficients of subsonic aircraft based on Roskam’s method, including the validation and its application to predict hinge moment coefficient of an Extra-300. The hinge moment coefficients are used to predict the stick forces of the aircraft during several aerobatic maneuver i.e. inside loop, half cuban 8, split-s, and aileron roll. The maximum longitudinal stick force is 566.97 N occurs in inside loop while the maximum lateral stick force is 340.82 N occurs in aileron roll. Furthermore, validation hinge moment prediction method is performed using Cessna 172 data.

Adaptive adjustment of interval predictive control based on combined model and application in shell brand petroleum distillation tower

NASA Astrophysics Data System (ADS)

Sun, Chao; Zhang, Chunran; Gu, Xinfeng; Liu, Bin

2017-10-01

Constraints of the optimization objective are often unable to be met when predictive control is applied to industrial production process. Then, online predictive controller will not find a feasible solution or a global optimal solution. To solve this problem, based on Back Propagation-Auto Regressive with exogenous inputs (BP-ARX) combined control model, nonlinear programming method is used to discuss the feasibility of constrained predictive control, feasibility decision theorem of the optimization objective is proposed, and the solution method of soft constraint slack variables is given when the optimization objective is not feasible. Based on this, for the interval control requirements of the controlled variables, the slack variables that have been solved are introduced, the adaptive weighted interval predictive control algorithm is proposed, achieving adaptive regulation of the optimization objective and automatically adjust of the infeasible interval range, expanding the scope of the feasible region, and ensuring the feasibility of the interval optimization objective. Finally, feasibility and effectiveness of the algorithm is validated through the simulation comparative experiments.

Sustained sensorimotor control as intermittent decisions about prediction errors: computational framework and application to ground vehicle steering.

PubMed

Markkula, Gustav; Boer, Erwin; Romano, Richard; Merat, Natasha

2018-06-01

A conceptual and computational framework is proposed for modelling of human sensorimotor control and is exemplified for the sensorimotor task of steering a car. The framework emphasises control intermittency and extends on existing models by suggesting that the nervous system implements intermittent control using a combination of (1) motor primitives, (2) prediction of sensory outcomes of motor actions, and (3) evidence accumulation of prediction errors. It is shown that approximate but useful sensory predictions in the intermittent control context can be constructed without detailed forward models, as a superposition of simple prediction primitives, resembling neurobiologically observed corollary discharges. The proposed mathematical framework allows straightforward extension to intermittent behaviour from existing one-dimensional continuous models in the linear control and ecological psychology traditions. Empirical data from a driving simulator are used in model-fitting analyses to test some of the framework's main theoretical predictions: it is shown that human steering control, in routine lane-keeping and in a demanding near-limit task, is better described as a sequence of discrete stepwise control adjustments, than as continuous control. Results on the possible roles of sensory prediction in control adjustment amplitudes, and of evidence accumulation mechanisms in control onset timing, show trends that match the theoretical predictions; these warrant further investigation. The results for the accumulation-based model align with other recent literature, in a possibly converging case against the type of threshold mechanisms that are often assumed in existing models of intermittent control.

Application of linear regression analysis in accuracy assessment of rolling force calculations

NASA Astrophysics Data System (ADS)

Poliak, E. I.; Shim, M. K.; Kim, G. S.; Choo, W. Y.

1998-10-01

Efficient operation of the computational models employed in process control systems require periodical assessment of the accuracy of their predictions. Linear regression is proposed as a tool which allows separate systematic and random prediction errors from those related to measurements. A quantitative characteristic of the model predictive ability is introduced in addition to standard statistical tests for model adequacy. Rolling force calculations are considered as an example for the application. However, the outlined approach can be used to assess the performance of any computational model.

Applied Distributed Model Predictive Control for Energy Efficient Buildings and Ramp Metering

NASA Astrophysics Data System (ADS)

Koehler, Sarah Muraoka

Industrial large-scale control problems present an interesting algorithmic design challenge. A number of controllers must cooperate in real-time on a network of embedded hardware with limited computing power in order to maximize system efficiency while respecting constraints and despite communication delays. Model predictive control (MPC) can automatically synthesize a centralized controller which optimizes an objective function subject to a system model, constraints, and predictions of disturbance. Unfortunately, the computations required by model predictive controllers for large-scale systems often limit its industrial implementation only to medium-scale slow processes. Distributed model predictive control (DMPC) enters the picture as a way to decentralize a large-scale model predictive control problem. The main idea of DMPC is to split the computations required by the MPC problem amongst distributed processors that can compute in parallel and communicate iteratively to find a solution. Some popularly proposed solutions are distributed optimization algorithms such as dual decomposition and the alternating direction method of multipliers (ADMM). However, these algorithms ignore two practical challenges: substantial communication delays present in control systems and also problem non-convexity. This thesis presents two novel and practically effective DMPC algorithms. The first DMPC algorithm is based on a primal-dual active-set method which achieves fast convergence, making it suitable for large-scale control applications which have a large communication delay across its communication network. In particular, this algorithm is suited for MPC problems with a quadratic cost, linear dynamics, forecasted demand, and box constraints. We measure the performance of this algorithm and show that it significantly outperforms both dual decomposition and ADMM in the presence of communication delay. The second DMPC algorithm is based on an inexact interior point method which is suited for nonlinear optimization problems. The parallel computation of the algorithm exploits iterative linear algebra methods for the main linear algebra computations in the algorithm. We show that the splitting of the algorithm is flexible and can thus be applied to various distributed platform configurations. The two proposed algorithms are applied to two main energy and transportation control problems. The first application is energy efficient building control. Buildings represent 40% of energy consumption in the United States. Thus, it is significant to improve the energy efficiency of buildings. The goal is to minimize energy consumption subject to the physics of the building (e.g. heat transfer laws), the constraints of the actuators as well as the desired operating constraints (thermal comfort of the occupants), and heat load on the system. In this thesis, we describe the control systems of forced air building systems in practice. We discuss the "Trim and Respond" algorithm which is a distributed control algorithm that is used in practice, and show that it performs similarly to a one-step explicit DMPC algorithm. Then, we apply the novel distributed primal-dual active-set method and provide extensive numerical results for the building MPC problem. The second main application is the control of ramp metering signals to optimize traffic flow through a freeway system. This application is particularly important since urban congestion has more than doubled in the past few decades. The ramp metering problem is to maximize freeway throughput subject to freeway dynamics (derived from mass conservation), actuation constraints, freeway capacity constraints, and predicted traffic demand. In this thesis, we develop a hybrid model predictive controller for ramp metering that is guaranteed to be persistently feasible and stable. This contrasts to previous work on MPC for ramp metering where such guarantees are absent. We apply a smoothing method to the hybrid model predictive controller and apply the inexact interior point method to this nonlinear non-convex ramp metering problem.

A system identification approach for developing model predictive controllers of antibody quality attributes in cell culture processes

PubMed Central

Schmitt, John; Beller, Justin; Russell, Brian; Quach, Anthony; Hermann, Elizabeth; Lyon, David; Breit, Jeffrey

2017-01-01

As the biopharmaceutical industry evolves to include more diverse protein formats and processes, more robust control of Critical Quality Attributes (CQAs) is needed to maintain processing flexibility without compromising quality. Active control of CQAs has been demonstrated using model predictive control techniques, which allow development of processes which are robust against disturbances associated with raw material variability and other potentially flexible operating conditions. Wide adoption of model predictive control in biopharmaceutical cell culture processes has been hampered, however, in part due to the large amount of data and expertise required to make a predictive model of controlled CQAs, a requirement for model predictive control. Here we developed a highly automated, perfusion apparatus to systematically and efficiently generate predictive models using application of system identification approaches. We successfully created a predictive model of %galactosylation using data obtained by manipulating galactose concentration in the perfusion apparatus in serialized step change experiments. We then demonstrated the use of the model in a model predictive controller in a simulated control scenario to successfully achieve a %galactosylation set point in a simulated fed‐batch culture. The automated model identification approach demonstrated here can potentially be generalized to many CQAs, and could be a more efficient, faster, and highly automated alternative to batch experiments for developing predictive models in cell culture processes, and allow the wider adoption of model predictive control in biopharmaceutical processes. © 2017 The Authors Biotechnology Progress published by Wiley Periodicals, Inc. on behalf of American Institute of Chemical Engineers Biotechnol. Prog., 33:1647–1661, 2017 PMID:28786215

Image processing system performance prediction and product quality evaluation

NASA Technical Reports Server (NTRS)

Stein, E. K.; Hammill, H. B. (Principal Investigator)

1976-01-01

The author has identified the following significant results. A new technique for image processing system performance prediction and product quality evaluation was developed. It was entirely objective, quantitative, and general, and should prove useful in system design and quality control. The technique and its application to determination of quality control procedures for the Earth Resources Technology Satellite NASA Data Processing Facility are described.

Bayesian modeling of flexible cognitive control

PubMed Central

Jiang, Jiefeng; Heller, Katherine; Egner, Tobias

2014-01-01

“Cognitive control” describes endogenous guidance of behavior in situations where routine stimulus-response associations are suboptimal for achieving a desired goal. The computational and neural mechanisms underlying this capacity remain poorly understood. We examine recent advances stemming from the application of a Bayesian learner perspective that provides optimal prediction for control processes. In reviewing the application of Bayesian models to cognitive control, we note that an important limitation in current models is a lack of a plausible mechanism for the flexible adjustment of control over conflict levels changing at varying temporal scales. We then show that flexible cognitive control can be achieved by a Bayesian model with a volatility-driven learning mechanism that modulates dynamically the relative dependence on recent and remote experiences in its prediction of future control demand. We conclude that the emergent Bayesian perspective on computational mechanisms of cognitive control holds considerable promise, especially if future studies can identify neural substrates of the variables encoded by these models, and determine the nature (Bayesian or otherwise) of their neural implementation. PMID:24929218

Quality Control Analysis of Selected Aspects of Programs Administered by the Bureau of Student Financial Assistance. Error-Prone Model Derived from 1978-1979 Quality Control Study. Data Report. [Task 3.

ERIC Educational Resources Information Center

Saavedra, Pedro; Kuchak, JoAnn

An error-prone model (EPM) to predict financial aid applicants who are likely to misreport on Basic Educational Opportunity Grant (BEOG) applications was developed, based on interviews conducted with a quality control sample of 1,791 students during 1978-1979. The model was designed to identify corrective methods appropriate for different types of…

TSAFE Interface Control Document v 2.0

NASA Technical Reports Server (NTRS)

Paielli, Russell A.; Bach, Ralph E.

2013-01-01

This document specifies the data interface for TSAFE, the Tactical Separation-Assured Flight Environment. TSAFE is a research prototype of a software application program for alerting air traffic controllers to imminent conflicts in enroute airspace. It is intended for Air Route Traffic Control Centers ("Centers") in the U.S. National Airspace System. It predicts trajectories for approximately 3 minutes into the future, searches for conflicts, and sends data about predicted conflicts to the client, which uses the data to alert an air traffic controller of conflicts. TSAFE itself does not provide a graphical user interface.

Diagnostic Inaccuracy of Smart Phone Applications for Melanoma Detection

PubMed Central

Wolf, Joel; Moreau, Jacqui; Akilov, Oleg; Patton, Timothy; English, Joseph C; Ho, Jon; Ferris, Laura Korb

2013-01-01

Objective To measure the performance of smart phone applications which evaluate photographs of skin lesions and provide the user feedback as to their likelihood of malignancy. Design Case-control diagnostic accuracy study Setting Academic dermatology department Participants Digital clinical images of pigmented cutaneous lesions (60 melanoma cases and 128 benign lesion controls), all with histologic diagnosis rendered by a board-certified dermatopathologist, obtained prior to biopsy in patients undergoing lesion removal as part of routine care. Main Outcome Measures Sensitivity, specificity, and positive and negative predictive values of four smart phone applications designed to aid non-clinician users in determining if their skin lesion is benign or malignant. Results Sensitivity of the four tested applications ranged from 6.8% to 98.1%. Specificity ranged from 30.4% to 93.7%. Positive predictive value ranged from 33.3% to 42.1%, and negative predictive value ranged from 65.4% to 97.0%. The highest sensitivity for melanoma diagnosis was observed for an application that sends the image directly to a board-certified dermatologist for analysis and the lowest sensitivity was observed for applications that use automated algorithms to analyze images. Conclusions The performance of smart phone applications in assessing melanoma risk is highly variable, and 3 out of 4 smart phone applications incorrectly classified 30% or more of melanomas as unconcerning. Reliance on these applications, which are not subject to regulatory oversight, in lieu of medical consultation, has the potential to delay the diagnosis of melanoma and to harm users. PMID:23325302

UV254 absorbance as real-time monitoring and control parameter for micropollutant removal in advanced wastewater treatment with powdered activated carbon.

PubMed

Altmann, Johannes; Massa, Lukas; Sperlich, Alexander; Gnirss, Regina; Jekel, Martin

2016-05-01

This study investigates the applicability of UV absorbance measurements at 254 nm (UVA254) to serve as a simple and reliable surrogate parameter to monitor and control the removal of organic micropollutants (OMPs) in advanced wastewater treatment applying powdered activated carbon (PAC). Correlations between OMP removal and corresponding UVA254 reduction were determined in lab-scale adsorption batch tests and successfully applied to a pilot-scale PAC treatment stage to predict OMP removals in aggregate samples with good accuracy. Real-time UVA254 measurements were utilized to evaluate adapted PAC dosing strategies and proved to be effective for online monitoring of OMP removal. Furthermore, active PAC dosing control according to differential UVA254 measurements was implemented and tested. While precise removal predictions based on real-time measurements were not accurate for all OMPs, UVA254-controlled dynamic PAC dosing was capable of achieving stable OMP removals. UVA254 can serve as an effective surrogate parameter for OMP removal in technical PAC applications. Even though the applicability as control parameter to adjust PAC dosing to water quality changes might be limited to applications with fast response between PAC adjustment and adsorptive removal (e.g. direct filtration), UVA254 measurements can also be used to monitor the adsorption efficiency in more complex PAC applications. Copyright © 2016 Elsevier Ltd. All rights reserved.

Computational Prediction of the Global Functional Genomic Landscape: Applications, Methods and Challenges

PubMed Central

Zhou, Weiqiang; Sherwood, Ben; Ji, Hongkai

2017-01-01

Technological advances have led to an explosive growth of high-throughput functional genomic data. Exploiting the correlation among different data types, it is possible to predict one functional genomic data type from other data types. Prediction tools are valuable in understanding the relationship among different functional genomic signals. They also provide a cost-efficient solution to inferring the unknown functional genomic profiles when experimental data are unavailable due to resource or technological constraints. The predicted data may be used for generating hypotheses, prioritizing targets, interpreting disease variants, facilitating data integration, quality control, and many other purposes. This article reviews various applications of prediction methods in functional genomics, discusses analytical challenges, and highlights some common and effective strategies used to develop prediction methods for functional genomic data. PMID:28076869

Computational Modeling in Concert with Laboratory Studies: Application to B Cell Differentiation

EPA Science Inventory

Remediation is expensive, so accurate prediction of dose-response is important to help control costs. Dose response is a function of biological mechanisms. Computational models of these mechanisms improve the efficiency of research and provide the capability for prediction.

Active control strategy for the running attitude of high-speed train under strong crosswind condition

NASA Astrophysics Data System (ADS)

Li, Decang; Meng, Jianjun; Bai, Huan; Xu, Ruxun

2018-07-01

This paper focuses on the safety of high-speed trains under strong crosswind conditions. A new active control strategy is proposed based on the adaptive predictive control theory. The new control strategy aims at adjusting the attitudes of a train by controlling the new-type intelligent giant magnetostrictive actuator (GMA). It combined adaptive control with dynamic matrix control; parameters of predictive controller was real-time adjusted by online distinguishing to enhance the robustness of the control algorithm. On this basis, a correction control algorithm is also designed to regulate the parameters of predictive controller based on the step response of a controlled objective. Finally, the simulation results show that the proposed control strategy can adjust the running attitudes of high-speed trains under strong crosswind conditions; they also indicate that the new active control strategy is effective and applicable in improving the safety performance of a train based on a host-target computer technology provided by Matlab/Simulink.

Generating optimal control simulations of musculoskeletal movement using OpenSim and MATLAB.

PubMed

Lee, Leng-Feng; Umberger, Brian R

2016-01-01

Computer modeling, simulation and optimization are powerful tools that have seen increased use in biomechanics research. Dynamic optimizations can be categorized as either data-tracking or predictive problems. The data-tracking approach has been used extensively to address human movement problems of clinical relevance. The predictive approach also holds great promise, but has seen limited use in clinical applications. Enhanced software tools would facilitate the application of predictive musculoskeletal simulations to clinically-relevant research. The open-source software OpenSim provides tools for generating tracking simulations but not predictive simulations. However, OpenSim includes an extensive application programming interface that permits extending its capabilities with scripting languages such as MATLAB. In the work presented here, we combine the computational tools provided by MATLAB with the musculoskeletal modeling capabilities of OpenSim to create a framework for generating predictive simulations of musculoskeletal movement based on direct collocation optimal control techniques. In many cases, the direct collocation approach can be used to solve optimal control problems considerably faster than traditional shooting methods. Cyclical and discrete movement problems were solved using a simple 1 degree of freedom musculoskeletal model and a model of the human lower limb, respectively. The problems could be solved in reasonable amounts of time (several seconds to 1-2 hours) using the open-source IPOPT solver. The problems could also be solved using the fmincon solver that is included with MATLAB, but the computation times were excessively long for all but the smallest of problems. The performance advantage for IPOPT was derived primarily by exploiting sparsity in the constraints Jacobian. The framework presented here provides a powerful and flexible approach for generating optimal control simulations of musculoskeletal movement using OpenSim and MATLAB. This should allow researchers to more readily use predictive simulation as a tool to address clinical conditions that limit human mobility.

Generating optimal control simulations of musculoskeletal movement using OpenSim and MATLAB

PubMed Central

Lee, Leng-Feng

2016-01-01

Computer modeling, simulation and optimization are powerful tools that have seen increased use in biomechanics research. Dynamic optimizations can be categorized as either data-tracking or predictive problems. The data-tracking approach has been used extensively to address human movement problems of clinical relevance. The predictive approach also holds great promise, but has seen limited use in clinical applications. Enhanced software tools would facilitate the application of predictive musculoskeletal simulations to clinically-relevant research. The open-source software OpenSim provides tools for generating tracking simulations but not predictive simulations. However, OpenSim includes an extensive application programming interface that permits extending its capabilities with scripting languages such as MATLAB. In the work presented here, we combine the computational tools provided by MATLAB with the musculoskeletal modeling capabilities of OpenSim to create a framework for generating predictive simulations of musculoskeletal movement based on direct collocation optimal control techniques. In many cases, the direct collocation approach can be used to solve optimal control problems considerably faster than traditional shooting methods. Cyclical and discrete movement problems were solved using a simple 1 degree of freedom musculoskeletal model and a model of the human lower limb, respectively. The problems could be solved in reasonable amounts of time (several seconds to 1–2 hours) using the open-source IPOPT solver. The problems could also be solved using the fmincon solver that is included with MATLAB, but the computation times were excessively long for all but the smallest of problems. The performance advantage for IPOPT was derived primarily by exploiting sparsity in the constraints Jacobian. The framework presented here provides a powerful and flexible approach for generating optimal control simulations of musculoskeletal movement using OpenSim and MATLAB. This should allow researchers to more readily use predictive simulation as a tool to address clinical conditions that limit human mobility. PMID:26835184

A system identification approach for developing model predictive controllers of antibody quality attributes in cell culture processes.

PubMed

Downey, Brandon; Schmitt, John; Beller, Justin; Russell, Brian; Quach, Anthony; Hermann, Elizabeth; Lyon, David; Breit, Jeffrey

2017-11-01

As the biopharmaceutical industry evolves to include more diverse protein formats and processes, more robust control of Critical Quality Attributes (CQAs) is needed to maintain processing flexibility without compromising quality. Active control of CQAs has been demonstrated using model predictive control techniques, which allow development of processes which are robust against disturbances associated with raw material variability and other potentially flexible operating conditions. Wide adoption of model predictive control in biopharmaceutical cell culture processes has been hampered, however, in part due to the large amount of data and expertise required to make a predictive model of controlled CQAs, a requirement for model predictive control. Here we developed a highly automated, perfusion apparatus to systematically and efficiently generate predictive models using application of system identification approaches. We successfully created a predictive model of %galactosylation using data obtained by manipulating galactose concentration in the perfusion apparatus in serialized step change experiments. We then demonstrated the use of the model in a model predictive controller in a simulated control scenario to successfully achieve a %galactosylation set point in a simulated fed-batch culture. The automated model identification approach demonstrated here can potentially be generalized to many CQAs, and could be a more efficient, faster, and highly automated alternative to batch experiments for developing predictive models in cell culture processes, and allow the wider adoption of model predictive control in biopharmaceutical processes. © 2017 The Authors Biotechnology Progress published by Wiley Periodicals, Inc. on behalf of American Institute of Chemical Engineers Biotechnol. Prog., 33:1647-1661, 2017. © 2017 The Authors Biotechnology Progress published by Wiley Periodicals, Inc. on behalf of American Institute of Chemical Engineers.

A Two-Time Scale Decentralized Model Predictive Controller Based on Input and Output Model

PubMed Central

Niu, Jian; Zhao, Jun; Xu, Zuhua; Qian, Jixin

2009-01-01

A decentralized model predictive controller applicable for some systems which exhibit different dynamic characteristics in different channels was presented in this paper. These systems can be regarded as combinations of a fast model and a slow model, the response speeds of which are in two-time scale. Because most practical models used for control are obtained in the form of transfer function matrix by plant tests, a singular perturbation method was firstly used to separate the original transfer function matrix into two models in two-time scale. Then a decentralized model predictive controller was designed based on the two models derived from the original system. And the stability of the control method was proved. Simulations showed that the method was effective. PMID:19834542

Modelling and model predictive control for a bicycle-rider system

NASA Astrophysics Data System (ADS)

Chu, T. D.; Chen, C. K.

2018-01-01

This study proposes a bicycle-rider control model based on model predictive control (MPC). First, a bicycle-rider model with leaning motion of the rider's upper body is developed. The initial simulation data of the bicycle rider are then used to identify the linear model of the system in state-space form for MPC design. Control characteristics of the proposed controller are assessed by simulating the roll-angle tracking control. In this riding task, the MPC uses steering and leaning torques as the control inputs to control the bicycle along a reference roll angle. The simulation results in different cases have demonstrated the applicability and performance of the MPC for bicycle-rider modelling.

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

Smith, Kandler; Shi, Ying; Santhanagopalan, Shriram

Predictive models of Li-ion battery lifetime must consider a multiplicity of electrochemical, thermal, and mechanical degradation modes experienced by batteries in application environments. To complicate matters, Li-ion batteries can experience different degradation trajectories that depend on storage and cycling history of the application environment. Rates of degradation are controlled by factors such as temperature history, electrochemical operating window, and charge/discharge rate. We present a generalized battery life prognostic model framework for battery systems design and control. The model framework consists of trial functions that are statistically regressed to Li-ion cell life datasets wherein the cells have been aged under differentmore » levels of stress. Degradation mechanisms and rate laws dependent on temperature, storage, and cycling condition are regressed to the data, with multiple model hypotheses evaluated and the best model down-selected based on statistics. The resulting life prognostic model, implemented in state variable form, is extensible to arbitrary real-world scenarios. The model is applicable in real-time control algorithms to maximize battery life and performance. We discuss efforts to reduce lifetime prediction error and accommodate its inevitable impact in controller design.« less

Fuzzy logic and neural network technologies

NASA Technical Reports Server (NTRS)

Villarreal, James A.; Lea, Robert N.; Savely, Robert T.

1992-01-01

Applications of fuzzy logic technologies in NASA projects are reviewed to examine their advantages in the development of neural networks for aerospace and commercial expert systems and control. Examples of fuzzy-logic applications include a 6-DOF spacecraft controller, collision-avoidance systems, and reinforcement-learning techniques. The commercial applications examined include a fuzzy autofocusing system, an air conditioning system, and an automobile transmission application. The practical use of fuzzy logic is set in the theoretical context of artificial neural systems (ANSs) to give the background for an overview of ANS research programs at NASA. The research and application programs include the Network Execution and Training Simulator and faster training algorithms such as the Difference Optimized Training Scheme. The networks are well suited for pattern-recognition applications such as predicting sunspots, controlling posture maintenance, and conducting adaptive diagnoses.

Prediction of force and acceleration control spectra for Space Shuttle orbiter sidewall-mounted payloads

NASA Technical Reports Server (NTRS)

Hipol, Philip J.

1990-01-01

The development of force and acceleration control spectra for vibration testing of Space Shuttle (STS) orbiter sidewall-mounted payloads requiresreliable estimates of the sidewall apparent weight and free (i.e. unloaded) vibration during lift-off. The feasibility of analytically predicting these quantities has been investigated through the development and analysis of a finite element model of the STS cargo bay. Analytical predictions of the sidewall apparent weight were compared with apparent weight measurements made on OV-101, and analytical predictions of the sidewall free vibration response during lift-off were compared with flight measurements obtained from STS-3 and STS-4. These analysis suggest that the cargo bay finite element model has potential application for the estimation of force and acceleration control spectra for STS sidewall-mounted payloads.

Comparisons of Predictions of the XB-70-1 Longitudinal Stability and Control Derivatives with Flight Results for Six Flight Conditions

NASA Technical Reports Server (NTRS)

Wolowicz, C. H.; Yancey, R. B.

1973-01-01

Preliminary correlations of flight-determined and predicted stability and control characteristics of the XB-70-1 reported in NASA TN D-4578 were subject to uncertainties in several areas which necessitated a review of prediction techniques particularly for the longitudinal characteristics. Reevaluation and updating of the original predictions, including aeroelastic corrections, for six specific flight-test conditions resulted in improved correlations of static pitch stability with flight data. The original predictions for the pitch-damping derivative, on the other hand, showed better correlation with flight data than the updated predictions. It appears that additional study is required in the application of aeroelastic corrections to rigid model wind-tunnel data and the theoretical determination of dynamic derivatives for this class of aircraft.

Model Predictive Control application for real time operation of controlled structures for the Water Authority Noorderzijlvest, The Netherlands

NASA Astrophysics Data System (ADS)

van Heeringen, Klaas-Jan; Gooijer, Jan; Knot, Floris; Talsma, Jan

2015-04-01

In the Netherlands, flood protection has always been a key issue to protect settlements against storm surges and riverine floods. Whereas flood protection traditionally focused on structural measures, nowadays the availability of meteorological and hydrological forecasts enable the application of more advanced real-time control techniques for operating the existing hydraulic infrastructure in an anticipatory and more efficient way. Model Predictive Control (MPC) is a powerful technique to derive optimal control variables with the help of model based predictions evaluated against a control objective. In a project for the regional water authority Noorderzijlvest in the north of the Netherlands, it has been shown that MPC can increase the safety level of the system during flood events by an anticipatory pre-release of water. Furthermore, energy costs of pumps can be reduced by making tactical use of the water storage and shifting pump activities during normal operating conditions to off-peak hours. In this way cheap energy is used in combination of gravity flow through gates during low tide periods. MPC has now been implemented for daily operational use of the whole water system of the water authority Noorderzijlvest. The system developed to a real time decision support system which not only supports the daily operation but is able to directly implement the optimal control settings at the structures. We explain how we set-up and calibrated a prediction model (RTC-Tools) that is accurate and fast enough for optimization purposes, and how we integrated it in the operational flood early warning system (Delft-FEWS). Beside the prediction model, the weights and the factors of the objective function are an important element of MPC, since they shape the control objective. We developed special features in Delft-FEWS to allow the operators to adjust the objective function in order to meet changing requirements and to evaluate different control strategies.

Real-time Adaptive Control Using Neural Generalized Predictive Control

NASA Technical Reports Server (NTRS)

Haley, Pam; Soloway, Don; Gold, Brian

1999-01-01

The objective of this paper is to demonstrate the feasibility of a Nonlinear Generalized Predictive Control algorithm by showing real-time adaptive control on a plant with relatively fast time-constants. Generalized Predictive Control has classically been used in process control where linear control laws were formulated for plants with relatively slow time-constants. The plant of interest for this paper is a magnetic levitation device that is nonlinear and open-loop unstable. In this application, the reference model of the plant is a neural network that has an embedded nominal linear model in the network weights. The control based on the linear model provides initial stability at the beginning of network training. In using a neural network the control laws are nonlinear and online adaptation of the model is possible to capture unmodeled or time-varying dynamics. Newton-Raphson is the minimization algorithm. Newton-Raphson requires the calculation of the Hessian, but even with this computational expense the low iteration rate make this a viable algorithm for real-time control.

Machine learning classification with confidence: application of transductive conformal predictors to MRI-based diagnostic and prognostic markers in depression.

PubMed

Nouretdinov, Ilia; Costafreda, Sergi G; Gammerman, Alexander; Chervonenkis, Alexey; Vovk, Vladimir; Vapnik, Vladimir; Fu, Cynthia H Y

2011-05-15

There is rapidly accumulating evidence that the application of machine learning classification to neuroimaging measurements may be valuable for the development of diagnostic and prognostic prediction tools in psychiatry. However, current methods do not produce a measure of the reliability of the predictions. Knowing the risk of the error associated with a given prediction is essential for the development of neuroimaging-based clinical tools. We propose a general probabilistic classification method to produce measures of confidence for magnetic resonance imaging (MRI) data. We describe the application of transductive conformal predictor (TCP) to MRI images. TCP generates the most likely prediction and a valid measure of confidence, as well as the set of all possible predictions for a given confidence level. We present the theoretical motivation for TCP, and we have applied TCP to structural and functional MRI data in patients and healthy controls to investigate diagnostic and prognostic prediction in depression. We verify that TCP predictions are as accurate as those obtained with more standard machine learning methods, such as support vector machine, while providing the additional benefit of a valid measure of confidence for each prediction. Copyright © 2010 Elsevier Inc. All rights reserved.

Cell Fate Reprogramming by Control of Intracellular Network Dynamics

PubMed Central

Zañudo, Jorge G. T.; Albert, Réka

2015-01-01

Identifying control strategies for biological networks is paramount for practical applications that involve reprogramming a cell’s fate, such as disease therapeutics and stem cell reprogramming. Here we develop a novel network control framework that integrates the structural and functional information available for intracellular networks to predict control targets. Formulated in a logical dynamic scheme, our approach drives any initial state to the target state with 100% effectiveness and needs to be applied only transiently for the network to reach and stay in the desired state. We illustrate our method’s potential to find intervention targets for cancer treatment and cell differentiation by applying it to a leukemia signaling network and to the network controlling the differentiation of helper T cells. We find that the predicted control targets are effective in a broad dynamic framework. Moreover, several of the predicted interventions are supported by experiments. PMID:25849586

On Application of Model Predictive Control to Power Converter with Switching

NASA Astrophysics Data System (ADS)

Zanma, Tadanao; Fukuta, Junichi; Doki, Shinji; Ishida, Muneaki; Okuma, Shigeru; Matsumoto, Takashi; Nishimori, Eiji

This paper concerns a DC-DC converter control. In DC-DC converters, there exist both continuous components such as inductance, conductance and resistance and discrete ones, IGBT and MOSFET as semiconductor switching elements. Such a system can be regarded as a hybrid dynamical system. Thus, this paper presents a dc-dc control technique based on the model predictive control. Specifically, a case in which the load of the dc-dc converter changes from active to sleep is considered. In the case, a control method which makes the output voltage follow to the reference quickly in transition, and the switching frequency be constant in steady state. In addition, in applying the model predictive control to power electronics circuits, the switching characteristic of the device and the restriction condition for protection are also considered. The effectiveness of the proposed method is illustrated by comparing a conventional method through some simulation results.

Control of Boundary Layers for Aero-optical Applications

DTIC Science & Technology

2015-06-23

range of subsonic and supersonic Mach numbers was developed and shown to correctly predict experimentally-observed reductions. Heating the wall allows...40 3.3 Extension to supersonic speeds...boundary layers at supersonic speeds. Comparing the model prediction to the experimental results, it was speculated that while the pressure effects can

An intelligent system with EMG-based joint angle estimation for telemanipulation.

PubMed

Suryanarayanan, S; Reddy, N P; Gupta, V

1996-01-01

Bio-control of telemanipulators is being researched as an alternate control strategy. This study investigates the use of surface EMG from the biceps to predict joint angle during flexion of the arm that can be used to control an anthropomorphic telemanipulator. An intelligent system based on neural networks and fuzzy logic has been developed to use the processed surface EMG signal and predict the joint angle. The system has been tested on various angles of flexion-extension of the arm and at several speeds of flexion-extension. Preliminary results show the RMS error between the predicted angle and the actual angle to be less than 3% during training and less than 15% during testing. The technique of direct bio-control using EMG has the potential as an interface for telemanipulation applications.

Application of color to reduce complexity in air traffic control.

DOT National Transportation Integrated Search

2002-11-01

The United States Air Traffic Control (ATC) system is designed to provide for the safe and efficient flow of air : traffic from origin to destination. The Federal Aviation Administration predicts that traffic levels will continue : increasing over th...

[Transmission dynamic model for echinococcosis granulosus: establishment and application].

PubMed

Yang, Shi-Jie; Wu, Wei-Ping

2009-06-01

A dynamic model of disease can be used to quantitatively describe the pattern and characteristics of disease transmission, predict the disease status and evaluate the efficacy of control strategy. This review summarizes the basic transmission dynamic models of echinococcosis granulosus and their application.

A Wavelet Neural Network Optimal Control Model for Traffic-Flow Prediction in Intelligent Transport Systems

NASA Astrophysics Data System (ADS)

Huang, Darong; Bai, Xing-Rong

Based on wavelet transform and neural network theory, a traffic-flow prediction model, which was used in optimal control of Intelligent Traffic system, is constructed. First of all, we have extracted the scale coefficient and wavelet coefficient from the online measured raw data of traffic flow via wavelet transform; Secondly, an Artificial Neural Network model of Traffic-flow Prediction was constructed and trained using the coefficient sequences as inputs and raw data as outputs; Simultaneous, we have designed the running principium of the optimal control system of traffic-flow Forecasting model, the network topological structure and the data transmitted model; Finally, a simulated example has shown that the technique is effectively and exactly. The theoretical results indicated that the wavelet neural network prediction model and algorithms have a broad prospect for practical application.

A Study on Predictive Analytics Application to Ship Machinery Maintenance

DTIC Science & Technology

2013-09-01

Looking at the nature of the time series forecasting method , it would be better applied to offline analysis . The application for real- time online...other system attributes in future. Two techniques of statistical analysis , mainly time series models and cumulative sum control charts, are discussed in...statistical tool employed for the two techniques of statistical analysis . Both time series forecasting as well as CUSUM control charts are shown to be

Validity of the MicroDYN Approach: Complex Problem Solving Predicts School Grades beyond Working Memory Capacity

ERIC Educational Resources Information Center

Schweizer, Fabian; Wustenberg, Sascha; Greiff, Samuel

2013-01-01

This study examines the validity of the complex problem solving (CPS) test MicroDYN by investigating a) the relation between its dimensions--rule identification (exploration strategy), rule knowledge (acquired knowledge), rule application (control performance)--and working memory capacity (WMC), and b) whether CPS predicts school grades in…

Predicting Intended and Self-perceived Sugar Restriction among Tanzanian Students using the Theory of Planned Behavior.

PubMed

Masalu, J R; Astrøm, A N

2001-07-01

This study examines the applicability and sufficiency of the Theory of Planned Behavior (TPB) in predicting intention and self-perceived behavior with respect to avoiding between-meal intake of sugared snacks and drinks. One thousand one hundred and twenty-three Tanzanian students (mean age 26.4 years) completed self-administered questionnaires designed to measure the components of the TPB during May-July, 1999. Self-perceived sugar consumption was obtained in a subsample of respondents (n = 228) four weeks later. The TPB provided a significant prediction of intention (R(2)= 0.44), with attitude (= 0.25), subjective norms (= 0.28) and perceived behavioral control (= 0.35) significant, and subsequent behavior (R(2) = 0.15, with intention (= 0.25) and perceived behavioral control (= 0.18) significant. Frequency of past behavior explained a significant, albeit small, amount of additional variance in intention (1 percent) and behavior (4 percent). The results indicate that the TPB is applicable to the prediction of food choice-related intention and behavior among young adult students living in a non-occidental setting.

Model predictive and reallocation problem for CubeSat fault recovery and attitude control

NASA Astrophysics Data System (ADS)

Franchi, Loris; Feruglio, Lorenzo; Mozzillo, Raffaele; Corpino, Sabrina

2018-01-01

In recent years, thanks to the increase of the know-how on machine-learning techniques and the advance of the computational capabilities of on-board processing, expensive computing algorithms, such as Model Predictive Control, have begun to spread in space applications even on small on-board processor. The paper presents an algorithm for an optimal fault recovery of a 3U CubeSat, developed in MathWorks Matlab & Simulink environment. This algorithm involves optimization techniques aiming at obtaining the optimal recovery solution, and involves a Model Predictive Control approach for the attitude control. The simulated system is a CubeSat in Low Earth Orbit: the attitude control is performed with three magnetic torquers and a single reaction wheel. The simulation neglects the errors in the attitude determination of the satellite, and focuses on the recovery approach and control method. The optimal recovery approach takes advantage of the properties of magnetic actuation, which gives the possibility of the redistribution of the control action when a fault occurs on a single magnetic torquer, even in absence of redundant actuators. In addition, the paper presents the results of the implementation of Model Predictive approach to control the attitude of the satellite.

Prediction of circulation control performance characteristics for Super STOL and STOL applications

NASA Astrophysics Data System (ADS)

Naqvi, Messam Abbas

The rapid air travel growth during the last three decades, has resulted in runway congestion at major airports. The current airports infrastructure will not be able to support the rapid growth trends expected in the next decade. Changes or upgrades in infrastructure alone would not be able to satisfy the growth requirements, and new airplane concepts such as the NASA proposed Super Short Takeoff and Landing and Extremely Short Takeoff & Landing (ESTOL) are being vigorously pursued. Aircraft noise pollution during Takeoff & Landing is another serious concern and efforts are aimed to reduce the airframe noise produced by Conventional High Lift Devices during Takeoff & Landing. Circulation control technology has the prospect of being a good alternative to resolve both the aforesaid issues. Circulation control airfoils are not only capable of producing very high values of lift (Cl values in excess of 8.0) at zero degree angle of attack, but also eliminate the noise generated by the conventional high lift devices and their associated weight penalty as well as their complex operation and storage. This will ensure not only satisfying the small takeoff and landing distances, but minimal acoustic signature in accordance with FAA requirements. The Circulation Control relies on the tendency of an emanating wall jet to independently control the circulation and lift on an airfoil. Unlike, conventional airfoil where rear stagnation point is located at the sharp trailing edge, circulation control airfoils possess a round trailing edge, therefore the rear stagnation point is free to move. The location of rear stagnation point is controlled by the blown jet momentum. This provides a secondary control in the form of jet momentum with which the lift generated can be controlled rather the only available control of incidence (angle of attack) in case of conventional airfoils. The use of Circulation control despite its promising potential has been limited only to research applications due to the lack of a simple prediction capability. This research effort was focused on the creation of a rapid prediction capability of Circulation Control Aerodynamic Characteristics which could help designers with rapid performance estimates for design space exploration. A morphological matrix was created with the available set of options which could be chosen to create this prediction capability starting with purely analytical physics based modeling to high fidelity CFD codes. Based on the available constraints, and desired accuracy meta-models have been created around the two dimensional circulation control performance results computed using Navier Stokes Equations (Computational Fluid Dynamics). DSS2, a two dimensional RANS code written by Professor Lakshmi Sankar was utilized for circulation control airfoil characteristics. The CFD code was first applied to the NCCR 1510-7607N airfoil to validate the model with available experimental results. It was then applied to compute the results of a fractional factorial design of experiments array. Metamodels were formulated using the neural networks to the results obtained from the Design of Experiments. Additional validation runs were performed to validate the model predictions. Metamodels are not only capable of rapid performance prediction, but also help generate the relation trends of response matrices with control variables and capture the complex interactions between control variables. Quantitative as well as qualitative assessments of results were performed by computation of aerodynamic forces & moments and flow field visualizations. Wing characteristics in three dimensions were obtained by integration over the whole wing using Prandtl's Wing Theory. The baseline Super STOL configuration [3] was then analyzed with the application of circulation control technology. The desired values of lift and drag to achieve the target values of Takeoff & Landing performance were compared with the optimal configurations obtained by the model. The same optimal configurations were then subjected to Super STOL cruise conditions to perform a trade off analysis between Takeoff and Cruise Performance. Supercritical airfoils modified for circulation control were also thoroughly analyzed for Takeoff and Cruise performance and may constitute a viable option for Super STOL & STOL Designs. The prediction capability produced by this research effort can be integrated with the current conceptual aircraft modeling & simulation framework. The prediction tool is applicable within the selected ranges of each variable, but methodology and formulation scheme adopted can be applied to any other design space exploration.

Neural network applications in telecommunications

NASA Technical Reports Server (NTRS)

Alspector, Joshua

1994-01-01

Neural network capabilities include automatic and organized handling of complex information, quick adaptation to continuously changing environments, nonlinear modeling, and parallel implementation. This viewgraph presentation presents Bellcore work on applications, learning chip computational function, learning system block diagram, neural network equalization, broadband access control, calling-card fraud detection, software reliability prediction, and conclusions.

Predictive IP controller for robust position control of linear servo system.

PubMed

Lu, Shaowu; Zhou, Fengxing; Ma, Yajie; Tang, Xiaoqi

2016-07-01

Position control is a typical application of linear servo system. In this paper, to reduce the system overshoot, an integral plus proportional (IP) controller is used in the position control implementation. To further improve the control performance, a gain-tuning IP controller based on a generalized predictive control (GPC) law is proposed. Firstly, to represent the dynamics of the position loop, a second-order linear model is used and its model parameters are estimated on-line by using a recursive least squares method. Secondly, based on the GPC law, an optimal control sequence is obtained by using receding horizon, then directly supplies the IP controller with the corresponding control parameters in the real operations. Finally, simulation and experimental results are presented to show the efficiency of proposed scheme. Copyright © 2016 ISA. Published by Elsevier Ltd. All rights reserved.

On the importance of identifying, characterizing, and predicting fundamental phenomena towards microbial electrochemistry applications.

PubMed

Torres, César Iván

2014-06-01

The development of microbial electrochemistry research toward technological applications has increased significantly in the past years, leading to many process configurations. This short review focuses on the need to identify and characterize the fundamental phenomena that control the performance of microbial electrochemical cells (MXCs). Specifically, it discusses the importance of recent efforts to discover and characterize novel microorganisms for MXC applications, as well as recent developments to understand transport limitations in MXCs. As we increase our understanding of how MXCs operate, it is imperative to continue modeling efforts in order to effectively predict their performance, design efficient MXC technologies, and implement them commercially. Thus, the success of MXC technologies largely depends on the path of identifying, understanding, and predicting fundamental phenomena that determine MXC performance. Copyright © 2013 Elsevier Ltd. All rights reserved.

Efficacy of predictive wavefront control for compensating aero-optical aberrations

NASA Astrophysics Data System (ADS)

Goorskey, David J.; Schmidt, Jason; Whiteley, Matthew R.

2013-07-01

Imaging and laser beam propagation from airborne platforms are degraded by dynamic aberrations due to air flow around the aircraft, aero-mechanical distortions and jitter, and free atmospheric turbulence. For certain applications, like dim-object imaging, free-space optical communications, and laser weapons, adaptive optics (AO) is necessary to compensate for the aberrations in real time. Aero-optical flow is a particularly interesting source of aberrations whose flowing structures can be exploited by adaptive and predictive AO controllers, thereby realizing significant performance gains. We analyze dynamic aero-optical wavefronts to determine the pointing angles at which predictive wavefront control is more effective than conventional, fixed-gain, linear-filter control. It was found that properties of the spatial decompositions and temporal statistics of the wavefronts are directly traceable to specific features in the air flow. Furthermore, the aero-optical wavefront aberrations at the side- and aft-looking angles were the most severe, but they also benefited the most from predictive AO.

Network control principles predict neuron function in the Caenorhabditis elegans connectome

PubMed Central

Chew, Yee Lian; Walker, Denise S.; Schafer, William R.; Barabási, Albert-László

2017-01-01

Recent studies on the controllability of complex systems offer a powerful mathematical framework to systematically explore the structure-function relationship in biological, social and technological networks1–3. Despite theoretical advances, we lack direct experimental proof of the validity of these widely used control principles. Here we fill this gap by applying a control framework to the connectome of the nematode C. elegans4–6, allowing us to predict the involvement of each C. elegans neuron in locomotor behaviours. We predict that control of the muscles or motor neurons requires twelve neuronal classes, which include neuronal groups previously implicated in locomotion by laser ablation7–13, as well as one previously uncharacterised neuron, PDB. We validate this prediction experimentally, finding that the ablation of PDB leads to a significant loss of dorsoventral polarity in large body bends. Importantly, control principles also allow us to investigate the involvement of individual neurons within each neuronal class. For example, we predict that, within the class of DD motor neurons, only three (DD04, DD05, or DD06) should affect locomotion when ablated individually. This prediction is also confirmed, with single-cell ablations of DD04 or DD05, but not DD02 or DD03, specifically affecting posterior body movements. Our predictions are robust to deletions of weak connections, missing connections, and rewired connections in the current connectome, indicating the potential applicability of this analytical framework to larger and less well-characterised connectomes. PMID:29045391

Network control principles predict neuron function in the Caenorhabditis elegans connectome

NASA Astrophysics Data System (ADS)

Yan, Gang; Vértes, Petra E.; Towlson, Emma K.; Chew, Yee Lian; Walker, Denise S.; Schafer, William R.; Barabási, Albert-László

2017-10-01

Recent studies on the controllability of complex systems offer a powerful mathematical framework to systematically explore the structure-function relationship in biological, social, and technological networks. Despite theoretical advances, we lack direct experimental proof of the validity of these widely used control principles. Here we fill this gap by applying a control framework to the connectome of the nematode Caenorhabditis elegans, allowing us to predict the involvement of each C. elegans neuron in locomotor behaviours. We predict that control of the muscles or motor neurons requires 12 neuronal classes, which include neuronal groups previously implicated in locomotion by laser ablation, as well as one previously uncharacterized neuron, PDB. We validate this prediction experimentally, finding that the ablation of PDB leads to a significant loss of dorsoventral polarity in large body bends. Importantly, control principles also allow us to investigate the involvement of individual neurons within each neuronal class. For example, we predict that, within the class of DD motor neurons, only three (DD04, DD05, or DD06) should affect locomotion when ablated individually. This prediction is also confirmed; single cell ablations of DD04 or DD05 specifically affect posterior body movements, whereas ablations of DD02 or DD03 do not. Our predictions are robust to deletions of weak connections, missing connections, and rewired connections in the current connectome, indicating the potential applicability of this analytical framework to larger and less well-characterized connectomes.

Network control principles predict neuron function in the Caenorhabditis elegans connectome.

PubMed

Yan, Gang; Vértes, Petra E; Towlson, Emma K; Chew, Yee Lian; Walker, Denise S; Schafer, William R; Barabási, Albert-László

2017-10-26

Recent studies on the controllability of complex systems offer a powerful mathematical framework to systematically explore the structure-function relationship in biological, social, and technological networks. Despite theoretical advances, we lack direct experimental proof of the validity of these widely used control principles. Here we fill this gap by applying a control framework to the connectome of the nematode Caenorhabditis elegans, allowing us to predict the involvement of each C. elegans neuron in locomotor behaviours. We predict that control of the muscles or motor neurons requires 12 neuronal classes, which include neuronal groups previously implicated in locomotion by laser ablation, as well as one previously uncharacterized neuron, PDB. We validate this prediction experimentally, finding that the ablation of PDB leads to a significant loss of dorsoventral polarity in large body bends. Importantly, control principles also allow us to investigate the involvement of individual neurons within each neuronal class. For example, we predict that, within the class of DD motor neurons, only three (DD04, DD05, or DD06) should affect locomotion when ablated individually. This prediction is also confirmed; single cell ablations of DD04 or DD05 specifically affect posterior body movements, whereas ablations of DD02 or DD03 do not. Our predictions are robust to deletions of weak connections, missing connections, and rewired connections in the current connectome, indicating the potential applicability of this analytical framework to larger and less well-characterized connectomes.

Predicting and Explaining Intentions to Participate in Continuing Education: An Application of the Theory of Reasoned Action.

ERIC Educational Resources Information Center

Pryor, Brandt W.

1990-01-01

To test the predictive utility of the theory of reasoned action, 110 oral surgeons completed a questionnaire regarding participation in continuing education. Multiple regression analysis showed that the theory accounted for over 41 percent of variance in intention to participate. Intention appeared controlled by attitude, determined by strength of…

Robust predictive control with optimal load tracking for critical applications. Final report

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

Tse, J.; Bentsman, J.; Miller, N.

1994-09-01

This report derives a multi-input multi-output (MIMO) version of a two-degree-of-freedom receding-horizon control law based on mixed H{sub 2}/H{infinity} minimization. First, the integrand in the frequency domain representation of the MIMO performance criterion is decomposed into disturbance and reference spectra. Then the controller is derived which minimizes the peak of the disturbance spectrum and the integral of the reference spectrum on the unit circle. The resulting two-degree-of-freedom MIMO control strategy, referred to as the minimax predictive multivariable control (MPC), is shown to have worst-case-disturbance-rejection and robust-stability properties superior to those of purely H{sub 2}-optimal controllers, such as Generalized Predictive Controlmore » (GPC), for identical horizons. An attractive feature of the receding horizon structure of MPC is that it can, in ways similar to GPC, directly incorporate input constraints and pre-programmed reference inputs, which are nontrivial tasks in the standard H{infinity} design.« less

Concurrent musculoskeletal dynamics and finite element analysis predicts altered gait patterns to reduce foot tissue loading.

PubMed

Halloran, Jason P; Ackermann, Marko; Erdemir, Ahmet; van den Bogert, Antonie J

2010-10-19

Current computational methods for simulating locomotion have primarily used muscle-driven multibody dynamics, in which neuromuscular control is optimized. Such simulations generally represent joints and soft tissue as simple kinematic or elastic elements for computational efficiency. These assumptions limit application in studies such as ligament injury or osteoarthritis, where local tissue loading must be predicted. Conversely, tissue can be simulated using the finite element method with assumed or measured boundary conditions, but this does not represent the effects of whole body dynamics and neuromuscular control. Coupling the two domains would overcome these limitations and allow prediction of movement strategies guided by tissue stresses. Here we demonstrate this concept in a gait simulation where a musculoskeletal model is coupled to a finite element representation of the foot. Predictive simulations incorporated peak plantar tissue deformation into the objective of the movement optimization, as well as terms to track normative gait data and minimize fatigue. Two optimizations were performed, first without the strain minimization term and second with the term. Convergence to realistic gait patterns was achieved with the second optimization realizing a 44% reduction in peak tissue strain energy density. The study demonstrated that it is possible to alter computationally predicted neuromuscular control to minimize tissue strain while including desired kinematic and muscular behavior. Future work should include experimental validation before application of the methodology to patient care. Copyright © 2010 Elsevier Ltd. All rights reserved.

A decision-support tool to predict spray deposition of insecticides in commercial potato fields and its implications for their performance

USDA-ARS?s Scientific Manuscript database

In conventional and most IPM programs, application of insecticides continues to be the most important responsive pest control tactic. For both immediate and long-term optimization and sustainability of insecticide applications, it is paramount to study the factors affecting the performance of insect...

Fracture control methods for space vehicles. Volume 2: Assessment of fracture mechanics technology for space shuttle applications

NASA Technical Reports Server (NTRS)

Ehret, R. M.

1974-01-01

The concepts explored in a state of the art review of those engineering fracture mechanics considered most applicable to the space shuttle vehicle include fracture toughness, precritical flaw growth, failure mechanisms, inspection methods (including proof test logic), and crack growth predictive analysis techniques.

An eye on reactor and computer control

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

Schryver, J.; Knee, B.

1992-01-01

At ORNL computer software has been developed to make possible an improved eye-gaze measurement technology. Such an inovation could be the basis for advanced eye-gaze systems that may have applications in reactor control, software development, cognitive engineering, evaluation of displays, prediction of mental workloads, and military target recognition.

Development of models to estimate the subgrade and subbase layers' resilient modulus from in situ devices test results for construction control.

DOT National Transportation Integrated Search

2008-04-01

The objective of this study was to develop resilient modulus prediction models for possible application in the quality control/quality assurance (QC/QA) procedures during and after the construction of pavement layers. Field and laboratory testing pro...

Efficient operation scheduling for adsorption chillers using predictive optimization-based control methods

NASA Astrophysics Data System (ADS)

Bürger, Adrian; Sawant, Parantapa; Bohlayer, Markus; Altmann-Dieses, Angelika; Braun, Marco; Diehl, Moritz

2017-10-01

Within this work, the benefits of using predictive control methods for the operation of Adsorption Cooling Machines (ACMs) are shown on a simulation study. Since the internal control decisions of series-manufactured ACMs often cannot be influenced, the work focuses on optimized scheduling of an ACM considering its internal functioning as well as forecasts for load and driving energy occurrence. For illustration, an assumed solar thermal climate system is introduced and a system model suitable for use within gradient-based optimization methods is developed. The results of a system simulation using a conventional scheme for ACM scheduling are compared to the results of a predictive, optimization-based scheduling approach for the same exemplary scenario of load and driving energy occurrence. The benefits of the latter approach are shown and future actions for application of these methods for system control are addressed.

Application of real-time machine learning to myoelectric prosthesis control: A case series in adaptive switching.

PubMed

Edwards, Ann L; Dawson, Michael R; Hebert, Jacqueline S; Sherstan, Craig; Sutton, Richard S; Chan, K Ming; Pilarski, Patrick M

2016-10-01

Myoelectric prostheses currently used by amputees can be difficult to control. Machine learning, and in particular learned predictions about user intent, could help to reduce the time and cognitive load required by amputees while operating their prosthetic device. The goal of this study was to compare two switching-based methods of controlling a myoelectric arm: non-adaptive (or conventional) control and adaptive control (involving real-time prediction learning). Case series study. We compared non-adaptive and adaptive control in two different experiments. In the first, one amputee and one non-amputee subject controlled a robotic arm to perform a simple task; in the second, three able-bodied subjects controlled a robotic arm to perform a more complex task. For both tasks, we calculated the mean time and total number of switches between robotic arm functions over three trials. Adaptive control significantly decreased the number of switches and total switching time for both tasks compared with the conventional control method. Real-time prediction learning was successfully used to improve the control interface of a myoelectric robotic arm during uninterrupted use by an amputee subject and able-bodied subjects. Adaptive control using real-time prediction learning has the potential to help decrease both the time and the cognitive load required by amputees in real-world functional situations when using myoelectric prostheses. © The International Society for Prosthetics and Orthotics 2015.

Stellar tracking attitude reference system

NASA Technical Reports Server (NTRS)

Klestadt, B.

1974-01-01

A satellite precision attitude control system was designed, based on the use of STARS as the principal sensing system. The entire system was analyzed and simulated in detail, considering the nonideal properties of the control and sensing components and realistic spacecraft mass properties. Experimental results were used to improve the star tracker noise model. The results of the simulation indicate that STARS performs in general as predicted in a realistic application and should be a strong contender in most precision earth pointing applications.

Isothermal life prediction of composite lamina using a damage mechanics approach

NASA Technical Reports Server (NTRS)

Abuelfoutouh, Nader M.; Verrilli, Michael J.; Halford, Gary R.

1989-01-01

A method for predicting isothermal plastic fatigue life of a composite lamina is presented in which both fibers and matrix are isotropic materials. In general, the fatigue resistances of the matrix, fibers, and interfacial material must be known in order to predict composite fatigue life. Composite fatigue life is predicted using only the matrix fatigue resistance due to inelasticity micromechanisms. The effect of the fiber orientation on loading direction is accounted for while predicting composite life. The application is currently limited to isothermal cases where the internal thermal stresses that might arise from thermal strain mismatch between fibers and matrix are negligible. The theory is formulated to predict the fatigue life of a composite lamina under either load or strain control. It is applied currently to predict the life of tungsten-copper composite lamina at 260 C under tension-tension load control. The calculated life of the lamina is in good agreement with available composite low cycle fatigue data.

Methods for predicting properties and tailoring salt solutions for industrial processes

NASA Technical Reports Server (NTRS)

Ally, Moonis R.

1993-01-01

An algorithm developed at Oak Ridge National Laboratory accurately and quickly predicts thermodynamic properties of concentrated aqueous salt solutions. This algorithm is much simpler and much faster than other modeling schemes and is unique because it can predict solution behavior at very high concentrations and under varying conditions. Typical industrial applications of this algorithm would be in manufacture of inorganic chemicals by crystallization, thermal storage, refrigeration and cooling, extraction of metals, emissions controls, etc.

Test and theory for piezoelectric actuator-active vibration control of rotating machinery

NASA Technical Reports Server (NTRS)

Palazzolo, A. B.; Lin, R. R.; Alexander, R. M.; Kascak, A. F.; Montague, J.

1989-01-01

The application of piezoelectric actuators for active vibration control (AVC) of rotating machinery is examined. Theory is derived and the resulting predictions are shown to agree closely with results of tests performed on an air turbine driven-overhung rotor. The test results show significant reduction in unbalance, transient and sub-synchronous responses. Results from a 30-hour endurance test support the AVD system reliability. Various aspects of the electro-mechanical stability of the control system are also discussed and illustrated. Finally, application of the AVC system to an actual jet engine is discussed.

Neural control of fast nonlinear systems--application to a turbocharged SI engine with VCT.

PubMed

Colin, Guillaume; Chamaillard, Yann; Bloch, Gérard; Corde, Gilles

2007-07-01

Today, (engine) downsizing using turbocharging appears as a major way in reducing fuel consumption and pollutant emissions of spark ignition (SI) engines. In this context, an efficient control of the air actuators [throttle, turbo wastegate, and variable camshaft timing (VCT)] is needed for engine torque control. This paper proposes a nonlinear model-based control scheme which combines separate, but coordinated, control modules. Theses modules are based on different control strategies: internal model control (IMC), model predictive control (MPC), and optimal control. It is shown how neural models can be used at different levels and included in the control modules to replace physical models, which are too complex to be online embedded, or to estimate nonmeasured variables. The results obtained from two different test benches show the real-time applicability and good control performance of the proposed methods.

Proceedings of the 2004 NASA/ONR Circulation Control Workshop, Part 1

NASA Technical Reports Server (NTRS)

Jones, Gregory S. (Editor); Joslin, Ronald D. (Editor)

2005-01-01

As technological advances influence the efficiency and effectiveness of aerodynamic and hydrodynamic applications, designs and operations, this workshop was intended to address the technologies, systems, challenges and successes specific to Coanda driven circulation control in aerodynamics and hydrodynamics. A major goal of this workshop was to determine the 2004 state-of-the-art in circulation control and understand the roadblocks to its application. The workshop addressed applications, CFD, and experiments related to circulation control, emphasizing fundamental physics, systems analysis, and applied research. The workshop consisted of 34 single session oral presentations and written papers that focused on Naval hydrodynamic vehicles (e.g. submarines), Fixed Wing Aviation, V/STOL platforms, propulsion systems (including wind turbine systems), ground vehicles (automotive and trucks) and miscellaneous applications (e.g., poultry exhaust systems and vacuum systems). Several advanced CFD codes were benchmarked using a two-dimensional NCCR circulation control airfoil. The CFD efforts highlighted inconsistencies in turbulence modeling, separation and performance predictions.

Regional Differences in Brain Volume Predict the Acquisition of Skill in a Complex Real-Time Strategy Videogame

ERIC Educational Resources Information Center

Basak, Chandramallika; Voss, Michelle W.; Erickson, Kirk I.; Boot, Walter R.; Kramer, Arthur F.

2011-01-01

Previous studies have found that differences in brain volume among older adults predict performance in laboratory tasks of executive control, memory, and motor learning. In the present study we asked whether regional differences in brain volume as assessed by the application of a voxel-based morphometry technique on high resolution MRI would also…

Passive cyclic pitch control for horizontal axis wind turbines

NASA Technical Reports Server (NTRS)

Bottrell, G. W.

1981-01-01

A flexible rotor concept, called the balanced pitch rotor, is described. The system provides passive adjustment of cyclic pitch in response to unbalanced pitching moments across the rotor disk. Various applications are described and performance predictions are made for wind shear and cross wind operating conditions. Comparisons with the teetered hub are made and significant cost savings are predicted.

Development of a Model for Human Operator Learning in Continuous Estimation and Control Tasks.

DTIC Science & Technology

1983-12-01

and (3) a " precognitive mode" in 𔄁 17 which the pilot is able to take full advantage of any predictability "" inherent in the external inputs and can...allow application of a partial feedforward strategy; and (3) a " precognitive " mode in which full advantage is taken of any predictability of the

Adaptive control of the packet transmission period with solar energy harvesting prediction in wireless sensor networks.

PubMed

Kwon, Kideok; Yang, Jihoon; Yoo, Younghwan

2015-04-24

A number of research works has studied packet scheduling policies in energy scavenging wireless sensor networks, based on the predicted amount of harvested energy. Most of them aim to achieve energy neutrality, which means that an embedded system can operate perpetually while meeting application requirements. Unlike other renewable energy sources, solar energy has the feature of distinct periodicity in the amount of harvested energy over a day. Using this feature, this paper proposes a packet transmission control policy that can enhance the network performance while keeping sensor nodes alive. Furthermore, this paper suggests a novel solar energy prediction method that exploits the relation between cloudiness and solar radiation. The experimental results and analyses show that the proposed packet transmission policy outperforms others in terms of the deadline miss rate and data throughput. Furthermore, the proposed solar energy prediction method can predict more accurately than others by 6.92%.

Stability theory applications to laminar-flow control

NASA Technical Reports Server (NTRS)

Malik, Mujeeb R.

1987-01-01

In order to design Laminar Flow Control (LFC) configurations, reliable methods are needed for boundary-layer transition predictions. Among the available methods, there are correlations based upon R sub e, shape factors, Goertler number and crossflow Reynolds number. The most advanced transition prediction method is based upon linear stability theory in the form of the e sup N method which has proven to be successful in predicting transition in two- and three-dimensional boundary layers. When transition occurs in a low disturbance environment, the e sup N method provides a viable design tool for transition prediction and LFC in both 2-D and 3-D subsonic/supersonic flows. This is true for transition dominated by either TS, crossflow, or Goertler instability. If Goertler/TS or crossflow/TS interaction is present, the e sup N will fail to predict transition. However, there is no evidence of such interaction at low amplitudes of Goertler and crossflow vortices.

KC-135 winglet program overview

NASA Technical Reports Server (NTRS)

Barber, M. R.; Selegan, D.

1982-01-01

A joint NASA/USAF program was conducted to accomplish the following objectives: (1) evaluate the benefits that could be achieved from the application of winglets to KC-135 aircraft; and (2) determine the ability of wind tunnel tests and analytical analysis to predict winglet characteristics. The program included wind-tunnel development of a test winglet configuration; analytical predictions of the changes to the aircraft resulting from the application of the test winglet; and finally, flight tests of the developed configuration. Pressure distribution, loads, stability and control, buffet, fuel mileage, and flutter data were obtained to fulfill the objectives of the program.

GPC-Based Stable Reconfigurable Control

NASA Technical Reports Server (NTRS)

Soloway, Don; Shi, Jian-Jun; Kelkar, Atul

2004-01-01

This paper presents development of multi-input multi-output (MIMO) Generalized Pre-dictive Control (GPC) law and its application to reconfigurable control design in the event of actuator saturation. A Controlled Auto-Regressive Integrating Moving Average (CARIMA) model is used to describe the plant dynamics. The control law is derived using input-output description of the system and is also related to the state-space form of the model. The stability of the GPC control law without reconfiguration is first established using Riccati-based approach and state-space formulation. A novel reconfiguration strategy is developed for the systems which have actuator redundancy and are faced with actuator saturation type failure. An elegant reconfigurable control design is presented with stability proof. Several numerical examples are presented to demonstrate the application of various results.

CFL3D: Its History and Some Recent Applications

NASA Technical Reports Server (NTRS)

Rumsey, C. L.; Biedron, R. T.; Thomas, J. L.

1997-01-01

The history of the Computational Fluids Laboratory -3D (CFL3D) Navier-Stokes computer code is discussed and a comprehensive reference list is given. Three recent advanced applications are presented (1) Wing with partial-spanflap, (2) F/A-18 with forebody control strake, and (3) Noise predictions for an advanced ducted propeller turbomachinery flow.

Development of a strategy and computational application to select candidate protein analogues with reduced HLA binding and immunogenicity.

PubMed

Dhanda, Sandeep Kumar; Grifoni, Alba; Pham, John; Vaughan, Kerrie; Sidney, John; Peters, Bjoern; Sette, Alessandro

2018-01-01

Unwanted immune responses against protein therapeutics can reduce efficacy or lead to adverse reactions. T-cell responses are key in the development of such responses, and are directed against immunodominant regions within the protein sequence, often associated with binding to several allelic variants of HLA class II molecules (promiscuous binders). Herein, we report a novel computational strategy to predict 'de-immunized' peptides, based on previous studies of erythropoietin protein immunogenicity. This algorithm (or method) first predicts promiscuous binding regions within the target protein sequence and then identifies residue substitutions predicted to reduce HLA binding. Further, this method anticipates the effect of any given substitution on flanking peptides, thereby circumventing the creation of nascent HLA-binding regions. As a proof-of-principle, the algorithm was applied to Vatreptacog α, an engineered Factor VII molecule associated with unintended immunogenicity. The algorithm correctly predicted the two immunogenic peptides containing the engineered residues. As a further validation, we selected and evaluated the immunogenicity of seven substitutions predicted to simultaneously reduce HLA binding for both peptides, five control substitutions with no predicted reduction in HLA-binding capacity, and additional flanking region controls. In vitro immunogenicity was detected in 21·4% of the cultures of peptides predicted to have reduced HLA binding and 11·4% of the flanking regions, compared with 46% for the cultures of the peptides predicted to be immunogenic. This method has been implemented as an interactive application, freely available online at http://tools.iedb.org/deimmunization/. © 2017 John Wiley & Sons Ltd.

Lithium-ion battery cell-level control using constrained model predictive control and equivalent circuit models

NASA Astrophysics Data System (ADS)

Xavier, Marcelo A.; Trimboli, M. Scott

2015-07-01

This paper introduces a novel application of model predictive control (MPC) to cell-level charging of a lithium-ion battery utilizing an equivalent circuit model of battery dynamics. The approach employs a modified form of the MPC algorithm that caters for direct feed-though signals in order to model near-instantaneous battery ohmic resistance. The implementation utilizes a 2nd-order equivalent circuit discrete-time state-space model based on actual cell parameters; the control methodology is used to compute a fast charging profile that respects input, output, and state constraints. Results show that MPC is well-suited to the dynamics of the battery control problem and further suggest significant performance improvements might be achieved by extending the result to electrochemical models.

Utility of the theory of reasoned action and theory of planned behavior for predicting Chinese adolescent smoking.

PubMed

Guo, Qian; Johnson, C Anderson; Unger, Jennifer B; Lee, Liming; Xie, Bin; Chou, Chih-Ping; Palmer, Paula H; Sun, Ping; Gallaher, Peggy; Pentz, MaryAnn

2007-05-01

One third of smokers worldwide live in China. Identifying predictors of smoking is important for prevention program development. This study explored whether the Theory of Reasoned Action (TRA) and Theory of Planned Behavior (TPB) predict adolescent smoking in China. Data were obtained from 14,434 middle and high school students (48.6% boys, 51.4% girls) in seven geographically varied cities in China. TRA and TPB were tested by multilevel mediation modeling, and compared by multilevel analyses and likelihood ratio tests. Perceived behavioral control was tested as a main effect in TPB and a moderation effect in TRA. The mediation effects of smoking intention were supported in both models (p<0.001). TPB accounted for significantly more variance than TRA (p<0.001). Perceived behavioral control significantly interacted with attitudes and social norms in TRA (p<0.001). Therefore, TRA and TPB are applicable to China to predict adolescent smoking. TPB is superior to TRA for the prediction and TRA can better predict smoking among students with lower than higher perceived behavioral control.

Structure-based control of complex networks with nonlinear dynamics.

PubMed

Zañudo, Jorge Gomez Tejeda; Yang, Gang; Albert, Réka

2017-07-11

What can we learn about controlling a system solely from its underlying network structure? Here we adapt a recently developed framework for control of networks governed by a broad class of nonlinear dynamics that includes the major dynamic models of biological, technological, and social processes. This feedback-based framework provides realizable node overrides that steer a system toward any of its natural long-term dynamic behaviors, regardless of the specific functional forms and system parameters. We use this framework on several real networks, identify the topological characteristics that underlie the predicted node overrides, and compare its predictions to those of structural controllability in control theory. Finally, we demonstrate this framework's applicability in dynamic models of gene regulatory networks and identify nodes whose override is necessary for control in the general case but not in specific model instances.

A statistical rain attenuation prediction model with application to the advanced communication technology satellite project. Part 2: Theoretical development of a dynamic model and application to rain fade durations and tolerable control delays for fade countermeasures

NASA Technical Reports Server (NTRS)

Manning, Robert M.

1987-01-01

A dynamic rain attenuation prediction model is developed for use in obtaining the temporal characteristics, on time scales of minutes or hours, of satellite communication link availability. Analagous to the associated static rain attenuation model, which yields yearly attenuation predictions, this dynamic model is applicable at any location in the world that is characterized by the static rain attenuation statistics peculiar to the geometry of the satellite link and the rain statistics of the location. Such statistics are calculated by employing the formalism of Part I of this report. In fact, the dynamic model presented here is an extension of the static model and reduces to the static model in the appropriate limit. By assuming that rain attenuation is dynamically described by a first-order stochastic differential equation in time and that this random attenuation process is a Markov process, an expression for the associated transition probability is obtained by solving the related forward Kolmogorov equation. This transition probability is then used to obtain such temporal rain attenuation statistics as attenuation durations and allowable attenuation margins versus control system delay.

Open Platform for Limit Protection with Carefree Maneuver Applications

NASA Technical Reports Server (NTRS)

Jeram, Geoffrey J.

2004-01-01

This Open Platform for Limit Protection guides the open design of maneuver limit protection systems in general, and manned, rotorcraft, aerospace applications in particular. The platform uses three stages of limit protection modules: limit cue creation, limit cue arbitration, and control system interface. A common set of limit cue modules provides commands that can include constraints, alerts, transfer functions, and friction. An arbitration module selects the "best" limit protection cues and distributes them to the most appropriate control path interface. This platform adopts a holistic approach to limit protection whereby it considers all potential interface points, including the pilot's visual, aural, and tactile displays; and automatic command restraint shaping for autonomous limit protection. For each functional module, this thesis guides the control system designer through the design choices and information interfaces among the modules. Limit cue module design choices include type of prediction, prediction mechanism, method of critical control calculation, and type of limit cue. Special consideration is given to the nature of the limit, particularly the level of knowledge about it, and the ramifications for limit protection design, especially with respect to intelligent control methods such as fuzzy inference systems and neural networks.

Model Based Predictive Control of Multivariable Hammerstein Processes with Fuzzy Logic Hypercube Interpolated Models

PubMed Central

Coelho, Antonio Augusto Rodrigues

2016-01-01

This paper introduces the Fuzzy Logic Hypercube Interpolator (FLHI) and demonstrates applications in control of multiple-input single-output (MISO) and multiple-input multiple-output (MIMO) processes with Hammerstein nonlinearities. FLHI consists of a Takagi-Sugeno fuzzy inference system where membership functions act as kernel functions of an interpolator. Conjunction of membership functions in an unitary hypercube space enables multivariable interpolation of N-dimensions. Membership functions act as interpolation kernels, such that choice of membership functions determines interpolation characteristics, allowing FLHI to behave as a nearest-neighbor, linear, cubic, spline or Lanczos interpolator, to name a few. The proposed interpolator is presented as a solution to the modeling problem of static nonlinearities since it is capable of modeling both a function and its inverse function. Three study cases from literature are presented, a single-input single-output (SISO) system, a MISO and a MIMO system. Good results are obtained regarding performance metrics such as set-point tracking, control variation and robustness. Results demonstrate applicability of the proposed method in modeling Hammerstein nonlinearities and their inverse functions for implementation of an output compensator with Model Based Predictive Control (MBPC), in particular Dynamic Matrix Control (DMC). PMID:27657723

Guidance and control 1992; Proceedings of the 15th Annual AAS Rocky Mountain Conference, Keystone, CO, Feb. 8-12, 1992

NASA Astrophysics Data System (ADS)

Culp, Robert D.; Zietz, Richard P.

The present volume on guidance and control discusses advances in guidance, navigation, and control, guidance and control storyboard displays, space robotic control, spacecraft control and flexible body interaction, and the Mission to Planet Earth. Attention is given to applications of Newton's method to attitude determination, a new family of low-cost momentum/reaction wheels, stellar attitude data handling, and satellite life prediction using propellant quantity measurements. Topics addressed include robust manipulator controller specification and design, implementations and applications of a manipulator control testbed, optimizing transparency in teleoperator architectures, and MIMO system identification using frequency response data. Also discussed are instrument configurations for the restructured Earth Observing System, the HIRIS instrument, clouds and the earth's radiant energy system, and large space-based systems for dealing with global change.

Freshwater Harmful Algal Blooms

EPA Pesticide Factsheets

EPA is seeking regular and early career applications proposing innovative research on the prediction, prevention, control and mitigation of freshwater HABs as well as the drivers, life cycle patterns, and fate of and effects from from less-common, less

Application of Computational Stability and Control Techniques Including Unsteady Aerodynamics and Aeroelastic Effects

NASA Technical Reports Server (NTRS)

Schuster, David M.; Edwards, John W.

2004-01-01

The motivation behind the inclusion of unsteady aerodynamics and aeroelastic effects in the computation of stability and control (S&C) derivatives will be discussed as they pertain to aeroelastic and aeroservoelastic analysis. This topic will be addressed in the context of two applications, the first being the estimation of S&C derivatives for a cable-mounted aeroservoelastic wind tunnel model tested in the NASA Langley Research Center (LaRC) Transonic Dynamics Tunnel (TDT). The second application will be the prediction of the nonlinear aeroservoelastic phenomenon known as Residual Pitch Oscillation (RPO) on the B-2 Bomber. Techniques and strategies used in these applications to compute S&C derivatives and perform flight simulations will be reviewed, and computational results will be presented.

REVIEW: Internal models in sensorimotor integration: perspectives from adaptive control theory

NASA Astrophysics Data System (ADS)

Tin, Chung; Poon, Chi-Sang

2005-09-01

Internal models and adaptive controls are empirical and mathematical paradigms that have evolved separately to describe learning control processes in brain systems and engineering systems, respectively. This paper presents a comprehensive appraisal of the correlation between these paradigms with a view to forging a unified theoretical framework that may benefit both disciplines. It is suggested that the classic equilibrium-point theory of impedance control of arm movement is analogous to continuous gain-scheduling or high-gain adaptive control within or across movement trials, respectively, and that the recently proposed inverse internal model is akin to adaptive sliding control originally for robotic manipulator applications. Modular internal models' architecture for multiple motor tasks is a form of multi-model adaptive control. Stochastic methods, such as generalized predictive control, reinforcement learning, Bayesian learning and Hebbian feedback covariance learning, are reviewed and their possible relevance to motor control is discussed. Possible applicability of a Luenberger observer and an extended Kalman filter to state estimation problems—such as sensorimotor prediction or the resolution of vestibular sensory ambiguity—is also discussed. The important role played by vestibular system identification in postural control suggests an indirect adaptive control scheme whereby system states or parameters are explicitly estimated prior to the implementation of control. This interdisciplinary framework should facilitate the experimental elucidation of the mechanisms of internal models in sensorimotor systems and the reverse engineering of such neural mechanisms into novel brain-inspired adaptive control paradigms in future.

Piloted Simulator Tests of a Guidance System which Can Continously Predict Landing Point of a Low L/D Vehicle During Atmosphere Re-Entry

NASA Technical Reports Server (NTRS)

Wingrove, Rodney C.; Coate, Robert E.

1961-01-01

The guidance system for maneuvering vehicles within a planetary atmosphere which was studied uses the concept of fast continuous prediction of the maximum maneuver capability from existing conditions rather than a stored-trajectory technique. used, desired touchdown points are compared with the maximum range capability and heating or acceleration limits, so that a proper decision and choice of control inputs can be made by the pilot. In the method of display and control a piloted fixed simulator was used t o demonstrate the feasibility od the concept and to study its application to control of lunar mission reentries and recoveries from aborts.

Computational Methods for Stability and Control (COMSAC): The Time Has Come

NASA Technical Reports Server (NTRS)

Hall, Robert M.; Biedron, Robert T.; Ball, Douglas N.; Bogue, David R.; Chung, James; Green, Bradford E.; Grismer, Matthew J.; Brooks, Gregory P.; Chambers, Joseph R.

2005-01-01

Powerful computational fluid dynamics (CFD) tools have emerged that appear to offer significant benefits as an adjunct to the experimental methods used by the stability and control community to predict aerodynamic parameters. The decreasing costs for and increasing availability of computing hours are making these applications increasingly viable as time goes on and the cost of computing continues to drop. This paper summarizes the efforts of four organizations to utilize high-end computational fluid dynamics (CFD) tools to address the challenges of the stability and control arena. General motivation and the backdrop for these efforts will be summarized as well as examples of current applications.

Fatigue behavior and life prediction of a SiC/Ti-24Al-11Nb composite under isothermal conditions. Ph.D. Thesis

NASA Technical Reports Server (NTRS)

Bartolotta, Paul A.

1991-01-01

Metal Matrix Composites (MMC) and Intermetallic Matrix Composites (IMC) were identified as potential material candidates for advanced aerospace applications. They are especially attractive for high temperature applications which require a low density material that maintains its structural integrity at elevated temperatures. High temperature fatigue resistance plays an important role in determining the structural integrity of the material. This study attempts to examine the relevance of test techniques, failure criterion, and life prediction as they pertain to an IMC material, specifically, unidirectional SiC fiber reinforced titanium aluminide. A series of strain and load controlled fatigue tests were conducted on unidirectional SiC/Ti-24Al-11Nb composite at 425 and 815 C. Several damage mechanism regimes were identified by using a strain-based representation of the data, Talreja's fatigue life diagram concept. Results of these tests were then used to address issues of test control modes, definition of failure, and testing techniques. Finally, a strain-based life prediction method was proposed for an IMC under tensile cyclic loadings at elevated temperatures.

Predictable and reliable ECG monitoring over IEEE 802.11 WLANs within a hospital.

PubMed

Park, Juyoung; Kang, Kyungtae

2014-09-01

Telecardiology provides mobility for patients who require constant electrocardiogram (ECG) monitoring. However, its safety is dependent on the predictability and robustness of data delivery, which must overcome errors in the wireless channel through which the ECG data are transmitted. We report here a framework that can be used to gauge the applicability of IEEE 802.11 wireless local area network (WLAN) technology to ECG monitoring systems in terms of delay constraints and transmission reliability. For this purpose, a medical-grade WLAN architecture achieved predictable delay through the combination of a medium access control mechanism based on the point coordination function provided by IEEE 802.11 and an error control scheme based on Reed-Solomon coding and block interleaving. The size of the jitter buffer needed was determined by this architecture to avoid service dropout caused by buffer underrun, through analysis of variations in transmission delay. Finally, we assessed this architecture in terms of service latency and reliability by modeling the transmission of uncompressed two-lead electrocardiogram data from the MIT-BIH Arrhythmia Database and highlight the applicability of this wireless technology to telecardiology.

Tailored high-resolution numerical weather forecasts for energy efficient predictive building control

NASA Astrophysics Data System (ADS)

Stauch, V. J.; Gwerder, M.; Gyalistras, D.; Oldewurtel, F.; Schubiger, F.; Steiner, P.

2010-09-01

The high proportion of the total primary energy consumption by buildings has increased the public interest in the optimisation of buildings' operation and is also driving the development of novel control approaches for the indoor climate. In this context, the use of weather forecasts presents an interesting and - thanks to advances in information and predictive control technologies and the continuous improvement of numerical weather prediction (NWP) models - an increasingly attractive option for improved building control. Within the research project OptiControl (www.opticontrol.ethz.ch) predictive control strategies for a wide range of buildings, heating, ventilation and air conditioning (HVAC) systems, and representative locations in Europe are being investigated with the aid of newly developed modelling and simulation tools. Grid point predictions for radiation, temperature and humidity of the high-resolution limited area NWP model COSMO-7 (see www.cosmo-model.org) and local measurements are used as disturbances and inputs into the building system. The control task considered consists in minimizing energy consumption whilst maintaining occupant comfort. In this presentation, we use the simulation-based OptiControl methodology to investigate the impact of COSMO-7 forecasts on the performance of predictive building control and the resulting energy savings. For this, we have selected building cases that were shown to benefit from a prediction horizon of up to 3 days and therefore, are particularly suitable for the use of numerical weather forecasts. We show that the controller performance is sensitive to the quality of the weather predictions, most importantly of the incident radiation on differently oriented façades. However, radiation is characterised by a high temporal and spatial variability in part caused by small scale and fast changing cloud formation and dissolution processes being only partially represented in the COSMO-7 grid point predictions. On the other hand, buildings are affected by particularly local weather conditions at the building site. To overcome this discrepancy, we make use of local measurements to statistically adapt the COSMO-7 model output to the meteorological conditions at the building. For this, we have developed a general correction algorithm that exploits systematic properties of the COSMO-7 prediction error and explicitly estimates the degree of temporal autocorrelation using online recursive estimation. The resulting corrected predictions are improved especially for the first few hours being the most crucial for the predictive controller and, ultimately for the reduction of primary energy consumption using predictive control. The use of numerical weather forecasts in predictive building automation is one example in a wide field of weather dependent advanced energy saving technologies. Our work particularly highlights the need for the development of specifically tailored weather forecast products by (statistical) postprocessing in order to meet the requirements of specific applications.

An Evolutionary Algorithm for Feature Subset Selection in Hard Disk Drive Failure Prediction

ERIC Educational Resources Information Center

Bhasin, Harpreet

2011-01-01

Hard disk drives are used in everyday life to store critical data. Although they are reliable, failure of a hard disk drive can be catastrophic, especially in applications like medicine, banking, air traffic control systems, missile guidance systems, computer numerical controlled machines, and more. The use of Self-Monitoring, Analysis and…

A model predictive current control of flux-switching permanent magnet machines for torque ripple minimization

NASA Astrophysics Data System (ADS)

Huang, Wentao; Hua, Wei; Yu, Feng

2017-05-01

Due to high airgap flux density generated by magnets and the special double salient structure, the cogging torque of the flux-switching permanent magnet (FSPM) machine is considerable, which limits the further applications. Based on the model predictive current control (MPCC) and the compensation control theory, a compensating-current MPCC (CC-MPCC) scheme is proposed and implemented to counteract the dominated components in cogging torque of an existing three-phase 12/10 FSPM prototyped machine, and thus to alleviate the influence of the cogging torque and improve the smoothness of electromagnetic torque as well as speed, where a comprehensive cost function is designed to evaluate the switching states. The simulated results indicate that the proposed CC-MPCC scheme can suppress the torque ripple significantly and offer satisfactory dynamic performances by comparisons with the conventional MPCC strategy. Finally, experimental results validate both the theoretical and simulated predictions.

An Application of the Theory of Planned Behavior to Sorority Alcohol Consumption

PubMed Central

Huchting, Karen; Lac, Andrew; LaBrie, Joseph W.

2008-01-01

Greek-affiliated college students have been found to drink more heavily and frequently than other students. With female student drinking on the rise over the past decade, sorority women may be at particular risk for heavy consumption patterns. The current study is the first to apply the Theory of Planned Behavior (TPB) to examine drinking patterns among a sorority-only sample. Two-hundred and forty-seven sorority members completed questionnaires measuring TPB variables of attitudes, norms, perceived behavioral control, and intentions, with drinking behaviors measured one month later. Latent structural equation modeling examined the pathways of the TPB model. Intentions to drink mediated the relationship between attitudes and norms on drinking behavior. Subjective norms predicted intentions to drink more than attitudes or perceived behavioral control. Perceived behavioral control did not predict intentions but did predict drinking behaviors. Interpretation and suggestions from these findings are discussed. PMID:18055130

Synthesising empirical results to improve predictions of post-wildfire runoff and erosion response

USGS Publications Warehouse

Shakesby, Richard A.; Moody, John A.; Martin, Deborah A.; Robichaud, Peter R.

2016-01-01

Advances in research into wildfire impacts on runoff and erosion have demonstrated increasing complexity of controlling factors and responses, which, combined with changing fire frequency, present challenges for modellers. We convened a conference attended by experts and practitioners in post-wildfire impacts, meteorology and related research, including modelling, to focus on priority research issues. The aim was to improve our understanding of controls and responses and the predictive capabilities of models. This conference led to the eight selected papers in this special issue. They address aspects of the distinctiveness in the controls and responses among wildfire regions, spatiotemporal rainfall variability, infiltration, runoff connectivity, debris flow formation and modelling applications. Here we summarise key findings from these papers and evaluate their contribution to improving understanding and prediction of post-wildfire runoff and erosion under changes in climate, human intervention and population pressure on wildfire-prone areas.

OAO battery data analysis

NASA Technical Reports Server (NTRS)

Gaston, S.; Wertheim, M.; Orourke, J. A.

1973-01-01

Summary, consolidation and analysis of specifications, manufacturing process and test controls, and performance results for OAO-2 and OAO-3 lot 20 Amp-Hr sealed nickel cadmium cells and batteries are reported. Correlation of improvements in control requirements with performance is a key feature. Updates for a cell/battery computer model to improve performance prediction capability are included. Applicability of regression analysis computer techniques to relate process controls to performance is checked.

Structural response synthesis

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

Ozisik, H.; Keltie, R.F.

The open loop control technique of predicting a conditioned input signal based on a specified output response for a second order system has been analyzed both analytically and numerically to gain a firm understanding of the method. Differences between this method of control and digital closed loop control using pole cancellation were investigated as a follow up to previous experimental work. Application of the technique to diamond turning using a fast tool is also discussed.

Factors related to reduction in the consumption of fast food: application of the theory-based approaches.

PubMed

Zeinab, Jalambadani; Gholamreza, Garmaroudi; Mehdi, Yaseri; Mahmood, Tavousi; Korush, Jafarian

2017-09-21

The Trans-Theoretical model (TTM) and Theory of Planned Behaviour (TPB) may be promising models for understanding and predicting reduction in the consumption of fast food. The aim of this study was to examine the applicability of the Trans-Theoretical model (TTM) and the additional predictive role of the subjective norms and perceived behavioural control in predicting reduction consumption of fast food in obese Iranian adolescent girls. A cross sectional study design was conducted among twelve randomly selected schools in Sabzevar, Iran from 2015 to 2017. Four hundred eighty five randomly selected students consented to participate in the study. Hierarchical regression models used to predict the role of important variables that can influence the reduction in the consumption of fast food among students. using SPSS version 22. Variables Perceived behavioural control (r=0.58, P<0.001), Subjective norms (r=0.51, P<0.001), self-efficacy (r=0.49, P<0.001), decisional balance (pros) (r=0.29, P<0.001), decisional balance (cons) (r=0.25, P<0.001), stage of change (r=0.38, P<0.001), were significantly and positively correlated while experiential processes of change (r=0.08, P=0.135) and behavioural processes of change (r=0.09, P=0.145), were not significant. The study demonstrated that the TTM (except the experiential and behavioural processes of change) focusing on the perceived behavioural control and subjective norms are useful models for reduction in the consumption of fast food.

Bridge deck service life prediction and costs.

DOT National Transportation Integrated Search

2007-01-01

The service life of Virginia's concrete bridge decks is generally controlled by chloride-induced corrosion of the reinforcing steel as a result of the application of winter maintenance deicing salts. A chloride corrosion model accounting for the vari...

Zone radiometer measurements on a model rocket exhaust plume

NASA Technical Reports Server (NTRS)

1972-01-01

Radiometer for analytical prediction of rocket plume-to-booster thermal radiation and convective heating is described. Applications for engine combustion analysis, incineration, and pollution control by high temperature processing are discussed. Illustrations of equipment are included.

Optical and infrared properties of glancing angle-deposited nanostructured tungsten films.

PubMed

Ungaro, Craig; Shah, Ankit; Kravchenko, Ivan; Hensley, Dale K; Gray, Stephen K; Gupta, Mool C

2015-02-15

Nanotextured tungsten thin films were obtained on a stainless steel (SS) substrate using the glancing-angle-deposition (GLAD) method. It was found that the optical absorption and thermal emittance of the SS substrate can be controlled by varying the parameters used during deposition. Finite-difference time-domain (FDTD) simulations were used to predict the optical absorption and infrared (IR) reflectance spectra of the fabricated samples, and good agreement was found between simulated and measured data. FDTD simulations were also used to predict the effect of changes in the height and periodicity of the nanotextures. These simulations show that good control over the absorption can be achieved by altering the height and periodicity of the nanostructure. These nanostructures were shown to be temperature stable up to 500°C with the addition of a protective HfO2 layer. Applications for this structure are explored, including a promising application for solar thermal energy systems.

Algorithms for Robust Identification and Control of Large Space Structures. Phase 1.

DTIC Science & Technology

1988-05-14

Variate Analysis," Proc. Amer. Control Conf., San Francisco, * pp. 445-451. LECTIQUE, J., Rault, A., Tessier, M., and Testud , J.L. (1978), "Multivariable...Rault, J.L. Testud , and J. Papon (1978), "Model Predictive Heuris- tic Control: Applications to Industrial Processes," Automatica, Vol. 14, pp. 413...Control ’. Conference, Minneapolis, MN, June. TESTUD , J.L. (1979), "Commande Numerique Multivariable du Ballon de Recupera- tion de Vapeur," Adersa/Gerbios

Lithium-ion battery cell-level control using constrained model predictive control and equivalent circuit models

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

Xavier, MA; Trimboli, MS

This paper introduces a novel application of model predictive control (MPC) to cell-level charging of a lithium-ion battery utilizing an equivalent circuit model of battery dynamics. The approach employs a modified form of the MPC algorithm that caters for direct feed-though signals in order to model near-instantaneous battery ohmic resistance. The implementation utilizes a 2nd-order equivalent circuit discrete-time state-space model based on actual cell parameters; the control methodology is used to compute a fast charging profile that respects input, output, and state constraints. Results show that MPC is well-suited to the dynamics of the battery control problem and further suggestmore » significant performance improvements might be achieved by extending the result to electrochemical models. (C) 2015 Elsevier B.V. All rights reserved.« less

Artificial neural network implementation of a near-ideal error prediction controller

NASA Technical Reports Server (NTRS)

Mcvey, Eugene S.; Taylor, Lynore Denise

1992-01-01

A theory has been developed at the University of Virginia which explains the effects of including an ideal predictor in the forward loop of a linear error-sampled system. It has been shown that the presence of this ideal predictor tends to stabilize the class of systems considered. A prediction controller is merely a system which anticipates a signal or part of a signal before it actually occurs. It is understood that an exact prediction controller is physically unrealizable. However, in systems where the input tends to be repetitive or limited, (i.e., not random) near ideal prediction is possible. In order for the controller to act as a stability compensator, the predictor must be designed in a way that allows it to learn the expected error response of the system. In this way, an unstable system will become stable by including the predicted error in the system transfer function. Previous and current prediction controller include pattern recognition developments and fast-time simulation which are applicable to the analysis of linear sampled data type systems. The use of pattern recognition techniques, along with a template matching scheme, has been proposed as one realizable type of near-ideal prediction. Since many, if not most, systems are repeatedly subjected to similar inputs, it was proposed that an adaptive mechanism be used to 'learn' the correct predicted error response. Once the system has learned the response of all the expected inputs, it is necessary only to recognize the type of input with a template matching mechanism and then to use the correct predicted error to drive the system. Suggested here is an alternate approach to the realization of a near-ideal error prediction controller, one designed using Neural Networks. Neural Networks are good at recognizing patterns such as system responses, and the back-propagation architecture makes use of a template matching scheme. In using this type of error prediction, it is assumed that the system error responses be known for a particular input and modeled plant. These responses are used in the error prediction controller. An analysis was done on the general dynamic behavior that results from including a digital error predictor in a control loop and these were compared to those including the near-ideal Neural Network error predictor. This analysis was done for a second and third order system.

Euler Technology Assessment - SPLITFLOW Code Applications for Stability and Control Analysis on an Advanced Fighter Model Employing Innovative Control Concepts

NASA Technical Reports Server (NTRS)

Jordan, Keith J.

1998-01-01

This report documents results from the NASA-Langley sponsored Euler Technology Assessment Study conducted by Lockheed-Martin Tactical Aircraft Systems (LMTAS). The purpose of the study was to evaluate the ability of the SPLITFLOW code using viscous and inviscid flow models to predict aerodynamic stability and control of an advanced fighter model. The inviscid flow model was found to perform well at incidence angles below approximately 15 deg, but not as well at higher angles of attack. The results using a turbulent, viscous flow model matched the trends of the wind tunnel data, but did not show significant improvement over the Euler solutions. Overall, the predictions were found to be useful for stability and control design purposes.

Robust model predictive control for constrained continuous-time nonlinear systems

NASA Astrophysics Data System (ADS)

Sun, Tairen; Pan, Yongping; Zhang, Jun; Yu, Haoyong

2018-02-01

In this paper, a robust model predictive control (MPC) is designed for a class of constrained continuous-time nonlinear systems with bounded additive disturbances. The robust MPC consists of a nonlinear feedback control and a continuous-time model-based dual-mode MPC. The nonlinear feedback control guarantees the actual trajectory being contained in a tube centred at the nominal trajectory. The dual-mode MPC is designed to ensure asymptotic convergence of the nominal trajectory to zero. This paper extends current results on discrete-time model-based tube MPC and linear system model-based tube MPC to continuous-time nonlinear model-based tube MPC. The feasibility and robustness of the proposed robust MPC have been demonstrated by theoretical analysis and applications to a cart-damper springer system and a one-link robot manipulator.

Circadian Phase Resetting via Single and Multiple Control Targets

PubMed Central

Bagheri, Neda; Stelling, Jörg; Doyle, Francis J.

2008-01-01

Circadian entrainment is necessary for rhythmic physiological functions to be appropriately timed over the 24-hour day. Disruption of circadian rhythms has been associated with sleep and neuro-behavioral impairments as well as cancer. To date, light is widely accepted to be the most powerful circadian synchronizer, motivating its use as a key control input for phase resetting. Through sensitivity analysis, we identify additional control targets whose individual and simultaneous manipulation (via a model predictive control algorithm) out-perform the open-loop light-based phase recovery dynamics by nearly 3-fold. We further demonstrate the robustness of phase resetting by synchronizing short- and long-period mutant phenotypes to the 24-hour environment; the control algorithm is robust in the presence of model mismatch. These studies prove the efficacy and immediate application of model predictive control in experimental studies and medicine. In particular, maintaining proper circadian regulation may significantly decrease the chance of acquiring chronic illness. PMID:18795146

A support vector machine based control application to the experimental three-tank system.

PubMed

Iplikci, Serdar

2010-07-01

This paper presents a support vector machine (SVM) approach to generalized predictive control (GPC) of multiple-input multiple-output (MIMO) nonlinear systems. The possession of higher generalization potential and at the same time avoidance of getting stuck into the local minima have motivated us to employ SVM algorithms for modeling MIMO systems. Based on the SVM model, detailed and compact formulations for calculating predictions and gradient information, which are used in the computation of the optimal control action, are given in the paper. The proposed MIMO SVM-based GPC method has been verified on an experimental three-tank liquid level control system. Experimental results have shown that the proposed method can handle the control task successfully for different reference trajectories. Moreover, a detailed discussion on data gathering, model selection and effects of the control parameters have been given in this paper. 2010 ISA. Published by Elsevier Ltd. All rights reserved.

Validation of a dye stain assay for vaginally inserted HEC-filled microbicide applicators

PubMed Central

Katzen, Lauren L.; Fernández-Romero, José A.; Sarna, Avina; Murugavel, Kailapuri G.; Gawarecki, Daniel; Zydowsky, Thomas M.; Mensch, Barbara S.

2011-01-01

Background The reliability and validity of self-reports of vaginal microbicide use are questionable given the explicit understanding that participants are expected to comply with study protocols. Our objective was to optimize the Population Council's previously validated dye stain assay (DSA) and related procedures, and establish predictive values for the DSA's ability to identify vaginally inserted single-use, low-density polyethylene microbicide applicators filled with hydroxyethylcellulose gel. Methods Applicators, inserted by 252 female sex workers enrolled in a microbicide feasibility study in Southern India, served as positive controls for optimization and validation experiments. Prior to validation, optimal dye concentration and staining time were ascertained. Three validation experiments were conducted to determine sensitivity, specificity, negative predictive values and positive predictive values. Results The dye concentration of 0.05% (w/v) FD&C Blue No. 1 Granular Food Dye and staining time of five seconds were determined to be optimal and were used for the three validation experiments. There were a total of 1,848 possible applicator readings across validation experiments; 1,703 (92.2%) applicator readings were correct. On average, the DSA performed with 90.6% sensitivity, 93.9% specificity, and had a negative predictive value of 93.8% and a positive predictive value of 91.0%. No statistically significant differences between experiments were noted. Conclusions The DSA was optimized and successfully validated for use with single-use, low-density polyethylene applicators filled with hydroxyethylcellulose (HEC) gel. We recommend including the DSA in future microbicide trials involving vaginal gels in order to identify participants who have low adherence to dosing regimens. In doing so, we can develop strategies to improve adherence as well as investigate the association between product use and efficacy. PMID:21992983

Fourth Aircraft Interior Noise Workshop

NASA Technical Reports Server (NTRS)

Stephens, David G. (Compiler)

1992-01-01

The fourth in a series of NASA/SAE Interior Noise Workshops was held on May 19 and 20, 1992. The theme of the workshop was new technology and applications for aircraft noise with emphasis on source noise prediction; cabin noise prediction; cabin noise control, including active and passive methods; and cabin interior noise procedures. This report is a compilation of the presentations made at the meeting which addressed the above issues.

Who succeeds at dental school? Factors predicting students' academic performance in a dental school in republic of Korea.

PubMed

Ihm, Jung-Joon; Lee, Gene; Kim, Kack-Kyun; Jang, Ki-Taeg; Jin, Bo-Hyoung

2013-12-01

The purpose of this study was to examine what cognitive and non-cognitive factors were responsible for predicting the academic performance of dental students in a dental school in the Republic of Korea. This school is one of those in Korea that now require applicants to have a bachelor's degree. In terms of cognitive factors, students' undergraduate grade point average (GPA) and Dental Education Eligibility Test (DEET) scores were used, while surveys were conducted to evaluate four non-cognitive measures: locus of control, self-esteem, self-directed learning, and interpersonal skills. A total of 353 students matriculating at Seoul National University School of Dentistry in 2005, 2006, 2007, and 2008 consented to the collection of records and completed the surveys. The main finding was that applicants who scored higher on internal locus of control and self-efficacy were more likely to be academically successful dental students. Self-directed learning was significantly associated with students ranked in the top 50 percent in cumulative GPA. However, students' interpersonal skills were negatively related to their academic performance. In particular, students' lack of achievement could be predicted by monitoring their first-year GPA. Therefore, the identification of those factors to predict dental school performance has implications for the dental curriculum and effective pedagogy in dental education.

Design-based modeling of magnetically actuated soft diaphragm materials

NASA Astrophysics Data System (ADS)

Jayaneththi, V. R.; Aw, K. C.; McDaid, A. J.

2018-04-01

Magnetic polymer composites (MPC) have shown promise for emerging biomedical applications such as lab-on-a-chip and implantable drug delivery. These soft material actuators are capable of fast response, large deformation and wireless actuation. Existing MPC modeling approaches are computationally expensive and unsuitable for rapid design prototyping and real-time control applications. This paper proposes a macro-scale 1-DOF model capable of predicting force and displacement of an MPC diaphragm actuator. Model validation confirmed both blocked force and displacement can be accurately predicted in a variety of working conditions i.e. different magnetic field strengths, static/dynamic fields, and gap distances. The contribution of this work includes a comprehensive experimental investigation of a macro-scale diaphragm actuator; the derivation and validation of a new phenomenological model to describe MPC actuation; and insights into the proposed model’s design-based functionality i.e. scalability and generalizability in terms of magnetic filler concentration and diaphragm diameter. Due to the lumped element modeling approach, the proposed model can also be adapted to alternative actuator configurations, and thus presents a useful tool for design, control and simulation of novel MPC applications.

Application of identification techniques to remote manipulator system flight data

NASA Technical Reports Server (NTRS)

Shepard, G. D.; Lepanto, J. A.; Metzinger, R. W.; Fogel, E.

1983-01-01

This paper addresses the application of identification techniques to flight data from the Space Shuttle Remote Manipulator System (RMS). A description of the remote manipulator, including structural and control system characteristics, sensors, and actuators is given. A brief overview of system identification procedures is presented, and the practical aspects of implementing system identification algorithms are discussed. In particular, the problems posed by desampling rate, numerical error, and system nonlinearities are considered. Simulation predictions of damping, frequency, and system order are compared with values identified from flight data to support an evaluation of RMS structural and control system models. Finally, conclusions are drawn regarding the application of identification techniques to flight data obtained from a flexible space structure.

Prediction of clinical depression scores and detection of changes in whole-brain using resting-state functional MRI data with partial least squares regression

PubMed Central

Shimizu, Yu; Yoshimoto, Junichiro; Takamura, Masahiro; Okada, Go; Okamoto, Yasumasa; Yamawaki, Shigeto; Doya, Kenji

2017-01-01

In diagnostic applications of statistical machine learning methods to brain imaging data, common problems include data high-dimensionality and co-linearity, which often cause over-fitting and instability. To overcome these problems, we applied partial least squares (PLS) regression to resting-state functional magnetic resonance imaging (rs-fMRI) data, creating a low-dimensional representation that relates symptoms to brain activity and that predicts clinical measures. Our experimental results, based upon data from clinically depressed patients and healthy controls, demonstrated that PLS and its kernel variants provided significantly better prediction of clinical measures than ordinary linear regression. Subsequent classification using predicted clinical scores distinguished depressed patients from healthy controls with 80% accuracy. Moreover, loading vectors for latent variables enabled us to identify brain regions relevant to depression, including the default mode network, the right superior frontal gyrus, and the superior motor area. PMID:28700672

Model predictive control of attitude maneuver of a geostationary flexible satellite based on genetic algorithm

NASA Astrophysics Data System (ADS)

TayyebTaher, M.; Esmaeilzadeh, S. Majid

2017-07-01

This article presents an application of Model Predictive Controller (MPC) to the attitude control of a geostationary flexible satellite. SIMO model has been used for the geostationary satellite, using the Lagrange equations. Flexibility is also included in the modelling equations. The state space equations are expressed in order to simplify the controller. Naturally there is no specific tuning rule to find the best parameters of an MPC controller which fits the desired controller. Being an intelligence method for optimizing problem, Genetic Algorithm has been used for optimizing the performance of MPC controller by tuning the controller parameter due to minimum rise time, settling time, overshoot of the target point of the flexible structure and its mode shape amplitudes to make large attitude maneuvers possible. The model included geosynchronous orbit environment and geostationary satellite parameters. The simulation results of the flexible satellite with attitude maneuver shows the efficiency of proposed optimization method in comparison with LQR optimal controller.

PREDICTING RETINOID RECEPTOR BINDING AFFINITY: COREPA-M APPLICATION

EPA Science Inventory

Retinoic acid and associated vitamin A derivatives comprise a class of endogenous hormones that activate different retinoic acid receptors RARs). Transcriptional events subsequent to this activation are key to controlling several aspects of vertebrate development. As such, identi...

Comprehensive report of aeropropulsion, space propulsion, space power, and space science applications of the Lewis Research Center

NASA Technical Reports Server (NTRS)

1988-01-01

The research activities of the Lewis Research Center for 1988 are summarized. The projects included are within basic and applied technical disciplines essential to aeropropulsion, space propulsion, space power, and space science/applications. These disciplines are materials science and technology, structural mechanics, life prediction, internal computational fluid mechanics, heat transfer, instruments and controls, and space electronics.

The Applications of Model-Based Geostatistics in Helminth Epidemiology and Control

PubMed Central

Magalhães, Ricardo J. Soares; Clements, Archie C.A.; Patil, Anand P.; Gething, Peter W.; Brooker, Simon

2011-01-01

Funding agencies are dedicating substantial resources to tackle helminth infections. Reliable maps of the distribution of helminth infection can assist these efforts by targeting control resources to areas of greatest need. The ability to define the distribution of infection at regional, national and subnational levels has been enhanced greatly by the increased availability of good quality survey data and the use of model-based geostatistics (MBG), enabling spatial prediction in unsampled locations. A major advantage of MBG risk mapping approaches is that they provide a flexible statistical platform for handling and representing different sources of uncertainty, providing plausible and robust information on the spatial distribution of infections to inform the design and implementation of control programmes. Focussing on schistosomiasis and soil-transmitted helminthiasis, with additional examples for lymphatic filariasis and onchocerciasis, we review the progress made to date with the application of MBG tools in large-scale, real-world control programmes and propose a general framework for their application to inform integrative spatial planning of helminth disease control programmes. PMID:21295680

Predictive control strategy of a gas turbine for improvement of combined cycle power plant dynamic performance and efficiency.

PubMed

Mohamed, Omar; Wang, Jihong; Khalil, Ashraf; Limhabrash, Marwan

2016-01-01

This paper presents a novel strategy for implementing model predictive control (MPC) to a large gas turbine power plant as a part of our research progress in order to improve plant thermal efficiency and load-frequency control performance. A generalized state space model for a large gas turbine covering the whole steady operational range is designed according to subspace identification method with closed loop data as input to the identification algorithm. Then the model is used in developing a MPC and integrated into the plant existing control strategy. The strategy principle is based on feeding the reference signals of the pilot valve, natural gas valve, and the compressor pressure ratio controller with the optimized decisions given by the MPC instead of direct application of the control signals. If the set points for the compressor controller and turbine valves are sent in a timely manner, there will be more kinetic energy in the plant to release faster responses on the output and the overall system efficiency is improved. Simulation results have illustrated the feasibility of the proposed application that has achieved significant improvement in the frequency variations and load following capability which are also translated to be improvements in the overall combined cycle thermal efficiency of around 1.1 % compared to the existing one.

Input filter compensation for switching regulators

NASA Technical Reports Server (NTRS)

Lee, F. C.

1984-01-01

Problems caused by input filter interaction and conventional input filter design techniques are discussed. The concept of feedforward control is modeled with an input filter and a buck regulator. Experimental measurement and comparison to the analytical predictions is carried out. Transient response and the use of a feedforward loop to stabilize the regulator system is described. Other possible applications for feedforward control are included.

Health Management Applications for International Space Station

NASA Technical Reports Server (NTRS)

Alena, Richard; Duncavage, Dan

2005-01-01

Traditional mission and vehicle management involves teams of highly trained specialists monitoring vehicle status and crew activities, responding rapidly to any anomalies encountered during operations. These teams work from the Mission Control Center and have access to engineering support teams with specialized expertise in International Space Station (ISS) subsystems. Integrated System Health Management (ISHM) applications can significantly augment these capabilities by providing enhanced monitoring, prognostic and diagnostic tools for critical decision support and mission management. The Intelligent Systems Division of NASA Ames Research Center is developing many prototype applications using model-based reasoning, data mining and simulation, working with Mission Control through the ISHM Testbed and Prototypes Project. This paper will briefly describe information technology that supports current mission management practice, and will extend this to a vision for future mission control workflow incorporating new ISHM applications. It will describe ISHM applications currently under development at NASA and will define technical approaches for implementing our vision of future human exploration mission management incorporating artificial intelligence and distributed web service architectures using specific examples. Several prototypes are under development, each highlighting a different computational approach. The ISStrider application allows in-depth analysis of Caution and Warning (C&W) events by correlating real-time telemetry with the logical fault trees used to define off-nominal events. The application uses live telemetry data and the Livingstone diagnostic inference engine to display the specific parameters and fault trees that generated the C&W event, allowing a flight controller to identify the root cause of the event from thousands of possibilities by simply navigating animated fault tree models on their workstation. SimStation models the functional power flow for the ISS Electrical Power System and can predict power balance for nominal and off-nominal conditions. SimStation uses realtime telemetry data to keep detailed computational physics models synchronized with actual ISS power system state. In the event of failure, the application can then rapidly diagnose root cause, predict future resource levels and even correlate technical documents relevant to the specific failure. These advanced computational models will allow better insight and more precise control of ISS subsystems, increasing safety margins by speeding up anomaly resolution and reducing,engineering team effort and cost. This technology will make operating ISS more efficient and is directly applicable to next-generation exploration missions and Crew Exploration Vehicles.

Application of Output Predictive Algorithmic Control to a Terrain Following Aircraft System.

DTIC Science & Technology

1982-03-01

non-linear regime the results from an optimal control solution may be questionable. 15 -**—• - •*- "•—"".’" CHAPTER 3 Output Prpdirl- ivf ...strongly influenced by two other factors as well - the sample time T and the least-squares cost function Q. unlike the deadbeat control law of Ref...design of aircraft control systems since these methods offer tremendous insight into the dynamic behavior of the system at relatively low cost . However

Status and trends in active control technology

NASA Technical Reports Server (NTRS)

Rediess, H. A.; Szalai, K. J.

1975-01-01

The emergence of highly reliable fly-by-wire flight control systems makes it possible to consider a strong reliance on automatic control systems in the design optimization of future aircraft. This design philosophy has been referred to as the control configured vehicle approach or the application of active control technology. Several studies and flight tests sponsored by the Air Force and NASA have demonstrated the potential benefits of control configured vehicles and active control technology. The present status and trends of active control technology are reviewed and the impact it will have on aircraft designs, design techniques, and the designer is predicted.

An Open Source Rapid Computer Aided Control System Design Toolchain Using Scilab, Scicos and RTAI Linux

NASA Astrophysics Data System (ADS)

Bouchpan-Lerust-Juéry, L.

2007-08-01

Current and next generation on-board computer systems tend to implement real-time embedded control applications (e.g. Attitude and Orbit Control Subsystem (AOCS), Packet Utililization Standard (PUS), spacecraft autonomy . . . ) which must meet high standards of Reliability and Predictability as well as Safety. All these requirements require a considerable amount of effort and cost for Space Sofware Industry. This paper, in a first part, presents a free Open Source integrated solution to develop RTAI applications from analysis, design, simulation and direct implementation using code generation based on Open Source and in its second part summarises this suggested approach, its results and the conclusion for further work.

Predictability of extremes in non-linear hierarchically organized systems

NASA Astrophysics Data System (ADS)

Kossobokov, V. G.; Soloviev, A.

2011-12-01

Understanding the complexity of non-linear dynamics of hierarchically organized systems progresses to new approaches in assessing hazard and risk of the extreme catastrophic events. In particular, a series of interrelated step-by-step studies of seismic process along with its non-stationary though self-organized behaviors, has led already to reproducible intermediate-term middle-range earthquake forecast/prediction technique that has passed control in forward real-time applications during the last two decades. The observed seismic dynamics prior to and after many mega, great, major, and strong earthquakes demonstrate common features of predictability and diverse behavior in course durable phase transitions in complex hierarchical non-linear system of blocks-and-faults of the Earth lithosphere. The confirmed fractal nature of earthquakes and their distribution in space and time implies that many traditional estimations of seismic hazard (from term-less to short-term ones) are usually based on erroneous assumptions of easy tractable analytical models, which leads to widespread practice of their deceptive application. The consequences of underestimation of seismic hazard propagate non-linearly into inflicted underestimation of risk and, eventually, into unexpected societal losses due to earthquakes and associated phenomena (i.e., collapse of buildings, landslides, tsunamis, liquefaction, etc.). The studies aimed at forecast/prediction of extreme events (interpreted as critical transitions) in geophysical and socio-economical systems include: (i) large earthquakes in geophysical systems of the lithosphere blocks-and-faults, (ii) starts and ends of economic recessions, (iii) episodes of a sharp increase in the unemployment rate, (iv) surge of the homicides in socio-economic systems. These studies are based on a heuristic search of phenomena preceding critical transitions and application of methodologies of pattern recognition of infrequent events. Any study of rare phenomena of highly complex origin, by their nature, implies using problem oriented methods, which design breaks the limits of classical statistical or econometric applications. The unambiguously designed forecast/prediction algorithms of the "yes or no" variety, analyze the observable quantitative integrals and indicators available to a given date, then provides unambiguous answer to the question whether a critical transition should be expected or not in the next time interval. Since the predictability of an originating non-linear dynamical system is limited in principle, the probabilistic component of forecast/prediction algorithms is represented by the empirical probabilities of alarms, on one side, and failures-to-predict, on the other, estimated on control sets achieved in the retro- and prospective experiments. Predicting in advance is the only decisive test of forecast/predictions and the relevant on-going experiments are conducted in the case seismic extremes, recessions, and increases of unemployment rate. The results achieved in real-time testing keep being encouraging and confirm predictability of the extremes.

The Theory of Planned Behavior as a Predictor of HIV Testing Intention.

PubMed

Ayodele, Olabode

2017-03-01

This investigation tests the theory of planned behavior (TPB) as a predictor of HIV testing intention among Nigerian university undergraduate students. A cross-sectional study of 392 students was conducted using a self-administered structured questionnaire that measured socio-demographics, perceived risk of human immunodeficiency virus (HIV) infection, and TPB constructs. Analysis was based on 273 students who had never been tested for HIV. Hierarchical multiple regression analysis assessed the applicability of the TPB in predicting HIV testing intention and additional predictive value of perceived risk of HIV infection. The prediction model containing TPB constructs explained 35% of the variance in HIV testing intention, with attitude and perceived behavioral control making significant and unique contributions to intention. Perceived risk of HIV infection contributed marginally (2%) but significantly to the final prediction model. Findings supported the TPB in predicting HIV testing intention. Although future studies must determine the generalizability of these results, the findings highlight the importance of perceived behavioral control, attitude, and perceived risk of HIV infection in the prediction of HIV testing intention among students who have not previously tested for HIV.

Schistosomes, snails and satellites.

PubMed

Brooker, S

2002-05-01

This paper gives an overview of the recent progress made in the use and application of geographical information systems (GIS) and remotely sensed (RS) satellite sensor data for the epidemiology and control of schistosomiasis in sub-Saharan Africa. Details are given of the use of GIS to collate, map and analyse available parasitological data. The use of RS data to understand better the broad scale environmental factors influencing schistosome distribution is defined and examples detailed for the prediction of schistosomiasis in unsampled areas. Finally, the current practical application of GIS and remote sensing are reviewed in the context of national control programmes.

Estimate of Errors of Pressure Predictions Without Meteorological Forecasts

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

Not Available

1957-07-31

Independent methods of estimating pressure were considered-- the range of application in height is from that of baro-fuzed tactical weapons (a few thousand feet) to that of the control of height of aircraft at high altitude (45,000 feet).

Development of an operationally efficient PTC braking enforcement algorithm for freight trains.

DOT National Transportation Integrated Search

2013-08-01

Software algorithms used in positive train control (PTC) systems designed to predict freight train stopping distance and enforce a penalty brake application have been shown to be overly conservative, which can lead to operational inefficiencies by in...

Deep learning and model predictive control for self-tuning mode-locked lasers

NASA Astrophysics Data System (ADS)

Baumeister, Thomas; Brunton, Steven L.; Nathan Kutz, J.

2018-03-01

Self-tuning optical systems are of growing importance in technological applications such as mode-locked fiber lasers. Such self-tuning paradigms require {\\em intelligent} algorithms capable of inferring approximate models of the underlying physics and discovering appropriate control laws in order to maintain robust performance for a given objective. In this work, we demonstrate the first integration of a {\\em deep learning} (DL) architecture with {\\em model predictive control} (MPC) in order to self-tune a mode-locked fiber laser. Not only can our DL-MPC algorithmic architecture approximate the unknown fiber birefringence, it also builds a dynamical model of the laser and appropriate control law for maintaining robust, high-energy pulses despite a stochastically drifting birefringence. We demonstrate the effectiveness of this method on a fiber laser which is mode-locked by nonlinear polarization rotation. The method advocated can be broadly applied to a variety of optical systems that require robust controllers.

On the study of control effectiveness and computational efficiency of reduced Saint-Venant model in model predictive control of open channel flow

NASA Astrophysics Data System (ADS)

Xu, M.; van Overloop, P. J.; van de Giesen, N. C.

2011-02-01

Model predictive control (MPC) of open channel flow is becoming an important tool in water management. The complexity of the prediction model has a large influence on the MPC application in terms of control effectiveness and computational efficiency. The Saint-Venant equations, called SV model in this paper, and the Integrator Delay (ID) model are either accurate but computationally costly, or simple but restricted to allowed flow changes. In this paper, a reduced Saint-Venant (RSV) model is developed through a model reduction technique, Proper Orthogonal Decomposition (POD), on the SV equations. The RSV model keeps the main flow dynamics and functions over a large flow range but is easier to implement in MPC. In the test case of a modeled canal reach, the number of states and disturbances in the RSV model is about 45 and 16 times less than the SV model, respectively. The computational time of MPC with the RSV model is significantly reduced, while the controller remains effective. Thus, the RSV model is a promising means to balance the control effectiveness and computational efficiency.

Improving Disease Prediction by Incorporating Family Disease History in Risk Prediction Models with Large-Scale Genetic Data.

PubMed

Gim, Jungsoo; Kim, Wonji; Kwak, Soo Heon; Choi, Hosik; Park, Changyi; Park, Kyong Soo; Kwon, Sunghoon; Park, Taesung; Won, Sungho

2017-11-01

Despite the many successes of genome-wide association studies (GWAS), the known susceptibility variants identified by GWAS have modest effect sizes, leading to notable skepticism about the effectiveness of building a risk prediction model from large-scale genetic data. However, in contrast to genetic variants, the family history of diseases has been largely accepted as an important risk factor in clinical diagnosis and risk prediction. Nevertheless, the complicated structures of the family history of diseases have limited their application in clinical practice. Here, we developed a new method that enables incorporation of the general family history of diseases with a liability threshold model, and propose a new analysis strategy for risk prediction with penalized regression analysis that incorporates both large numbers of genetic variants and clinical risk factors. Application of our model to type 2 diabetes in the Korean population (1846 cases and 1846 controls) demonstrated that single-nucleotide polymorphisms accounted for 32.5% of the variation explained by the predicted risk scores in the test data set, and incorporation of family history led to an additional 6.3% improvement in prediction. Our results illustrate that family medical history provides valuable information on the variation of complex diseases and improves prediction performance. Copyright © 2017 by the Genetics Society of America.

Are there reliable constitutive laws for dynamic friction?

PubMed

Woodhouse, Jim; Putelat, Thibaut; McKay, Andrew

2015-09-28

Structural vibration controlled by interfacial friction is widespread, ranging from friction dampers in gas turbines to the motion of violin strings. To predict, control or prevent such vibration, a constitutive description of frictional interactions is inevitably required. A variety of friction models are discussed to assess their scope and validity, in the light of constraints provided by different experimental observations. Three contrasting case studies are used to illustrate how predicted behaviour can be extremely sensitive to the choice of frictional constitutive model, and to explore possible experimental paths to discriminate between and calibrate dynamic friction models over the full parameter range needed for real applications. © 2015 The Author(s).

Predicting Physical Time Series Using Dynamic Ridge Polynomial Neural Networks

PubMed Central

Al-Jumeily, Dhiya; Ghazali, Rozaida; Hussain, Abir

2014-01-01

Forecasting naturally occurring phenomena is a common problem in many domains of science, and this has been addressed and investigated by many scientists. The importance of time series prediction stems from the fact that it has wide range of applications, including control systems, engineering processes, environmental systems and economics. From the knowledge of some aspects of the previous behaviour of the system, the aim of the prediction process is to determine or predict its future behaviour. In this paper, we consider a novel application of a higher order polynomial neural network architecture called Dynamic Ridge Polynomial Neural Network that combines the properties of higher order and recurrent neural networks for the prediction of physical time series. In this study, four types of signals have been used, which are; The Lorenz attractor, mean value of the AE index, sunspot number, and heat wave temperature. The simulation results showed good improvements in terms of the signal to noise ratio in comparison to a number of higher order and feedforward neural networks in comparison to the benchmarked techniques. PMID:25157950

Predicting physical time series using dynamic ridge polynomial neural networks.

PubMed

Al-Jumeily, Dhiya; Ghazali, Rozaida; Hussain, Abir

2014-01-01

Forecasting naturally occurring phenomena is a common problem in many domains of science, and this has been addressed and investigated by many scientists. The importance of time series prediction stems from the fact that it has wide range of applications, including control systems, engineering processes, environmental systems and economics. From the knowledge of some aspects of the previous behaviour of the system, the aim of the prediction process is to determine or predict its future behaviour. In this paper, we consider a novel application of a higher order polynomial neural network architecture called Dynamic Ridge Polynomial Neural Network that combines the properties of higher order and recurrent neural networks for the prediction of physical time series. In this study, four types of signals have been used, which are; The Lorenz attractor, mean value of the AE index, sunspot number, and heat wave temperature. The simulation results showed good improvements in terms of the signal to noise ratio in comparison to a number of higher order and feedforward neural networks in comparison to the benchmarked techniques.

Predictive and Reactive Grip Force Responses to Rapid Load Increases in People With Multiple Sclerosis.

PubMed

Allgöwer, Kathrin; Kern, Claudia; Hermsdörfer, Joachim

2017-03-01

To determine the effects of multiple sclerosis (MS) on predictive and reactive grip force control in a catching task and on clinical tests of hand function. Case-control study with matched-pairs control group. University prevention and rehabilitation center. Participants (N=30) consisted of people with multiple sclerosis (PwMS) (n=15) and healthy controls (n=15), matched for sex, age, and hand dominance. Not applicable. Performance on the Expanded Disability Status Scale (EDSS), Nine-Hole Peg Test (9-HPT), Jebsen-Taylor Hand Function Test (JTHFT), and 2-point discrimination (2PD) was evaluated. To analyze grip force control, blindfolded subjects held a receptacle equipped with grip force and acceleration sensors in their hand. In a catching task, a weight was dropped from (1) the experimenter's hand unexpectedly into the receptacle (reactive force control); and (2) from the subject's opposite hand (predictive force control). Grip forces and time lags were analyzed. PwMS (mean EDSS ± SD, 4.2±1.86) had impairments in the 9-HPT and JTHFT (P<.001). The 2PD did not differ significantly between PwMS and controls. During reactive force control (catching task 1), PwMS showed significantly higher grip forces immediately after impact (P<.05), and a significant prolongation of the time from grip force increase until reaching the peak of grip force (P<.001). PwMS and controls did not differ during predictive force control (catching task 2; P>.1). Exaggerated grip force responses and alterations of timing after an unpredictable perturbation, combined with preserved grip force control during predictable conditions, is a characteristic pattern of fine motor control deficits in MS. Measures of reactive grip force responses may be used to complement neurologic assessments. Further studies exploring the usefulness of these measures should be performed in a broader community of PwMS. Copyright © 2016 American Congress of Rehabilitation Medicine. Published by Elsevier Inc. All rights reserved.

Operational flood control of a low-lying delta system using large time step Model Predictive Control

NASA Astrophysics Data System (ADS)

Tian, Xin; van Overloop, Peter-Jules; Negenborn, Rudy R.; van de Giesen, Nick

2015-01-01

The safety of low-lying deltas is threatened not only by riverine flooding but by storm-induced coastal flooding as well. For the purpose of flood control, these deltas are mostly protected in a man-made environment, where dikes, dams and other adjustable infrastructures, such as gates, barriers and pumps are widely constructed. Instead of always reinforcing and heightening these structures, it is worth considering making the most of the existing infrastructure to reduce the damage and manage the delta in an operational and overall way. In this study, an advanced real-time control approach, Model Predictive Control, is proposed to operate these structures in the Dutch delta system (the Rhine-Meuse delta). The application covers non-linearity in the dynamic behavior of the water system and the structures. To deal with the non-linearity, a linearization scheme is applied which directly uses the gate height instead of the structure flow as the control variable. Given the fact that MPC needs to compute control actions in real-time, we address issues regarding computational time. A new large time step scheme is proposed in order to save computation time, in which different control variables can have different control time steps. Simulation experiments demonstrate that Model Predictive Control with the large time step setting is able to control a delta system better and much more efficiently than the conventional operational schemes.

Biomedical Informatics Approaches to Identifying Drug-Drug Interactions: Application to Insulin Secretagogues

PubMed Central

Han, Xu; Chiang, ChienWei; Leonard, Charles E.; Bilker, Warren B.; Brensinger, Colleen M.; Li, Lang; Hennessy, Sean

2017-01-01

Background Drug-drug interactions with insulin secretagogues are associated with increased risk of serious hypoglycemia in patients with type 2 diabetes. We aimed to systematically screen for drugs that interact with the five most commonly used secretagogues―glipizide, glyburide, glimepiride, repaglinide, and nateglinide―to cause serious hypoglycemia. Methods We screened 400 drugs frequently co-prescribed with the secretagogues as candidate interacting precipitants. We first predicted the drug–drug interaction potential based on the pharmacokinetics of each secretagogue–precipitant pair. We then performed pharmacoepidemiologic screening for each secretagogue of interest, and for metformin as a negative control, using an administrative claims database and the self-controlled case series design. The overall rate ratios (RRs) and those for four predefined risk periods were estimated using Poisson regression. The RRs were adjusted for multiple estimation using semi-Bayes method, and then adjusted for metformin results to distinguish native effects of the precipitant from a drug–drug interaction. Results We predicted 34 pharmacokinetic drug–drug interactions with the secretagogues, nine moderate and 25 weak. There were 140 and 61 secretagogue–precipitant pairs associated with increased rates of serious hypoglycemia before and after the metformin adjustment, respectively. The results from pharmacokinetic prediction correlated poorly with those from pharmacoepidemiologic screening. Conclusions The self-controlled case series design has the potential to be widely applicable to screening for drug–drug interactions that lead to adverse outcomes identifiable in healthcare databases. Coupling pharmacokinetic prediction with pharmacoepidemiologic screening did not notably improve the ability to identify drug–drug interactions in this case. PMID:28169935

The BioMedical Admissions Test for medical student selection: issues of fairness and bias.

PubMed

Emery, Joanne L; Bell, John F; Vidal Rodeiro, Carmen L

2011-01-01

The BioMedical Admissions Test (BMAT) forms part of the undergraduate medical admission process at the University of Cambridge. The fairness of admissions tests is an important issue. Aims were to investigate the relationships between applicants' background variables and BMAT scores, whether they were offered a place or rejected and, for those admitted, performance on the first year course examinations. Multilevel regression models were employed with data from three combined applicant cohorts. Admission rates for different groups were investigated with and without controlling for BMAT performance. The fairness of the BMAT was investigated by determining, for those admitted, whether scores predicted examination performance equitably. Despite some differences in applicants' BMAT performance (e.g. by school type and gender), BMAT scores predicted mean examination marks equitably for all background variables considered. The probability of achieving a 1st class examination result, however, was slightly under-predicted for those admitted from schools and colleges entering relatively few applicants. Not all differences in admission rates were accounted for by BMAT performance. However, the test constitutes only one part of a compensatory admission system in which other factors, such as interview performance, are important considerations. Results are in support of the equity of the BMAT.

Sense and Respond Logistics: Integrating Prediction, Responsiveness, and Control Capabilities

DTIC Science & Technology

2006-01-01

logistics SAR sense and respond SCM Supply Chain Management SCN Supply Chain Network SIDA sense, interpret, decide, act SOS source of supply TCN...commodity supply chain management ( SCM ), will have WS- SCMs that focus on integrating information for a particular MDS. 8 In the remainder of this...developed applications of ABMs for SCM .21 Applications of Agents and Agent-Based Modeling Agents have been used in telecommunications, e-commerce

A distributed predictive control approach for periodic flow-based networks: application to drinking water systems

NASA Astrophysics Data System (ADS)

Grosso, Juan M.; Ocampo-Martinez, Carlos; Puig, Vicenç

2017-10-01

This paper proposes a distributed model predictive control approach designed to work in a cooperative manner for controlling flow-based networks showing periodic behaviours. Under this distributed approach, local controllers cooperate in order to enhance the performance of the whole flow network avoiding the use of a coordination layer. Alternatively, controllers use both the monolithic model of the network and the given global cost function to optimise the control inputs of the local controllers but taking into account the effect of their decisions over the remainder subsystems conforming the entire network. In this sense, a global (all-to-all) communication strategy is considered. Although the Pareto optimality cannot be reached due to the existence of non-sparse coupling constraints, the asymptotic convergence to a Nash equilibrium is guaranteed. The resultant strategy is tested and its effectiveness is shown when applied to a large-scale complex flow-based network: the Barcelona drinking water supply system.

Fatigue response of perforated titanium for application in laminar flow control

NASA Technical Reports Server (NTRS)

Johnson, W. Steven; Miller, Jennifer L.; Newman, Jr., James

1996-01-01

The room temperature tensile and fatigue response of non-perforated and perforated titanium for laminar flow control application was investigated both experimentally and analytically. Results showed that multiple perforations did not affect the tensile response, but did reduce the fatigue life. A two dimensional finite element stress analysis was used to determine that the stress fields from adjacent perforations did not influence one another. The stress fields around the holes did not overlap one another, allowing the materials to be modeled as a plate with a center hole. Fatigue life was predicted using an equivalent MW flow size approach to relate the experimental results to microstructural features of the titanium. Predictions using flaw sizes ranging from 1 to 15 microns correlated within a factor of 2 with the experimental results by using a flow stress of 260 MPa. By using two different flow stresses in the crack closure model and correcting for plasticity, the experimental results were bounded by the predictions for high applied stresses. Further analysis of the complex geometry of the perforations and the local material chemistry is needed to further understand the fatigue behavior of the perforated titanium.

Real Time Optimal Control of Supercapacitor Operation for Frequency Response

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

Luo, Yusheng; Panwar, Mayank; Mohanpurkar, Manish

2016-07-01

Supercapacitors are gaining wider applications in power systems due to fast dynamic response. Utilizing supercapacitors by means of power electronics interfaces for power compensation is a proven effective technique. For applications such as requency restoration if the cost of supercapacitors maintenance as well as the energy loss on the power electronics interfaces are addressed. It is infeasible to use traditional optimization control methods to mitigate the impacts of frequent cycling. This paper proposes a Front End Controller (FEC) using Generalized Predictive Control featuring real time receding optimization. The optimization constraints are based on cost and thermal management to enhance tomore » the utilization efficiency of supercapacitors. A rigorous mathematical derivation is conducted and test results acquired from Digital Real Time Simulator are provided to demonstrate effectiveness.« less

Watershed Management Tool for Selection and Spacial Allocation of Non-Point Source Pollution Control Practices

EPA Science Inventory

Distributed-parameter watershed models are often utilized for evaluating the effectiveness of sediment and nutrient abatement strategies through the traditional {calibrate→ validate→ predict} approach. The applicability of the method is limited due to modeling approximations. In ...

Collaborative development of predictive toxicology applications

PubMed Central

2010-01-01

OpenTox provides an interoperable, standards-based Framework for the support of predictive toxicology data management, algorithms, modelling, validation and reporting. It is relevant to satisfying the chemical safety assessment requirements of the REACH legislation as it supports access to experimental data, (Quantitative) Structure-Activity Relationship models, and toxicological information through an integrating platform that adheres to regulatory requirements and OECD validation principles. Initial research defined the essential components of the Framework including the approach to data access, schema and management, use of controlled vocabularies and ontologies, architecture, web service and communications protocols, and selection and integration of algorithms for predictive modelling. OpenTox provides end-user oriented tools to non-computational specialists, risk assessors, and toxicological experts in addition to Application Programming Interfaces (APIs) for developers of new applications. OpenTox actively supports public standards for data representation, interfaces, vocabularies and ontologies, Open Source approaches to core platform components, and community-based collaboration approaches, so as to progress system interoperability goals. The OpenTox Framework includes APIs and services for compounds, datasets, features, algorithms, models, ontologies, tasks, validation, and reporting which may be combined into multiple applications satisfying a variety of different user needs. OpenTox applications are based on a set of distributed, interoperable OpenTox API-compliant REST web services. The OpenTox approach to ontology allows for efficient mapping of complementary data coming from different datasets into a unifying structure having a shared terminology and representation. Two initial OpenTox applications are presented as an illustration of the potential impact of OpenTox for high-quality and consistent structure-activity relationship modelling of REACH-relevant endpoints: ToxPredict which predicts and reports on toxicities for endpoints for an input chemical structure, and ToxCreate which builds and validates a predictive toxicity model based on an input toxicology dataset. Because of the extensible nature of the standardised Framework design, barriers of interoperability between applications and content are removed, as the user may combine data, models and validation from multiple sources in a dependable and time-effective way. PMID:20807436

Collaborative development of predictive toxicology applications.

PubMed

Hardy, Barry; Douglas, Nicki; Helma, Christoph; Rautenberg, Micha; Jeliazkova, Nina; Jeliazkov, Vedrin; Nikolova, Ivelina; Benigni, Romualdo; Tcheremenskaia, Olga; Kramer, Stefan; Girschick, Tobias; Buchwald, Fabian; Wicker, Joerg; Karwath, Andreas; Gütlein, Martin; Maunz, Andreas; Sarimveis, Haralambos; Melagraki, Georgia; Afantitis, Antreas; Sopasakis, Pantelis; Gallagher, David; Poroikov, Vladimir; Filimonov, Dmitry; Zakharov, Alexey; Lagunin, Alexey; Gloriozova, Tatyana; Novikov, Sergey; Skvortsova, Natalia; Druzhilovsky, Dmitry; Chawla, Sunil; Ghosh, Indira; Ray, Surajit; Patel, Hitesh; Escher, Sylvia

2010-08-31

OpenTox provides an interoperable, standards-based Framework for the support of predictive toxicology data management, algorithms, modelling, validation and reporting. It is relevant to satisfying the chemical safety assessment requirements of the REACH legislation as it supports access to experimental data, (Quantitative) Structure-Activity Relationship models, and toxicological information through an integrating platform that adheres to regulatory requirements and OECD validation principles. Initial research defined the essential components of the Framework including the approach to data access, schema and management, use of controlled vocabularies and ontologies, architecture, web service and communications protocols, and selection and integration of algorithms for predictive modelling. OpenTox provides end-user oriented tools to non-computational specialists, risk assessors, and toxicological experts in addition to Application Programming Interfaces (APIs) for developers of new applications. OpenTox actively supports public standards for data representation, interfaces, vocabularies and ontologies, Open Source approaches to core platform components, and community-based collaboration approaches, so as to progress system interoperability goals.The OpenTox Framework includes APIs and services for compounds, datasets, features, algorithms, models, ontologies, tasks, validation, and reporting which may be combined into multiple applications satisfying a variety of different user needs. OpenTox applications are based on a set of distributed, interoperable OpenTox API-compliant REST web services. The OpenTox approach to ontology allows for efficient mapping of complementary data coming from different datasets into a unifying structure having a shared terminology and representation.Two initial OpenTox applications are presented as an illustration of the potential impact of OpenTox for high-quality and consistent structure-activity relationship modelling of REACH-relevant endpoints: ToxPredict which predicts and reports on toxicities for endpoints for an input chemical structure, and ToxCreate which builds and validates a predictive toxicity model based on an input toxicology dataset. Because of the extensible nature of the standardised Framework design, barriers of interoperability between applications and content are removed, as the user may combine data, models and validation from multiple sources in a dependable and time-effective way.

Efficient Machine Learning Approach for Optimizing Scientific Computing Applications on Emerging HPC Architectures

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

Arumugam, Kamesh

Efficient parallel implementations of scientific applications on multi-core CPUs with accelerators such as GPUs and Xeon Phis is challenging. This requires - exploiting the data parallel architecture of the accelerator along with the vector pipelines of modern x86 CPU architectures, load balancing, and efficient memory transfer between different devices. It is relatively easy to meet these requirements for highly structured scientific applications. In contrast, a number of scientific and engineering applications are unstructured. Getting performance on accelerators for these applications is extremely challenging because many of these applications employ irregular algorithms which exhibit data-dependent control-ow and irregular memory accesses. Furthermore,more » these applications are often iterative with dependency between steps, and thus making it hard to parallelize across steps. As a result, parallelism in these applications is often limited to a single step. Numerical simulation of charged particles beam dynamics is one such application where the distribution of work and memory access pattern at each time step is irregular. Applications with these properties tend to present significant branch and memory divergence, load imbalance between different processor cores, and poor compute and memory utilization. Prior research on parallelizing such irregular applications have been focused around optimizing the irregular, data-dependent memory accesses and control-ow during a single step of the application independent of the other steps, with the assumption that these patterns are completely unpredictable. We observed that the structure of computation leading to control-ow divergence and irregular memory accesses in one step is similar to that in the next step. It is possible to predict this structure in the current step by observing the computation structure of previous steps. In this dissertation, we present novel machine learning based optimization techniques to address the parallel implementation challenges of such irregular applications on different HPC architectures. In particular, we use supervised learning to predict the computation structure and use it to address the control-ow and memory access irregularities in the parallel implementation of such applications on GPUs, Xeon Phis, and heterogeneous architectures composed of multi-core CPUs with GPUs or Xeon Phis. We use numerical simulation of charged particles beam dynamics simulation as a motivating example throughout the dissertation to present our new approach, though they should be equally applicable to a wide range of irregular applications. The machine learning approach presented here use predictive analytics and forecasting techniques to adaptively model and track the irregular memory access pattern at each time step of the simulation to anticipate the future memory access pattern. Access pattern forecasts can then be used to formulate optimization decisions during application execution which improves the performance of the application at a future time step based on the observations from earlier time steps. In heterogeneous architectures, forecasts can also be used to improve the memory performance and resource utilization of all the processing units to deliver a good aggregate performance. We used these optimization techniques and anticipation strategy to design a cache-aware, memory efficient parallel algorithm to address the irregularities in the parallel implementation of charged particles beam dynamics simulation on different HPC architectures. Experimental result using a diverse mix of HPC architectures shows that our approach in using anticipation strategy is effective in maximizing data reuse, ensuring workload balance, minimizing branch and memory divergence, and in improving resource utilization.« less

A fuzzy model of superelastic shape memory alloys for vibration control in civil engineering applications

NASA Astrophysics Data System (ADS)

Ozbulut, O. E.; Mir, C.; Moroni, M. O.; Sarrazin, M.; Roschke, P. N.

2007-06-01

Two experimental test programs are conducted to collect data and simulate the dynamic behavior of CuAlBe shape memory alloy (SMA) wires. First, in order to evaluate the effect of temperature changes on superelastic SMA wires, a large number of cyclic, sinusoidal, tensile tests are performed at 1 Hz. These tests are conducted in a controlled environment at 0, 25 and 50 °C with three different strain amplitudes. Second, in order to assess the dynamic effects of the material, a series of laboratory experiments is conducted on a shake table with a scale model of a three-story structure that is stiffened with SMA wires. Data from these experiments are used to create fuzzy inference systems (FISs) that can predict hysteretic behavior of CuAlBe wire. Both fuzzy models employ a total of three input variables (strain, strain-rate, and temperature or pre-stress) and an output variable (predicted stress). Gaussian membership functions are used to fuzzify data for each of the input and output variables. Values of the initially assigned membership functions are adjusted using a neural-fuzzy procedure to more accurately predict the correct stress level in the wires. Results of the trained FISs are validated using test results from experimental records that had not been previously used in the training procedure. Finally, a set of numerical simulations is conducted to illustrate practical use of these wires in a civil engineering application. The results reveal the applicability for structural vibration control of pseudoelastic CuAlBe wire whose highly nonlinear behavior is modeled by a simple, accurate, and computationally efficient FIS.

Artificial neural networks and approximate reasoning for intelligent control in space

NASA Technical Reports Server (NTRS)

Berenji, Hamid R.

1991-01-01

A method is introduced for learning to refine the control rules of approximate reasoning-based controllers. A reinforcement-learning technique is used in conjunction with a multi-layer neural network model of an approximate reasoning-based controller. The model learns by updating its prediction of the physical system's behavior. The model can use the control knowledge of an experienced operator and fine-tune it through the process of learning. Some of the space domains suitable for applications of the model such as rendezvous and docking, camera tracking, and tethered systems control are discussed.

Application of Multivariable Model Predictive Advanced Control for a 2×310T/H CFB Boiler Unit

NASA Astrophysics Data System (ADS)

Weijie, Zhao; Zongllao, Dai; Rong, Gou; Wengan, Gong

When a CFB boiler is in automatic control, there are strong interactions between various process variables and inverse response characteristics of bed temperature control target. Conventional Pill control strategy cannot deliver satisfactory control demand. Kalman wave filter technology is used to establish a non-linear combustion model, based on the CFB combustion characteristics of bed fuel inventory, heating values, bed lime inventory and consumption. CFB advanced combustion control utilizes multivariable model predictive control technology to optimize primary and secondary air flow, bed temperature, air flow, fuel flow and heat flux. In addition to providing advanced combustion control to 2×310t/h CFB+1×100MW extraction condensing turbine generator unit, the control also provides load allocation optimization and advanced control for main steam pressure, combustion and temperature. After the successful implementation, under 10% load change, main steam pressure varied less than ±0.07MPa, temperature less than ±1°C, bed temperature less than ±4°C, and air flow (O2) less than ±0.4%.

Design and implementation of a beam-waveguide mirror control system for vernier pointing of the DSS-13 antenna

NASA Technical Reports Server (NTRS)

Alvarez, L. S.; Moore, M.; Veruttipong, W.; Andres, E.

1994-01-01

The design and implementation of an antenna beam-waveguide (BWG) mirror position control system at the DSS-13 34-m antenna is presented. While it has several potential applications, a positioner on the last flat-plate BWG mirror (M6) at DSS 13 is installed to demonstrate the conical scan (conscan) angle-tracking technique at the Ka-band (32-GHz) operating frequency. Radio frequency (RF) beam-scanning predictions for the M6 mirror, computed from a diffraction analysis, are presented. From these predictions, position control system requirements are then derived. The final mechanical positioner and servo system designs, as implemented at DSS 13, are illustrated with detailed design descriptions given in the appendices. Preliminary measurements of antenna Ka-band beam scan versus M6 mirror tilt made at DSS 13 in December 1993 are presented. After reduction, the initial measurements are shown to be in agreement with the RF predicts. Plans for preliminary conscan experimentation at DSS 13 are summarized.

Trajectory Orientation: A Technology-Enabled Concept Requiring a Shift in Controller Roles and Responsibilities

NASA Technical Reports Server (NTRS)

Leiden, Ken; Green, Steven

2000-01-01

The development of a decision support tool (DST) for the en-route domain with accurate conflict prediction time horizons of 20 minutes has introduced an interesting problem. A 20 minute time horizon for conflict prediction often results in the predicted conflict occurring one or more sectors downstream from the sector controller who "owns" (i-e., is responsible for the safe separation of aircraft) one or both of the aircraft in the conflict pair. Based on current roles and responsibilities of today's en route controllers, the upstream controller would not resolve this conflict. In most cases, the downstream controller would wait until the conflicting aircraft entered higher sector before resolving the conflict. This results in a delay of several minutes from the time when the conflict was initially predicted. This delay is inefficient from both a controller workload and user's cost of operations perspective. Trajectory orientation, a new concept for facilitating an efficient, conflict-free flight path across several sectors while conforming to metering or miles-in-trail spacing, is proposed as an alternative to today's sector-oriented method. This concept necessitates a fundamental shift in thinking about inter-sector coordination. Instead of operating independently, with the main focus on protecting their internal airspace, controllers would work cooperatively, depending on each other for well-planned, conflict-free flow of aircraft. To support the trajectory orientation concept, a long time horizon (15 to 20 minutes) for conflict prediction and resolution would most likely be a primary requirement. In addition, new tools, such as controller-pilot data link will be identified to determine their necessity and applicability for trajectory orientation. Finally, with significant controller participation from selected Air Route Traffic Control Centers, potential shifts in R-side/D-side roles and responsibilities as well as the creation of a new controller position for multi-sector planning will be examined to determine the most viable solutions.

A Novel Dynamic Update Framework for Epileptic Seizure Prediction

PubMed Central

Wang, Minghui; Hong, Xiaojun; Han, Jie

2014-01-01

Epileptic seizure prediction is a difficult problem in clinical applications, and it has the potential to significantly improve the patients' daily lives whose seizures cannot be controlled by either drugs or surgery. However, most current studies of epileptic seizure prediction focus on high sensitivity and low false-positive rate only and lack the flexibility for a variety of epileptic seizures and patients' physical conditions. Therefore, a novel dynamic update framework for epileptic seizure prediction is proposed in this paper. In this framework, two basic sample pools are constructed and updated dynamically. Furthermore, the prediction model can be updated to be the most appropriate one for the prediction of seizures' arrival. Mahalanobis distance is introduced in this part to solve the problem of side information, measuring the distance between two data sets. In addition, a multichannel feature extraction method based on Hilbert-Huang transform and extreme learning machine is utilized to extract the features of a patient's preseizure state against the normal state. At last, a dynamic update epileptic seizure prediction system is built up. Simulations on Freiburg database show that the proposed system has a better performance than the one without update. The research of this paper is significantly helpful for clinical applications, especially for the exploitation of online portable devices. PMID:25050381

A novel dynamic update framework for epileptic seizure prediction.

PubMed

Han, Min; Ge, Sunan; Wang, Minghui; Hong, Xiaojun; Han, Jie

2014-01-01

Epileptic seizure prediction is a difficult problem in clinical applications, and it has the potential to significantly improve the patients' daily lives whose seizures cannot be controlled by either drugs or surgery. However, most current studies of epileptic seizure prediction focus on high sensitivity and low false-positive rate only and lack the flexibility for a variety of epileptic seizures and patients' physical conditions. Therefore, a novel dynamic update framework for epileptic seizure prediction is proposed in this paper. In this framework, two basic sample pools are constructed and updated dynamically. Furthermore, the prediction model can be updated to be the most appropriate one for the prediction of seizures' arrival. Mahalanobis distance is introduced in this part to solve the problem of side information, measuring the distance between two data sets. In addition, a multichannel feature extraction method based on Hilbert-Huang transform and extreme learning machine is utilized to extract the features of a patient's preseizure state against the normal state. At last, a dynamic update epileptic seizure prediction system is built up. Simulations on Freiburg database show that the proposed system has a better performance than the one without update. The research of this paper is significantly helpful for clinical applications, especially for the exploitation of online portable devices.

A Grammatical Approach to RNA-RNA Interaction Prediction

NASA Astrophysics Data System (ADS)

Kato, Yuki; Akutsu, Tatsuya; Seki, Hiroyuki

2007-11-01

Much attention has been paid to two interacting RNA molecules involved in post-transcriptional control of gene expression. Although there have been a few studies on RNA-RNA interaction prediction based on dynamic programming algorithm, no grammar-based approach has been proposed. The purpose of this paper is to provide a new modeling for RNA-RNA interaction based on multiple context-free grammar (MCFG). We present a polynomial time parsing algorithm for finding the most likely derivation tree for the stochastic version of MCFG, which is applicable to RNA joint secondary structure prediction including kissing hairpin loops. Also, elementary tests on RNA-RNA interaction prediction have shown that the proposed method is comparable to Alkan et al.'s method.

Comparisons of several aerodynamic methods for application to dynamic loads analyses

NASA Technical Reports Server (NTRS)

Kroll, R. I.; Miller, R. D.

1976-01-01

The results of a study are presented in which the applicability at subsonic speeds of several aerodynamic methods for predicting dynamic gust loads on aircraft, including active control systems, was examined and compared. These aerodynamic methods varied from steady state to an advanced unsteady aerodynamic formulation. Brief descriptions of the structural and aerodynamic representations and of the motion and load equations are presented. Comparisons of numerical results achieved using the various aerodynamic methods are shown in detail. From these results, aerodynamic representations for dynamic gust analyses are identified. It was concluded that several aerodynamic methods are satisfactory for dynamic gust analyses of configurations having either controls fixed or active control systems that primarily affect the low frequency rigid body aircraft response.

Optical and infrared properties of glancing angle-deposited nanostructured tungsten films

DOE PAGES

Ungaro, Craig; Shah, Ankit; Kravchenko, Ivan; ...

2015-02-06

For this study, nanotextured tungsten thin films were obtained on a stainless steel (SS) substrate using the glancing-angle-deposition (GLAD) method. It was found that the optical absorption and thermal emittance of the SS substrate can be controlled by varying the parameters used during deposition. Finite-difference time-domain (FDTD) simulations were used to predict the optical absorption and infrared (IR) reflectance spectra of the fabricated samples, and good agreement was found between simulated and measured data. FDTD simulations were also used to predict the effect of changes in the height and periodicity of the nanotextures. These simulations show that good control overmore » the absorption can be achieved by altering the height and periodicity of the nanostructure. These nanostructures were shown to be temperature stable up to 500°C with the addition of a protective HfO 2 layer. Finally, applications for this structure are explored, including a promising application for solar thermal energy systems.« less

Stimulated emission depletion microscopy resolves individual nitrogen vacancy centers in diamond nanocrystals.

PubMed

Arroyo-Camejo, Silvia; Adam, Marie-Pierre; Besbes, Mondher; Hugonin, Jean-Paul; Jacques, Vincent; Greffet, Jean-Jacques; Roch, Jean-François; Hell, Stefan W; Treussart, François

2013-12-23

Nitrogen-vacancy (NV) color centers in nanodiamonds are highly promising for bioimaging and sensing. However, resolving individual NV centers within nanodiamond particles and the controlled addressing and readout of their spin state has remained a major challenge. Spatially stochastic super-resolution techniques cannot provide this capability in principle, whereas coordinate-controlled super-resolution imaging methods, like stimulated emission depletion (STED) microscopy, have been predicted to fail in nanodiamonds. Here we show that, contrary to these predictions, STED can resolve single NV centers in 40-250 nm sized nanodiamonds with a resolution of ≈10 nm. Even multiple adjacent NVs located in single nanodiamonds can be imaged individually down to relative distances of ≈15 nm. Far-field optical super-resolution of NVs inside nanodiamonds is highly relevant for bioimaging applications of these fluorescent nanolabels. The targeted addressing and readout of individual NV(-) spins inside nanodiamonds by STED should also be of high significance for quantum sensing and information applications.

Neural network control of focal position during time-lapse microscopy of cells.

PubMed

Wei, Ling; Roberts, Elijah

2018-05-09

Live-cell microscopy is quickly becoming an indispensable technique for studying the dynamics of cellular processes. Maintaining the specimen in focus during image acquisition is crucial for high-throughput applications, especially for long experiments or when a large sample is being continuously scanned. Automated focus control methods are often expensive, imperfect, or ill-adapted to a specific application and are a bottleneck for widespread adoption of high-throughput, live-cell imaging. Here, we demonstrate a neural network approach for automatically maintaining focus during bright-field microscopy. Z-stacks of yeast cells growing in a microfluidic device were collected and used to train a convolutional neural network to classify images according to their z-position. We studied the effect on prediction accuracy of the various hyperparameters of the neural network, including downsampling, batch size, and z-bin resolution. The network was able to predict the z-position of an image with ±1 μm accuracy, outperforming human annotators. Finally, we used our neural network to control microscope focus in real-time during a 24 hour growth experiment. The method robustly maintained the correct focal position compensating for 40 μm of focal drift and was insensitive to changes in the field of view. About ~100 annotated z-stacks were required to train the network making our method quite practical for custom autofocus applications.

Fault diagnosis and fault-tolerant finite control set-model predictive control of a multiphase voltage-source inverter supplying BLDC motor.

PubMed

Salehifar, Mehdi; Moreno-Equilaz, Manuel

2016-01-01

Due to its fault tolerance, a multiphase brushless direct current (BLDC) motor can meet high reliability demand for application in electric vehicles. The voltage-source inverter (VSI) supplying the motor is subjected to open circuit faults. Therefore, it is necessary to design a fault-tolerant (FT) control algorithm with an embedded fault diagnosis (FD) block. In this paper, finite control set-model predictive control (FCS-MPC) is developed to implement the fault-tolerant control algorithm of a five-phase BLDC motor. The developed control method is fast, simple, and flexible. A FD method based on available information from the control block is proposed; this method is simple, robust to common transients in motor and able to localize multiple open circuit faults. The proposed FD and FT control algorithm are embedded in a five-phase BLDC motor drive. In order to validate the theory presented, simulation and experimental results are conducted on a five-phase two-level VSI supplying a five-phase BLDC motor. Copyright © 2015 ISA. Published by Elsevier Ltd. All rights reserved.

Model-on-Demand Predictive Control for Nonlinear Hybrid Systems With Application to Adaptive Behavioral Interventions

PubMed Central

Nandola, Naresh N.; Rivera, Daniel E.

2011-01-01

This paper presents a data-centric modeling and predictive control approach for nonlinear hybrid systems. System identification of hybrid systems represents a challenging problem because model parameters depend on the mode or operating point of the system. The proposed algorithm applies Model-on-Demand (MoD) estimation to generate a local linear approximation of the nonlinear hybrid system at each time step, using a small subset of data selected by an adaptive bandwidth selector. The appeal of the MoD approach lies in the fact that model parameters are estimated based on a current operating point; hence estimation of locations or modes governed by autonomous discrete events is achieved automatically. The local MoD model is then converted into a mixed logical dynamical (MLD) system representation which can be used directly in a model predictive control (MPC) law for hybrid systems using multiple-degree-of-freedom tuning. The effectiveness of the proposed MoD predictive control algorithm for nonlinear hybrid systems is demonstrated on a hypothetical adaptive behavioral intervention problem inspired by Fast Track, a real-life preventive intervention for improving parental function and reducing conduct disorder in at-risk children. Simulation results demonstrate that the proposed algorithm can be useful for adaptive intervention problems exhibiting both nonlinear and hybrid character. PMID:21874087

Nonlinear time-series-based adaptive control applications

NASA Technical Reports Server (NTRS)

Mohler, R. R.; Rajkumar, V.; Zakrzewski, R. R.

1991-01-01

A control design methodology based on a nonlinear time-series reference model is presented. It is indicated by highly nonlinear simulations that such designs successfully stabilize troublesome aircraft maneuvers undergoing large changes in angle of attack as well as large electric power transients due to line faults. In both applications, the nonlinear controller was significantly better than the corresponding linear adaptive controller. For the electric power network, a flexible AC transmission system with series capacitor power feedback control is studied. A bilinear autoregressive moving average reference model is identified from system data, and the feedback control is manipulated according to a desired reference state. The control is optimized according to a predictive one-step quadratic performance index. A similar algorithm is derived for control of rapid changes in aircraft angle of attack over a normally unstable flight regime. In the latter case, however, a generalization of a bilinear time-series model reference includes quadratic and cubic terms in angle of attack.

Nonlinear adaptive networks: A little theory, a few applications

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

Jones, R.D.; Qian, S.; Barnes, C.W.

1990-01-01

We present the theory of nonlinear adaptive networks and discuss a few applications. In particular, we review the theory of feedforward backpropagation networks. We than present the theory of the Connectionist Normalized Linear Spline network in both its feedforward and iterated modes. Also, we briefly discuss the theory of stochastic cellular automata. We then discuss applications to chaotic time series tidal prediction in Venice Lagoon, sonar transient detection, control of nonlinear processes, balancing a double inverted pendulum and design advice for free electron lasers. 26 refs., 23 figs.

Spatial pattern formation facilitates eradication of infectious diseases

PubMed Central

Eisinger, Dirk; Thulke, Hans-Hermann

2008-01-01

Control of animal-born diseases is a major challenge faced by applied ecologists and public health managers. To improve cost-effectiveness, the effort required to control such pathogens needs to be predicted as accurately as possible. In this context, we reviewed the anti-rabies vaccination schemes applied around the world during the past 25 years. We contrasted predictions from classic approaches based on theoretical population ecology (which governs rabies control to date) with a newly developed individual-based model. Our spatially explicit approach allowed for the reproduction of pattern formation emerging from a pathogen's spread through its host population. We suggest that a much lower management effort could eliminate the disease than that currently in operation. This is supported by empirical evidence from historic field data. Adapting control measures to the new prediction would save one-third of resources in future control programmes. The reason for the lower prediction is the spatial structure formed by spreading infections in spatially arranged host populations. It is not the result of technical differences between models. Synthesis and applications. For diseases predominantly transmitted by neighbourhood interaction, our findings suggest that the emergence of spatial structures facilitates eradication. This may have substantial implications for the cost-effectiveness of existing disease management schemes, and suggests that when planning management strategies consideration must be given to methods that reflect the spatial nature of the pathogen–host system. PMID:18784795

Experimental Study of Ultrasound Contrast Agent Mediated Heat Transfer for Therapeutic Applications

NASA Astrophysics Data System (ADS)

Razansky, D.; Adam, D. R.; Einziger, P. D.

2006-05-01

Ultrasound Contrast Agents (UCA) have been recently suggested as efficient enhancers of ultrasonic power deposition in tissue. The ultrasonic energy absorption by UCA, considered as disadvantageous in diagnostic imaging, might be valuable in therapeutic applications such as targeted hyperthermia or ablation treatments. The current study, based on theoretical predictions, was designed to experimentally measure the dissipation and heating effects of encapsulated UCA (Optison™) in a well-controlled and calibrated environment.

Combining quantitative trait loci analysis with physiological models to predict genotype-specific transpiration rates.

PubMed

Reuning, Gretchen A; Bauerle, William L; Mullen, Jack L; McKay, John K

2015-04-01

Transpiration is controlled by evaporative demand and stomatal conductance (gs ), and there can be substantial genetic variation in gs . A key parameter in empirical models of transpiration is minimum stomatal conductance (g0 ), a trait that can be measured and has a large effect on gs and transpiration. In Arabidopsis thaliana, g0 exhibits both environmental and genetic variation, and quantitative trait loci (QTL) have been mapped. We used this information to create a genetically parameterized empirical model to predict transpiration of genotypes. For the parental lines, this worked well. However, in a recombinant inbred population, the predictions proved less accurate. When based only upon their genotype at a single g0 QTL, genotypes were less distinct than our model predicted. Follow-up experiments indicated that both genotype by environment interaction and a polygenic inheritance complicate the application of genetic effects into physiological models. The use of ecophysiological or 'crop' models for predicting transpiration of novel genetic lines will benefit from incorporating further knowledge of the genetic control and degree of independence of core traits/parameters underlying gs variation. © 2014 John Wiley & Sons Ltd.

The insertion of human dynamics models in the flight control loops of V/STOL research aircraft. Appendix 2: The optimal control model of a pilot in V/STOL aircraft control loops

NASA Technical Reports Server (NTRS)

Zipf, Mark E.

1989-01-01

An overview is presented of research work focussed on the design and insertion of classical models of human pilot dynamics within the flight control loops of V/STOL aircraft. The pilots were designed and configured for use in integrated control system research and design. The models of human behavior that were considered are: McRuer-Krendel (a single variable transfer function model); and Optimal Control Model (a multi-variable approach based on optimal control and stochastic estimation theory). These models attempt to predict human control response characteristics when confronted with compensatory tracking and state regulation tasks. An overview, mathematical description, and discussion of predictive limitations of the pilot models is presented. Design strategies and closed loop insertion configurations are introduced and considered for various flight control scenarios. Models of aircraft dynamics (both transfer function and state space based) are developed and discussed for their use in pilot design and application. Pilot design and insertion are illustrated for various flight control objectives. Results of pilot insertion within the control loops of two V/STOL research aricraft (Sikorski Black Hawk UH-60A, McDonnell Douglas Harrier II AV-8B) are presented and compared against actual pilot flight data. Conclusions are reached on the ability of the pilot models to adequately predict human behavior when confronted with similar control objectives.

Using Social Networking Sites for Communicable Disease Control: Innovative Contact Tracing or Breach of Confidentiality?

PubMed

Mandeville, Kate L; Harris, Matthew; Thomas, H Lucy; Chow, Yimmy; Seng, Claude

2014-04-01

Social media applications such as Twitter, YouTube and Facebook have attained huge popularity, with more than three billion people and organizations predicted to have a social networking account by 2015. Social media offers a rapid avenue of communication with the public and has potential benefits for communicable disease control and surveillance. However, its application in everyday public health practice raises a number of important issues around confidentiality and autonomy. We report here a case from local level health protection where the friend of an individual with meningococcal septicaemia used a social networking site to notify potential contacts.

Engineering bacterial translation initiation - Do we have all the tools we need?

PubMed

Vigar, Justin R J; Wieden, Hans-Joachim

2017-11-01

Reliable tools that allow precise and predictable control over gene expression are critical for the success of nearly all bioengineering applications. Translation initiation is the most regulated phase during protein biosynthesis, and is therefore a promising target for exerting control over gene expression. At the translational level, the copy number of a protein can be fine-tuned by altering the interaction between the translation initiation region of an mRNA and the ribosome. These interactions can be controlled by modulating the mRNA structure using numerous approaches, including small molecule ligands, RNAs, or RNA-binding proteins. A variety of naturally occurring regulatory elements have been repurposed, facilitating advances in synthetic gene regulation strategies. The pursuit of a comprehensive understanding of mechanisms governing translation initiation provides the framework for future engineering efforts. Here we outline state-of-the-art strategies used to predictably control translation initiation in bacteria. We also discuss current limitations in the field and future goals. Due to its function as the rate-determining step, initiation is the ideal point to exert effective translation regulation. Several engineering tools are currently available to rationally design the initiation characteristics of synthetic mRNAs. However, improvements are required to increase the predictability, effectiveness, and portability of these tools. Predictable and reliable control over translation initiation will allow greater predictability when designing, constructing, and testing genetic circuits. The ability to build more complex circuits predictably will advance synthetic biology and contribute to our fundamental understanding of the underlying principles of these processes. "This article is part of a Special Issue entitled "Biochemistry of Synthetic Biology - Recent Developments" Guest Editor: Dr. Ilka Heinemann and Dr. Patrick O'Donoghue. Copyright © 2017 Elsevier B.V. All rights reserved.

Prediction of aircraft handling qualities using analytical models of the human pilot

NASA Technical Reports Server (NTRS)

Hess, R. A.

1982-01-01

The optimal control model (OCM) of the human pilot is applied to the study of aircraft handling qualities. Attention is focused primarily on longitudinal tasks. The modeling technique differs from previous applications of the OCM in that considerable effort is expended in simplifying the pilot/vehicle analysis. After briefly reviewing the OCM, a technique for modeling the pilot controlling higher order systems is introduced. Following this, a simple criterion for determining the susceptibility of an aircraft to pilot-induced oscillations (PIO) is formulated. Finally, a model-based metric for pilot rating prediction is discussed. The resulting modeling procedure provides a relatively simple, yet unified approach to the study of a variety of handling qualities problems.

Prediction of aircraft handling qualities using analytical models of the human pilot

NASA Technical Reports Server (NTRS)

Hess, R. A.

1982-01-01

The optimal control model (OCM) of the human pilot is applied to the study of aircraft handling qualities. Attention is focused primarily on longitudinal tasks. The modeling technique differs from previous applications of the OCM in that considerable effort is expended in simplifying the pilot/vehicle analysis. After briefly reviewing the OCM, a technique for modeling the pilot controlling higher order systems is introduced. Following this, a simple criterion for determining the susceptibility of an aircraft to pilot induced oscillations is formulated. Finally, a model based metric for pilot rating prediction is discussed. The resulting modeling procedure provides a relatively simple, yet unified approach to the study of a variety of handling qualities problems.

An analytical approach for predicting pilot induced oscillations

NASA Technical Reports Server (NTRS)

Hess, R. A.

1981-01-01

The optimal control model (OCM) of the human pilot is applied to the study of aircraft handling qualities. Attention is focused primarily on longitudinal tasks. The modeling technique differs from previous applications of the OCM in that considerable effort is expended in simplifying the pilot/vehicle analysis. After briefly reviewing the OCM, a technique for modeling the pilot controlling higher order systems is introduced. Following this, a simple criterion or determining the susceptability of an aircraft to pilot induced oscillations (PIO) is formulated. Finally, a model-based metric for pilot rating prediction is discussed. The resulting modeling procedure provides a relatively simple, yet unified approach to the study of a variety of handling qualities problems.

The applications of model-based geostatistics in helminth epidemiology and control.

PubMed

Magalhães, Ricardo J Soares; Clements, Archie C A; Patil, Anand P; Gething, Peter W; Brooker, Simon

2011-01-01

Funding agencies are dedicating substantial resources to tackle helminth infections. Reliable maps of the distribution of helminth infection can assist these efforts by targeting control resources to areas of greatest need. The ability to define the distribution of infection at regional, national and subnational levels has been enhanced greatly by the increased availability of good quality survey data and the use of model-based geostatistics (MBG), enabling spatial prediction in unsampled locations. A major advantage of MBG risk mapping approaches is that they provide a flexible statistical platform for handling and representing different sources of uncertainty, providing plausible and robust information on the spatial distribution of infections to inform the design and implementation of control programmes. Focussing on schistosomiasis and soil-transmitted helminthiasis, with additional examples for lymphatic filariasis and onchocerciasis, we review the progress made to date with the application of MBG tools in large-scale, real-world control programmes and propose a general framework for their application to inform integrative spatial planning of helminth disease control programmes. Copyright © 2011 Elsevier Ltd. All rights reserved.

Actively Controlled Shaft Seals for Aerospace Applications

NASA Technical Reports Server (NTRS)

Salant, Richard F.; Wolff, Paul

1995-01-01

This study experimentally investigates an actively controlled mechanical seal for aerospace applications. The seal of interest is a gas seal, which is considerably more compact than previous actively controlled mechanical seals that were developed for industrial use. In a mechanical seal, the radial convergence of the seal interface has a primary effect on the film thickness. Active control of the film thickness is established by controlling the radial convergence of the seal interface with a piezoelectric actuator. An actively controlled mechanical seal was initially designed and evaluated using a mathematical model. Based on these results, a seal was fabricated and tested under laboratory conditions. The seal was tested with both helium and air, at rotational speeds up to 3770 rad/sec, and at sealed pressures as high as 1.48 x 10(exp 6) Pa. The seal was operated with both manual control and with a closed-loop control system that used either the leakage rate or face temperature as the feedback. The output of the controller was the voltage applied to the piezoelectric actuator. The seal operated successfully for both short term tests (less than one hour) and for longer term tests (four hours) with a closed-loop control system. The leakage rates were typically 5-15 slm (standard liters per minute), and the face temperatures were generally maintained below 100C. When leakage rate was used as the feedback signal, the setpoint leakage rate was typically maintained within 1 slm. However, larger deviations occurred during sudden changes in sealed pressure. When face temperature was used as the feedback signal, the setpoint face temperature was generally maintained within 3 C, with larger deviations occurring when the sealed pressure changes suddenly. the experimental results were compared to the predictions from the mathematical model. The model was successful in predicting the trends in leakage rate that occurred as the balance ratio and sealed pressure changed, although the leakage rates were not quantitatively predicted with a high degree of accuracy. This model could be useful in providing valuable design information for future actively controlled mechanical seals.

Adaptive envelope protection methods for aircraft

NASA Astrophysics Data System (ADS)

Unnikrishnan, Suraj

Carefree handling refers to the ability of a pilot to operate an aircraft without the need to continuously monitor aircraft operating limits. At the heart of all carefree handling or maneuvering systems, also referred to as envelope protection systems, are algorithms and methods for predicting future limit violations. Recently, envelope protection methods that have gained more acceptance, translate limit proximity information to its equivalent in the control channel. Envelope protection algorithms either use very small prediction horizon or are static methods with no capability to adapt to changes in system configurations. Adaptive approaches maximizing prediction horizon such as dynamic trim, are only applicable to steady-state-response critical limit parameters. In this thesis, a new adaptive envelope protection method is developed that is applicable to steady-state and transient response critical limit parameters. The approach is based upon devising the most aggressive optimal control profile to the limit boundary and using it to compute control limits. Pilot-in-the-loop evaluations of the proposed approach are conducted at the Georgia Tech Carefree Maneuver lab for transient longitudinal hub moment limit protection. Carefree maneuvering is the dual of carefree handling in the realm of autonomous Uninhabited Aerial Vehicles (UAVs). Designing a flight control system to fully and effectively utilize the operational flight envelope is very difficult. With the increasing role and demands for extreme maneuverability there is a need for developing envelope protection methods for autonomous UAVs. In this thesis, a full-authority automatic envelope protection method is proposed for limit protection in UAVs. The approach uses adaptive estimate of limit parameter dynamics and finite-time horizon predictions to detect impending limit boundary violations. Limit violations are prevented by treating the limit boundary as an obstacle and by correcting nominal control/command inputs to track a limit parameter safe-response profile near the limit boundary. The method is evaluated using software-in-the-loop and flight evaluations on the Georgia Tech unmanned rotorcraft platform---GTMax. The thesis also develops and evaluates an extension for calculating control margins based on restricting limit parameter response aggressiveness near the limit boundary.

A tuning algorithm for model predictive controllers based on genetic algorithms and fuzzy decision making.

PubMed

van der Lee, J H; Svrcek, W Y; Young, B R

2008-01-01

Model Predictive Control is a valuable tool for the process control engineer in a wide variety of applications. Because of this the structure of an MPC can vary dramatically from application to application. There have been a number of works dedicated to MPC tuning for specific cases. Since MPCs can differ significantly, this means that these tuning methods become inapplicable and a trial and error tuning approach must be used. This can be quite time consuming and can result in non-optimum tuning. In an attempt to resolve this, a generalized automated tuning algorithm for MPCs was developed. This approach is numerically based and combines a genetic algorithm with multi-objective fuzzy decision-making. The key advantages to this approach are that genetic algorithms are not problem specific and only need to be adapted to account for the number and ranges of tuning parameters for a given MPC. As well, multi-objective fuzzy decision-making can handle qualitative statements of what optimum control is, in addition to being able to use multiple inputs to determine tuning parameters that best match the desired results. This is particularly useful for multi-input, multi-output (MIMO) cases where the definition of "optimum" control is subject to the opinion of the control engineer tuning the system. A case study will be presented in order to illustrate the use of the tuning algorithm. This will include how different definitions of "optimum" control can arise, and how they are accounted for in the multi-objective decision making algorithm. The resulting tuning parameters from each of the definition sets will be compared, and in doing so show that the tuning parameters vary in order to meet each definition of optimum control, thus showing the generalized automated tuning algorithm approach for tuning MPCs is feasible.

Predicting strain using forward modelling of restored cross-sections: Application to rollover anticlines over listric normal faults

NASA Astrophysics Data System (ADS)

Poblet, Josep; Bulnes, Mayte

2007-12-01

A strategy to predict strain across geological structures, based on previous techniques, is modified and evaluated, and a practical application is shown. The technique, which employs cross-section restoration combined with kinematic forward modelling, consists of restoring a section, placing circular strain markers on different domains of the restoration, and forward modelling the restored section with strain markers until the present-day stage is reached. The restoration algorithm employed must be also used to forward model the structure. The ellipses in the forward modelled section allow determining the strain state of the structure and may indirectly predict orientation and distribution of minor structures such as small-scale fractures. The forward model may be frozen at different time steps (different growth stages) allowing prediction of both spatial and temporal variation of strain. The method is evaluated through its application to two stages of a clay experiment, that includes strain markers, and its geometry and deformation history are well documented, providing a strong control on the results. To demonstrate the method's potential, it is successfully applied to a depth-converted seismic profile in the Central Sumatra Basin, Indonesia. This allowed us to gain insight into the deformation undergone by rollover anticlines over listric normal faults.

Health Care Psychology: Prospects for the Well-Being of Children.

ERIC Educational Resources Information Center

Wright, Logan

1979-01-01

Health care psychology is distinguished from traditional child psychology in that it emphasizes clinical application and is concerned with primary mental health care. Diagnosis, classification, prediction, and treatment and control strategies in the field offer definite solutions to problems such as tracheotomy addiction, encopresis, psychogenic…

Praedicere Possumus: An Italian web-based application for predictive microbiology to ensure food safety.

PubMed

Polese, Pierluigi; Torre, Manuela Del; Stecchini, Mara Lucia

2018-03-31

The use of predictive modelling tools, which mainly describe the response of microorganisms to a particular set of environmental conditions, may contribute to a better understanding of microbial behaviour in foods. In this paper, a tertiary model, in the form of a readily available and userfriendly web-based application Praedicere Possumus (PP) is presented with research examples from our laboratories. Through the PP application, users have access to different modules, which apply a set of published models considered reliable for determining the compliance of a food product with EU safety criteria and for optimising processing throughout the identification of critical control points. The application pivots around a growth/no-growth boundary model, coupled with a growth model, and includes thermal and non-thermal inactivation models. Integrated functionalities, such as the fractional contribution of each inhibitory factor to growth probability (f) and the time evolution of the growth probability (P t ), have also been included. The PP application is expected to assist food industry and food safety authorities in their common commitment towards the improvement of food safety.

Ultrasound-induced inertial cavitation from gas-stabilizing nanoparticles.

PubMed

Kwan, J J; Graham, S; Myers, R; Carlisle, R; Stride, E; Coussios, C C

2015-08-01

The understanding of cavitation from nanoparticles has been hindered by the inability to control nanobubble size. We present a method to manufacture nanoparticles with a tunable single hemispherical depression (nanocups) of mean diameter 90, 260, or 650 nm entrapping a nanobubble. A modified Rayleigh-Plesset crevice model predicts the inertial cavitation threshold as a function of cavity size and frequency, and is verified experimentally. The ability to tune cavitation nanonuclei and predict their behavior will be useful for applications ranging from cancer therapy to ultrasonic cleaning.

Cognitive control predicts use of model-based reinforcement learning.

PubMed

Otto, A Ross; Skatova, Anya; Madlon-Kay, Seth; Daw, Nathaniel D

2015-02-01

Accounts of decision-making and its neural substrates have long posited the operation of separate, competing valuation systems in the control of choice behavior. Recent theoretical and experimental work suggest that this classic distinction between behaviorally and neurally dissociable systems for habitual and goal-directed (or more generally, automatic and controlled) choice may arise from two computational strategies for reinforcement learning (RL), called model-free and model-based RL, but the cognitive or computational processes by which one system may dominate over the other in the control of behavior is a matter of ongoing investigation. To elucidate this question, we leverage the theoretical framework of cognitive control, demonstrating that individual differences in utilization of goal-related contextual information--in the service of overcoming habitual, stimulus-driven responses--in established cognitive control paradigms predict model-based behavior in a separate, sequential choice task. The behavioral correspondence between cognitive control and model-based RL compellingly suggests that a common set of processes may underpin the two behaviors. In particular, computational mechanisms originally proposed to underlie controlled behavior may be applicable to understanding the interactions between model-based and model-free choice behavior.

Analysis of explicit model predictive control for path-following control

PubMed Central

2018-01-01

In this paper, explicit Model Predictive Control(MPC) is employed for automated lane-keeping systems. MPC has been regarded as the key to handle such constrained systems. However, the massive computational complexity of MPC, which employs online optimization, has been a major drawback that limits the range of its target application to relatively small and/or slow problems. Explicit MPC can reduce this computational burden using a multi-parametric quadratic programming technique(mp-QP). The control objective is to derive an optimal front steering wheel angle at each sampling time so that autonomous vehicles travel along desired paths, including straight, circular, and clothoid parts, at high entry speeds. In terms of the design of the proposed controller, a method of choosing weighting matrices in an optimization problem and the range of horizons for path-following control are described through simulations. For the verification of the proposed controller, simulation results obtained using other control methods such as MPC, Linear-Quadratic Regulator(LQR), and driver model are employed, and CarSim, which reflects the features of a vehicle more realistically than MATLAB/Simulink, is used for reliable demonstration. PMID:29534080

Analysis of explicit model predictive control for path-following control.

PubMed

Lee, Junho; Chang, Hyuk-Jun

2018-01-01

In this paper, explicit Model Predictive Control(MPC) is employed for automated lane-keeping systems. MPC has been regarded as the key to handle such constrained systems. However, the massive computational complexity of MPC, which employs online optimization, has been a major drawback that limits the range of its target application to relatively small and/or slow problems. Explicit MPC can reduce this computational burden using a multi-parametric quadratic programming technique(mp-QP). The control objective is to derive an optimal front steering wheel angle at each sampling time so that autonomous vehicles travel along desired paths, including straight, circular, and clothoid parts, at high entry speeds. In terms of the design of the proposed controller, a method of choosing weighting matrices in an optimization problem and the range of horizons for path-following control are described through simulations. For the verification of the proposed controller, simulation results obtained using other control methods such as MPC, Linear-Quadratic Regulator(LQR), and driver model are employed, and CarSim, which reflects the features of a vehicle more realistically than MATLAB/Simulink, is used for reliable demonstration.

Prediction of Isoelectric Point of Manganese and Cobalt Lamellar Oxides: Application to Controlled Synthesis of Mixed Oxides.

PubMed

Tang, Céline; Giaume, Domitille; Guerlou-Demourgues, Liliane; Lefèvre, Grégory; Barboux, Philippe

2018-05-30

To design novel layered materials, bottom-up strategy is very promising. It consists of (1) synthesizing various layered oxides, (2) exfoliating them, then (3) restacking them in a controlled way. The last step is based on electrostatic interactions between different layered oxides and is difficult to control. The aim of this study is to facilitate this step by predicting the isoelectric point (IEP) of exfoliated materials. The Multisite Complexation model (MUSIC) was used for this objective and was shown to be able to predict IEP from the mean oxidation state of the metal in the (hydr)oxides, as the main parameter. Moreover, the effect of exfoliation on IEP has also been calculated. Starting from platelets with a high basal surface area over total surface area, we show that the exfoliation process has no impact on calculated IEP value, as verified with experiments. Moreover, the restacked materials containing different monometallic (hydr)oxide layers also have an IEP consistent with values calculated with the model. This study proves that MUSIC model is a useful tool to predict IEP of various complex metal oxides and hydroxides.

Frontal Theta Reflects Uncertainty and Unexpectedness during Exploration and Exploitation

PubMed Central

Figueroa, Christina M.; Cohen, Michael X; Frank, Michael J.

2012-01-01

In order to understand the exploitation/exploration trade-off in reinforcement learning, previous theoretical and empirical accounts have suggested that increased uncertainty may precede the decision to explore an alternative option. To date, the neural mechanisms that support the strategic application of uncertainty-driven exploration remain underspecified. In this study, electroencephalography (EEG) was used to assess trial-to-trial dynamics relevant to exploration and exploitation. Theta-band activities over middle and lateral frontal areas have previously been implicated in EEG studies of reinforcement learning and strategic control. It was hypothesized that these areas may interact during top-down strategic behavioral control involved in exploratory choices. Here, we used a dynamic reward–learning task and an associated mathematical model that predicted individual response times. This reinforcement-learning model generated value-based prediction errors and trial-by-trial estimates of exploration as a function of uncertainty. Mid-frontal theta power correlated with unsigned prediction error, although negative prediction errors had greater power overall. Trial-to-trial variations in response-locked frontal theta were linearly related to relative uncertainty and were larger in individuals who used uncertainty to guide exploration. This finding suggests that theta-band activities reflect prefrontal-directed strategic control during exploratory choices. PMID:22120491

Clinical Application of Vibration Controlled Transient Elastography in Patients with Chronic Hepatitis B

PubMed Central

Liang, Xie-Er; Chen, Yong-Peng

2017-01-01

Abstract Evaluation of the extent and progression of liver fibrosis and cirrhosis is of critical importance in the management and prognosis of patients with chronic hepatitis B. Due to the limitation of liver biopsy, non-invasive methods, especially liver stiffness measurement (LSM) by vibration controlled transient elastography, have been developed and widely applied for liver fibrosis assessment. LSM aims to reduce, but not to substitute, the need for liver biopsy for fibrosis/cirrhosis diagnosis. While LSM may have potential utility in monitoring treatment response, its applications in prediction of liver complications in terms of portal hypertension and esophageal varices, as well as disease prognosis, have been gradually validated. Here, we review the latest clinical applications of LSM in patients with chronic hepatitis B. PMID:29226103

[Clinical applications of dosing algorithm in the predication of warfarin maintenance dose].

PubMed

Huang, Sheng-wen; Xiang, Dao-kang; An, Bang-quan; Li, Gui-fang; Huang, Ling; Wu, Hai-li

2011-12-27

To evaluate the feasibility of clinical application for genetic based dosing algorithm in the predication of warfarin maintenance dose in Chinese population. The clinical data were collected and blood samples harvested from a total of 126 patients undergoing heart valve replacement. The genotypes of VKORC1 and CYP2C9 were determined by melting curve analysis after PCR. They were divided randomly into the study and control groups. In the study group, the first three doses of warfarin were prescribed according to the predicted warfarin maintenance dose while warfarin was initiated at 2.5 mg/d in the control group. The warfarin doses were adjusted according to the measured international normalized ratio (INR) values. And all subjects were followed for 50 days after an initiation of warfarin therapy. At the end of a 50-day follow-up period, the proportions of the patients on a stable dose were 82.4% (42/51) and 62.5% (30/48) for the study and control groups respectively. The mean durations of reaching a stable dose of warfarin were (27.5 ± 1.8) and (34.7 ± 1.8) days and the median durations were (24.0 ± 1.7) and (33.0 ± 4.5) days in the study and control groups respectively. Significant differences existed in the durations of reaching a stable dose between the two groups (P = 0.012). Compared with the control group, the hazard ratio (HR) for the duration of reaching a stable dose was 1.786 in the study group (95%CI 1.088 - 2.875, P = 0.026). The predicted dosing algorithm incorporating genetic and non-genetic factors may shorten the duration of achieving efficiently a stable dose of warfarin. And the present study validates the feasibility of its clinical application.

Prediction of final error level in learning and repetitive control

NASA Astrophysics Data System (ADS)

Levoci, Peter A.

Repetitive control (RC) is a field that creates controllers to eliminate the effects of periodic disturbances on a feedback control system. The methods have applications in spacecraft problems, to isolate fine pointing equipment from periodic vibration disturbances such as slight imbalances in momentum wheels or cryogenic pumps. A closely related field of control design is iterative learning control (ILC) which aims to eliminate tracking error in a task that repeats, each time starting from the same initial condition. Experiments done on a robot at NASA Langley Research Center showed that the final error levels produced by different candidate repetitive and learning controllers can be very different, even when each controller is analytically proven to converge to zero error in the deterministic case. Real world plant and measurement noise and quantization noise (from analog to digital and digital to analog converters) in these control methods are acted on as if they were error sources that will repeat and should be cancelled, which implies that the algorithms amplify such errors. Methods are developed that predict the final error levels of general first order ILC, of higher order ILC including current cycle learning, and of general RC, in the presence of noise, using frequency response methods. The method involves much less computation than the corresponding time domain approach that involves large matrices. The time domain approach was previously developed for ILC and handles a certain class of ILC methods. Here methods are created to include zero-phase filtering that is very important in creating practical designs. Also, time domain methods are developed for higher order ILC and for repetitive control. Since RC and ILC must be implemented digitally, all of these methods predict final error levels at the sample times. It is shown here that RC can easily converge to small error levels between sample times, but that ILC in most applications will have large and diverging intersample error if in fact zero error is reached at the sample times. This is independent of the ILC law used, and is purely a property of the physical system. Methods are developed to address this issue.

Models for nearly every occasion: Part III - One box decreasing emission models.

PubMed

Hewett, Paul; Ganser, Gary H

2017-11-01

New one box "well-mixed room" decreasing emission (DE) models are introduced that allow for local exhaust or local exhaust with filtered return, as well the recirculation of a filtered (or cleaned) portion of the general room ventilation. For each control device scenario, a steady state and transient model is presented. The transient equations predict the concentration at any time t after the application of a known mass of a volatile substance to a surface, and can be used to predict the task exposure profile, the average task exposure, as well as peak and short-term exposures. The steady state equations can be used to predict the "average concentration per application" that is reached whenever the substance is repeatedly applied. Whenever the beginning and end concentrations are expected to be zero (or near zero) the steady state equations can also be used to predict the average concentration for a single task with multiple applications during the task, or even a series of such tasks. The transient equations should be used whenever these criteria cannot be met. A structured calibration procedure is proposed that utilizes a mass balance approach. Depending upon the DE model selected, one or more calibration measurements are collected. Using rearranged versions of the steady state equations, estimates of the model variables-e.g., the mass of the substance applied during each application, local exhaust capture efficiency, and the various cleaning or filtration efficiencies-can be calculated. A new procedure is proposed for estimating the emission rate constant.

Structure-based control of complex networks with nonlinear dynamics

NASA Astrophysics Data System (ADS)

Zanudo, Jorge G. T.; Yang, Gang; Albert, Reka

What can we learn about controlling a system solely from its underlying network structure? Here we use a framework for control of networks governed by a broad class of nonlinear dynamics that includes the major dynamic models of biological, technological, and social processes. This feedback-based framework provides realizable node overrides that steer a system towards any of its natural long term dynamic behaviors, regardless of the dynamic details and system parameters. We use this framework on several real networks, identify the topological characteristics that underlie the predicted node overrides, and compare its predictions to those of classical structural control theory. Finally, we demonstrate this framework's applicability in dynamic models of gene regulatory networks and identify nodes whose override is necessary for control in the general case, but not in specific model instances. This work was supported by NSF Grants PHY 1205840 and IIS 1160995. JGTZ is a recipient of a Stand Up To Cancer - The V Foundation Convergence Scholar Award.

Short-term Operation of Multi-purpose Reservoir using Model Predictive Control

NASA Astrophysics Data System (ADS)

Uysal, Gokcen; Schwanenberg, Dirk; Alvarado Montero, Rodolfo; Sensoy, Aynur; Arda Sorman, Ali

2017-04-01

Operation of water structures especially with conflicting water supply and flood mitigation objectives is under more stress attributed to growing water demand and changing hydro-climatic conditions. Model Predictive Control (MPC) based optimal control solutions has been successfully applied to different water resources applications. In this study, Feedback Control (FBC) and MPC get combined and an improved joint optimization-simulation operating scheme is proposed. Water supply and flood control objectives are fulfilled by incorporating the long term water supply objectives into a time-dependent variable guide curve policy whereas the extreme floods are attenuated by means of short-term optimization based on MPC. A final experiment is carried out to assess the lead time performance and reliability of forecasts in a hindcasting experiment with imperfect, perturbed forecasts. The framework is tested in Yuvacık Dam reservoir where the main water supply reservoir of Kocaeli City in the northwestern part of Turkey (the Marmara region) and it requires a challenging gate operation due to restricted downstream flow conditions.

Application of dynamical systems theory to the high angle of attack dynamics of the F-14

NASA Technical Reports Server (NTRS)

Jahnke, Craig C.; Culick, Fred E. C.

1990-01-01

Dynamical systems theory has been used to study the nonlinear dynamics of the F-14. An eight degree of freedom model that does not include the control system present in operational F-14s has been analyzed. The aerodynamic model, supplied by NASA, includes nonlinearities as functions of the angles of attack and sideslip, the rotation rate, and the elevator deflection. A continuation method has been used to calculate the steady states of the F-14 as continuous functions of the control surface deflections. Bifurcations of these steady states have been used to predict the onset of wing rock, spiral divergence, and jump phenomena which cause the aircraft to enter a spin. A simple feedback control system was designed to eliminate the wing rock and spiral divergence instabilities. The predictions were verified with numerical simulations.

Determining Functional Reliability of Pyrotechnic Mechanical Devices

NASA Technical Reports Server (NTRS)

Bement, Laurence J.; Multhaup, Herbert A.

1997-01-01

This paper describes a new approach for evaluating mechanical performance and predicting the mechanical functional reliability of pyrotechnic devices. Not included are other possible failure modes, such as the initiation of the pyrotechnic energy source. The requirement of hundreds or thousands of consecutive, successful tests on identical components for reliability predictions, using the generally accepted go/no-go statistical approach routinely ignores physics of failure. The approach described in this paper begins with measuring, understanding and controlling mechanical performance variables. Then, the energy required to accomplish the function is compared to that delivered by the pyrotechnic energy source to determine mechanical functional margin. Finally, the data collected in establishing functional margin is analyzed to predict mechanical functional reliability, using small-sample statistics. A careful application of this approach can provide considerable cost improvements and understanding over that of go/no-go statistics. Performance and the effects of variables can be defined, and reliability predictions can be made by evaluating 20 or fewer units. The application of this approach to a pin puller used on a successful NASA mission is provided as an example.

Effect of Interfacial Turbulence and Accommodation Coefficient on CFD Predictions of Pressurization and Pressure Control in Cryogenic Storage Tank

NASA Technical Reports Server (NTRS)

Kassemi, Mohammad; Kartuzova, Olga; Hylton, Sonya

2015-01-01

Laminar models agree closely with the pressure evolution and vapor phase temperature stratification but under-predict liquid temperatures. Turbulent SST k-w and k-e models under-predict the pressurization rate and extent of stratification in the vapor but represent liquid temperature distributions fairly well. These conclusions seem to equally apply to large cryogenic tank simulations as well as small scale simulant fluid pressurization cases. Appropriate turbulent models that represent both interfacial and bulk vapor phase turbulence with greater fidelity are needed. Application of LES models to the tank pressurization problem can serve as a starting point.

ShinyGPAS: interactive genomic prediction accuracy simulator based on deterministic formulas.

PubMed

Morota, Gota

2017-12-20

Deterministic formulas for the accuracy of genomic predictions highlight the relationships among prediction accuracy and potential factors influencing prediction accuracy prior to performing computationally intensive cross-validation. Visualizing such deterministic formulas in an interactive manner may lead to a better understanding of how genetic factors control prediction accuracy. The software to simulate deterministic formulas for genomic prediction accuracy was implemented in R and encapsulated as a web-based Shiny application. Shiny genomic prediction accuracy simulator (ShinyGPAS) simulates various deterministic formulas and delivers dynamic scatter plots of prediction accuracy versus genetic factors impacting prediction accuracy, while requiring only mouse navigation in a web browser. ShinyGPAS is available at: https://chikudaisei.shinyapps.io/shinygpas/ . ShinyGPAS is a shiny-based interactive genomic prediction accuracy simulator using deterministic formulas. It can be used for interactively exploring potential factors that influence prediction accuracy in genome-enabled prediction, simulating achievable prediction accuracy prior to genotyping individuals, or supporting in-class teaching. ShinyGPAS is open source software and it is hosted online as a freely available web-based resource with an intuitive graphical user interface.

Benefit assessment of NASA space technology goals

NASA Technical Reports Server (NTRS)

1976-01-01

The socio-economic benefits to be derived from system applications of space technology goals developed by NASA were assessed. Specific studies include: electronic mail; personal telephone communications; weather and climate monitoring, prediction, and control; crop production forecasting and water availability; planetary engineering of the planet Venus; and planetary exploration.

Predictive Models of Procedural Human Supervisory Control Behavior

DTIC Science & Technology

2011-01-01

Campbell in Australia and Prof. Axel Schulte in Germany: they say a mind stretched by an idea never goes back to its original size, thank you for...recurrent neural network (RNN). Neural nets have been successfully used in diverse applications such as handwriting recognition (Gader, Mohamed et al

The McDonaldization of Academic Libraries?

ERIC Educational Resources Information Center

Quinn, Brian

2000-01-01

Discusses the McDonaldization thesis that suggests that many aspects of the fast food industry are making their way into other areas of society. Explores whether this thesis is applicable to academic libraries, focusing on efficiency, calculability, predictability, control, user expectations, pros and cons of teams, and creativity and information…

A pre-admission program for underrepresented minority and disadvantaged students: application, acceptance, graduation rates and timeliness of graduating from medical school.

PubMed

Strayhorn, G

2000-04-01

To determine whether students' performances in a pre-admission program predicted whether participants would (1) apply to medical school, (2) get accepted, and (3) graduate. Using prospectively collected data from participants in the University of North Carolina at Chapel Hill's Medical Education Development Program (MEDP) and data from the Association of American Colleges Student and Applicant Information Management System, the author identified 371 underrepresented minority (URM) students who were full-time participants and completed the program between 1984 and 1989, prior to their acceptance into medical school. Logistic regression analysis was used to determine whether MEDP performance significantly predicted (after statistically controlling for traditional predictors of these outcomes) the proportions of URM participants who applied to medical school and were accepted, the timeliness of graduating, and the proportion graduating. Odds ratios with 95% confidence intervals were calculated to determine the associations between the independent and outcome variables. In separate logistic regression models, MEDP performance predicted the study's outcomes after statistically controlling for traditional predictors with 95% confidence intervals. Pre-admission programs with similar outcomes can improve the diversity of the physician workforce and the access to health care for underrepresented minority and economically disadvantaged populations.

Controlling the hydration of the skin though the application of occluding barrier creams

PubMed Central

Sparr, Emma; Millecamps, Danielle; Isoir, Muriel; Burnier, Véronique; Larsson, Åsa; Cabane, Bernard

2013-01-01

The skin is a barrier membrane that separates environments with profoundly different water contents. The barrier properties are assured by the outer layer of the skin, the stratum corneum (SC), which controls the transepidermal water loss. The SC acts as a responding membrane, since its hydration and permeability vary with the boundary condition, which is the activity of water at the outer surface of the skin. We show how this boundary condition can be changed by the application of a barrier cream that makes a film with a high resistance to the transport of water. We present a quantitative model that predicts hydration and water transport in SC that is covered by such a film. We also develop an experimental method for measuring the specific resistance to water transport of films made of occluding barrier creams. Finally, we combine the theoretical model with the measured properties of the barrier creams to predict how a film of cream changes the activity of water at the outer surface of the SC. Using the known variations of SC permeability and hydration with the water activity in its environment (i.e. the relative humidity), we can thus predict how a film of barrier cream changes SC hydration. PMID:23269846

Controlling the hydration of the skin though the application of occluding barrier creams.

PubMed

Sparr, Emma; Millecamps, Danielle; Isoir, Muriel; Burnier, Véronique; Larsson, Åsa; Cabane, Bernard

2013-03-06

The skin is a barrier membrane that separates environments with profoundly different water contents. The barrier properties are assured by the outer layer of the skin, the stratum corneum (SC), which controls the transepidermal water loss. The SC acts as a responding membrane, since its hydration and permeability vary with the boundary condition, which is the activity of water at the outer surface of the skin. We show how this boundary condition can be changed by the application of a barrier cream that makes a film with a high resistance to the transport of water. We present a quantitative model that predicts hydration and water transport in SC that is covered by such a film. We also develop an experimental method for measuring the specific resistance to water transport of films made of occluding barrier creams. Finally, we combine the theoretical model with the measured properties of the barrier creams to predict how a film of cream changes the activity of water at the outer surface of the SC. Using the known variations of SC permeability and hydration with the water activity in its environment (i.e. the relative humidity), we can thus predict how a film of barrier cream changes SC hydration.

Empirical Research of Micro-blog Information Transmission Range by Guard nodes

NASA Astrophysics Data System (ADS)

Chen, Shan; Ji, Ling; Li, Guang

2018-03-01

The prediction and evaluation of information transmission in online social networks is a challenge. It is significant to solve this issue for monitoring public option and advertisement communication. First, the prediction process is described by a set language. Then with Sina Microblog system as used as the case object, the relationship between node influence and coverage rate is analyzed by using the topology structure of information nodes. A nonlinear model is built by a statistic method in a specific, bounded and controlled Microblog network. It can predict the message coverage rate by guard nodes. The experimental results show that the prediction model has higher accuracy to the source nodes which have lower influence in social network and practical application.

Non-fragile observer-based output feedback control for polytopic uncertain system under distributed model predictive control approach

NASA Astrophysics Data System (ADS)

Zhu, Kaiqun; Song, Yan; Zhang, Sunjie; Zhong, Zhaozhun

2017-07-01

In this paper, a non-fragile observer-based output feedback control problem for the polytopic uncertain system under distributed model predictive control (MPC) approach is discussed. By decomposing the global system into some subsystems, the computation complexity is reduced, so it follows that the online designing time can be saved.Moreover, an observer-based output feedback control algorithm is proposed in the framework of distributed MPC to deal with the difficulties in obtaining the states measurements. In this way, the presented observer-based output-feedback MPC strategy is more flexible and applicable in practice than the traditional state-feedback one. What is more, the non-fragility of the controller has been taken into consideration in favour of increasing the robustness of the polytopic uncertain system. After that, a sufficient stability criterion is presented by using Lyapunov-like functional approach, meanwhile, the corresponding control law and the upper bound of the quadratic cost function are derived by solving an optimisation subject to convex constraints. Finally, some simulation examples are employed to show the effectiveness of the method.

Towards energy efficient operation of Heating, Ventilation and Air Conditioning systems via advanced supervisory control design

NASA Astrophysics Data System (ADS)

Oswiecinska, A.; Hibbs, J.; Zajic, I.; Burnham, K. J.

2015-11-01

This paper presents conceptual control solution for reliable and energy efficient operation of heating, ventilation and air conditioning (HVAC) systems used in large volume building applications, e.g. warehouse facilities or exhibition centres. Advanced two-level scalable control solution, designed to extend capabilities of the existing low-level control strategies via remote internet connection, is presented. The high-level, supervisory controller is based on Model Predictive Control (MPC) architecture, which is the state-of-the-art for indoor climate control systems. The innovative approach benefits from using passive heating and cooling control strategies for reducing the HVAC system operational costs, while ensuring that required environmental conditions are met.

Graphene levitation and orientation control using a magnetic field

NASA Astrophysics Data System (ADS)

Niu, Chao; Lin, Feng; Wang, Zhiming M.; Bao, Jiming; Hu, Jonathan

2018-01-01

This paper studies graphene levitation and orientation control using a magnetic field. The torques in all three spatial directions induced by diamagnetic forces are used to predict stable conditions for different shapes of millimeter-sized graphite plates. We find that graphite plates, in regular polygon shapes with an even number of sides, will be levitated in a stable manner above four interleaved permanent magnets. In addition, the orientation of micrometer-sized graphene flakes near a permanent magnet is studied in both air and liquid environments. Using these analyses, we are able to simulate optical transmission and reflection on a writing board and thereby reveal potential applications using this technology for display screens. Understanding the control of graphene flake orientation will lead to the discovery of future applications using graphene flakes.

ITC/USA/'90; Proceedings of the International Telemetering Conference, Las Vegas, NV, Oct. 29-Nov. 2, 1990

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

Not Available

1990-01-01

This conference presents papers in the fields of airborne telemetry, measurement technology, video instrumentation and monitoring, tracking and receiving systems, and real-time processing in telemetry. Topics presented include packet telemetry ground station simulation, a predictable performance wideband noise generator, an improved drone tracking control system transponder, the application of neural networks to drone control, and an integrated real-time turbine engine flight test system.

Spatial Map of Synthesized Criteria for the Redundancy Resolution of Human Arm Movements.

PubMed

Li, Zhi; Milutinovic, Dejan; Rosen, Jacob

2015-11-01

The kinematic redundancy of the human arm enables the elbow position to rotate about the axis going through the shoulder and wrist, which results in infinite possible arm postures when the arm reaches to a target in a 3-D workspace. To infer the control strategy the human motor system uses to resolve redundancy in reaching movements, this paper compares five redundancy resolution criteria and evaluates their arm posture prediction performance using data on healthy human motion. Two synthesized criteria are developed to provide better real-time arm posture prediction than the five individual criteria. Of these two, the criterion synthesized using an exponential method predicts the arm posture more accurately than that using a least squares approach, and therefore is preferable for inferring the contributions of the individual criteria to motor control during reaching movements. As a methodology contribution, this paper proposes a framework to compare and evaluate redundancy resolution criteria for arm motion control. A cluster analysis which associates criterion contributions with regions of the workspace provides a guideline for designing a real-time motion control system applicable to upper-limb exoskeletons for stroke rehabilitation.

The impact of circulation control on rotary aircraft controls systems

NASA Technical Reports Server (NTRS)

Kingloff, R. F.; Cooper, D. E.

1987-01-01

Application of circulation to rotary wing systems is a new development. Efforts to determine the near and far field flow patterns and to analytically predict those flow patterns have been underway for some years. Rotary wing applications present a new set of challenges in circulation control technology. Rotary wing sections must accommodate substantial Mach number, free stream dynamic pressure and section angle of attack variation at each flight condition within the design envelope. They must also be capable of short term circulation blowing modulation to produce control moments and vibration alleviation in addition to a lift augmentation function. Control system design must provide this primary control moment, vibration alleviation and lift augmentation function. To accomplish this, one must simultaneously control the compressed air source and its distribution. The control law algorithm must therefore address the compressor as the air source, the plenum as the air pressure storage and the pneumatic flow gates or valves that distribute and meter the stored pressure to the rotating blades. Also, mechanical collective blade pitch, rotor shaft angle of attack and engine power control must be maintained.

Statistical prediction of dynamic distortion of inlet flow using minimum dynamic measurement. An application to the Melick statistical method and inlet flow dynamic distortion prediction without RMS measurements

NASA Technical Reports Server (NTRS)

Schweikhard, W. G.; Chen, Y. S.

1986-01-01

The Melick method of inlet flow dynamic distortion prediction by statistical means is outlined. A hypothetic vortex model is used as the basis for the mathematical formulations. The main variables are identified by matching the theoretical total pressure rms ratio with the measured total pressure rms ratio. Data comparisons, using the HiMAT inlet test data set, indicate satisfactory prediction of the dynamic peak distortion for cases with boundary layer control device vortex generators. A method for the dynamic probe selection was developed. Validity of the probe selection criteria is demonstrated by comparing the reduced-probe predictions with the 40-probe predictions. It is indicated that the the number of dynamic probes can be reduced to as few as two and still retain good accuracy.

Fuzzy Behavior-Based Navigation for Planetary

NASA Technical Reports Server (NTRS)

Tunstel, Edward; Danny, Harrison; Lippincott, Tanya; Jamshidi, Mo

1997-01-01

Adaptive behavioral capabilities are necessary for robust rover navigation in unstructured and partially-mapped environments. A control approach is described which exploits the approximate reasoning capability of fuzzy logic to produce adaptive motion behavior. In particular, a behavior-based architecture for hierarchical fuzzy control of microrovers is presented. Its structure is described, as well as mechanisms of control decision-making which give rise to adaptive behavior. Control decisions for local navigation result from a consensus of recommendations offered only by behaviors that are applicable to current situations. Simulation predicts the navigation performance on a microrover in simplified Mars-analog terrain.

Alternative control technology document for bakery oven emissions. Final report

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

Sanford, C.W.

The document was produced in response to a request by the baking industry for Federal guidance to assist in providing a more uniform information base for State decision-making with regard to control of bakery oven emissions. The information in the document pertains to bakeries that produce yeast-leavened bread, rolls, buns, and similar products but not crackers, sweet goods, or baked foodstuffs that are not yeast leavened. Information on the baking processes, equipment, operating parameters, potential emissions from baking, and potential emission control options are presented. Catalytic and regenerative oxidation are identified as the most appropriate existing control technologies applicable tomore » VOC emissions from bakery ovens. Cost analyses for catalytic and regenerative oxidation are included. A predictive formula for use in estimating oven emissions has been derived from source tests done in junction with the development of the document. Its use and applicability are described.« less

DemQSAR: predicting human volume of distribution and clearance of drugs

NASA Astrophysics Data System (ADS)

Demir-Kavuk, Ozgur; Bentzien, Jörg; Muegge, Ingo; Knapp, Ernst-Walter

2011-12-01

In silico methods characterizing molecular compounds with respect to pharmacologically relevant properties can accelerate the identification of new drugs and reduce their development costs. Quantitative structure-activity/-property relationship (QSAR/QSPR) correlate structure and physico-chemical properties of molecular compounds with a specific functional activity/property under study. Typically a large number of molecular features are generated for the compounds. In many cases the number of generated features exceeds the number of molecular compounds with known property values that are available for learning. Machine learning methods tend to overfit the training data in such situations, i.e. the method adjusts to very specific features of the training data, which are not characteristic for the considered property. This problem can be alleviated by diminishing the influence of unimportant, redundant or even misleading features. A better strategy is to eliminate such features completely. Ideally, a molecular property can be described by a small number of features that are chemically interpretable. The purpose of the present contribution is to provide a predictive modeling approach, which combines feature generation, feature selection, model building and control of overtraining into a single application called DemQSAR. DemQSAR is used to predict human volume of distribution (VDss) and human clearance (CL). To control overtraining, quadratic and linear regularization terms were employed. A recursive feature selection approach is used to reduce the number of descriptors. The prediction performance is as good as the best predictions reported in the recent literature. The example presented here demonstrates that DemQSAR can generate a model that uses very few features while maintaining high predictive power. A standalone DemQSAR Java application for model building of any user defined property as well as a web interface for the prediction of human VDss and CL is available on the webpage of DemPRED: http://agknapp.chemie.fu-berlin.de/dempred/.

DemQSAR: predicting human volume of distribution and clearance of drugs.

PubMed

Demir-Kavuk, Ozgur; Bentzien, Jörg; Muegge, Ingo; Knapp, Ernst-Walter

2011-12-01

In silico methods characterizing molecular compounds with respect to pharmacologically relevant properties can accelerate the identification of new drugs and reduce their development costs. Quantitative structure-activity/-property relationship (QSAR/QSPR) correlate structure and physico-chemical properties of molecular compounds with a specific functional activity/property under study. Typically a large number of molecular features are generated for the compounds. In many cases the number of generated features exceeds the number of molecular compounds with known property values that are available for learning. Machine learning methods tend to overfit the training data in such situations, i.e. the method adjusts to very specific features of the training data, which are not characteristic for the considered property. This problem can be alleviated by diminishing the influence of unimportant, redundant or even misleading features. A better strategy is to eliminate such features completely. Ideally, a molecular property can be described by a small number of features that are chemically interpretable. The purpose of the present contribution is to provide a predictive modeling approach, which combines feature generation, feature selection, model building and control of overtraining into a single application called DemQSAR. DemQSAR is used to predict human volume of distribution (VD(ss)) and human clearance (CL). To control overtraining, quadratic and linear regularization terms were employed. A recursive feature selection approach is used to reduce the number of descriptors. The prediction performance is as good as the best predictions reported in the recent literature. The example presented here demonstrates that DemQSAR can generate a model that uses very few features while maintaining high predictive power. A standalone DemQSAR Java application for model building of any user defined property as well as a web interface for the prediction of human VD(ss) and CL is available on the webpage of DemPRED: http://agknapp.chemie.fu-berlin.de/dempred/ .

Aeroservoelasticity

NASA Technical Reports Server (NTRS)

Noll, Thomas E.

1990-01-01

The paper describes recent accomplishments and current research projects along four main thrusts in aeroservoelasticity at NASA Langley. One activity focuses on enhancing the modeling and analysis procedures to accurately predict aeroservoelastic interactions. Improvements to the minimum-state method of approximating unsteady aerodynamics are shown to provide precise low-order models for design and simulation tasks. Recent extensions in aerodynamic correction-factor methodology are also described. With respect to analysis procedures, the paper reviews novel enhancements to matched filter theory and random process theory for predicting the critical gust profile and the associated time-correlated gust loads for structural design considerations. Two research projects leading towards improved design capability are also summarized: (1) an integrated structure/control design capability and (2) procedures for obtaining low-order robust digital control laws for aeroelastic applications.

Robust model predictive control for optimal continuous drug administration.

PubMed

Sopasakis, Pantelis; Patrinos, Panagiotis; Sarimveis, Haralambos

2014-10-01

In this paper the model predictive control (MPC) technology is used for tackling the optimal drug administration problem. The important advantage of MPC compared to other control technologies is that it explicitly takes into account the constraints of the system. In particular, for drug treatments of living organisms, MPC can guarantee satisfaction of the minimum toxic concentration (MTC) constraints. A whole-body physiologically-based pharmacokinetic (PBPK) model serves as the dynamic prediction model of the system after it is formulated as a discrete-time state-space model. Only plasma measurements are assumed to be measured on-line. The rest of the states (drug concentrations in other organs and tissues) are estimated in real time by designing an artificial observer. The complete system (observer and MPC controller) is able to drive the drug concentration to the desired levels at the organs of interest, while satisfying the imposed constraints, even in the presence of modelling errors, disturbances and noise. A case study on a PBPK model with 7 compartments, constraints on 5 tissues and a variable drug concentration set-point illustrates the efficiency of the methodology in drug dosing control applications. The proposed methodology is also tested in an uncertain setting and proves successful in presence of modelling errors and inaccurate measurements. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

Fish consumption in a sample of people in Bandar Abbas, Iran: application of the theory of planned behavior.

PubMed

Aghamolaei, Teamur; Sadat Tavafian, Sedigheh; Madani, Abdoulhossain

2012-09-01

This study aimed to apply the conceptual framework of the theory of planned behavior (TPB) to explain fish consumption in a sample of people who lived in Bandar Abbass, Iran. We investigated the role of three traditional constructs of TPB that included attitude, social norms, and perceived behavioral control in an effort to characterize the intention to consume fish as well as the behavioral trends that characterize fish consumption. Data were derived from a cross-sectional sample of 321 subjects. Alpha coefficient correlation and linear regression analysis were applied to test the relationships between constructs. The predictors of fish consumption frequency were also evaluated. Multiple regression analysis revealed that attitude, subjective norms, and perceived behavioral control significantly predicted intention to eat fish (R2 = 0.54, F = 128.4, P < 0.001). Multiple regression analysis for the intention to eat fish and perceived behavioral control revealed that both factors significantly predicted fish consumption frequency (R2 = 0.58, F = 223.1, P < 0.001). The results indicated that the models fit well with the data. Attitude, subjective norms, and perceived behavioral control all had significant positive impacts on behavioral intention. Moreover, both intention and perceived behavioral control could be used to predict the frequency of fish consumption.

Two Decades of Negative Thermal Expansion Research: Where Do We Stand?

PubMed Central

Lind, Cora

2012-01-01

Negative thermal expansion (NTE) materials have become a rapidly growing area of research over the past two decades. The initial discovery of materials displaying NTE over a large temperature range, combined with elucidation of the mechanism behind this unusual property, was followed by predictions that these materials will find use in various applications through controlled thermal expansion composites. While some patents have been filed and devices built, a number of obstacles have prevented the widespread implementation of NTE materials to date. This paper reviews NTE materials that contract due to transverse atomic vibrations, their potential for use in controlled thermal expansion composites, and known problems that could interfere with such applications. PMID:28817027

High-throughput prediction of tablet weight and trimethoprim content of compound sulfamethoxazole tablets for controlling the uniformity of dosage units by NIR.

PubMed

Dong, Yanhong; Li, Juan; Zhong, Xiaoxiao; Cao, Liya; Luo, Yang; Fan, Qi

2016-04-15

This paper establishes a novel method to simultaneously predict the tablet weight (TW) and trimethoprim (TMP) content of compound sulfamethoxazole tablets (SMZCO) by near infrared (NIR) spectroscopy with partial least squares (PLS) regression for controlling the uniformity of dosage units (UODU). The NIR spectra for 257 samples were measured using the optimized parameter values and pretreated using the optimized chemometric techniques. After the outliers were ignored, two PLS models for predicting TW and TMP content were respectively established by using the selected spectral sub-ranges and the reference values. The TW model reaches the correlation coefficient of calibration (R(c)) 0.9543 and the TMP content model has the R(c) 0.9205. The experimental results indicate that this strategy expands the NIR application in controlling UODU, especially in the high-throughput and rapid analysis of TWs and contents of the compound pharmaceutical tablets, and may be an important complement to the common NIR on-line analytical method for pharmaceutical tablets. Copyright © 2016 Elsevier B.V. All rights reserved.

Controlling the Surface Chemistry of Graphite by Engineered Self-Assembled Peptides

PubMed Central

Khatayevich, Dmitriy; So, Christopher R.; Hayamizu, Yuhei; Gresswell, Carolyn; Sarikaya, Mehmet

2012-01-01

The systematic control over surface chemistry is a long-standing challenge in biomedical and nanotechnological applications for graphitic materials. As a novel approach, we utilize graphite-binding dodecapeptides that self-assemble into dense domains to form monolayer thick long-range ordered films on graphite. Specifically, the peptides are rationally designed through their amino acid sequences to predictably display hydrophilic and hydrophobic characteristics while maintaining their self-assembly capabilities on the solid substrate. The peptides are observed to maintain a high tolerance for sequence modification, allowing the control over surface chemistry via their amino acid sequence. Furthermore, through a single step co-assembly of two different designed peptides, we predictably and precisely tune the wettability of the resulting functionalized graphite surfaces from 44 to 83 degrees. The modular molecular structures and predictable behavior of short peptides demonstrated here give rise to a novel platform for functionalizing graphitic materials that offers numerous advantages, including non-invasive modification of the substrate, bio-compatible processing in an aqueous environment, and simple fusion with other functional biological molecules. PMID:22428620

A Graph Based Approach to Nonlinear Model Predictive Control with Application to Combustion Control and Flow Control

DTIC Science & Technology

2015-08-21

plants (200 MW and above) produce the majority of the nation’s energy demands, and these are the most heavily regulated by the EPA . The automotive...existing engines are not achieving the best possible efficiency. As in the electric power industry, EPA regulation is a major factor in the US...automotive engine market. Cummins, for example, was the only company in the market to meet the 2010 EPA standards for NOx emissions with their release of a 6.7

Stream Processors

NASA Astrophysics Data System (ADS)

Erez, Mattan; Dally, William J.

Stream processors, like other multi core architectures partition their functional units and storage into multiple processing elements. In contrast to typical architectures, which contain symmetric general-purpose cores and a cache hierarchy, stream processors have a significantly leaner design. Stream processors are specifically designed for the stream execution model, in which applications have large amounts of explicit parallel computation, structured and predictable control, and memory accesses that can be performed at a coarse granularity. Applications in the streaming model are expressed in a gather-compute-scatter form, yielding programs with explicit control over transferring data to and from on-chip memory. Relying on these characteristics, which are common to many media processing and scientific computing applications, stream architectures redefine the boundary between software and hardware responsibilities with software bearing much of the complexity required to manage concurrency, locality, and latency tolerance. Thus, stream processors have minimal control consisting of fetching medium- and coarse-grained instructions and executing them directly on the many ALUs. Moreover, the on-chip storage hierarchy of stream processors is under explicit software control, as is all communication, eliminating the need for complex reactive hardware mechanisms.

Application of principal component regression and artificial neural network in FT-NIR soluble solids content determination of intact pear fruit

NASA Astrophysics Data System (ADS)

Ying, Yibin; Liu, Yande; Fu, Xiaping; Lu, Huishan

2005-11-01

The artificial neural networks (ANNs) have been used successfully in applications such as pattern recognition, image processing, automation and control. However, majority of today's applications of ANNs is back-propagate feed-forward ANN (BP-ANN). In this paper, back-propagation artificial neural networks (BP-ANN) were applied for modeling soluble solid content (SSC) of intact pear from their Fourier transform near infrared (FT-NIR) spectra. One hundred and sixty-four pear samples were used to build the calibration models and evaluate the models predictive ability. The results are compared to the classical calibration approaches, i.e. principal component regression (PCR), partial least squares (PLS) and non-linear PLS (NPLS). The effects of the optimal methods of training parameters on the prediction model were also investigated. BP-ANN combine with principle component regression (PCR) resulted always better than the classical PCR, PLS and Weight-PLS methods, from the point of view of the predictive ability. Based on the results, it can be concluded that FT-NIR spectroscopy and BP-ANN models can be properly employed for rapid and nondestructive determination of fruit internal quality.

Fast and predictable video compression in software design and implementation of an H.261 codec

NASA Astrophysics Data System (ADS)

Geske, Dagmar; Hess, Robert

1998-09-01

The use of software codecs for video compression becomes commonplace in several videoconferencing applications. In order to reduce conflicts with other applications used at the same time, mechanisms for resource reservation on endsystems need to determine an upper bound for computing time used by the codec. This leads to the demand for predictable execution times of compression/decompression. Since compression schemes as H.261 inherently depend on the motion contained in the video, an adaptive admission control is required. This paper presents a data driven approach based on dynamical reduction of the number of processed macroblocks in peak situations. Besides the absolute speed is a point of interest. The question, whether and how software compression of high quality video is feasible on today's desktop computers, is examined.

Upper and Middle Atmospheric Density Modeling Requirements for Spacecraft Design and Operations

NASA Technical Reports Server (NTRS)

Davis, M. H. (Editor); Smith, R. E. (Editor); Johnson, D. L. (Editor)

1987-01-01

Presented and discussed are concerns with applications of neutral atmospheric density models to space vehicle engineering design and operational problems. The area of concern which the atmospheric model developers and the model users considered, involved middle atmosphere (50 to 90 km altitude) and thermospheric (above 90 km) models and their engineering application. Engineering emphasis involved areas such as orbital decay and lifetime prediction along with attitude and control studies for different types of space and reentry vehicles.

Towards the application of one-dimensional sonomyography for powered upper-limb prosthetic control using machine learning models.

PubMed

Guo, Jing-Yi; Zheng, Yong-Ping; Xie, Hong-Bo; Koo, Terry K

2013-02-01

The inherent properties of surface electromyography limit its potential for multi-degrees of freedom control. Our previous studies demonstrated that wrist angle could be predicted by muscle thickness measured from B-mode ultrasound, and hence, it could be an alternative signal for prosthetic control. However, an ultrasound imaging machine is too bulky and expensive. We aim to utilize a portable A-mode ultrasound system to examine the feasibility of using one-dimensional sonomyography (i.e. muscle thickness signals detected by A-mode ultrasound) to predict wrist angle with three different machine learning models - (1) support vector machine (SVM), (2) radial basis function artificial neural network (RBF ANN), and (3) back-propagation artificial neural network (BP ANN). Feasibility study using nine healthy subjects. Each subject performed wrist extension guided at 15, 22.5, and 30 cycles/minute, respectively. Data obtained from 22.5 cycles/minute trials was used to train the models and the remaining trials were used for cross-validation. Prediction accuracy was quantified by relative root mean square error (RMSE) and correlation coefficients (CC). Excellent prediction was noted using SVM (RMSE = 13%, CC = 0.975), which outperformed the other methods. It appears that one-dimensional sonomyography could be an alternative signal for prosthetic control. Clinical relevance Surface electromyography has inherent limitations that prohibit its full functional use for prosthetic control. Research that explores alternative signals to improve prosthetic control (such as the one-dimensional sonomyography signals evaluated in this study) may revolutionize powered prosthesis design and ultimately benefit amputee patients.

Application of parameter estimation to aircraft stability and control: The output-error approach

NASA Technical Reports Server (NTRS)

Maine, Richard E.; Iliff, Kenneth W.

1986-01-01

The practical application of parameter estimation methodology to the problem of estimating aircraft stability and control derivatives from flight test data is examined. The primary purpose of the document is to present a comprehensive and unified picture of the entire parameter estimation process and its integration into a flight test program. The document concentrates on the output-error method to provide a focus for detailed examination and to allow us to give specific examples of situations that have arisen. The document first derives the aircraft equations of motion in a form suitable for application to estimation of stability and control derivatives. It then discusses the issues that arise in adapting the equations to the limitations of analysis programs, using a specific program for an example. The roles and issues relating to mass distribution data, preflight predictions, maneuver design, flight scheduling, instrumentation sensors, data acquisition systems, and data processing are then addressed. Finally, the document discusses evaluation and the use of the analysis results.

The seasonal timing of warming that controls onset of the growing season.

PubMed

Clark, James S; Melillo, Jerry; Mohan, Jacqueline; Salk, Carl

2014-04-01

Forecasting how global warming will affect onset of the growing season is essential for predicting terrestrial productivity, but suffers from conflicting evidence. We show that accurate estimates require ways to connect discrete observations of changing tree status (e.g., pre- vs. post budbreak) with continuous responses to fluctuating temperatures. By coherently synthesizing discrete observations with continuous responses to temperature variation, we accurately quantify how increasing temperature variation accelerates onset of growth. Application to warming experiments at two latitudes demonstrates that maximum responses to warming are concentrated in late winter, weeks ahead of the main budbreak period. Given that warming will not occur uniformly over the year, knowledge of when temperature variation has the most impact can guide prediction. Responses are large and heterogeneous, yet predictable. The approach has immediate application to forecasting effects of warming on growing season length, requiring only information that is readily available from weather stations and generated in climate models. © 2013 John Wiley & Sons Ltd.

4D Origami by Smart Embroidery.

PubMed

Stoychev, Georgi; Razavi, Mir Jalil; Wang, Xianqiao; Ionov, Leonid

2017-09-01

There exist many methods for processing of materials: extrusion, injection molding, fibers spinning, 3D printing, to name a few. In most cases, materials with a static, fixed shape are produced. However, numerous advanced applications require customized elements with reconfigurable shape. The few available techniques capable of overcoming this problem are expensive and/or time-consuming. Here, the use of one of the most ancient technologies for structuring, embroidering, is proposed to generate sophisticated patterns of active materials, and, in this way, to achieve complex actuation. By combining experiments and computational modeling, the fundamental rules that can predict the folding behavior of sheets with a variety of stitch-patterns are elucidated. It is demonstrated that theoretical mechanics analysis is only suitable to predict the behavior of the simplest experimental setups, whereas computer modeling gives better predictions for more complex cases. Finally, the applicability of the rules by designing basic origami structures and wrinkling substrates with controlled thermal insulation properties is shown. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Evaluation and prediction of solar radiation for energy management based on neural networks

NASA Astrophysics Data System (ADS)

Aldoshina, O. V.; Van Tai, Dinh

2017-08-01

Currently, there is a high rate of distribution of renewable energy sources and distributed power generation based on intelligent networks; therefore, meteorological forecasts are particularly useful for planning and managing the energy system in order to increase its overall efficiency and productivity. The application of artificial neural networks (ANN) in the field of photovoltaic energy is presented in this article. Implemented in this study, two periodically repeating dynamic ANS, that are the concentration of the time delay of a neural network (CTDNN) and the non-linear autoregression of a network with exogenous inputs of the NAEI, are used in the development of a model for estimating and daily forecasting of solar radiation. ANN show good productivity, as reliable and accurate models of daily solar radiation are obtained. This allows to successfully predict the photovoltaic output power for this installation. The potential of the proposed method for controlling the energy of the electrical network is shown using the example of the application of the NAEI network for predicting the electric load.

Neural Network Based Models for Fusion Applications

NASA Astrophysics Data System (ADS)

Meneghini, Orso; Tema Biwole, Arsene; Luda, Teobaldo; Zywicki, Bailey; Rea, Cristina; Smith, Sterling; Snyder, Phil; Belli, Emily; Staebler, Gary; Canty, Jeff

2017-10-01

Whole device modeling, engineering design, experimental planning and control applications demand models that are simultaneously physically accurate and fast. This poster reports on the ongoing effort towards the development and validation of a series of models that leverage neural-­network (NN) multidimensional regression techniques to accelerate some of the most mission critical first principle models for the fusion community, such as: the EPED workflow for prediction of the H-Mode and Super H-Mode pedestal structure the TGLF and NEO models for the prediction of the turbulent and neoclassical particle, energy and momentum fluxes; and the NEO model for the drift-kinetic solution of the bootstrap current. We also applied NNs on DIII-D experimental data for disruption prediction and quantifying the effect of RMPs on the pedestal and ELMs. All of these projects were supported by the infrastructure provided by the OMFIT integrated modeling framework. Work supported by US DOE under DE-SC0012656, DE-FG02-95ER54309, DE-FC02-04ER54698.

Application of a Novel Grey Self-Memory Coupling Model to Forecast the Incidence Rates of Two Notifiable Diseases in China: Dysentery and Gonorrhea

PubMed Central

Guo, Xiaojun; Liu, Sifeng; Wu, Lifeng; Tang, Lingling

2014-01-01

Objective In this study, a novel grey self-memory coupling model was developed to forecast the incidence rates of two notifiable infectious diseases (dysentery and gonorrhea); the effectiveness and applicability of this model was assessed based on its ability to predict the epidemiological trend of infectious diseases in China. Methods The linear model, the conventional GM(1,1) model and the GM(1,1) model with self-memory principle (SMGM(1,1) model) were used to predict the incidence rates of the two notifiable infectious diseases based on statistical incidence data. Both simulation accuracy and prediction accuracy were assessed to compare the predictive performances of the three models. The best-fit model was applied to predict future incidence rates. Results Simulation results show that the SMGM(1,1) model can take full advantage of the systematic multi-time historical data and possesses superior predictive performance compared with the linear model and the conventional GM(1,1) model. By applying the novel SMGM(1,1) model, we obtained the possible incidence rates of the two representative notifiable infectious diseases in China. Conclusion The disadvantages of the conventional grey prediction model, such as sensitivity to initial value, can be overcome by the self-memory principle. The novel grey self-memory coupling model can predict the incidence rates of infectious diseases more accurately than the conventional model, and may provide useful references for making decisions involving infectious disease prevention and control. PMID:25546054

Application of a novel grey self-memory coupling model to forecast the incidence rates of two notifiable diseases in China: dysentery and gonorrhea.

PubMed

Guo, Xiaojun; Liu, Sifeng; Wu, Lifeng; Tang, Lingling

2014-01-01

In this study, a novel grey self-memory coupling model was developed to forecast the incidence rates of two notifiable infectious diseases (dysentery and gonorrhea); the effectiveness and applicability of this model was assessed based on its ability to predict the epidemiological trend of infectious diseases in China. The linear model, the conventional GM(1,1) model and the GM(1,1) model with self-memory principle (SMGM(1,1) model) were used to predict the incidence rates of the two notifiable infectious diseases based on statistical incidence data. Both simulation accuracy and prediction accuracy were assessed to compare the predictive performances of the three models. The best-fit model was applied to predict future incidence rates. Simulation results show that the SMGM(1,1) model can take full advantage of the systematic multi-time historical data and possesses superior predictive performance compared with the linear model and the conventional GM(1,1) model. By applying the novel SMGM(1,1) model, we obtained the possible incidence rates of the two representative notifiable infectious diseases in China. The disadvantages of the conventional grey prediction model, such as sensitivity to initial value, can be overcome by the self-memory principle. The novel grey self-memory coupling model can predict the incidence rates of infectious diseases more accurately than the conventional model, and may provide useful references for making decisions involving infectious disease prevention and control.

Real time optimal guidance of low-thrust spacecraft: an application of nonlinear model predictive control.

PubMed

Arrieta-Camacho, Juan José; Biegler, Lorenz T

2005-12-01

Real time optimal guidance is considered for a class of low thrust spacecraft. In particular, nonlinear model predictive control (NMPC) is utilized for computing the optimal control actions required to transfer a spacecraft from a low Earth orbit to a mission orbit. The NMPC methodology presented is able to cope with unmodeled disturbances. The dynamics of the transfer are modeled using a set of modified equinoctial elements because they do not exhibit singularities for zero inclination and zero eccentricity. The idea behind NMPC is the repeated solution of optimal control problems; at each time step, a new control action is computed. The optimal control problem is solved using a direct method-fully discretizing the equations of motion. The large scale nonlinear program resulting from the discretization procedure is solved using IPOPT--a primal-dual interior point algorithm. Stability and robustness characteristics of the NMPC algorithm are reviewed. A numerical example is presented that encourages further development of the proposed methodology: the transfer from low-Earth orbit to a molniya orbit.

Constrained model predictive control, state estimation and coordination

NASA Astrophysics Data System (ADS)

Yan, Jun

In this dissertation, we study the interaction between the control performance and the quality of the state estimation in a constrained Model Predictive Control (MPC) framework for systems with stochastic disturbances. This consists of three parts: (i) the development of a constrained MPC formulation that adapts to the quality of the state estimation via constraints; (ii) the application of such a control law in a multi-vehicle formation coordinated control problem in which each vehicle operates subject to a no-collision constraint posed by others' imperfect prediction computed from finite bit-rate, communicated data; (iii) the design of the predictors and the communication resource assignment problem that satisfy the performance requirement from Part (ii). Model Predictive Control (MPC) is of interest because it is one of the few control design methods which preserves standard design variables and yet handles constraints. MPC is normally posed as a full-state feedback control and is implemented in a certainty-equivalence fashion with best estimates of the states being used in place of the exact state. However, if the state constraints were handled in the same certainty-equivalence fashion, the resulting control law could drive the real state to violate the constraints frequently. Part (i) focuses on exploring the inclusion of state estimates into the constraints. It does this by applying constrained MPC to a system with stochastic disturbances. The stochastic nature of the problem requires re-posing the constraints in a probabilistic form. In Part (ii), we consider applying constrained MPC as a local control law in a coordinated control problem of a group of distributed autonomous systems. Interactions between the systems are captured via constraints. First, we inspect the application of constrained MPC to a completely deterministic case. Formation stability theorems are derived for the subsystems and conditions on the local constraint set are derived in order to guarantee local stability or convergence to a target state. If these conditions are met for all subsystems, then this stability is inherited by the overall system. For the case when each subsystem suffers from disturbances in the dynamics, own self-measurement noises, and quantization errors on neighbors' information due to the finite-bit-rate channels, the constrained MPC strategy developed in Part (i) is appropriate to apply. In Part (iii), we discuss the local predictor design and bandwidth assignment problem in a coordinated vehicle formation context. The MPC controller used in Part (ii) relates the formation control performance and the information quality in the way that large standoff implies conservative performance. We first develop an LMI (Linear Matrix Inequality) formulation for cross-estimator design in a simple two-vehicle scenario with non-standard information: one vehicle does not have access to the other's exact control value applied at each sampling time, but to its known, pre-computed, coupling linear feedback control law. Then a similar LMI problem is formulated for the bandwidth assignment problem that minimizes the total number of bits by adjusting the prediction gain matrices and the number of bits assigned to each variable. (Abstract shortened by UMI.)

Testing a hydraulic trait based model of stomatal control: results from a controlled drought experiment on aspen (Populus tremuloides, Michx.) and ponderosa pine (Pinus ponderosa, Douglas)

NASA Astrophysics Data System (ADS)

Love, D. M.; Venturas, M.; Sperry, J.; Wang, Y.; Anderegg, W.

2017-12-01

Modeling approaches for tree stomatal control often rely on empirical fitting to provide accurate estimates of whole tree transpiration (E) and assimilation (A), which are limited in their predictive power by the data envelope used to calibrate model parameters. Optimization based models hold promise as a means to predict stomatal behavior under novel climate conditions. We designed an experiment to test a hydraulic trait based optimization model, which predicts stomatal conductance from a gain/risk approach. Optimal stomatal conductance is expected to maximize the potential carbon gain by photosynthesis, and minimize the risk to hydraulic transport imposed by cavitation. The modeled risk to the hydraulic network is assessed from cavitation vulnerability curves, a commonly measured physiological trait in woody plant species. Over a growing season garden grown plots of aspen (Populus tremuloides, Michx.) and ponderosa pine (Pinus ponderosa, Douglas) were subjected to three distinct drought treatments (moderate, severe, severe with rehydration) relative to a control plot to test model predictions. Model outputs of predicted E, A, and xylem pressure can be directly compared to both continuous data (whole tree sapflux, soil moisture) and point measurements (leaf level E, A, xylem pressure). The model also predicts levels of whole tree hydraulic impairment expected to increase mortality risk. This threshold is used to estimate survivorship in the drought treatment plots. The model can be run at two scales, either entirely from climate (meteorological inputs, irrigation) or using the physiological measurements as a starting point. These data will be used to study model performance and utility, and aid in developing the model for larger scale applications.

Constructing the effect of alternative intervention strategies on historic epidemics.

PubMed

Cook, A R; Gibson, G J; Gottwald, T R; Gilligan, C A

2008-10-06

Data from historical epidemics provide a vital and sometimes under-used resource from which to devise strategies for future control of disease. Previous methods for retrospective analysis of epidemics, in which alternative interventions are compared, do not make full use of the information; by using only partial information on the historical trajectory, augmentation of control may lead to predictions of a paradoxical increase in disease. Here we introduce a novel statistical approach that takes full account of the available information in constructing the effect of alternative intervention strategies in historic epidemics. The key to the method lies in identifying a suitable mapping between the historic and notional outbreaks, under alternative control strategies. We do this by using the Sellke construction as a latent process linking epidemics. We illustrate the application of the method with two examples. First, using temporal data for the common human cold, we show the improvement under the new method in the precision of predictions for different control strategies. Second, we show the generality of the method for retrospective analysis of epidemics by applying it to a spatially extended arboreal epidemic in which we demonstrate the relative effectiveness of host culling strategies that differ in frequency and spatial extent. Some of the inferential and philosophical issues that arise are discussed along with the scope of potential application of the new method.

Real-time estimation of FES-induced joint torque with evoked EMG : Application to spinal cord injured patients.

PubMed

Li, Zhan; Guiraud, David; Andreu, David; Benoussaad, Mourad; Fattal, Charles; Hayashibe, Mitsuhiro

2016-06-22

Functional electrical stimulation (FES) is a neuroprosthetic technique for restoring lost motor function of spinal cord injured (SCI) patients and motor-impaired subjects by delivering short electrical pulses to their paralyzed muscles or motor nerves. FES induces action potentials respectively on muscles or nerves so that muscle activity can be characterized by the synchronous recruitment of motor units with its compound electromyography (EMG) signal is called M-wave. The recorded evoked EMG (eEMG) can be employed to predict the resultant joint torque, and modeling of FES-induced joint torque based on eEMG is an essential step to provide necessary prediction of the expected muscle response before achieving accurate joint torque control by FES. Previous works on FES-induced torque tracking issues were mainly based on offline analysis. However, toward personalized clinical rehabilitation applications, real-time FES systems are essentially required considering the subject-specific muscle responses against electrical stimulation. This paper proposes a wireless portable stimulator used for estimating/predicting joint torque based on real time processing of eEMG. Kalman filter and recurrent neural network (RNN) are embedded into the real-time FES system for identification and estimation. Prediction results on 3 able-bodied subjects and 3 SCI patients demonstrate promising performances. As estimators, both Kalman filter and RNN approaches show clinically feasible results on estimation/prediction of joint torque with eEMG signals only, moreover RNN requires less computational requirement. The proposed real-time FES system establishes a platform for estimating and assessing the mechanical output, the electromyographic recordings and associated models. It will contribute to open a new modality for personalized portable neuroprosthetic control toward consolidated personal healthcare for motor-impaired patients.

Predicting Future-Year Ozone Concentrations: Integrated Observational-Modeling Approach for Probabilistic Evaluation of the Efficacy of Emission Control strategies

EPA Science Inventory

Regional-scale air quality models are being used to demonstrate attainment of the ozone air quality standard. In current regulatory applications, a regional-scale air quality model is applied for a base year and a future year with reduced emissions using the same meteorological ...

Adaptive Model Predictive Control of Diesel Engine Selective Catalytic Reduction (SCR) Systems

ERIC Educational Resources Information Center

McKinley, Thomas L.

2009-01-01

Selective catalytic reduction or SCR is coming into worldwide use for diesel engine emissions reduction for on- and off-highway vehicles. These applications are characterized by broad operating range as well as rapid and unpredictable changes in operating conditions. Significant nonlinearity, input and output constraints, and stringent performance…

Development of models to estimate the subgrade and subbase layers' resilient modulus from in-situ devices test results for construction control.

DOT National Transportation Integrated Search

2009-05-01

The primary objective of this research was to develop models that predict the resilient modulus of cohesive and granular soils from the test results of various in-situ test devices for possible application in QA/QC during construction of pavement str...

Stressor-response modeling using the 2D water quality model and regression trees to predict chlorophyll-a in a reservoir system

USDA-ARS?s Scientific Manuscript database

In order to control algal blooms, stressor-response relationships between water quality metrics, environmental variables, and algal growth should be understood and modeled. Machine-learning methods were suggested to express stressor-response relationships found by application of mechanistic water qu...

ANN-PSO Integrated Optimization Methodology for Intelligent Control of MMC Machining

NASA Astrophysics Data System (ADS)

Chandrasekaran, Muthumari; Tamang, Santosh

2017-08-01

Metal Matrix Composites (MMC) show improved properties in comparison with non-reinforced alloys and have found increased application in automotive and aerospace industries. The selection of optimum machining parameters to produce components of desired surface roughness is of great concern considering the quality and economy of manufacturing process. In this study, a surface roughness prediction model for turning Al-SiCp MMC is developed using Artificial Neural Network (ANN). Three turning parameters viz., spindle speed ( N), feed rate ( f) and depth of cut ( d) were considered as input neurons and surface roughness was an output neuron. ANN architecture having 3 -5 -1 is found to be optimum and the model predicts with an average percentage error of 7.72 %. Particle Swarm Optimization (PSO) technique is used for optimizing parameters to minimize machining time. The innovative aspect of this work is the development of an integrated ANN-PSO optimization method for intelligent control of MMC machining process applicable to manufacturing industries. The robustness of the method shows its superiority for obtaining optimum cutting parameters satisfying desired surface roughness. The method has better convergent capability with minimum number of iterations.

Modeling take-over performance in level 3 conditionally automated vehicles.

PubMed

Gold, Christian; Happee, Riender; Bengler, Klaus

2018-07-01

Taking over vehicle control from a Level 3 conditionally automated vehicle can be a demanding task for a driver. The take-over determines the controllability of automated vehicle functions and thereby also traffic safety. This paper presents models predicting the main take-over performance variables take-over time, minimum time-to-collision, brake application and crash probability. These variables are considered in relation to the situational and driver-related factors time-budget, traffic density, non-driving-related task, repetition, the current lane and driver's age. Regression models were developed using 753 take-over situations recorded in a series of driving simulator experiments. The models were validated with data from five other driving simulator experiments of mostly unrelated authors with another 729 take-over situations. The models accurately captured take-over time, time-to-collision and crash probability, and moderately predicted the brake application. Especially the time-budget, traffic density and the repetition strongly influenced the take-over performance, while the non-driving-related tasks, the lane and drivers' age explained a minor portion of the variance in the take-over performances. Copyright © 2017 Elsevier Ltd. All rights reserved.

An Efficient Computational Model to Predict Protonation at the Amide Nitrogen and Reactivity along the C–N Rotational Pathway

PubMed Central

Szostak, Roman; Aubé, Jeffrey

2015-01-01

N-protonation of amides is critical in numerous biological processes, including amide bonds proteolysis and protein folding, as well as in organic synthesis as a method to activate amide bonds towards unconventional reactivity. A computational model enabling prediction of protonation at the amide bond nitrogen atom along the C–N rotational pathway is reported. Notably, this study provides a blueprint for the rational design and application of amides with a controlled degree of rotation in synthetic chemistry and biology. PMID:25766378

Theoretical prediction of airplane stability derivatives at subcritical speeds

NASA Technical Reports Server (NTRS)

Tulinius, J.; Clever, W.; Nieman, A.; Dunn, K.; Gaither, B.

1973-01-01

The theoretical development and application is described of an analysis for predicting the major static and rotary stability derivatives for a complete airplane. The analysis utilizes potential flow theory to compute the surface flow fields and pressures on any configuration that can be synthesized from arbitrary lifting bodies and nonplanar thick lifting panels. The pressures are integrated to obtain section and total configuration loads and moments due side slip, angle of attack, pitching motion, rolling motion, yawing motion, and control surface deflection. Subcritical compressibility is accounted for by means of the Gothert similarity rule.

Mass Uncertainty and Application For Space Systems

NASA Technical Reports Server (NTRS)

Beech, Geoffrey

2013-01-01

Expected development maturity under contract (spec) should correlate with Project/Program Approved MGA Depletion Schedule in Mass Properties Control Plan. If specification NTE, MGA is inclusive of Actual MGA (A5 & A6). If specification is not an NTE Actual MGA (e.g. nominal), then MGA values are reduced by A5 values and A5 is representative of remaining uncertainty. Basic Mass = Engineering Estimate based on design and construction principles with NO embedded margin MGA Mass = Basic Mass * assessed % from approved MGA schedule. Predicted Mass = Basic + MGA. Aggregate MGA % = (Aggregate Predicted - Aggregate Basic) /Aggregate Basic.

Exhaled Breath Markers for Nonimaging and Noninvasive Measures for Detection of Multiple Sclerosis.

PubMed

Broza, Yoav Y; Har-Shai, Lior; Jeries, Raneen; Cancilla, John C; Glass-Marmor, Lea; Lejbkowicz, Izabella; Torrecilla, José S; Yao, Xuelin; Feng, Xinliang; Narita, Akimitsu; Müllen, Klaus; Miller, Ariel; Haick, Hossam

2017-11-15

Multiple sclerosis (MS) is the most common chronic neurological disease affecting young adults. MS diagnosis is based on clinical characteristics and confirmed by examination of the cerebrospinal fluids (CSF) or by magnetic resonance imaging (MRI) of the brain or spinal cord or both. However, neither of the current diagnostic procedures are adequate as a routine tool to determine disease state. Thus, diagnostic biomarkers are needed. In the current study, a novel approach that could meet these expectations is presented. The approach is based on noninvasive analysis of volatile organic compounds (VOCs) in breath. Exhaled breath was collected from 204 participants, 146 MS and 58 healthy control individuals. Analysis was performed by gas-chromatography mass-spectrometry (GC-MS) and nanomaterial-based sensor array. Predictive models were derived from the sensors, using artificial neural networks (ANNs). GC-MS analysis revealed significant differences in VOC abundance between MS patients and controls. Sensor data analysis on training sets was able to discriminate in binary comparisons between MS patients and controls with accuracies up to 90%. Blinded sets showed 95% positive predictive value (PPV) between MS-remission and control, 100% sensitivity with 100% negative predictive value (NPV) between MS not-treated (NT) and control, and 86% NPV between relapse and control. Possible links between VOC biomarkers and the MS pathogenesis were established. Preliminary results suggest the applicability of a new nanotechnology-based method for MS diagnostics.

Prediction of two-dimensional electron gas mediated magnetoelectric coupling at ferroelectric PbTiO3/SrTiO3 heterostructures

NASA Astrophysics Data System (ADS)

Wei, Lan-ying; Lian, Chao; Meng, Sheng

2017-05-01

First-principles calculations predict the emergence of magnetoelectric coupling mediated by two-dimensional electron gas (2DEG) at the ferroelectric PbTiO3/SrTiO3 heterostructure. Free electrons endowed by naturally existing oxygen vacancies in SrTiO3 are driven to the heterostructure interface under the polarizing field of ferroelectric PbTiO3 to form a 2DEG. The electrons are captured by interfacial Ti atoms, which surprisingly exhibits ferromagnetism even at room temperature with a small critical density of ˜15.5 μ C /cm2 . The ferroelectricity-controlled ferromagnetism mediated by interfacial 2DEG shows strong magnetoelectric coupling strength, enabling convenient control of magnetism by electric field and vice versa. The PbTiO3/SrTiO3 heterostructure is cheap, easily grown, and controllable, promising future applications in low-cost spintronics and information storage at ambient condition.

Protective mechanical ventilation in United Kingdom critical care units: A multicentre audit

PubMed Central

Martin, Matthew J; Richardson, Neil; Bourdeaux, Christopher P

2016-01-01

Lung protective ventilation is becoming increasingly used for all critically ill patients being mechanically ventilated on a mandatory ventilator mode. Compliance with the universal application of this ventilation strategy in intensive care units in the United Kingdom is unknown. This 24-h audit of ventilation practice took place in 16 intensive care units in two regions of the United Kingdom. The mean tidal volume for all patients being ventilated on a mandatory ventilator mode was 7.2(±1.4) ml kg−1 predicted body weight and overall compliance with low tidal volume ventilation (≤6.5 ml kg−1 predicted body weight) was 34%. The mean tidal volume for patients ventilated with volume-controlled ventilation was 7.0(±1.2) ml kg−1 predicted body weight and 7.9(±1.8) ml kg−1 predicted body weight for pressure-controlled ventilation (P < 0.0001). Overall compliance with recommended levels of positive end-expiratory pressure was 72%. Significant variation in practice existed both at a regional and individual unit level. PMID:28979556

Protective mechanical ventilation in United Kingdom critical care units: A multicentre audit.

PubMed

Newell, Christopher P; Martin, Matthew J; Richardson, Neil; Bourdeaux, Christopher P

2017-05-01

Lung protective ventilation is becoming increasingly used for all critically ill patients being mechanically ventilated on a mandatory ventilator mode. Compliance with the universal application of this ventilation strategy in intensive care units in the United Kingdom is unknown. This 24-h audit of ventilation practice took place in 16 intensive care units in two regions of the United Kingdom. The mean tidal volume for all patients being ventilated on a mandatory ventilator mode was 7.2(±1.4) ml kg -1 predicted body weight and overall compliance with low tidal volume ventilation (≤6.5 ml kg -1 predicted body weight) was 34%. The mean tidal volume for patients ventilated with volume-controlled ventilation was 7.0(±1.2) ml kg -1 predicted body weight and 7.9(±1.8) ml kg -1 predicted body weight for pressure-controlled ventilation ( P  < 0.0001). Overall compliance with recommended levels of positive end-expiratory pressure was 72%. Significant variation in practice existed both at a regional and individual unit level.

Analysis of Orbital Lifetime Prediction Parameters in Preparation for Post-Mission Disposal

NASA Astrophysics Data System (ADS)

Choi, Ha-Yeon; Kim, Hae-Dong; Seong, Jae-Dong

2015-12-01

Atmospheric drag force is an important source of perturbation of Low Earth Orbit (LEO) orbit satellites, and solar activity is a major factor for changes in atmospheric density. In particular, the orbital lifetime of a satellite varies with changes in solar activity, so care must be taken in predicting the remaining orbital lifetime during preparation for post-mission disposal. In this paper, the System Tool Kit (STK®) Long-term Orbit Propagator is used to analyze the changes in orbital lifetime predictions with respect to solar activity. In addition, the STK® Lifetime tool is used to analyze the change in orbital lifetime with respect to solar flux data generation, which is needed for the orbital lifetime calculation, and its control on the drag coefficient control. Analysis showed that the application of the most recent solar flux file within the Lifetime tool gives a predicted trend that is closest to the actual orbit. We also examine the effect of the drag coefficient, by performing a comparative analysis between varying and constant coefficients in terms of solar activity intensities.

When do normative beliefs about aggression predict aggressive behavior? An application of I3 theory.

PubMed

Li, Jian-Bin; Nie, Yan-Gang; Boardley, Ian D; Dou, Kai; Situ, Qiao-Min

2015-01-01

I(3) theory assumes that aggressive behavior is dependent on three orthogonal processes (i.e., Instigator, Impellance, and Inhibition). Previous studies showed that Impellance (trait aggressiveness, retaliation tendencies) better predicted aggression when Instigator was strong and Inhibition was weak. In the current study, we predicted that another Impellance (i.e., normative beliefs about aggression) might predict aggression when Instigator was absent and Inhibition was high (i.e., the perfect calm proposition). In two experiments, participants first completed the normative beliefs about aggression questionnaire. Two weeks later, participants' self-control resources were manipulated either using the Stroop task (study 1, N = 148) or through an "e-crossing" task (study 2, N = 180). Afterwards, with or without being provoked, participants played a game with an ostensible partner where they had a chance to aggress against them. Study 1 found that normative beliefs about aggression negatively and significantly predicted aggressive behavior only when provocation was absent and self-control resources were not depleted. In Study 2, normative beliefs about aggression negatively predicted aggressive behavior at marginal significance level only in the "no-provocation and no-depletion" condition. In conclusion, the current study provides partial support for the perfect calm proposition and I(3) theory. © 2015 Wiley Periodicals, Inc.

Preview Scheduled Model Predictive Control For Horizontal Axis Wind Turbines

NASA Astrophysics Data System (ADS)

Laks, Jason H.

This research investigates the use of model predictive control (MPC) in application to wind turbine operation from start-up to cut-out. The studies conducted are focused on the design of an MPC controller for a 650˜KW, three-bladed horizontal axis turbine that is in operation at the National Renewable Energy Laboratory's National Wind Technology Center outside of Golden, Colorado. This turbine is at the small end of utility scale turbines, but it provides advanced instrumentation and control capabilities, and there is a good probability that the approach developed in simulation for this thesis, will be field tested on the actual turbine. A contribution of this thesis is a method to combine the use of preview measurements with MPC while also providing regulation of turbine speed and cyclic blade loading. A common MPC technique provides integral-like control to achieve offset-free operation. At the same time in wind turbine applications, multiple studies have developed "feed-forward" controls based on applying a gain to an estimate of the wind speed changes obtained from an observer incorporating a disturbance model. These approaches are based on a technique that can be referred to as disturbance accommodating control (DAC). In this thesis, it is shown that offset-free tracking MPC is equivalent to a DAC approach when the disturbance gain is computed to satisfy a regulator equation. Although the MPC literature has recognized that this approach provides "structurally stable" disturbance rejection and tracking, this step is not typically divorced from the MPC computations repeated each sample hit. The DAC formulation is conceptually simpler, and essentially uncouples regulation considerations from MPC related issues. This thesis provides a self contained proof that the DAC formulation (an observer-controller and appropriate disturbance gain) provides structurally stable regulation.

An Efficient Interval Type-2 Fuzzy CMAC for Chaos Time-Series Prediction and Synchronization.

PubMed

Lee, Ching-Hung; Chang, Feng-Yu; Lin, Chih-Min

2014-03-01

This paper aims to propose a more efficient control algorithm for chaos time-series prediction and synchronization. A novel type-2 fuzzy cerebellar model articulation controller (T2FCMAC) is proposed. In some special cases, this T2FCMAC can be reduced to an interval type-2 fuzzy neural network, a fuzzy neural network, and a fuzzy cerebellar model articulation controller (CMAC). So, this T2FCMAC is a more generalized network with better learning ability, thus, it is used for the chaos time-series prediction and synchronization. Moreover, this T2FCMAC realizes the un-normalized interval type-2 fuzzy logic system based on the structure of the CMAC. It can provide better capabilities for handling uncertainty and more design degree of freedom than traditional type-1 fuzzy CMAC. Unlike most of the interval type-2 fuzzy system, the type-reduction of T2FCMAC is bypassed due to the property of un-normalized interval type-2 fuzzy logic system. This causes T2FCMAC to have lower computational complexity and is more practical. For chaos time-series prediction and synchronization applications, the training architectures with corresponding convergence analyses and optimal learning rates based on Lyapunov stability approach are introduced. Finally, two illustrated examples are presented to demonstrate the performance of the proposed T2FCMAC.

Calibration and prediction of removal function in magnetorheological finishing.

PubMed

Dai, Yifan; Song, Ci; Peng, Xiaoqiang; Shi, Feng

2010-01-20

A calibrated and predictive model of the removal function has been established based on the analysis of a magnetorheological finishing (MRF) process. By introducing an efficiency coefficient of the removal function, the model can be used to calibrate the removal function in a MRF figuring process and to accurately predict the removal function of a workpiece to be polished whose material is different from the spot part. Its correctness and feasibility have been validated by simulations. Furthermore, applying this model to the MRF figuring experiments, the efficiency coefficient of the removal function can be identified accurately to make the MRF figuring process deterministic and controllable. Therefore, all the results indicate that the calibrated and predictive model of the removal function can improve the finishing determinacy and increase the model applicability in a MRF process.

Cognitive Control Predicts Use of Model-Based Reinforcement-Learning

PubMed Central

Otto, A. Ross; Skatova, Anya; Madlon-Kay, Seth; Daw, Nathaniel D.

2015-01-01

Accounts of decision-making and its neural substrates have long posited the operation of separate, competing valuation systems in the control of choice behavior. Recent theoretical and experimental work suggest that this classic distinction between behaviorally and neurally dissociable systems for habitual and goal-directed (or more generally, automatic and controlled) choice may arise from two computational strategies for reinforcement learning (RL), called model-free and model-based RL, but the cognitive or computational processes by which one system may dominate over the other in the control of behavior is a matter of ongoing investigation. To elucidate this question, we leverage the theoretical framework of cognitive control, demonstrating that individual differences in utilization of goal-related contextual information—in the service of overcoming habitual, stimulus-driven responses—in established cognitive control paradigms predict model-based behavior in a separate, sequential choice task. The behavioral correspondence between cognitive control and model-based RL compellingly suggests that a common set of processes may underpin the two behaviors. In particular, computational mechanisms originally proposed to underlie controlled behavior may be applicable to understanding the interactions between model-based and model-free choice behavior. PMID:25170791

Cognitive task load in a naval ship control centre: from identification to prediction.

PubMed

Grootjen, M; Neerincx, M A; Veltman, J A

Deployment of information and communication technology will lead to further automation of control centre tasks and an increasing amount of information to be processed. A method for establishing adequate levels of cognitive task load for the operators in such complex environments has been developed. It is based on a model distinguishing three load factors: time occupied, task-set switching, and level of information processing. Application of the method resulted in eight scenarios for eight extremes of task load (i.e. low and high values for each load factor). These scenarios were performed by 13 teams in a high-fidelity control centre simulator of the Royal Netherlands Navy. The results show that the method provides good prediction of the task load that will actually appear in the simulator. The model allowed identification of under- and overload situations showing negative effects on operator performance corresponding to controlled experiments in a less realistic task environment. Tools proposed to keep the operator at an optimum task load are (adaptive) task allocation and interface support.

Application of Model-based Prognostics to a Pneumatic Valves Testbed

NASA Technical Reports Server (NTRS)

Daigle, Matthew; Kulkarni, Chetan S.; Gorospe, George

2014-01-01

Pneumatic-actuated valves play an important role in many applications, including cryogenic propellant loading for space operations. Model-based prognostics emphasizes the importance of a model that describes the nominal and faulty behavior of a system, and how faulty behavior progresses in time, causing the end of useful life of the system. We describe the construction of a testbed consisting of a pneumatic valve that allows the injection of faulty behavior and controllable fault progression. The valve opens discretely, and is controlled through a solenoid valve. Controllable leaks of pneumatic gas in the testbed are introduced through proportional valves, allowing the testing and validation of prognostics algorithms for pneumatic valves. A new valve prognostics approach is developed that estimates fault progression and predicts remaining life based only on valve timing measurements. Simulation experiments demonstrate and validate the approach.

Designing asymmetric multiferroics with strong magnetoelectric coupling

NASA Astrophysics Data System (ADS)

Lu, Xuezeng; Xiang, Hongjun; Rondinelli, James; Materials Theory; Design Group Team

2015-03-01

Multiferroics offer exciting opportunities for electric-field control of magnetism. Single-phase multiferroics suitable for such applications at room temperature need much more study. Here, we propose the concept of an alternative type of multiferroics, namely, the ``asymmetric multiferroic.'' In asymmetric multiferroics, two locally stable ferroelectric states are not symmetrically equivalent, leading to different magnetic properties between these two states. Furthermore, we predict from first principles that a Fe-Cr-Mo superlattice with the LiNbO3-type structure is such an asymmetric multiferroic. The strong ferrimagnetism, high ferroelectric polarization, and significant dependence of the magnetic transition temperature on polarization make this asymmetric multiferroic an ideal candidate for realizing electric-field control of magnetism at room temperature. Our study suggests that the asymmetric multiferroic may provide an alternative playground for voltage control of magnetism and find its applications in spintronics and quantum computing.

Designing asymmetric multiferroics with strong magnetoelectric coupling

NASA Astrophysics Data System (ADS)

Lu, X. Z.; Xiang, H. J.

2014-09-01

Multiferroics offer exciting opportunities for electric-field control of magnetism. Single-phase multiferroics suitable for such applications at room temperature need much more study. Here, we propose the concept of an alternative type of multiferroics, namely, the "asymmetric multiferroic." In asymmetric multiferroics, two locally stable ferroelectric states are not symmetrically equivalent, leading to different magnetic properties between these two states. Furthermore, we predict from first principles that a Fe-Cr-Mo superlattice with the LiNbO3-type structure is such an asymmetric multiferroic. The strong ferrimagnetism, high ferroelectric polarization, and significant dependence of the magnetic transition temperature on polarization make this asymmetric multiferroic an ideal candidate for realizing electric-field control of magnetism at room temperature. Our study suggests that the asymmetric multiferroic may provide an alternative playground for voltage control of magnetism and find its applications in spintronics and quantum computing.

Objective Versus Subjective Measures of Executive Functions: Predictors of Participation and Quality of Life in Parkinson Disease?

PubMed

Vlagsma, Thialda T; Koerts, Janneke; Tucha, Oliver; Dijkstra, Hilde T; Duits, Annelien A; van Laar, Teus; Spikman, Jacoba M

2017-11-01

To determine whether objective (neuropsychological tests) and subjective measures (questionnaires) of executive functions (EFs) are associated in patients with Parkinson disease (PD), and to determine to what extent level of participation and quality of life (QoL) of patients with PD can be predicted by these measures of EFs. Correlational research design (case-control and prediction design). Departments of neuropsychology of 3 medical centers. A sample (N=136) of patients with PD (n=42) and their relatives, and controls without PD (n=94). Not applicable. A test battery measuring EFs. In addition, patients, their relatives, and controls completed the Dysexecutive Questionnaire, Brock Adaptive Functioning Questionnaire, and Barkley Deficits in Executive Functioning Scale - time management questionnaires measuring complaints about EFs. Participation and QoL were measured with the Impact on Participation and Autonomy scale and the Parkinson's Disease Questionnaire-39, respectively. Patients with PD showed impairments in EFs on objective tests and reported significantly more complaints about EFs than did controls without PD. No associations were found between patients' performances on objective and subjective measures of EFs. However, both objective and subjective measures predicted patients' level of participation. In addition, subjective measures of EFs predicted QoL in patients with PD. These findings show that objective and subjective measures of EFs are not interchangeable and that both approaches predict level of participation and QoL in patients with PD. However, within this context, sex needs to be taken into account. Copyright © 2017 American Congress of Rehabilitation Medicine. Published by Elsevier Inc. All rights reserved.

Characterization of the space shuttle reaction control system engine

NASA Technical Reports Server (NTRS)

Wilson, M. S.; Stechman, R. C.; Edelman, R. B.; Fortune, O. F.; Economos, C.

1972-01-01

A computer program was developed and written in FORTRAN 5 which predicts the transient and steady state performance and heat transfer characteristics of a pulsing GO2/GH2 rocket engine. This program predicts the dynamic flow and ignition characteristics which, when combined in a quasi-steady state manner with the combustion and mixing analysis program, will provide the thrust and specific impulse of the engine as a function of time. The program also predicts the transient and steady state heat transfer characteristics of the engine using various cooling concepts. The computer program, test case, and documentation are presented. The program is applicable to any system capable of utilizing the FORTRAN 4 or FORTRAN 5 language.

Neural network-based nonlinear model predictive control vs. linear quadratic gaussian control

USGS Publications Warehouse

Cho, C.; Vance, R.; Mardi, N.; Qian, Z.; Prisbrey, K.

1997-01-01

One problem with the application of neural networks to the multivariable control of mineral and extractive processes is determining whether and how to use them. The objective of this investigation was to compare neural network control to more conventional strategies and to determine if there are any advantages in using neural network control in terms of set-point tracking, rise time, settling time, disturbance rejection and other criteria. The procedure involved developing neural network controllers using both historical plant data and simulation models. Various control patterns were tried, including both inverse and direct neural network plant models. These were compared to state space controllers that are, by nature, linear. For grinding and leaching circuits, a nonlinear neural network-based model predictive control strategy was superior to a state space-based linear quadratic gaussian controller. The investigation pointed out the importance of incorporating state space into neural networks by making them recurrent, i.e., feeding certain output state variables into input nodes in the neural network. It was concluded that neural network controllers can have better disturbance rejection, set-point tracking, rise time, settling time and lower set-point overshoot, and it was also concluded that neural network controllers can be more reliable and easy to implement in complex, multivariable plants.

Gross Motor Function Measure Evolution Ratio: Use as a Control for Natural Progression in Cerebral Palsy.

PubMed

Marois, Pierre; Marois, Mikael; Pouliot-Laforte, Annie; Vanasse, Michel; Lambert, Jean; Ballaz, Laurent

2016-05-01

To develop a new way to interpret Gross Motor Function Measure (GMFM-66) score improvement in studies conducted without control groups in children with cerebral palsy (CP). The curves, which describe the pattern of motor development according to the children's Gross Motor Function Classification System level, were used as historical control to define the GMFM-66 expected natural evolution in children with CP. These curves have been modeled and generalized to fit the curve to particular children characteristics. Research center. Not applicable. Not applicable. Not applicable. Assuming that the GMFM-66 score evolution followed the shape of the Rosenbaum curves, by taking into account the age and GMFM-66 score of children, the expected natural evolution of the GMFM-66 score was predicted for any group of children with CP who were <8 years old. Because the expected natural evolution could be predicted for a specific group of children with CP, the efficacy of a treatment could be determined by comparing the GMFM-66 score evolution measured before and after treatment with the expected natural evolution for the same period. A new index, the Gross Motor Function Measure Evolution Ratio, was defined as follows: Gross Motor Function Measure Evolution Ratio=measured GMFM-66 score change/expected natural evolution. For practical or ethical reasons, it is almost impossible to use control groups in studies evaluating effectiveness of many therapeutic modalities. The Gross Motor Function Measure Evolution Ratio gives the opportunity to take into account the expected natural evolution of the gross motor function of children with CP, which is essential to accurately interpret the therapy effect on the GMFM-66. Copyright © 2016 American Congress of Rehabilitation Medicine. Published by Elsevier Inc. All rights reserved.

Poisson Mixture Regression Models for Heart Disease Prediction.

PubMed

Mufudza, Chipo; Erol, Hamza

2016-01-01

Early heart disease control can be achieved by high disease prediction and diagnosis efficiency. This paper focuses on the use of model based clustering techniques to predict and diagnose heart disease via Poisson mixture regression models. Analysis and application of Poisson mixture regression models is here addressed under two different classes: standard and concomitant variable mixture regression models. Results show that a two-component concomitant variable Poisson mixture regression model predicts heart disease better than both the standard Poisson mixture regression model and the ordinary general linear Poisson regression model due to its low Bayesian Information Criteria value. Furthermore, a Zero Inflated Poisson Mixture Regression model turned out to be the best model for heart prediction over all models as it both clusters individuals into high or low risk category and predicts rate to heart disease componentwise given clusters available. It is deduced that heart disease prediction can be effectively done by identifying the major risks componentwise using Poisson mixture regression model.

Poisson Mixture Regression Models for Heart Disease Prediction

PubMed Central

Erol, Hamza

2016-01-01

Early heart disease control can be achieved by high disease prediction and diagnosis efficiency. This paper focuses on the use of model based clustering techniques to predict and diagnose heart disease via Poisson mixture regression models. Analysis and application of Poisson mixture regression models is here addressed under two different classes: standard and concomitant variable mixture regression models. Results show that a two-component concomitant variable Poisson mixture regression model predicts heart disease better than both the standard Poisson mixture regression model and the ordinary general linear Poisson regression model due to its low Bayesian Information Criteria value. Furthermore, a Zero Inflated Poisson Mixture Regression model turned out to be the best model for heart prediction over all models as it both clusters individuals into high or low risk category and predicts rate to heart disease componentwise given clusters available. It is deduced that heart disease prediction can be effectively done by identifying the major risks componentwise using Poisson mixture regression model. PMID:27999611

A Cloud Based Framework For Monitoring And Predicting Subsurface System Behaviour

NASA Astrophysics Data System (ADS)

Versteeg, R. J.; Rodzianko, A.; Johnson, D. V.; Soltanian, M. R.; Dwivedi, D.; Dafflon, B.; Tran, A. P.; Versteeg, O. J.

2015-12-01

Subsurface system behavior is driven and controlled by the interplay of physical, chemical, and biological processes which occur at multiple temporal and spatial scales. Capabilities to monitor, understand and predict this behavior in an effective and timely manner are needed for both scientific purposes and for effective subsurface system management. Such capabilities require three elements: Models, Data and an enabling cyberinfrastructure, which allow users to use these models and data in an effective manner. Under a DOE Office of Science funded STTR award Subsurface Insights and LBNL have designed and implemented a cloud based predictive assimilation framework (PAF) which automatically ingests, controls quality and stores heterogeneous physical and chemical subsurface data and processes these data using different inversion and modeling codes to provide information on the current state and evolution of subsurface systems. PAF is implemented as a modular cloud based software application with five components: (1) data acquisition, (2) data management, (3) data assimilation and processing, (4) visualization and result delivery and (5) orchestration. Serverside PAF uses ZF2 (a PHP web application framework) and Python and both open source (ODM2) and in house developed data models. Clientside PAF uses CSS and JS to allow for interactive data visualization and analysis. Client side modularity (which allows for a responsive interface) of the system is achieved by implementing each core capability of PAF (such as data visualization, user configuration and control, electrical geophysical monitoring and email/SMS alerts on data streams) as a SPA (Single Page Application). One of the recent enhancements is the full integration of a number of flow and mass transport and parameter estimation codes (e.g., MODFLOW, MT3DMS, PHT3D, TOUGH, PFLOTRAN) in this framework. This integration allows for autonomous and user controlled modeling of hydrological and geochemical processes. In our presentation we will discuss our software architecture and present the results of using these codes and the overall developed performance of our framework using hydrological, geochemical and geophysical data from the LBNL SFA2 Rifle field site.

Application of miniaturized near-infrared spectroscopy for quality control of extemporaneous orodispersible films.

PubMed

Foo, Wen Chin; Widjaja, Effendi; Khong, Yuet Mei; Gokhale, Rajeev; Chan, Sui Yung

2018-02-20

Extemporaneous oral preparations are routinely compounded in the pharmacy due to a lack of suitable formulations for special populations. Such small-scale pharmacy preparations also present an avenue for individualized pharmacotherapy. Orodispersible films (ODF) have increasingly been evaluated as a suitable dosage form for extemporaneous oral preparations. Nevertheless, as with all other extemporaneous preparations, safety and quality remain a concern. Although the United States Pharmacopeia (USP) recommends analytical testing of compounded preparations for quality assurance, pharmaceutical assays are typically not routinely performed for such non-sterile pharmacy preparations, due to the complexity and high cost of conventional assay methods such as high performance liquid chromatography (HPLC). Spectroscopic methods including Raman, infrared and near-infrared spectroscopy have been successfully applied as quality control tools in the industry. The state-of-art benchtop spectrometers used in those studies have the advantage of superior resolution and performance, but are not suitable for use in a small-scale pharmacy setting. In this study, we investigated the application of a miniaturized near infrared (NIR) spectrometer as a quality control tool for identification and quantification of drug content in extemporaneous ODFs. Miniaturized near infrared (NIR) spectroscopy is suitable for small-scale pharmacy applications in view of its small size, portability, simple user interface, rapid measurement and real-time prediction results. Nevertheless, the challenge with miniaturized NIR spectroscopy is its lower resolution compared to state-of-art benchtop equipment. We have successfully developed NIR spectroscopy calibration models for identification of ODFs containing five different drugs, and quantification of drug content in ODFs containing 2-10mg ondansetron (OND). The qualitative model for drug identification produced 100% prediction accuracy. The quantitative model to predict OND drug content in ODFs was divided into two calibrations for improved accuracy: Calibration I and II covered the 2-4mg and 4-10mg ranges respectively. Validation was performed for method accuracy, linearity and precision. In conclusion, this study demonstrates the feasibility of miniaturized NIR spectroscopy as a quality control tool for small-scale, pharmacy preparations. Due to its non-destructive nature, every dosage unit can be tested thus affording positive impact on patient safety. Copyright © 2017 Elsevier B.V. All rights reserved.

Control and Optimization of Electric Ship Propulsion Systems with Hybrid Energy Storage

NASA Astrophysics Data System (ADS)

Hou, Jun

Electric ships experience large propulsion-load fluctuations on their drive shaft due to encountered waves and the rotational motion of the propeller, affecting the reliability of the shipboard power network and causing wear and tear. This dissertation explores new solutions to address these fluctuations by integrating a hybrid energy storage system (HESS) and developing energy management strategies (EMS). Advanced electric propulsion drive concepts are developed to improve energy efficiency, performance and system reliability by integrating HESS, developing advanced control solutions and system integration strategies, and creating tools (including models and testbed) for design and optimization of hybrid electric drive systems. A ship dynamics model which captures the underlying physical behavior of the electric ship propulsion system is developed to support control development and system optimization. To evaluate the effectiveness of the proposed control approaches, a state-of-the-art testbed has been constructed which includes a system controller, Li-Ion battery and ultra-capacitor (UC) modules, a high-speed flywheel, electric motors with their power electronic drives, DC/DC converters, and rectifiers. The feasibility and effectiveness of HESS are investigated and analyzed. Two different HESS configurations, namely battery/UC (B/UC) and battery/flywheel (B/FW), are studied and analyzed to provide insights into the advantages and limitations of each configuration. Battery usage, loss analysis, and sensitivity to battery aging are also analyzed for each configuration. In order to enable real-time application and achieve desired performance, a model predictive control (MPC) approach is developed, where a state of charge (SOC) reference of flywheel for B/FW or UC for B/UC is used to address the limitations imposed by short predictive horizons, because the benefits of flywheel and UC working around high-efficiency range are ignored by short predictive horizons. Given the multi-frequency characteristics of load fluctuations, a filter-based control strategy is developed to illustrate the importance of the coordination within the HESS. Without proper control strategies, the HESS solution could be worse than a single energy storage system solution. The proposed HESS, when introduced into an existing shipboard electrical propulsion system, will interact with the power generation systems. A model-based analysis is performed to evaluate the interactions of the multiple power sources when a hybrid energy storage system is introduced. The study has revealed undesirable interactions when the controls are not coordinated properly, and leads to the conclusion that a proper EMS is needed. Knowledge of the propulsion-load torque is essential for the proposed system-level EMS, but this load torque is immeasurable in most marine applications. To address this issue, a model-based approach is developed so that load torque estimation and prediction can be incorporated into the MPC. In order to evaluate the effectiveness of the proposed approach, an input observer with linear prediction is developed as an alternative approach to obtain the load estimation and prediction. Comparative studies are performed to illustrate the importance of load torque estimation and prediction, and demonstrate the effectiveness of the proposed approach in terms of improved efficiency, enhanced reliability, and reduced wear and tear. Finally, the real-time MPC algorithm has been implemented on a physical testbed. Three different efforts have been made to enable real-time implementation: a specially tailored problem formulation, an efficient optimization algorithm and a multi-core hardware implementation. Compared to the filter-based strategy, the proposed real-time MPC achieves superior performance, in terms of the enhanced system reliability, improved HESS efficiency, and extended battery life.

National Stormwater Calculator: Low Impact Development ...

EPA Pesticide Factsheets

The National Stormwater Calculator (NSC) makes it easy to estimate runoff reduction when planning a new development or redevelopment site with low impact development (LID) stormwater controls. The Calculator is currently deployed as a Windows desktop application. The Calculator is organized as a wizard style application that walks the user through the steps necessary to perform runoff calculations on a single urban sub-catchment of 10 acres or less in size. Using an interactive map, the user can select the sub-catchment location and the Calculator automatically acquires hydrologic data for the site.A new LID cost estimation module has been developed for the Calculator. This project involved programming cost curves into the existing Calculator desktop application. The integration of cost components of LID controls into the Calculator increases functionality and will promote greater use of the Calculator as a stormwater management and evaluation tool. The addition of the cost estimation module allows planners and managers to evaluate LID controls based on comparison of project cost estimates and predicted LID control performance. Cost estimation is accomplished based on user-identified size (or auto-sizing based on achieving volume control or treatment of a defined design storm), configuration of the LID control infrastructure, and other key project and site-specific variables, including whether the project is being applied as part of new development or redevelopm

Fast Demand Forecast of Electric Vehicle Charging Stations for Cell Phone Application

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

Majidpour, Mostafa; Qiu, Charlie; Chung, Ching-Yen

This paper describes the core cellphone application algorithm which has been implemented for the prediction of energy consumption at Electric Vehicle (EV) Charging Stations at UCLA. For this interactive user application, the total time of accessing database, processing the data and making the prediction, needs to be within a few seconds. We analyze four relatively fast Machine Learning based time series prediction algorithms for our prediction engine: Historical Average, kNearest Neighbor, Weighted k-Nearest Neighbor, and Lazy Learning. The Nearest Neighbor algorithm (k Nearest Neighbor with k=1) shows better performance and is selected to be the prediction algorithm implemented for themore » cellphone application. Two applications have been designed on top of the prediction algorithm: one predicts the expected available energy at the station and the other one predicts the expected charging finishing time. The total time, including accessing the database, data processing, and prediction is about one second for both applications.« less

Geary autocorrelation and DCCA coefficient: Application to predict apoptosis protein subcellular localization via PSSM

NASA Astrophysics Data System (ADS)

Liang, Yunyun; Liu, Sanyang; Zhang, Shengli

2017-02-01

Apoptosis is a fundamental process controlling normal tissue homeostasis by regulating a balance between cell proliferation and death. Predicting subcellular location of apoptosis proteins is very helpful for understanding its mechanism of programmed cell death. Prediction of apoptosis protein subcellular location is still a challenging and complicated task, and existing methods mainly based on protein primary sequences. In this paper, we propose a new position-specific scoring matrix (PSSM)-based model by using Geary autocorrelation function and detrended cross-correlation coefficient (DCCA coefficient). Then a 270-dimensional (270D) feature vector is constructed on three widely used datasets: ZD98, ZW225 and CL317, and support vector machine is adopted as classifier. The overall prediction accuracies are significantly improved by rigorous jackknife test. The results show that our model offers a reliable and effective PSSM-based tool for prediction of apoptosis protein subcellular localization.

Prediction-Oriented Marker Selection (PROMISE): With Application to High-Dimensional Regression.

PubMed

Kim, Soyeon; Baladandayuthapani, Veerabhadran; Lee, J Jack

2017-06-01

In personalized medicine, biomarkers are used to select therapies with the highest likelihood of success based on an individual patient's biomarker/genomic profile. Two goals are to choose important biomarkers that accurately predict treatment outcomes and to cull unimportant biomarkers to reduce the cost of biological and clinical verifications. These goals are challenging due to the high dimensionality of genomic data. Variable selection methods based on penalized regression (e.g., the lasso and elastic net) have yielded promising results. However, selecting the right amount of penalization is critical to simultaneously achieving these two goals. Standard approaches based on cross-validation (CV) typically provide high prediction accuracy with high true positive rates but at the cost of too many false positives. Alternatively, stability selection (SS) controls the number of false positives, but at the cost of yielding too few true positives. To circumvent these issues, we propose prediction-oriented marker selection (PROMISE), which combines SS with CV to conflate the advantages of both methods. Our application of PROMISE with the lasso and elastic net in data analysis shows that, compared to CV, PROMISE produces sparse solutions, few false positives, and small type I + type II error, and maintains good prediction accuracy, with a marginal decrease in the true positive rates. Compared to SS, PROMISE offers better prediction accuracy and true positive rates. In summary, PROMISE can be applied in many fields to select regularization parameters when the goals are to minimize false positives and maximize prediction accuracy.

[Application of ARIMA model to predict number of malaria cases in China].

PubMed

Hui-Yu, H; Hua-Qin, S; Shun-Xian, Z; Lin, A I; Yan, L U; Yu-Chun, C; Shi-Zhu, L I; Xue-Jiao, T; Chun-Li, Y; Wei, H U; Jia-Xu, C

2017-08-15

Objective To study the application of autoregressive integrated moving average (ARIMA) model to predict the monthly reported malaria cases in China, so as to provide a reference for prevention and control of malaria. Methods SPSS 24.0 software was used to construct the ARIMA models based on the monthly reported malaria cases of the time series of 20062015 and 2011-2015, respectively. The data of malaria cases from January to December, 2016 were used as validation data to compare the accuracy of the two ARIMA models. Results The models of the monthly reported cases of malaria in China were ARIMA (2, 1, 1) (1, 1, 0) 12 and ARIMA (1, 0, 0) (1, 1, 0) 12 respectively. The comparison between the predictions of the two models and actual situation of malaria cases showed that the ARIMA model based on the data of 2011-2015 had a higher accuracy of forecasting than the model based on the data of 2006-2015 had. Conclusion The establishment and prediction of ARIMA model is a dynamic process, which needs to be adjusted unceasingly according to the accumulated data, and in addition, the major changes of epidemic characteristics of infectious diseases must be considered.

Annual research briefs, 1993. [Center for Turbulence Research

NASA Technical Reports Server (NTRS)

1993-01-01

The 1993 annual progress reports of the Research Fellow and students of the Center for Turbulence Research are included. The first group of reports are directed towards the theory and application of active control in turbulent flows including the development of a systematic mathematical procedure based on the Navier Stokes equations for flow control. The second group of reports are concerned with the prediction of turbulent flows. The remaining articles are devoted to turbulent reacting flows, turbulence physics, experiments, and simulations.

Reasoning about energy in qualitative simulation

NASA Technical Reports Server (NTRS)

Fouche, Pierre; Kuipers, Benjamin J.

1992-01-01

While possible behaviors of a mechanism that are consistent with an incomplete state of knowledge can be predicted through qualitative modeling and simulation, spurious behaviors corresponding to no solution of any ordinary differential equation consistent with the model may be generated. The present method for energy-related reasoning eliminates an important source of spurious behaviors, as demonstrated by its application to a nonlinear, proportional-integral controlled. It is shown that such qualitative properties of such a system as stability and zero-offset control are captured by the simulation.

Evaluation of liquid aerosol transport through porous media

NASA Astrophysics Data System (ADS)

Hall, R.; Murdoch, L.; Falta, R.; Looney, B.; Riha, B.

2016-07-01

Application of remediation methods in contaminated vadose zones has been hindered by an inability to effectively distribute liquid- or solid-phase amendments. Injection as aerosols in a carrier gas could be a viable method for achieving useful distributions of amendments in unsaturated materials. The objectives of this work were to characterize radial transport of aerosols in unsaturated porous media, and to develop capabilities for predicting results of aerosol injection scenarios at the field-scale. Transport processes were investigated by conducting lab-scale injection experiments with radial flow geometry, and predictive capabilities were obtained by developing and validating a numerical model for simulating coupled aerosol transport, deposition, and multi-phase flow in porous media. Soybean oil was transported more than 2 m through sand by injecting it as micron-scale aerosol droplets. Oil saturation in the sand increased with time to a maximum of 0.25, and decreased with radial distance in the experiments. The numerical analysis predicted the distribution of oil saturation with only minor calibration. The results indicated that evolution of oil saturation was controlled by aerosol deposition and subsequent flow of the liquid oil, and simulation requires including these two coupled processes. The calibrated model was used to evaluate field applications. The results suggest that amendments can be delivered to the vadose zone as aerosols, and that gas injection rate and aerosol particle size will be important controls on the process.

Large space structure model reduction and control system design based upon actuator and sensor influence functions

NASA Technical Reports Server (NTRS)

Yam, Y.; Lang, J. H.; Johnson, T. L.; Shih, S.; Staelin, D. H.

1983-01-01

A model reduction procedure based on aggregation with respect to sensor and actuator influences rather than modes is presented for large systems of coupled second-order differential equations. Perturbation expressions which can predict the effects of spillover on both the aggregated and residual states are derived. These expressions lead to the development of control system design constraints which are sufficient to guarantee, to within the validity of the perturbations, that the residual states are not destabilized by control systems designed from the reduced model. A numerical example is provided to illustrate the application of the aggregation and control system design method.

Predicting the optoelectronic properties of nanowire films based on control of length polydispersity

NASA Astrophysics Data System (ADS)

Large, Matthew J.; Burn, Jake; King, Alice A.; Ogilvie, Sean P.; Jurewicz, Izabela; Dalton, Alan B.

2016-05-01

We demonstrate that the optoelectronic properties of percolating thin films of silver nanowires (AgNWs) are predominantly dependent upon the length distribution of the constituent AgNWs. A generalized expression is derived to describe the dependence of both sheet resistance and optical transmission on this distribution. We experimentally validate the relationship using ultrasonication to controllably vary the length distribution. These results have major implications where nanowire-based films are a desirable material for transparent conductor applications; in particular when application-specific performance criteria must be met. It is of particular interest to have a simple method to generalize the properties of bulk films from an understanding of the base material, as this will speed up the optimisation process. It is anticipated that these results may aid in the adoption of nanowire films in industry, for applications such as touch sensors or photovoltaic electrode structures.

Application of laminar flow control to high-bypass-ratio turbofan engine nacelles

NASA Technical Reports Server (NTRS)

Wie, Y. S.; Collier, F. S., Jr.; Wagner, R. D.

1991-01-01

Recently, the concept of the application of hybrid laminar flow to modern commercial transport aircraft was successfully flight tested on a Boeing 757 aircraft. In this limited demonstration, in which only part of the upper surface of the swept wing was designed for the attainment of laminar flow, significant local drag reduction was measured. This paper addresses the potential application of this technology to laminarize the external surface of large, modern turbofan engine nacelles which may comprise as much as 5-10 percent of the total wetted area of future commercial transports. A hybrid-laminar-flow-control (HLFC) pressure distribution is specified and the corresponding nacelle geometry is computed utilizing a predictor/corrector design method. Linear stability calculations are conducted to provide predictions of the extent of the laminar boundary layer. Performance studies are presented to determine potential benefits in terms of reduced fuel consumption.

Growth and modelling of spherical crystalline morphologies of molecular materials

NASA Astrophysics Data System (ADS)

Shalev, O.; Biswas, S.; Yang, Y.; Eddir, T.; Lu, W.; Clarke, R.; Shtein, M.

2014-10-01

Crystalline, yet smooth, sphere-like morphologies of small molecular compounds are desirable in a wide range of applications but are very challenging to obtain using common growth techniques, where either amorphous films or faceted crystallites are the norm. Here we show solvent-free, guard flow-assisted organic vapour jet printing of non-faceted, crystalline microspheroids of archetypal small molecular materials used in organic electronic applications. We demonstrate how process parameters control the size distribution of the spheroids and propose an analytical model and a phase diagram predicting the surface morphology evolution of different molecules based on processing conditions, coupled with the thermophysical and mechanical properties of the molecules. This experimental approach opens a path for exciting applications of small molecular organic compounds in optical coatings, textured surfaces with controlled wettability, pharmaceutical and food substance printing and others, where thick organic films and particles with high surface area are needed.

Study on Noise Prediction Model and Control Schemes for Substation

PubMed Central

Gao, Yang; Liu, Songtao

2014-01-01

With the government's emphasis on environmental issues of power transmission and transformation project, noise pollution has become a prominent problem now. The noise from the working transformer, reactor, and other electrical equipment in the substation will bring negative effect to the ambient environment. This paper focuses on using acoustic software for the simulation and calculation method to control substation noise. According to the characteristics of the substation noise and the techniques of noise reduction, a substation's acoustic field model was established with the SoundPLAN software to predict the scope of substation noise. On this basis, 4 reasonable noise control schemes were advanced to provide some helpful references for noise control during the new substation's design and construction process. And the feasibility and application effect of these control schemes can be verified by using the method of simulation modeling. The simulation results show that the substation always has the problem of excessive noise at boundary under the conventional measures. The excess noise can be efficiently reduced by taking the corresponding noise reduction methods. PMID:24672356

Trial application of reliability technology to emergency diesel generators at the Trojan Nuclear Power Plant

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

Wong, S.M.; Boccio, J.L.; Karimian, S.

1986-01-01

In this paper, a trial application of reliability technology to the emergency diesel generator system at the Trojan Nuclear Power Plant is presented. An approach for formulating a reliability program plan for this system is being developed. The trial application has shown that a reliability program process, using risk- and reliability-based techniques, can be interwoven into current plant operational activities to help in controlling, analyzing, and predicting faults that can challenge safety systems. With the cooperation of the utility, Portland General Electric Co., this reliability program can eventually be implemented at Trojan to track its effectiveness.

Common spaceborne multicomputer operating system and development environment

NASA Technical Reports Server (NTRS)

Craymer, L. G.; Lewis, B. F.; Hayes, P. J.; Jones, R. L.

1994-01-01

A preliminary technical specification for a multicomputer operating system is developed. The operating system is targeted for spaceborne flight missions and provides a broad range of real-time functionality, dynamic remote code-patching capability, and system fault tolerance and long-term survivability features. Dataflow concepts are used for representing application algorithms. Functional features are included to ensure real-time predictability for a class of algorithms which require data-driven execution on an iterative steady state basis. The development environment supports the development of algorithm code, design of control parameters, performance analysis, simulation of real-time dataflow applications, and compiling and downloading of the resulting application.

Assessment of flat rolling theories for the use in a model-based controller for high-precision rolling applications

NASA Astrophysics Data System (ADS)

Stockert, Sven; Wehr, Matthias; Lohmar, Johannes; Abel, Dirk; Hirt, Gerhard

2017-10-01

In the electrical and medical industries the trend towards further miniaturization of devices is accompanied by the demand for smaller manufacturing tolerances. Such industries use a plentitude of small and narrow cold rolled metal strips with high thickness accuracy. Conventional rolling mills can hardly achieve further improvement of these tolerances. However, a model-based controller in combination with an additional piezoelectric actuator for high dynamic roll adjustment is expected to enable the production of the required metal strips with a thickness tolerance of +/-1 µm. The model-based controller has to be based on a rolling theory which can describe the rolling process very accurately. Additionally, the required computing time has to be low in order to predict the rolling process in real-time. In this work, four rolling theories from literature with different levels of complexity are tested for their suitability for the predictive controller. Rolling theories of von Kármán, Siebel, Bland & Ford and Alexander are implemented in Matlab and afterwards transferred to the real-time computer used for the controller. The prediction accuracy of these theories is validated using rolling trials with different thickness reduction and a comparison to the calculated results. Furthermore, the required computing time on the real-time computer is measured. Adequate results according the prediction accuracy can be achieved with the rolling theories developed by Bland & Ford and Alexander. A comparison of the computing time of those two theories reveals that Alexander's theory exceeds the sample rate of 1 kHz of the real-time computer.

Application of a Physics-Based Stabilization Criterion to Flight System Thermal Testing

NASA Technical Reports Server (NTRS)

Baker, Charles; Garrison, Matthew; Cottingham, Christine; Peabody, Sharon

2010-01-01

The theory shown here can provide thermal stability criteria based on physics and a goal steady state error rather than on an arbitrary "X% Q/mC(sub P)" method. The ability to accurately predict steady-state temperatures well before thermal balance is reached could be very useful during testing. This holds true for systems where components are changing temperature at different rates, although it works better for the components closest to the sink. However, the application to these test cases shows some significant limitations: This theory quickly falls apart if the thermal control system in question is tightly coupled to a large mass not accounted for in the calculations, so it is more useful in subsystem-level testing than full orbiter tests. Tight couplings to a fluctuating sink causes noise in the steady state temperature predictions.

A tide prediction and tide height control system for laboratory mesocosms

PubMed Central

Long, Jeremy D.

2015-01-01

Experimental mesocosm studies of rocky shore and estuarine intertidal systems may benefit from the application of natural tide cycles to better replicate variation in immersion time, water depth, and attendant fluctuations in abiotic and edaphic conditions. Here we describe a stand-alone microcontroller tide prediction open-source software program, coupled with a mechanical tidal elevation control system, which allows continuous adjustment of aquarium water depths in synchrony with local tide cycles. We used this system to monitor the growth of Spartina foliosa marsh cordgrass and scale insect herbivores at three simulated shore elevations in laboratory mesocosms. Plant growth decreased with increasing shore elevation, while scale insect population growth on the plants was not strongly affected by immersion time. This system shows promise for a range of laboratory mesocosm studies where natural tide cycling could impact organism performance or behavior, while the tide prediction system could additionally be utilized in field experiments where treatments need to be applied at certain stages of the tide cycle. PMID:26623195

Premorbid social adjustment and association with attenuated psychotic symptoms in clinical high-risk and help-seeking youth.

PubMed

Tarbox-Berry, S I; Perkins, D O; Woods, S W; Addington, J

2018-04-01

Attenuated positive symptom syndrome (APSS), characterized by 'putatively prodromal' attenuated psychotic-like pathology, indicates increased risk for psychosis. Poor premorbid social adjustment predicts severity of APSS symptoms and predicts subsequent psychosis in APSS-diagnosed individuals, suggesting application for improving detection of 'true' prodromal youth who will transition to psychosis. However, these predictive associations have not been tested in controls and therefore may be independent of the APSS diagnosis, negating utility for improving prediction in APSS-diagnosed individuals. Association between premorbid social maladjustment and severity of positive, negative, disorganized, and general APSS symptoms was tested in 156 individuals diagnosed with APSS and 76 help-seeking (non-APSS) controls enrolled in the Enhancing the Prospective Prediction of Psychosis (PREDICT) study using prediction analysis. Premorbid social maladjustment was associated with social anhedonia, reduced expression of emotion, restricted ideational richness, and deficits in occupational functioning, independent of the APSS diagnosis. Associations between social maladjustment and suspiciousness, unusual thought content, avolition, dysphoric mood, and impaired tolerance to normal stress were uniquely present in participants meeting APSS criteria. Social maladjustment was associated with odd behavior/appearance and diminished experience of emotions and self only in participants who did not meet APSS criteria. Predictive associations between poor premorbid social adjustment and attenuated psychotic-like pathology were identified, a subset of which were indicative of high risk for psychosis. This study offers a method for improving risk identification while ruling out low-risk individuals.

Predicting Quarantine Failure Rates

PubMed Central

2004-01-01

Preemptive quarantine through contact-tracing effectively controls emerging infectious diseases. Occasionally this quarantine fails, however, and infected persons are released. The probability of quarantine failure is typically estimated from disease-specific data. Here a simple, exact estimate of the failure rate is derived that does not depend on disease-specific parameters. This estimate is universally applicable to all infectious diseases. PMID:15109418

A quantitative measure for degree of automation and its relation to system performance and mental load.

PubMed

Wei, Z G; Macwan, A P; Wieringa, P A

1998-06-01

In this paper we quantitatively model degree of automation (DofA) in supervisory control as a function of the number and nature of tasks to be performed by the operator and automation. This model uses a task weighting scheme in which weighting factors are obtained from task demand load, task mental load, and task effect on system performance. The computation of DofA is demonstrated using an experimental system. Based on controlled experiments using operators, analyses of the task effect on system performance, the prediction and assessment of task demand load, and the prediction of mental load were performed. Each experiment had a different DofA. The effect of a change in DofA on system performance and mental load was investigated. It was found that system performance became less sensitive to changes in DofA at higher levels of DofA. The experimental data showed that when the operator controlled a partly automated system, perceived mental load could be predicted from the task mental load for each task component, as calculated by analyzing a situation in which all tasks were manually controlled. Actual or potential applications of this research include a methodology to balance and optimize the automation of complex industrial systems.

Cueing an unresolved personal goal causes persistent ruminative self-focus: an experimental evaluation of control theories of rumination.

PubMed

Roberts, Henrietta; Watkins, Edward R; Wills, Andy J

2013-12-01

Control theory predicts that the detection of goal discrepancies initiates ruminative self-focus (Martin & Tesser, 1996). Despite the breadth of applications and interest in control theory, there is a lack of experimental evidence evaluating this prediction. The present study provided the first experimental test of this prediction. We examined uninstructed state rumination in response to the cueing of resolved and unresolved goals in a non-clinical population using a novel measure of online rumination. Consistent with control theory, cueing an unresolved goal resulted in significantly greater recurrent intrusive ruminative thoughts than cueing a resolved goal. Individual differences in trait rumination moderated the impact of the goal cueing task on the extent of state rumination: individuals who had a stronger tendency to habitually ruminate were more susceptible to the effects of cueing goal discrepancies. The findings await replication in a clinically depressed sample where there is greater variability and higher levels of trait rumination. These results indicate that control theories of goal pursuit provide a valuable framework for understanding the circumstances that trigger state rumination. Additionally, our measure of uninstructed online state rumination was found to be a valid and sensitive index of the extent and temporal course of state rumination, indicating its value for further investigating the proximal causes of state rumination. Copyright © 2013 Elsevier Ltd. All rights reserved.

[Google Flu Trends--the initial application of big data in public health].

PubMed

Zou, Xiaohui; Zhu, Wenfei; Yang, Lei; Shu, Yuelong

2015-06-01

Google Flu Trends (GFT) was the first application of big data in the public health field. GFT was open online in 2009 and attracted worldwide attention immediately. However, GFT failed catching the 2009 pandemic H1N1 and kept overestimating the intensity of influenza-like illness in the 2012-2014 season in the United States. GFT model has been updated for three times since 2009, making its prediction bias controlled. Here, we summarized the mechanism GFT worked, the strategy GFT used to update, and its influence on public health.

Advances in traction drive technology

NASA Technical Reports Server (NTRS)

Loewenthal, S. H.; Anderson, N. E.; Rohn, D. A.

1983-01-01

Traction drives are traced from early uses as main transmissions in automobiles at the turn of the century to modern, high-powered traction drives capable of transmitting hundreds of horsepower. Recent advances in technology are described which enable today's traction drive to be a serious candidate for off-highway vehicles and helicopter applications. Improvements in materials, traction fluids, design techniques, power loss and life prediction methods will be highlighted. Performance characteristics of the Nasvytis fixed-ratio drive are given. Promising future drive applications, such as helicopter main transmissions and servo-control positioning mechanisms are also addressed.

Navier-Stokes, dynamics and aeroelastic computations for vortical flows, buffet and flutter applications

NASA Technical Reports Server (NTRS)

Kandil, Osama A.

1993-01-01

Research on Navier-Stokes, dynamics, and aeroelastic computations for vortical flows, buffet, and flutter applications was performed. Progress during the period from 1 Oct. 1992 to 30 Sep. 1993 is included. Papers on the following topics are included: vertical tail buffet in vortex breakdown flows; simulation of tail buffet using delta wing-vertical tail configuration; shock-vortex interaction over a 65-degree delta wing in transonic flow; supersonic vortex breakdown over a delta wing in transonic flow; and prediction and control of slender wing rock.

[Prediction of schistosomiasis infection rates of population based on ARIMA-NARNN model].

PubMed

Ke-Wei, Wang; Yu, Wu; Jin-Ping, Li; Yu-Yu, Jiang

2016-07-12

To explore the effect of the autoregressive integrated moving average model-nonlinear auto-regressive neural network (ARIMA-NARNN) model on predicting schistosomiasis infection rates of population. The ARIMA model, NARNN model and ARIMA-NARNN model were established based on monthly schistosomiasis infection rates from January 2005 to February 2015 in Jiangsu Province, China. The fitting and prediction performances of the three models were compared. Compared to the ARIMA model and NARNN model, the mean square error (MSE), mean absolute error (MAE) and mean absolute percentage error (MAPE) of the ARIMA-NARNN model were the least with the values of 0.011 1, 0.090 0 and 0.282 4, respectively. The ARIMA-NARNN model could effectively fit and predict schistosomiasis infection rates of population, which might have a great application value for the prevention and control of schistosomiasis.

A statistical rain attenuation prediction model with application to the advanced communication technology satellite project. 3: A stochastic rain fade control algorithm for satellite link power via non linear Markow filtering theory

NASA Technical Reports Server (NTRS)

Manning, Robert M.

1991-01-01

The dynamic and composite nature of propagation impairments that are incurred on Earth-space communications links at frequencies in and above 30/20 GHz Ka band, i.e., rain attenuation, cloud and/or clear air scintillation, etc., combined with the need to counter such degradations after the small link margins have been exceeded, necessitate the use of dynamic statistical identification and prediction processing of the fading signal in order to optimally estimate and predict the levels of each of the deleterious attenuation components. Such requirements are being met in NASA's Advanced Communications Technology Satellite (ACTS) Project by the implementation of optimal processing schemes derived through the use of the Rain Attenuation Prediction Model and nonlinear Markov filtering theory.

A QSPR model for prediction of diffusion coefficient of non-electrolyte organic compounds in air at ambient condition.

PubMed

Mirkhani, Seyyed Alireza; Gharagheizi, Farhad; Sattari, Mehdi

2012-03-01

Evaluation of diffusion coefficients of pure compounds in air is of great interest for many diverse industrial and air quality control applications. In this communication, a QSPR method is applied to predict the molecular diffusivity of chemical compounds in air at 298.15K and atmospheric pressure. Four thousand five hundred and seventy nine organic compounds from broad spectrum of chemical families have been investigated to propose a comprehensive and predictive model. The final model is derived by Genetic Function Approximation (GFA) and contains five descriptors. Using this dedicated model, we obtain satisfactory results quantified by the following statistical results: Squared Correlation Coefficient=0.9723, Standard Deviation Error=0.003 and Average Absolute Relative Deviation=0.3% for the predicted properties from existing experimental values. Copyright © 2011 Elsevier Ltd. All rights reserved.

Management of Vortices Trailing Flapped Wings via Separation Control

NASA Technical Reports Server (NTRS)

Greenblatt, David

2005-01-01

A pilot study was conducted on a flapped semi-span model to investigate the concept and viability of near-wake vortex management via separation control. Passive control was achieved by means of a simple fairing and active control was achieved via zero mass-flux blowing slots. Vortex sheet strength, estimated by integrating surface pressure ports, was used to predict vortex characteristics by means of inviscid rollup relations. Furthermore, vortices trailing the flaps were mapped using a seven-hole probe. Separation control was found to have a marked effect on vortex location, strength, tangential velocity, axial velocity and size over a wide range of angles of attack and control conditions. In general, the vortex trends were well predicted by the inviscid rollup relations. Manipulation of the separated flow near the flap edges exerted significant control over both outboard and inboard edge vortices while producing negligible lift excursions. Dynamic separation and attachment control was found to be an effective means for dynamically perturbing the vortex from arbitrarily long wavelengths down to wavelengths less than a typical wingspan. In summary, separation control has the potential for application to time-independent or time-dependent wake alleviation schemes, where the latter can be deployed to minimize adverse effects on ride-quality and dynamic structural loading.

Study and classification of the abdominal adiposity throughout the application of the two-dimensional predictive equation Garaulet et al., in the clinical practice.

PubMed

Piernas Sánchez, C M; Morales Falo, E M; Zamora Navarro, S; Garaulet Aza, M

2010-01-01

The excess of visceral abdominal adipose tissue is one of the major concerns in obesity and its clinical treatment. To apply the two-dimensional predictive equation proposed by Garaulet et al. to determine the abdominal fat distribution and to compare the results with the body composition obtained by multi-frequency bioelectrical impedance analysis (M-BIA). We studied 230 women, who underwent anthropometry and M-BIA. The predictive equation was applied. Multivariate lineal and partial correlation analyses were performed with control for BMI and % body fat, using SPSS 15.0 with statistical significance P < 0.05. Overall, women were considered as having subcutaneous distribution of abdominal fat. Truncal fat, regional fat and muscular mass were negatively associated with VA/SA(predicted), while the visceral index obtained by M-BIA was positively correlated with VA/SA(predicted). The predictive equation may be useful in the clinical practice to obtain an accurate, costless and safe classification of abdominal obesity.

On Predictive Understanding of Extreme Events: Pattern Recognition Approach; Prediction Algorithms; Applications to Disaster Preparedness

NASA Astrophysics Data System (ADS)

Keilis-Borok, V. I.; Soloviev, A.; Gabrielov, A.

2011-12-01

We describe a uniform approach to predicting different extreme events, also known as critical phenomena, disasters, or crises. The following types of such events are considered: strong earthquakes; economic recessions (their onset and termination); surges of unemployment; surges of crime; and electoral changes of the governing party. A uniform approach is possible due to the common feature of these events: each of them is generated by a certain hierarchical dissipative complex system. After a coarse-graining, such systems exhibit regular behavior patterns; we look among them for "premonitory patterns" that signal the approach of an extreme event. We introduce methodology, based on the optimal control theory, assisting disaster management in choosing optimal set of disaster preparedness measures undertaken in response to a prediction. Predictions with their currently realistic (limited) accuracy do allow preventing a considerable part of the damage by a hierarchy of preparedness measures. Accuracy of prediction should be known, but not necessarily high.

Factors related to reduction in the consumption of fast food: application of the theory-based approaches

PubMed Central

Zeinab, Jalambadani; Gholamreza, Garmaroudi; Mehdi, Yaseri; Mahmood, Tavousi; Korush, Jafarian

2017-01-01

Background The Trans-Theoretical model (TTM) and Theory of Planned Behaviour (TPB) may be promising models for understanding and predicting reduction in the consumption of fast food. The aim of this study was to examine the applicability of the Trans-Theoretical model (TTM) and the additional predictive role of the subjective norms and perceived behavioural control in predicting reduction consumption of fast food in obese Iranian adolescent girls. Materials and Methods. A cross sectional study design was conducted among twelve randomly selected schools in Sabzevar, Iran from 2015 to 2017. Four hundred eighty five randomly selected students consented to participate in the study. Hierarchical regression models used to predict the role of important variables that can influence the reduction in the consumption of fast food among students. using SPSS version 22. Results Variables Perceived behavioural control (r=0.58, P<0.001), Subjective norms (r=0.51, P<0.001), self-efficacy (r=0.49, P<0.001), decisional balance (pros) (r=0.29, P<0.001), decisional balance (cons) (r=0.25, P<0.001), stage of change (r=0.38, P<0.001), were significantly and positively correlated while experiential processes of change (r=0.08, P=0.135) and behavioural processes of change (r=0.09, P=0.145), were not significant. Conclusions The study demonstrated that the TTM (except the experiential and behavioural processes of change) focusing on the perceived behavioural control and subjective norms are useful models for reduction in the consumption of fast food. Significance for public health The Ministries of Education and Public Health should cooperate in supporting the below-mentioned formal and non-formal school, family and community nutritional education and activities. Lastly, the Ministry of Public Health should conduct programmes with restaurant owners on healthy Iranian food and its hygienic presentation and promotion, to enhance their ability to compete with fast-food restaurants. PMID:29071252

Morphological diversity of nitroguanidine crystals with enhanced mechanical performance and thermodynamic stability

NASA Astrophysics Data System (ADS)

Luo, Zhilong; Cui, Yingdan; Dong, Weibing; Xu, Qipeng; Zou, Gaoxing; Kang, Chao; Hou, Baohong; Chen, Song; Gong, Junbo

2017-12-01

Nitroguanidine (NQ) is a commonly used explosive, which has been widely used for both civilian and military explosive applications. However, the weak flowability and mechanical performance limit its application. In this work, mechanical performance and thermodynamic stability of NQ crystals were improved by controlling crystal morphologies in the crystallization process. Typical NQ crystals with multiple morphologies and single crystal form were obtained in the presence of additives during the cooling crystallization. The morphology controlled NQ crystals showed higher density, unimodal crystal size distribution and enhanced flowability. The additives showed the inhibitory effect on the nucleation of NQ crystals by in-situ FBRM and PVM determination, and the mechanism was analyzed by means of morphological prediction and molecular simulation. Furthermore, the morphology controlled NQ crystals suggested higher thermodynamic stability according to the calculation of entropy, enthalpy, Gibbs free energy and apparent activation energy on the basis of DSC results.

IECON '87: Industrial applications of control and simulation; Proceedings of the 1987 International Conference on Industrial Electronics, Control, and Instrumentation, Cambridge, MA, Nov. 3, 4, 1987

NASA Technical Reports Server (NTRS)

Hartley, Tom T. (Editor)

1987-01-01

Recent advances in control-system design and simulation are discussed in reviews and reports. Among the topics considered are fast algorithms for generating near-optimal binary decision programs, trajectory control of robot manipulators with compensation of load effects via a six-axis force sensor, matrix integrators for real-time simulation, a high-level control language for an autonomous land vehicle, and a practical engineering design method for stable model-reference adaptive systems. Also addressed are the identification and control of flexible-limb robots with unknown loads, adaptive control and robust adaptive control for manipulators with feedforward compensation, adaptive pole-placement controllers with predictive action, variable-structure strategies for motion control, and digital signal-processor-based variable-structure controls.

Application of Machine Learning to Predict Dietary Lapses During Weight Loss.

PubMed

Goldstein, Stephanie P; Zhang, Fengqing; Thomas, John G; Butryn, Meghan L; Herbert, James D; Forman, Evan M

2018-05-01

Individuals who adhere to dietary guidelines provided during weight loss interventions tend to be more successful with weight control. Any deviation from dietary guidelines can be referred to as a "lapse." There is a growing body of research showing that lapses are predictable using a variety of physiological, environmental, and psychological indicators. With recent technological advancements, it may be possible to assess these triggers and predict dietary lapses in real time. The current study sought to use machine learning techniques to predict lapses and evaluate the utility of combining both group- and individual-level data to enhance lapse prediction. The current study trained and tested a machine learning algorithm capable of predicting dietary lapses from a behavioral weight loss program among adults with overweight/obesity (n = 12). Participants were asked to follow a weight control diet for 6 weeks and complete ecological momentary assessment (EMA; repeated brief surveys delivered via smartphone) regarding dietary lapses and relevant triggers. WEKA decision trees were used to predict lapses with an accuracy of 0.72 for the group of participants. However, generalization of the group algorithm to each individual was poor, and as such, group- and individual-level data were combined to improve prediction. The findings suggest that 4 weeks of individual data collection is recommended to attain optimal model performance. The predictive algorithm could be utilized to provide in-the-moment interventions to prevent dietary lapses and therefore enhance weight losses. Furthermore, methods in the current study could be translated to other types of health behavior lapses.

Jacques Loeb, B. F. Skinner, and the legacy of prediction and control

PubMed Central

Hackenberg, Timothy D.

1995-01-01

The biologist Jacques Loeb is an important figure in the history of behavior analysis. Between 1890 and 1915, Loeb championed an approach to experimental biology that would later exert substantial influence on the work of B. F. Skinner and behavior analysis. This paper examines some of these sources of influence, with a particular emphasis on Loeb's firm commitment to prediction and control as fundamental goals of an experimental life science, and how these goals were extended and broadened by Skinner. Both Loeb and Skinner adopted a pragmatic approach to science that put practical control of their subject matter above formal theory testing, both based their research programs on analyses of reproducible units involving the intact organism, and both strongly endorsed technological applications of basic laboratory science. For Loeb, but especially for Skinner, control came to mean something more than mere experimental or technological control for its own sake; it became synonomous with scientific understanding. This view follows from (a) the successful working model of science Loeb and Skinner inherited from Ernst Mach, in which science is viewed as human social activity, and effective practical action is taken as the basis of scientific knowledge, and (b) Skinner's analysis of scientific activity, situated in the world of direct experience and related to practices arranged by scientific verbal communities. From this perspective, prediction and control are human acts that arise from and are maintained by social circumstances in which such acts meet with effective consequences. PMID:22478220

Predicting Droplet Formation on Centrifugal Microfluidic Platforms

NASA Astrophysics Data System (ADS)

Moebius, Jacob Alfred

Centrifugal microfluidics is a widely known research tool for biological sample and water quality analysis. Currently, the standard equipment used for such diagnostic applications include slow, bulky machines controlled by multiple operators. These machines can be condensed into a smaller, faster benchtop sample-to-answer system. Sample processing is an important step taken to extract, isolate, and convert biological factors, such as nucleic acids or proteins, from a raw sample to an analyzable solution. Volume definition is one such step. The focus of this thesis is the development of a model predicting monodispersed droplet formation and the application of droplets as a technique for volume definition. First, a background of droplet microfluidic platforms is presented, along with current biological analysis technologies and the advantages of integrating such technologies onto microfluidic platforms. Second, background and theories of centrifugal microfluidics is given, followed by theories relevant to droplet emulsions. Third, fabrication techniques for centrifugal microfluidic designs are discussed. Finally, the development of a model for predicting droplet formation on the centrifugal microfluidic platform are presented for the rest of the thesis. Predicting droplet formation analytically based on the volumetric flow rates of the continuous and dispersed phases, the ratios of these two flow rates, and the interfacial tension between the continuous and dispersed phases presented many challenges, which will be discussed in this work. Experimental validation was completed using continuous phase solutions of different interfacial tensions. To conclude, prospective applications are discussed with expected challenges.

Assessment of generalizability, applicability and predictability (GAP) for evaluating external validity in studies of universal family-based prevention of alcohol misuse in young people: systematic methodological review of randomized controlled trials.

PubMed

Fernandez-Hermida, Jose Ramon; Calafat, Amador; Becoña, Elisardo; Tsertsvadze, Alexander; Foxcroft, David R

2012-09-01

To assess external validity characteristics of studies from two Cochrane Systematic Reviews of the effectiveness of universal family-based prevention of alcohol misuse in young people. Two reviewers used an a priori developed external validity rating form and independently assessed three external validity dimensions of generalizability, applicability and predictability (GAP) in randomized controlled trials. The majority (69%) of the included 29 studies were rated 'unclear' on the reporting of sufficient information for judging generalizability from sample to study population. Ten studies (35%) were rated 'unclear' on the reporting of sufficient information for judging applicability to other populations and settings. No study provided an assessment of the validity of the trial end-point measures for subsequent mortality, morbidity, quality of life or other economic or social outcomes. Similarly, no study reported on the validity of surrogate measures using established criteria for assessing surrogate end-points. Studies evaluating the benefits of family-based prevention of alcohol misuse in young people are generally inadequate at reporting information relevant to generalizability of the findings or implications for health or social outcomes. Researchers, study authors, peer reviewers, journal editors and scientific societies should take steps to improve the reporting of information relevant to external validity in prevention trials. © 2012 The Authors. Addiction © 2012 Society for the Study of Addiction.

Heat and momentum transfer model studies applicable to once-through, forced convection potassium boiling

NASA Technical Reports Server (NTRS)

Sabin, C. M.; Poppendiek, H. F.

1971-01-01

A number of heat transfer and fluid flow mechanisms that control once-through, forced convection potassium boiling are studied analytically. The topics discussed are: (1) flow through tubes containing helical wire inserts, (2) motion of droplets entrained in vapor flow, (3) liquid phase distribution in boilers, (4) temperature distributions in boiler tube walls, (5) mechanisms of heat transfer regime change, and (6) heat transfer in boiler tubes. Whenever possible, comparisons of predicted and actual performances are made. The model work presented aids in the prediction of operating characteristics of actual boilers.

Application of dynamical systems theory to nonlinear aircraft dynamics

NASA Technical Reports Server (NTRS)

Culick, Fred E. C.; Jahnke, Craig C.

1988-01-01

Dynamical systems theory has been used to study nonlinear aircraft dynamics. A six degree of freedom model that neglects gravity has been analyzed. The aerodynamic model, supplied by NASA, is for a generic swept wing fighter and includes nonlinearities as functions of the angle of attack. A continuation method was used to calculate the steady states of the aircraft, and bifurcations of these steady states, as functions of the control deflections. Bifurcations were used to predict jump phenomena and the onset of periodic motion for roll coupling instabilities and high angle of attack maneuvers. The predictions were verified with numerical simulations.

Motion compensation for robotic lung tumour radiotherapy in remote locations: A personalised medicine approach

NASA Astrophysics Data System (ADS)

Ionescu, Clara M.; Copot, Cosmin; Verellen, Dirk

2017-03-01

The purpose of this work is to integrate the concept of patient-in-the-closed-loop application with tumour treatment of cancer-diagnosed patients in remote areas. The generic closed loop control objective is effective synchronisation of the radiation focus to the movement of a lung tissue tumour during actual breathing of the patient. This is facilitated by accurate repositioning of a robotic arm manipulator, i.e. we emulate the Cyberknife Robotic Radiosurgery system. Predictive control with disturbance filter is used in this application in a minimalistic model design. Performance of the control structure is validated by means of simulation using real recorded breathing patterns from patients measured in 3D space. Latency in communication protocol is taken into account, given telerobotics involve autonomous operation of a robot interacting with a human being in different location. Our results suggest that the proposed closed loop control structure has practical potential to individualise the treatment and improves accuracy by at least 15%.

Maneuvering a reentry body via magneto-gasdynamic forces

NASA Astrophysics Data System (ADS)

Ohare, Leo Patrick

1992-04-01

Some of the characteristics of the interaction of an electrically conducting fluid with a non-uniform applied magnetic field and a potential magnetogasdynamic control system which may be used on future aerospace vehicles are presented. The flow through a two dimensional channel is predicted by numerically solving the magnetogasdynamic equations using a time marching technique. The fluid was modeled as a compressible, inviscid, supersonic gas with finite electrical conductivity. Development of the algorithm provided a means to predict and analyze phenomena associated with magnetogasdynamic flows which had not been previously explored using numerical methods. One such phenomena was the prediction of oblique waves resulting from the interaction of an electrically conducting fluid with a non-uniform applied magnetic field. Development of this tool provided a means to explore an application which might have potential use for future aerospace vehicle missions. In order to appreciate the significance of this technology, predictions were made of the pitching moment about a slender blunted cone, generated by a system relying on the fluid-magnetic interaction. These moments were compared to predictions of a pitching moment generated by a deflecting control surface on the same vehicle. It was shown that the proposed magnetogasdynamic system could produce moments which were on the same order as the moments produced by the flap systems at low deflection angles.

Predictive Analytical Model for Isolator Shock-Train Location in a Mach 2.2 Direct-Connect Supersonic Combustion Tunnel

NASA Astrophysics Data System (ADS)

Lingren, Joe; Vanstone, Leon; Hashemi, Kelley; Gogineni, Sivaram; Donbar, Jeffrey; Akella, Maruthi; Clemens, Noel

2016-11-01

This study develops an analytical model for predicting the leading shock of a shock-train in the constant area isolator section in a Mach 2.2 direct-connect scramjet simulation tunnel. The effective geometry of the isolator is assumed to be a weakly converging duct owing to boundary-layer growth. For some given pressure rise across the isolator, quasi-1D equations relating to isentropic or normal shock flows can be used to predict the normal shock location in the isolator. The surface pressure distribution through the isolator was measured during experiments and both the actual and predicted locations can be calculated. Three methods of finding the shock-train location are examined, one based on the measured pressure rise, one using a non-physics-based control model, and one using the physics-based analytical model. It is shown that the analytical model performs better than the non-physics-based model in all cases. The analytic model is less accurate than the pressure threshold method but requires significantly less information to compute. In contrast to other methods for predicting shock-train location, this method is relatively accurate and requires as little as a single pressure measurement. This makes this method potentially useful for unstart control applications.

Broad control of disulfide stability through microenvironmental effects and analysis in complex redox environments.

PubMed

Wu, Chuanliu; Wang, Shuo; Brülisauer, Lorine; Leroux, Jean-Christophe; Gauthier, Marc A

2013-07-08

Disulfide bonds stabilize the tertiary- and quaternary structure of proteins. In addition, they can be used to engineer redox-sensitive (bio)materials and drug-delivery systems. Many of these applications require control of the stability of the disulfide bond. It has recently been shown that the charged microenvironment of the disulfide can be used to alter their stability by ∼3 orders of magnitude in a predictable and finely tunable manner at acidic pH. The aim of this work is to extend these findings to physiological pH and to demonstrate the validity of this approach in complex redox milieu. Disulfide microenvironments were manipulated synergistically with steric hindrance herein to control disulfide bond stability over ∼3 orders of magnitude at neutral pH. Control of disulfide stability through microenvironmental effects could also be observed in complex redox buffers (including serum) and in the presence of cells. Such fine and predictable control of disulfide properties is not achievable using other existing approaches. These findings provide easily implementable and general tools for controlling the responsiveness of biomaterials and drug delivery systems toward various local endogenous redox environments.

Nonlinear predictive control for durability enhancement and efficiency improvement in a fuel cell power system

NASA Astrophysics Data System (ADS)

Luna, Julio; Jemei, Samir; Yousfi-Steiner, Nadia; Husar, Attila; Serra, Maria; Hissel, Daniel

2016-10-01

In this work, a nonlinear model predictive control (NMPC) strategy is proposed to improve the efficiency and enhance the durability of a proton exchange membrane fuel cell (PEMFC) power system. The PEMFC controller is based on a distributed parameters model that describes the nonlinear dynamics of the system, considering spatial variations along the gas channels. Parasitic power from different system auxiliaries is considered, including the main parasitic losses which are those of the compressor. A nonlinear observer is implemented, based on the discretised model of the PEMFC, to estimate the internal states. This information is included in the cost function of the controller to enhance the durability of the system by means of avoiding local starvation and inappropriate water vapour concentrations. Simulation results are presented to show the performance of the proposed controller over a given case study in an automotive application (New European Driving Cycle). With the aim of representing the most relevant phenomena that affects the PEMFC voltage, the simulation model includes a two-phase water model and the effects of liquid water on the catalyst active area. The control model is a simplified version that does not consider two-phase water dynamics.

Automated System Checkout to Support Predictive Maintenance for the Reusable Launch Vehicle

NASA Technical Reports Server (NTRS)

Patterson-Hine, Ann; Deb, Somnath; Kulkarni, Deepak; Wang, Yao; Lau, Sonie (Technical Monitor)

1998-01-01

The Propulsion Checkout and Control System (PCCS) is a predictive maintenance software system. The real-time checkout procedures and diagnostics are designed to detect components that need maintenance based on their condition, rather than using more conventional approaches such as scheduled or reliability centered maintenance. Predictive maintenance can reduce turn-around time and cost and increase safety as compared to conventional maintenance approaches. Real-time sensor validation, limit checking, statistical anomaly detection, and failure prediction based on simulation models are employed. Multi-signal models, useful for testability analysis during system design, are used during the operational phase to detect and isolate degraded or failed components. The TEAMS-RT real-time diagnostic engine was developed to utilize the multi-signal models by Qualtech Systems, Inc. Capability of predicting the maintenance condition was successfully demonstrated with a variety of data, from simulation to actual operation on the Integrated Propulsion Technology Demonstrator (IPTD) at Marshall Space Flight Center (MSFC). Playback of IPTD valve actuations for feature recognition updates identified an otherwise undetectable Main Propulsion System 12 inch prevalve degradation. The algorithms were loaded into the Propulsion Checkout and Control System for further development and are the first known application of predictive Integrated Vehicle Health Management to an operational cryogenic testbed. The software performed successfully in real-time, meeting the required performance goal of 1 second cycle time.

Building Energy Modeling and Control Methods for Optimization and Renewables Integration

NASA Astrophysics Data System (ADS)

Burger, Eric M.

This dissertation presents techniques for the numerical modeling and control of building systems, with an emphasis on thermostatically controlled loads. The primary objective of this work is to address technical challenges related to the management of energy use in commercial and residential buildings. This work is motivated by the need to enhance the performance of building systems and by the potential for aggregated loads to perform load following and regulation ancillary services, thereby enabling the further adoption of intermittent renewable energy generation technologies. To increase the generalizability of the techniques, an emphasis is placed on recursive and adaptive methods which minimize the need for customization to specific buildings and applications. The techniques presented in this dissertation can be divided into two general categories: modeling and control. Modeling techniques encompass the processing of data streams from sensors and the training of numerical models. These models enable us to predict the energy use of a building and of sub-systems, such as a heating, ventilation, and air conditioning (HVAC) unit. Specifically, we first present an ensemble learning method for the short-term forecasting of total electricity demand in buildings. As the deployment of intermittent renewable energy resources continues to rise, the generation of accurate building-level electricity demand forecasts will be valuable to both grid operators and building energy management systems. Second, we present a recursive parameter estimation technique for identifying a thermostatically controlled load (TCL) model that is non-linear in the parameters. For TCLs to perform demand response services in real-time markets, online methods for parameter estimation are needed. Third, we develop a piecewise linear thermal model of a residential building and train the model using data collected from a custom-built thermostat. This model is capable of approximating unmodeled dynamics within a building by learning from sensor data. Control techniques encompass the application of optimal control theory, model predictive control, and convex distributed optimization to TCLs. First, we present the alternative control trajectory (ACT) representation, a novel method for the approximate optimization of non-convex discrete systems. This approach enables the optimal control of a population of non-convex agents using distributed convex optimization techniques. Second, we present a distributed convex optimization algorithm for the control of a TCL population. Experimental results demonstrate the application of this algorithm to the problem of renewable energy generation following. This dissertation contributes to the development of intelligent energy management systems for buildings by presenting a suite of novel and adaptable modeling and control techniques. Applications focus on optimizing the performance of building operations and on facilitating the integration of renewable energy resources.

Recent activities within the Aeroservoelasticity Branch at the NASA Langley Research Center

NASA Technical Reports Server (NTRS)

Noll, Thomas E.; Perry, Boyd, III; Gilbert, Michael G.

1989-01-01

The objective of research in aeroservoelasticity at the NASA Langley Research Center is to enhance the modeling, analysis, and multidisciplinary design methodologies for obtaining multifunction digital control systems for application to flexible flight vehicles. Recent accomplishments are discussed, and a status report on current activities within the Aeroservoelasticity Branch is presented. In the area of modeling, improvements to the Minimum-State Method of approximating unsteady aerodynamics are shown to provide precise, low-order aeroservoelastic models for design and simulation activities. Analytical methods based on Matched Filter Theory and Random Process Theory to provide efficient and direct predictions of the critical gust profile and the time-correlated gust loads for linear structural design considerations are also discussed. Two research projects leading towards improved design methodology are summarized. The first program is developing an integrated structure/control design capability based on hierarchical problem decomposition, multilevel optimization and analytical sensitivities. The second program provides procedures for obtaining low-order, robust digital control laws for aeroelastic applications. In terms of methodology validation and application the current activities associated with the Active Flexible Wing project are reviewed.

Bayesian additive decision trees of biomarker by treatment interactions for predictive biomarker detection and subgroup identification.

PubMed

Zhao, Yang; Zheng, Wei; Zhuo, Daisy Y; Lu, Yuefeng; Ma, Xiwen; Liu, Hengchang; Zeng, Zhen; Laird, Glen

2017-10-11

Personalized medicine, or tailored therapy, has been an active and important topic in recent medical research. Many methods have been proposed in the literature for predictive biomarker detection and subgroup identification. In this article, we propose a novel decision tree-based approach applicable in randomized clinical trials. We model the prognostic effects of the biomarkers using additive regression trees and the biomarker-by-treatment effect using a single regression tree. Bayesian approach is utilized to periodically revise the split variables and the split rules of the decision trees, which provides a better overall fitting. Gibbs sampler is implemented in the MCMC procedure, which updates the prognostic trees and the interaction tree separately. We use the posterior distribution of the interaction tree to construct the predictive scores of the biomarkers and to identify the subgroup where the treatment is superior to the control. Numerical simulations show that our proposed method performs well under various settings comparing to existing methods. We also demonstrate an application of our method in a real clinical trial.

Ordering transition in salt-doped diblock copolymers

DOE PAGES

Qin, Jian; de Pablo, Juan J.

2016-04-26

Lithium salt-doped block copolymers offer promise for applications as solid electrolytes in lithium ion batteries. Control of the conductivity and mechanical properties of these materials, for membrane applications relies critically on the ability to predict and manipulate their microphase separation temperature. Past attempts to predict the so-called "order-disorder transition temperature" of copolymer electrolytes have relied on approximate treatments of electrostatic interactions. In this work, we introduce a coarse-grained simulation model that treats Coulomb interactions explicitly, and we use it to investigate the ordering transition of charged block copolymers. The order-disorder transition temperature is determined from the ordering free energy, whichmore » we calculate with a high level of precision using a density-of-states approach. Our calculations allow us to discern a delicate competition between two physical effects: ion association, which raises the transition temperature, and solvent dilution, which lowers the transition temperature. Lastly, in the intermediate salt concentration regime, our results predict that the order-disorder transition temperature increases with salt content, in agreement with available experimental data.« less

Sex differences in theory-based predictors of leisure time physical activity in a population-based sample of adults with spinal cord injury.

PubMed

Stapleton, Jessie N; Martin Ginis, Kathleen A

2014-09-01

To examine sex differences in theory-based predictors of leisure time physical activity (LTPA) among men and women with spinal cord injury, and secondarily, to identify factors that might explain any sex differences in social cognitions. A secondary analysis of Study of Health and Activity in People with Spinal Cord Injury survey data. Community. Community-dwelling men (n=536) and women (n=164) recruited from 4 rehabilitation and research centers. Not applicable. Subjective norms, attitudes, barrier self-efficacy, perceived controllability (PC), and intentions. Men had stronger PC and barrier self-efficacy than women. Hierarchical regression analyses revealed that social support significantly predicted PC for both sexes, and health, pain, and physical independence also significantly predicted PC for men. Social support, health, and pain significantly predicted barrier self-efficacy for men. Social support was the only significant predictor of barrier self-efficacy for women. Women felt significantly less control over their physical activity behavior and had lower confidence to overcome barriers to physical activity than did men. Although social support predicted PC and barrier self-efficacy in both men and women, men seemed to take additional factors into consideration when formulating their control beliefs for LTPA. Copyright © 2014 American Congress of Rehabilitation Medicine. Published by Elsevier Inc. All rights reserved.

On the neutralization of acid rock drainage by carbonate and silicate minerals

NASA Astrophysics Data System (ADS)

Sherlock, E. J.; Lawrence, R. W.; Poulin, R.

1995-02-01

The net result of acid-generating and-neutralizing reactions within mining wastes is termed acid rock drainage (ARD). The oxidation of sulfide minerals is the major contributor to acid generation. Dissolution and alteration of various minerals can contribute to the neutralization of acid. Definitions of alkalinity, acidity, and buffer capacity are reviewed, and a detailed discussion of the dissolution and neutralizing capacity of carbonate and silicate minerals related to equilibium conditions, dissolution mechanism, and kinetics is provided. Factors that determine neutralization rate by carbonate and silicate minerals include: pH, PCO 2, equilibrium conditions, temperature, mineral composition and structure, redox conditions, and the presence of “foreign” ions. Similar factors affect sulfide oxidation. Comparison of rates shows sulfides react fastest, followed by carbonates and silicates. The differences in the reaction mechanisms and kinetics of neutralization have important implications in the prediction, control, and regulation of ARD. Current static and kinetic prediction methods upon which mine permitting, ARD control, and mine closure plans are based do not consider sample mineralogy or the kinetics of the acid-generating and-neutralizing reactions. Erroneous test interpretations and predictions can result. The importance of considering mineralogy for site-specific interpretation is highlighted. Uncertainty in prediction leads to difficulties for the mine operator in developing satisfactory and cost-effective control and remediation measures. Thus, the application of regulations and guidelines for waste management planning need to beflexible.

Load application for the contact mechanics analysis and wear prediction of total knee replacement.

PubMed

Zhang, Jing; Chen, Zhenxian; Wang, Ling; Li, Dichen; Jin, Zhongmin

2017-05-01

Tibiofemoral contact forces in total knee replacement have been measured at the medial and lateral sites respectively using an instrumented prosthesis, and predicted from musculoskeletal multibody dynamics models with a reasonable accuracy. However, it is uncommon that the medial and lateral forces are applied separately to replace a total axial load according to the ISO standard in the majority of current finite element analyses. In this study, we quantified the different effects of applying the medial and lateral loads separately versus the traditional total axial load application on contact mechanics and wear prediction of a patient-specific knee prosthesis. The load application position played an important role under the medial-lateral load application. The loading set which produced the closest load distribution to the multibody dynamics model was used to predict the contact mechanics and wear for the prosthesis and compared with the total axial load application. The medial-lateral load distribution using the present method was found to be closer to the multibody dynamics prediction than the traditional total axial load application, and the maximum contact pressure and contact area were consistent with the corresponding load variation. The predicted total volumetric wear rate and area were similar between the two load applications. However, the split of the predicted wear volumes on the medial and the lateral sides was different. The lateral volumetric wear rate was 31.46% smaller than the medial from the traditional load application prediction, while from the medial-lateral load application, the lateral side was only 11.8% smaller than the medial. The medial-lateral load application could provide a new and more accurate method of load application for patient-specific preclinical contact mechanics and wear prediction of knee implants.

Numerical natural rubber curing simulation, obtaining a controlled gradient of the state of cure in a thick-section part

NASA Astrophysics Data System (ADS)

El Labban, A.; Mousseau, P.; Bailleul, J. L.; Deterre, R.

2007-04-01

Although numerical simulation has proved to be a useful tool to predict the rubber vulcanization process, few applications in the process control have been reported. Because the end-use rubber properties depend on the state of cure distribution in the parts thickness, the prediction of the optimal distribution remains a challenge for the rubber industry. The analysis of the vulcanization process requires the determination of the thermal behavior of the material and the cure kinetics. A nonisothermal vulcanization model with nonisothermal induction time is used in this numerical study. Numerical results are obtained for natural rubber (NR) thick-section part curing. A controlled gradient of the state of cure in the part thickness is obtained by a curing process that consists not only in mold heating phase, but also a forced convection mold cooling phase in order to stop the vulcanization process and to control the vulcanization distribution. The mold design that allows this control is described. In the heating phase, the state of cure is mainly controlled by the chemical kinetics (the induction time), but in the cooling phase, it is the heat diffusion that controls the state of cure distribution. A comparison among different cooling conditions is shown and a good state of cure gradient control is obtained.

Intelligent Engine Systems: Adaptive Control

NASA Technical Reports Server (NTRS)

Gibson, Nathan

2008-01-01

We have studied the application of the baseline Model Predictive Control (MPC) algorithm to the control of main fuel flow rate (WF36), variable bleed valve (AE24) and variable stator vane (STP25) control of a simulated high-bypass turbofan engine. Using reference trajectories for thrust and turbine inlet temperature (T41) generated by a simulated new engine, we have examined MPC for tracking these two reference outputs while controlling a deteriorated engine. We have examined the results of MPC control for six different transients: two idle-to-takeoff transients at sea level static (SLS) conditions, one takeoff-to-idle transient at SLS, a Bode power command and reverse Bode power command at 20,000 ft/Mach 0.5, and a reverse Bode transient at 35,000 ft/Mach 0.84. For all cases, our primary focus was on the computational effort required by MPC for varying MPC update rates, control horizons, and prediction horizons. We have also considered the effects of these MPC parameters on the performance of the control, with special emphasis on the thrust tracking error, the peak T41, and the sizes of violations of the constraints on the problem, primarily the booster stall margin limit, which for most cases is the lone constraint that is violated with any frequency.

Active Control of Wind-Tunnel Model Aeroelastic Response Using Neural Networks

NASA Technical Reports Server (NTRS)

Scott, Robert C.

2000-01-01

NASA Langley Research Center, Hampton, VA 23681 Under a joint research and development effort conducted by the National Aeronautics and Space Administration and The Boeing Company (formerly McDonnell Douglas) three neural-network based control systems were developed and tested. The control systems were experimentally evaluated using a transonic wind-tunnel model in the Langley Transonic Dynamics Tunnel. One system used a neural network to schedule flutter suppression control laws, another employed a neural network in a predictive control scheme, and the third employed a neural network in an inverse model control scheme. All three of these control schemes successfully suppressed flutter to or near the limits of the testing apparatus, and represent the first experimental applications of neural networks to flutter suppression. This paper will summarize the findings of this project.

Application of seasonal auto-regressive integrated moving average model in forecasting the incidence of hand-foot-mouth disease in Wuhan, China.

PubMed

Peng, Ying; Yu, Bin; Wang, Peng; Kong, De-Guang; Chen, Bang-Hua; Yang, Xiao-Bing

2017-12-01

Outbreaks of hand-foot-mouth disease (HFMD) have occurred many times and caused serious health burden in China since 2008. Application of modern information technology to prediction and early response can be helpful for efficient HFMD prevention and control. A seasonal auto-regressive integrated moving average (ARIMA) model for time series analysis was designed in this study. Eighty-four-month (from January 2009 to December 2015) retrospective data obtained from the Chinese Information System for Disease Prevention and Control were subjected to ARIMA modeling. The coefficient of determination (R 2 ), normalized Bayesian Information Criterion (BIC) and Q-test P value were used to evaluate the goodness-of-fit of constructed models. Subsequently, the best-fitted ARIMA model was applied to predict the expected incidence of HFMD from January 2016 to December 2016. The best-fitted seasonal ARIMA model was identified as (1,0,1)(0,1,1) 12 , with the largest coefficient of determination (R 2 =0.743) and lowest normalized BIC (BIC=3.645) value. The residuals of the model also showed non-significant autocorrelations (P Box-Ljung (Q) =0.299). The predictions by the optimum ARIMA model adequately captured the pattern in the data and exhibited two peaks of activity over the forecast interval, including a major peak during April to June, and again a light peak for September to November. The ARIMA model proposed in this study can forecast HFMD incidence trend effectively, which could provide useful support for future HFMD prevention and control in the study area. Besides, further observations should be added continually into the modeling data set, and parameters of the models should be adjusted accordingly.

A Review of Challenges in the Use of fMRI for Disease Classification / Characterization and A Projection Pursuit Application from Multi-site fMRI Schizophrenia Study.

PubMed

Demirci, Oguz; Clark, Vincent P; Magnotta, Vincent A; Andreasen, Nancy C; Lauriello, John; Kiehl, Kent A; Pearlson, Godfrey D; Calhoun, Vince D

2008-09-01

Functional magnetic resonance imaging (fMRI) is a fairly new technique that has the potential to characterize and classify brain disorders such as schizophrenia. It has the possibility of playing a crucial role in designing objective prognostic/diagnostic tools, but also presents numerous challenges to analysis and interpretation. Classification provides results for individual subjects, rather than results related to group differences. This is a more complicated endeavor that must be approached more carefully and efficient methods should be developed to draw generalized and valid conclusions out of high dimensional data with a limited number of subjects, especially for heterogeneous disorders whose pathophysiology is unknown. Numerous research efforts have been reported in the field using fMRI activation of schizophrenia patients and healthy controls. However, the results are usually not generalizable to larger data sets and require careful definition of the techniques used both in designing algorithms and reporting prediction accuracies. In this review paper, we survey a number of previous reports and also identify possible biases (cross-validation, class size, e.g.) in class comparison/prediction problems. Some suggestions to improve the effectiveness of the presentation of the prediction accuracy results are provided. We also present our own results using a projection pursuit algorithm followed by an application of independent component analysis proposed in an earlier study. We classify schizophrenia versus healthy controls using fMRI data of 155 subjects from two sites obtained during three different tasks. The results are compared in order to investigate the effectiveness of each task and differences between patients with schizophrenia and healthy controls were investigated.

Selecting an Informative/Discriminating Multivariate Response for Inverse Prediction

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

Thomas, Edward V.; Lewis, John. R.; Anderson-Cook, Christine Michaela

The inverse prediction is important in a variety of scientific and engineering applications, such as to predict properties/characteristics of an object by using multiple measurements obtained from it. Inverse prediction can be accomplished by inverting parameterized forward models that relate the measurements (responses) to the properties/characteristics of interest. Sometimes forward models are computational/science based; but often, forward models are empirically based response surface models, obtained by using the results of controlled experimentation. For empirical models, it is important that the experiments provide a sound basis to develop accurate forward models in terms of the properties/characteristics (factors). And while nature dictatesmore » the causal relationships between factors and responses, experimenters can control the complexity, accuracy, and precision of forward models constructed via selection of factors, factor levels, and the set of trials that are performed. Recognition of the uncertainty in the estimated forward models leads to an errors-in-variables approach for inverse prediction. The forward models (estimated by experiments or science based) can also be used to analyze how well candidate responses complement one another for inverse prediction over the range of the factor space of interest. Furthermore, one may find that some responses are complementary, redundant, or noninformative. Simple analysis and examples illustrate how an informative and discriminating subset of responses could be selected among candidates in cases where the number of responses that can be acquired during inverse prediction is limited by difficulty, expense, and/or availability of material.« less

Selecting an Informative/Discriminating Multivariate Response for Inverse Prediction

DOE PAGES

Thomas, Edward V.; Lewis, John. R.; Anderson-Cook, Christine Michaela; ...

2017-07-01

The inverse prediction is important in a variety of scientific and engineering applications, such as to predict properties/characteristics of an object by using multiple measurements obtained from it. Inverse prediction can be accomplished by inverting parameterized forward models that relate the measurements (responses) to the properties/characteristics of interest. Sometimes forward models are computational/science based; but often, forward models are empirically based response surface models, obtained by using the results of controlled experimentation. For empirical models, it is important that the experiments provide a sound basis to develop accurate forward models in terms of the properties/characteristics (factors). And while nature dictatesmore » the causal relationships between factors and responses, experimenters can control the complexity, accuracy, and precision of forward models constructed via selection of factors, factor levels, and the set of trials that are performed. Recognition of the uncertainty in the estimated forward models leads to an errors-in-variables approach for inverse prediction. The forward models (estimated by experiments or science based) can also be used to analyze how well candidate responses complement one another for inverse prediction over the range of the factor space of interest. Furthermore, one may find that some responses are complementary, redundant, or noninformative. Simple analysis and examples illustrate how an informative and discriminating subset of responses could be selected among candidates in cases where the number of responses that can be acquired during inverse prediction is limited by difficulty, expense, and/or availability of material.« less

Standardization of Negative Controls in Diagnostic Immunohistochemistry: Recommendations From the International Ad Hoc Expert Panel

PubMed Central

Torlakovic, Emina E.; Francis, Glenn; Garratt, John; Gilks, Blake; Hyjek, Elizabeth; Ibrahim, Merdol; Miller, Rodney; Nielsen, Søren; Petcu, Eugen B.; Swanson, Paul E.; Taylor, Clive R.; Vyberg, Mogens

2014-01-01

Standardization of controls, both positive and negative controls, is needed for diagnostic immunohistochemistry (dIHC). The use of IHC-negative controls, irrespective of type, although well established, is not standardized. As such, the relevance and applicability of negative controls continues to challenge both pathologists and laboratory budgets. Despite the clear theoretical notion that appropriate controls serve to demonstrate the sensitivity and specificity of the dIHC test, it remains unclear which types of positive and negative controls are applicable and/or useful in day-to-day clinical practice. There is a perceived need to provide “best practice recommendations” for the use of negative controls. This perception is driven not only by logistics and cost issues, but also by increased pressure for accurate IHC testing, especially when IHC is performed for predictive markers, the number of which is rising as personalized medicine continues to develop. Herein, an international ad hoc expert panel reviews classification of negative controls relevant to clinical practice, proposes standard terminology for negative controls, considers the total evidence of IHC specificity that is available to pathologists, and develops a set of recommendations for the use of negative controls in dIHC based on “fit-for-use” principles. PMID:24714041

A statistical rain attenuation prediction model with application to the advanced communication technology satellite project. 1: Theoretical development and application to yearly predictions for selected cities in the United States

NASA Technical Reports Server (NTRS)

Manning, Robert M.

1986-01-01

A rain attenuation prediction model is described for use in calculating satellite communication link availability for any specific location in the world that is characterized by an extended record of rainfall. Such a formalism is necessary for the accurate assessment of such availability predictions in the case of the small user-terminal concept of the Advanced Communication Technology Satellite (ACTS) Project. The model employs the theory of extreme value statistics to generate the necessary statistical rainrate parameters from rain data in the form compiled by the National Weather Service. These location dependent rain statistics are then applied to a rain attenuation model to obtain a yearly prediction of the occurrence of attenuation on any satellite link at that location. The predictions of this model are compared to those of the Crane Two-Component Rain Model and some empirical data and found to be very good. The model is then used to calculate rain attenuation statistics at 59 locations in the United States (including Alaska and Hawaii) for the 20 GHz downlinks and 30 GHz uplinks of the proposed ACTS system. The flexibility of this modeling formalism is such that it allows a complete and unified treatment of the temporal aspects of rain attenuation that leads to the design of an optimum stochastic power control algorithm, the purpose of which is to efficiently counter such rain fades on a satellite link.

Fingerstroke time estimates for touchscreen-based mobile gaming interaction.

PubMed

Lee, Ahreum; Song, Kiburm; Ryu, Hokyoung Blake; Kim, Jieun; Kwon, Gyuhyun

2015-12-01

The growing popularity of gaming applications and ever-faster mobile carrier networks have called attention to an intriguing issue that is closely related to command input performance. A challenging mirroring game service, which simultaneously provides game service to both PC and mobile phone users, allows them to play games against each other with very different control interfaces. Thus, for efficient mobile game design, it is essential to apply a new predictive model for measuring how potential touch input compares to the PC interfaces. The present study empirically tests the keystroke-level model (KLM) for predicting the time performance of basic interaction controls on the touch-sensitive smartphone interface (i.e., tapping, pointing, dragging, and flicking). A modified KLM, tentatively called the fingerstroke-level model (FLM), is proposed using time estimates on regression models. Copyright © 2015 Elsevier B.V. All rights reserved.

Cross-organism learning method to discover new gene functionalities.

PubMed

Domeniconi, Giacomo; Masseroli, Marco; Moro, Gianluca; Pinoli, Pietro

2016-04-01

Knowledge of gene and protein functions is paramount for the understanding of physiological and pathological biological processes, as well as in the development of new drugs and therapies. Analyses for biomedical knowledge discovery greatly benefit from the availability of gene and protein functional feature descriptions expressed through controlled terminologies and ontologies, i.e., of gene and protein biomedical controlled annotations. In the last years, several databases of such annotations have become available; yet, these valuable annotations are incomplete, include errors and only some of them represent highly reliable human curated information. Computational techniques able to reliably predict new gene or protein annotations with an associated likelihood value are thus paramount. Here, we propose a novel cross-organisms learning approach to reliably predict new functionalities for the genes of an organism based on the known controlled annotations of the genes of another, evolutionarily related and better studied, organism. We leverage a new representation of the annotation discovery problem and a random perturbation of the available controlled annotations to allow the application of supervised algorithms to predict with good accuracy unknown gene annotations. Taking advantage of the numerous gene annotations available for a well-studied organism, our cross-organisms learning method creates and trains better prediction models, which can then be applied to predict new gene annotations of a target organism. We tested and compared our method with the equivalent single organism approach on different gene annotation datasets of five evolutionarily related organisms (Homo sapiens, Mus musculus, Bos taurus, Gallus gallus and Dictyostelium discoideum). Results show both the usefulness of the perturbation method of available annotations for better prediction model training and a great improvement of the cross-organism models with respect to the single-organism ones, without influence of the evolutionary distance between the considered organisms. The generated ranked lists of reliably predicted annotations, which describe novel gene functionalities and have an associated likelihood value, are very valuable both to complement available annotations, for better coverage in biomedical knowledge discovery analyses, and to quicken the annotation curation process, by focusing it on the prioritized novel annotations predicted. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

Predicting county-level cancer incidence rates and counts in the United States

PubMed Central

Yu, Binbing

2018-01-01

Many countries, including the United States, publish predicted numbers of cancer incidence and death in current and future years for the whole country. These predictions provide important information on the cancer burden for cancer control planners, policymakers and the general public. Based on evidence from several empirical studies, the joinpoint (segmented-line linear regression) model has been adopted by the American Cancer Society to estimate the number of new cancer cases in the United States and in individual states since 2007. Recently, cancer incidence in smaller geographic regions such as counties and FIPS code regions is of increasing interest by local policymakers. The natural extension is to directly apply the joinpoint model to county-level cancer incidence data. The direct application has several drawbacks and its performance has not been evaluated. To address the concerns, we developed a spatial random-effects joinpoint model for county-level cancer incidence data. The proposed model was used to predict both cancer incidence rates and counts at the county level. The standard joinpoint model and the proposed method were compared through a validation study. The proposed method out-performed the standard joinpoint model for almost all cancer sites, especially for moderate or rare cancer sites and for counties with small population sizes. As an application, we predicted county-level prostate cancer incidence rates and counts for the year 2011 in Connecticut. PMID:23670947

Annotation and prediction of stress and workload from physiological and inertial signals.

PubMed

Ghosh, Arindam; Danieli, Morena; Riccardi, Giuseppe

2015-08-01

Continuous daily stress and high workload can have negative effects on individuals' physical and mental well-being. It has been shown that physiological signals may support the prediction of stress and workload. However, previous research is limited by the low diversity of signals concurring to such predictive tasks and controlled experimental design. In this paper we present 1) a pipeline for continuous and real-life acquisition of physiological and inertial signals 2) a mobile agent application for on-the-go event annotation and 3) an end-to-end signal processing and classification system for stress and workload from diverse signal streams. We study physiological signals such as Galvanic Skin Response (GSR), Skin Temperature (ST), Inter Beat Interval (IBI) and Blood Volume Pulse (BVP) collected using a non-invasive wearable device; and inertial signals collected from accelerometer and gyroscope sensors. We combine them with subjects' inputs (e.g. event tagging) acquired using the agent application, and their emotion regulation scores. In our experiments we explore signal combination and selection techniques for stress and workload prediction from subjects whose signals have been recorded continuously during their daily life. The end-to-end classification system is described for feature extraction, signal artifact removal, and classification. We show that a combination of physiological, inertial and user event signals provides accurate prediction of stress for real-life users and signals.

Rapid hybridization of nucleic acids using isotachophoresis

PubMed Central

Bercovici, Moran; Han, Crystal M.; Liao, Joseph C.; Santiago, Juan G.

2012-01-01

We use isotachophoresis (ITP) to control and increase the rate of nucleic acid hybridization reactions in free solution. We present a new physical model, validation experiments, and demonstrations of this assay. We studied the coupled physicochemical processes of preconcentration, mixing, and chemical reaction kinetics under ITP. Our experimentally validated model enables a closed form solution for ITP-aided reaction kinetics, and reveals a new characteristic time scale which correctly predicts order 10,000-fold speed-up of chemical reaction rate for order 100 pM reactants, and greater enhancement at lower concentrations. At 500 pM concentration, we measured a reaction time which is 14,000-fold lower than that predicted for standard second-order hybridization. The model and method are generally applicable to acceleration of reactions involving nucleic acids, and may be applicable to a wide range of reactions involving ionic reactants. PMID:22733732

Towards a renewal of the propeller in aeronautics

NASA Technical Reports Server (NTRS)

Berger, D.; Jacquet, P.

1985-01-01

The reasons for reconsidering the propeller for aircraft propulsion, the areas of application, and necessary developments are considered. Rising fuel costs and an increasing theoretical and experimental data base for turboprop engines have demonstrated that significant cost savings can be realized by the use of propellers. Propellers are well-suited to powering aircraft traveling at speeds up to Mach 0.65. Work is progressing on the development of a 150 seat aircraft which has a cruise speed of Mach 0.8, powered by a turboprop attached to an engine of 15,000 shp. Aeroelasticity analyses ae necessary in order to characterize the behavior of thin profile propfan blades, particularly to predict the oscillations through the entire functional range. High-power reducers must be developed, and the level of cabin noise must be controlled to less than 90 dB. Commercial applications are predicted for turboprops in specific instances.

Fault tolerant control of multivariable processes using auto-tuning PID controller.

PubMed

Yu, Ding-Li; Chang, T K; Yu, Ding-Wen

2005-02-01

Fault tolerant control of dynamic processes is investigated in this paper using an auto-tuning PID controller. A fault tolerant control scheme is proposed composing an auto-tuning PID controller based on an adaptive neural network model. The model is trained online using the extended Kalman filter (EKF) algorithm to learn system post-fault dynamics. Based on this model, the PID controller adjusts its parameters to compensate the effects of the faults, so that the control performance is recovered from degradation. The auto-tuning algorithm for the PID controller is derived with the Lyapunov method and therefore, the model predicted tracking error is guaranteed to converge asymptotically. The method is applied to a simulated two-input two-output continuous stirred tank reactor (CSTR) with various faults, which demonstrate the applicability of the developed scheme to industrial processes.

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

Simpson, L.

ITN Energy Systems, Inc., and Global Solar Energy, Inc., with the assistance of NREL's PV Manufacturing R&D program, have continued the advancement of CIGS production technology through the development of trajectory-oriented predictive/control models, fault-tolerance control, control-platform development, in-situ sensors, and process improvements. Modeling activities to date include the development of physics-based and empirical models for CIGS and sputter-deposition processing, implementation of model-based control, and application of predictive models to the construction of new evaporation sources and for control. Model-based control is enabled through implementation of reduced or empirical models into a control platform. Reliability improvement activities include implementation of preventivemore » maintenance schedules; detection of failed sensors/equipment and reconfiguration to continue processing; and systematic development of fault prevention and reconfiguration strategies for the full range of CIGS PV production deposition processes. In-situ sensor development activities have resulted in improved control and indicated the potential for enhanced process status monitoring and control of the deposition processes. Substantial process improvements have been made, including significant improvement in CIGS uniformity, thickness control, efficiency, yield, and throughput. In large measure, these gains have been driven by process optimization, which, in turn, have been enabled by control and reliability improvements due to this PV Manufacturing R&D program. This has resulted in substantial improvements of flexible CIGS PV module performance and efficiency.« less

Recent advances in chemical functionalization of nanoparticles with biomolecules for analytical applications.

PubMed

Oh, Ju-Hwan; Park, Do Hyun; Joo, Jang Ho; Lee, Jae-Seung

2015-11-01

The recent synthetic development of a variety of nanoparticles has led to their widespread application in diagnostics and therapeutics. In particular, the controlled size and shape of nanoparticles precisely determine their unique chemical and physical properties, which is highly attractive for accurate analysis of given systems. In addition to efforts toward controlling the synthesis and properties of nanoparticles, the surface functionalization of nanoparticles with biomolecules has been intensively investigated since the mid-1990s. The complicated yet programmable properties of biomolecules have proved to substantially enhance and enrich the novel functions of nanoparticles to achieve "smart" nanoparticle materials. In this review, the advances in chemical functionalization of four types of representative nanoparticle with DNA and protein molecules in the past five years are critically reviewed, and their future trends are predicted.

Novel Functional Genomics Approaches: A Promising Future in the Combat Against Plant Viruses.

PubMed

Fondong, Vincent N; Nagalakshmi, Ugrappa; Dinesh-Kumar, Savithramma P

2016-10-01

Advances in functional genomics and genome editing approaches have provided new opportunities and potential to accelerate plant virus control efforts through modification of host and viral genomes in a precise and predictable manner. Here, we discuss application of RNA-based technologies, including artificial micro RNA, transacting small interfering RNA, and Cas9 (clustered regularly interspaced short palindromic repeat-associated protein 9), which are currently being successfully deployed in generating virus-resistant plants. We further discuss the reverse genetics approach, targeting induced local lesions in genomes (TILLING) and its variant, known as EcoTILLING, that are used in the identification of plant virus recessive resistance gene alleles. In addition to describing specific applications of these technologies in plant virus control, this review discusses their advantages and limitations.

Repeated applications of a transdermal patch: analytical solution and optimal control of the delivery rate.

PubMed

Simon, L

2007-10-01

The integral transform technique was implemented to solve a mathematical model developed for percutaneous drug absorption. The model included repeated application and removal of a patch from the skin. Fick's second law of diffusion was used to study the transport of a medicinal agent through the vehicle and subsequent penetration into the stratum corneum. Eigenmodes and eigenvalues were computed and introduced into an inversion formula to estimate the delivery rate and the amount of drug in the vehicle and the skin. A dynamic programming algorithm calculated the optimal doses necessary to achieve a desired transdermal flux. The analytical method predicted profiles that were in close agreement with published numerical solutions and provided an automated strategy to perform therapeutic drug monitoring and control.

Bayesian inference of physiologically meaningful parameters from body sway measurements.

PubMed

Tietäväinen, A; Gutmann, M U; Keski-Vakkuri, E; Corander, J; Hæggström, E

2017-06-19

The control of the human body sway by the central nervous system, muscles, and conscious brain is of interest since body sway carries information about the physiological status of a person. Several models have been proposed to describe body sway in an upright standing position, however, due to the statistical intractability of the more realistic models, no formal parameter inference has previously been conducted and the expressive power of such models for real human subjects remains unknown. Using the latest advances in Bayesian statistical inference for intractable models, we fitted a nonlinear control model to posturographic measurements, and we showed that it can accurately predict the sway characteristics of both simulated and real subjects. Our method provides a full statistical characterization of the uncertainty related to all model parameters as quantified by posterior probability density functions, which is useful for comparisons across subjects and test settings. The ability to infer intractable control models from sensor data opens new possibilities for monitoring and predicting body status in health applications.

Using Magnetic Fields to Control Convection during Protein Crystallization: Analysis and Validation Studies

NASA Technical Reports Server (NTRS)

Ramachandran, N.; Leslie, F. W.

2004-01-01

The effect of convection during the crystallization of proteins is not very well understood. In a gravitational field, convection is caused by crystal sedimentation and by solutal buoyancy induced flow and these can lead to crystal imperfections. While crystallization in microgravity can approach diffusion limited growth conditions (no convection), terrestrially strong magnetic fields can be used to control fluid flow and sedimentation effects. In this work, we develop the analysis for magnetic flow control and test the predictions using analog experiments. Specifically, experiments on solutal convection in a paramagnetic fluid were conducted in a strong magnetic field gradient using a dilute solution of Manganese Chloride. The observed flows indicate that the magnetic field can completely counter the settling effects of gravity locally and are consistent with the theoretical predictions presented. This phenomenon suggests that magnetic fields may be useful in mimicking the microgravity environment of space for some crystal growth ana biological applications where fluid convection is undesirable.

Stochastic stability assessment of a semi-free piston engine generator concept

NASA Astrophysics Data System (ADS)

Kigezi, T. N.; Gonzalez Anaya, J. A.; Dunne, J. F.

2016-09-01

Small engines, as power generators with low-noise and vibration characteristics, are needed in two niche application areas: as electric vehicle range extenders and as domestic micro Combined Heat and Power systems. A recent semi-free piston design known as the AMOCATIC generator fully meets this requirement. The engine potentially allows for high energy conversion efficiencies at resonance derived from having a mass and spring assembly. As with free-piston engines in general, stability and control of piston motion has been cited as the prime challenge limiting the technology's widespread application. Using physical principles, we derive in this paper two important results: an energy balance criterion and a related general stability criterion for a semi-free piston engine. Control is achieved by systematically designing a Proportional Integral (PI) controller using a control-oriented engine model for which a specific stability condition is stated. All results are presented in closed form throughout the paper. Simulation results under stochastic pressure conditions show that the proposed energy balance, stability criterion, and PI controller, operate as predicted to yield stable engine operation at fixed compression ratio.

Feedforward hysteresis compensation in trajectory control of piezoelectrically-driven nanostagers

NASA Astrophysics Data System (ADS)

Bashash, Saeid; Jalili, Nader

2006-03-01

Complex structural nonlinearities of piezoelectric materials drastically degrade their performance in variety of micro- and nano-positioning applications. From the precision positioning and control perspective, the multi-path time-history dependent hysteresis phenomenon is the most concerned nonlinearity in piezoelectric actuators to be analyzed. To realize the underlying physics of this phenomenon and to develop an efficient compensation strategy, the intelligent properties of hysteresis with the effects of non-local memories are discussed. Through performing a set of experiments on a piezoelectrically-driven nanostager with high resolution capacitive position sensor, it is shown that for the precise prediction of hysteresis path, certain memory units are required to store the previous hysteresis trajectory data. Based on the experimental observations, a constitutive memory-based mathematical modeling framework is developed and trained for the precise prediction of hysteresis path for arbitrarily assigned input profiles. Using the inverse hysteresis model, a feedforward control strategy is then developed and implemented on the nanostager to compensate for the system everpresent nonlinearity. Experimental results demonstrate that the controller remarkably eliminates the nonlinear effect if memory units are sufficiently chosen for the inverse model.

Exposure–response model for sibutramine and placebo: suggestion for application to long-term weight-control drug development

PubMed Central

Han, Seunghoon; Jeon, Sangil; Hong, Taegon; Lee, Jongtae; Bae, Soo Hyeon; Park, Wan-su; Park, Gab-jin; Youn, Sunil; Jang, Doo Yeon; Kim, Kyung-Soo; Yim, Dong-Seok

2015-01-01

No wholly successful weight-control drugs have been developed to date, despite the tremendous demand. We present an exposure–response model of sibutramine mesylate that can be applied during clinical development of other weight-control drugs. Additionally, we provide a model-based evaluation of sibutramine efficacy. Data from a double-blind, randomized, placebo-controlled, multicenter study were used (N=120). Subjects in the treatment arm were initially given 8.37 mg sibutramine base daily, and those who lost <2 kg after 4 weeks’ treatment were escalated to 12.55 mg. The duration of treatment was 24 weeks. Drug concentration and body weight were measured predose and at 4 weeks, 8 weeks, and 24 weeks after treatment initiation. Exposure and response to sibutramine, including the placebo effect, were modeled using NONMEM 7.2. An asymptotic model approaching the final body weight was chosen to describe the time course of weight loss. Extent of weight loss was described successfully using a sigmoidal exposure–response relationship of the drug with a constant placebo effect in each individual. The placebo effect was influenced by subjects’ sex and baseline body mass index. Maximal weight loss was predicted to occur around 1 year after treatment initiation. The difference in mean weight loss between the sibutramine (daily 12.55 mg) and placebo groups was predicted to be 4.5% in a simulation of 1 year of treatment, with considerable overlap of prediction intervals. Our exposure–response model, which included the placebo effect, is the first example of a quantitative model that can be used to predict the efficacy of weight-control drugs. Similar approaches can help decision-making during clinical development of novel weight-loss drugs. PMID:26392753

Exposure-response model for sibutramine and placebo: suggestion for application to long-term weight-control drug development.

PubMed

Han, Seunghoon; Jeon, Sangil; Hong, Taegon; Lee, Jongtae; Bae, Soo Hyeon; Park, Wan-su; Park, Gab-jin; Youn, Sunil; Jang, Doo Yeon; Kim, Kyung-Soo; Yim, Dong-Seok

2015-01-01

No wholly successful weight-control drugs have been developed to date, despite the tremendous demand. We present an exposure-response model of sibutramine mesylate that can be applied during clinical development of other weight-control drugs. Additionally, we provide a model-based evaluation of sibutramine efficacy. Data from a double-blind, randomized, placebo-controlled, multicenter study were used (N=120). Subjects in the treatment arm were initially given 8.37 mg sibutramine base daily, and those who lost <2 kg after 4 weeks' treatment were escalated to 12.55 mg. The duration of treatment was 24 weeks. Drug concentration and body weight were measured predose and at 4 weeks, 8 weeks, and 24 weeks after treatment initiation. Exposure and response to sibutramine, including the placebo effect, were modeled using NONMEM 7.2. An asymptotic model approaching the final body weight was chosen to describe the time course of weight loss. Extent of weight loss was described successfully using a sigmoidal exposure-response relationship of the drug with a constant placebo effect in each individual. The placebo effect was influenced by subjects' sex and baseline body mass index. Maximal weight loss was predicted to occur around 1 year after treatment initiation. The difference in mean weight loss between the sibutramine (daily 12.55 mg) and placebo groups was predicted to be 4.5% in a simulation of 1 year of treatment, with considerable overlap of prediction intervals. Our exposure-response model, which included the placebo effect, is the first example of a quantitative model that can be used to predict the efficacy of weight-control drugs. Similar approaches can help decision-making during clinical development of novel weight-loss drugs.

Prediction error and somatosensory insula activation in women recovered from anorexia nervosa

PubMed Central

Frank, Guido K.W.; Collier, Shaleise; Shott, Megan E.; O’Reilly, Randall C.

2016-01-01

Background Previous research in patients with anorexia nervosa showed heightened brain response during a taste reward conditioning task and heightened sensitivity to rewarding and punishing stimuli. Here we tested the hypothesis that individuals recovered from anorexia nervosa would also experience greater brain activation during this task as well as higher sensitivity to salient stimuli than controls. Methods Women recovered from restricting-type anorexia nervosa and healthy control women underwent fMRI during application of a prediction error taste reward learning paradigm. Results Twenty-four women recovered from anorexia nervosa (mean age 30.3 ± 8.1 yr) and 24 control women (mean age 27.4 ± 6.3 yr) took part in this study. The recovered anorexia nervosa group showed greater left posterior insula activation for the prediction error model analysis than the control group (family-wise error– and small volume–corrected p < 0.05). A group × condition analysis found greater posterior insula response in women recovered from anorexia nervosa than controls for unexpected stimulus omission, but not for unexpected receipt. Sensitivity to punishment was elevated in women recovered from anorexia nervosa. Limitations This was a cross-sectional study, and the sample size was modest. Conclusion Anorexia nervosa after recovery is associated with heightened prediction error–related brain response in the posterior insula as well as greater response to unexpected reward stimulus omission. This finding, together with behaviourally increased sensitivity to punishment, could indicate that individuals recovered from anorexia nervosa are particularly responsive to punishment. The posterior insula processes somatosensory stimuli, including unexpected bodily states, and greater response could indicate altered perception or integration of unexpected or maybe unwanted bodily feelings. Whether those findings develop during the ill state or whether they are biological traits requires further study. PMID:26836623

Prediction error and somatosensory insula activation in women recovered from anorexia nervosa.

PubMed

Frank, Guido K W; Collier, Shaleise; Shott, Megan E; O'Reilly, Randall C

2016-08-01

Previous research in patients with anorexia nervosa showed heightened brain response during a taste reward conditioning task and heightened sensitivity to rewarding and punishing stimuli. Here we tested the hypothesis that individuals recovered from anorexia nervosa would also experience greater brain activation during this task as well as higher sensitivity to salient stimuli than controls. Women recovered from restricting-type anorexia nervosa and healthy control women underwent fMRI during application of a prediction error taste reward learning paradigm. Twenty-four women recovered from anorexia nervosa (mean age 30.3 ± 8.1 yr) and 24 control women (mean age 27.4 ± 6.3 yr) took part in this study. The recovered anorexia nervosa group showed greater left posterior insula activation for the prediction error model analysis than the control group (family-wise error- and small volume-corrected p < 0.05). A group × condition analysis found greater posterior insula response in women recovered from anorexia nervosa than controls for unexpected stimulus omission, but not for unexpected receipt. Sensitivity to punishment was elevated in women recovered from anorexia nervosa. This was a cross-sectional study, and the sample size was modest. Anorexia nervosa after recovery is associated with heightened prediction error-related brain response in the posterior insula as well as greater response to unexpected reward stimulus omission. This finding, together with behaviourally increased sensitivity to punishment, could indicate that individuals recovered from anorexia nervosa are particularly responsive to punishment. The posterior insula processes somatosensory stimuli, including unexpected bodily states, and greater response could indicate altered perception or integration of unexpected or maybe unwanted bodily feelings. Whether those findings develop during the ill state or whether they are biological traits requires further study.

Testing a cognitive model to predict posttraumatic stress disorder following childbirth.

PubMed

King, Lydia; McKenzie-McHarg, Kirstie; Horsch, Antje

2017-01-14

One third of women describes their childbirth as traumatic and between 0.8 and 6.9% goes on to develop posttraumatic stress disorder (PTSD). The cognitive model of PTSD has been shown to be applicable to a range of trauma samples. However, childbirth is qualitatively different to other trauma types and special consideration needs to be taken when applying it to this population. Previous studies have investigated some cognitive variables in isolation but no study has so far looked at all the key processes described in the cognitive model. This study therefore aimed to investigate whether theoretically-derived variables of the cognitive model explain unique variance in postnatal PTSD symptoms when key demographic, obstetric and clinical risk factors are controlled for. One-hundred and fifty-seven women who were between 1 and 12 months post-partum (M = 6.5 months) completed validated questionnaires assessing PTSD and depressive symptoms, childbirth experience, postnatal social support, trauma memory, peritraumatic processing, negative appraisals, dysfunctional cognitive and behavioural strategies and obstetric as well as demographic risk factors in an online survey. A PTSD screening questionnaire suggested that 5.7% of the sample might fulfil diagnostic criteria for PTSD. Overall, risk factors alone predicted 43% of variance in PTSD symptoms and cognitive behavioural factors alone predicted 72.7%. A final model including both risk factors and cognitive behavioural factors explained 73.7% of the variance in PTSD symptoms, 37.1% of which was unique variance predicted by cognitive factors. All variables derived from Ehlers and Clark's cognitive model significantly explained variance in PTSD symptoms following childbirth, even when clinical, demographic and obstetric were controlled for. Our findings suggest that the CBT model is applicable and useful as a way of understanding and informing the treatment of PTSD following childbirth.

Examples of Current and Future Uses of Neural-Net Image Processing for Aerospace Applications

NASA Technical Reports Server (NTRS)

Decker, Arthur J.

2004-01-01

Feed forward artificial neural networks are very convenient for performing correlated interpolation of pairs of complex noisy data sets as well as detecting small changes in image data. Image-to-image, image-to-variable and image-to-index applications have been tested at Glenn. Early demonstration applications are summarized including image-directed alignment of optics, tomography, flow-visualization control of wind-tunnel operations and structural-model-trained neural networks. A practical application is reviewed that employs neural-net detection of structural damage from interference fringe patterns. Both sensor-based and optics-only calibration procedures are available for this technique. These accomplishments have generated the knowledge necessary to suggest some other applications for NASA and Government programs. A tomography application is discussed to support Glenn's Icing Research tomography effort. The self-regularizing capability of a neural net is shown to predict the expected performance of the tomography geometry and to augment fast data processing. Other potential applications involve the quantum technologies. It may be possible to use a neural net as an image-to-image controller of an optical tweezers being used for diagnostics of isolated nano structures. The image-to-image transformation properties also offer the potential for simulating quantum computing. Computer resources are detailed for implementing the black box calibration features of the neural nets.

Arrays of horizontal carbon nanotubes of controlled chirality grown using designed catalysts

NASA Astrophysics Data System (ADS)

Zhang, Shuchen; Kang, Lixing; Wang, Xiao; Tong, Lianming; Yang, Liangwei; Wang, Zequn; Qi, Kuo; Deng, Shibin; Li, Qingwen; Bai, Xuedong; Ding, Feng; Zhang, Jin

2017-02-01

The semiconductor industry is increasingly of the view that Moore’s law—which predicts the biennial doubling of the number of transistors per microprocessor chip—is nearing its end. Consequently, the pursuit of alternative semiconducting materials for nanoelectronic devices, including single-walled carbon nanotubes (SWNTs), continues. Arrays of horizontal nanotubes are particularly appealing for technological applications because they optimize current output. However, the direct growth of horizontal SWNT arrays with controlled chirality, that would enable the arrays to be adapted for a wider range of applications and ensure the uniformity of the fabricated devices, has not yet been achieved. Here we show that horizontal SWNT arrays with predicted chirality can be grown from the surfaces of solid carbide catalysts by controlling the symmetries of the active catalyst surface. We obtained horizontally aligned metallic SWNT arrays with an average density of more than 20 tubes per micrometre in which 90 per cent of the tubes had chiral indices of (12, 6), and semiconducting SWNT arrays with an average density of more than 10 tubes per micrometre in which 80 per cent of the nanotubes had chiral indices of (8, 4). The nanotubes were grown using uniform size Mo2C and WC solid catalysts. Thermodynamically, the SWNT was selectively nucleated by matching its structural symmetry and diameter with those of the catalyst. We grew nanotubes with chiral indices of (2m, m) (where m is a positive integer), the yield of which could be increased by raising the concentration of carbon to maximize the kinetic growth rate in the chemical vapour deposition process. Compared to previously reported methods, such as cloning, seeding and specific-structure-matching growth, our strategy of controlling the thermodynamics and kinetics offers more degrees of freedom, enabling the chirality of as-grown SWNTs in an array to be tuned, and can also be used to predict the growth conditions required to achieve the desired chiralities.

Magnetophoresis of flexible DNA-based dumbbell structures

NASA Astrophysics Data System (ADS)

Babić, B.; Ghai, R.; Dimitrov, K.

2008-02-01

Controlled movement and manipulation of magnetic micro- and nanostructures using magnetic forces can give rise to important applications in biomedecine, diagnostics, and immunology. We report controlled magnetophoresis and stretching, in aqueous solution, of a DNA-based dumbbell structure containing magnetic and diamagnetic microspheres. The velocity and stretching of the dumbbell were experimentally measured and correlated with a theoretical model based on the forces acting on individual magnetic beads or the entire dumbbell structures. The results show that precise and predictable manipulation of dumbbell structures is achievable and can potentially be applied to immunomagnetic cell separators.

The HART II International Workshop: An Assessment of the State-of-the-Art in Comprehensive Code Prediction

NASA Technical Reports Server (NTRS)

vanderWall, Berend G.; Lim, Joon W.; Smith, Marilyn J.; Jung, Sung N.; Bailly, Joelle; Baeder, James D.; Boyd, D. Douglas, Jr.

2013-01-01

Significant advancements in computational fluid dynamics (CFD) and their coupling with computational structural dynamics (CSD, or comprehensive codes) for rotorcraft applications have been achieved recently. Despite this, CSD codes with their engineering level of modeling the rotor blade dynamics, the unsteady sectional aerodynamics and the vortical wake are still the workhorse for the majority of applications. This is especially true when a large number of parameter variations is to be performed and their impact on performance, structural loads, vibration and noise is to be judged in an approximate yet reliable and as accurate as possible manner. In this article, the capabilities of such codes are evaluated using the HART II International Workshop database, focusing on a typical descent operating condition which includes strong blade-vortex interactions. A companion article addresses the CFD/CSD coupled approach. Three cases are of interest: the baseline case and two cases with 3/rev higher harmonic blade root pitch control (HHC) with different control phases employed. One setting is for minimum blade-vortex interaction noise radiation and the other one for minimum vibration generation. The challenge is to correctly predict the wake physics-especially for the cases with HHC-and all the dynamics, aerodynamics, modifications of the wake structure and the aero-acoustics coming with it. It is observed that the comprehensive codes used today have a surprisingly good predictive capability when they appropriately account for all of the physics involved. The minimum requirements to obtain these results are outlined.

An Assessment of Comprehensive Code Prediction State-of-the-Art Using the HART II International Workshop Data

NASA Technical Reports Server (NTRS)

vanderWall, Berend G.; Lim, Joon W.; Smith, Marilyn J.; Jung, Sung N.; Bailly, Joelle; Baeder, James D.; Boyd, D. Douglas, Jr.

2012-01-01

Despite significant advancements in computational fluid dynamics and their coupling with computational structural dynamics (= CSD, or comprehensive codes) for rotorcraft applications, CSD codes with their engineering level of modeling the rotor blade dynamics, the unsteady sectional aerodynamics and the vortical wake are still the workhorse for the majority of applications. This is especially true when a large number of parameter variations is to be performed and their impact on performance, structural loads, vibration and noise is to be judged in an approximate yet reliable and as accurate as possible manner. In this paper, the capabilities of such codes are evaluated using the HART II Inter- national Workshop data base, focusing on a typical descent operating condition which includes strong blade-vortex interactions. Three cases are of interest: the baseline case and two cases with 3/rev higher harmonic blade root pitch control (HHC) with different control phases employed. One setting is for minimum blade-vortex interaction noise radiation and the other one for minimum vibration generation. The challenge is to correctly predict the wake physics - especially for the cases with HHC - and all the dynamics, aerodynamics, modifications of the wake structure and the aero-acoustics coming with it. It is observed that the comprehensive codes used today have a surprisingly good predictive capability when they appropriately account for all of the physics involved. The minimum requirements to obtain these results are outlined.

Using the Theory of Planned Behavior to predict intention to comply with a food recall message.

PubMed

Freberg, Karen

2013-01-01

The Theory of Planned Behavior (TPB) has provided considerable insight into the public's intention to comply with many different health-related messages, but has not been applied previously to intention to comply with food safety recommendations and recalls ( Hallman & Cuite, 2010 ). Because food recalls can differ from other health messages in their urgency, timing, and cessation, the applicability of the TPB in this domain is unknown. The research reported here attempted to address this gap using a nationally representative consumer panel. Results showed that, consistent with the theory's predictions, attitudes and subjective norms were predictive of the intention to comply with a food recall message, with attitudes having a much greater impact on intent to comply than subjective norms. Perceived behavioral control failed to predict intention to comply. Implications of these results for health public relations and crisis communications and recommendations for future research were discussed.

Genetic Programming as Alternative for Predicting Development Effort of Individual Software Projects

PubMed Central

Chavoya, Arturo; Lopez-Martin, Cuauhtemoc; Andalon-Garcia, Irma R.; Meda-Campaña, M. E.

2012-01-01

Statistical and genetic programming techniques have been used to predict the software development effort of large software projects. In this paper, a genetic programming model was used for predicting the effort required in individually developed projects. Accuracy obtained from a genetic programming model was compared against one generated from the application of a statistical regression model. A sample of 219 projects developed by 71 practitioners was used for generating the two models, whereas another sample of 130 projects developed by 38 practitioners was used for validating them. The models used two kinds of lines of code as well as programming language experience as independent variables. Accuracy results from the model obtained with genetic programming suggest that it could be used to predict the software development effort of individual projects when these projects have been developed in a disciplined manner within a development-controlled environment. PMID:23226305

Predicting game-attending behavior in amateur athletes: the moderating role of intention stability.

PubMed

Lu, Wan Chen; Cheng, Chih-Fu; Chen, Lung Hung

2013-10-01

The theory of planned behavior is a well-established theory in predicting human behavior. However, there is evidence of an inconsistent relationship between intention and behavior. Therefore, the purpose of the current study is to further investigate the gap between intention and behavior. The study proposes intention stability as the moderator. Participants (N = 154, M age = 23 yr., SD = 6.7) were recruited from Internet volleyball forums and local volleyball courts in Taiwan. Multiple hierarchical regression was used to analyze the data. The results indicated that perceived behavioral control significantly predicted game-attending behavior through intention. However, attitude and subjective norms did not significantly predict behavioral intention. In addition, intention stability moderated the relationship between intention and behavior and indicated the relationship between intention and behavior was strong when intention stability was high. On the contrary, when intention stability was low, the relationship between intention and behavior was weak. Implications and applications are discussed.

Streakline-based closed-loop control of a bluff body flow

NASA Astrophysics Data System (ADS)

Roca, Pablo; Cammilleri, Ada; Duriez, Thomas; Mathelin, Lionel; Artana, Guillermo

2014-04-01

A novel closed-loop control methodology is introduced to stabilize a cylinder wake flow based on images of streaklines. Passive scalar tracers are injected upstream the cylinder and their concentration is monitored downstream at certain image sectors of the wake. An AutoRegressive with eXogenous inputs mathematical model is built from these images and a Generalized Predictive Controller algorithm is used to compute the actuation required to stabilize the wake by adding momentum tangentially to the cylinder wall through plasma actuators. The methodology is new and has real-world applications. It is demonstrated on a numerical simulation and the provided results show that good performances are achieved.

Development and demonstration of a flutter-suppression system using active controls. [wind tunnel tests

NASA Technical Reports Server (NTRS)

Sandford, M. C.; Abel, I.; Gray, D. L.

1975-01-01

The application of active control technology to suppress flutter was demonstrated successfully in the transonic dynamics tunnel with a delta-wing model. The model was a simplified version of a proposed supersonic transport wing design. An active flutter suppression method based on an aerodynamic energy criterion was verified by using three different control laws. The first two control laws utilized both leading-edge and trailing-edge active control surfaces, whereas the third control law required only a single trailing-edge active control surface. At a Mach number of 0.9 the experimental results demonstrated increases in the flutter dynamic pressure from 12.5 percent to 30 percent with active controls. Analytical methods were developed to predict both open-loop and closed-loop stability, and the results agreed reasonably well with the experimental results.

The Application of Satellite-Derived, High-Resolution Land Use/Land Cover Data to Improve Urban Air Quality Model Forecasts

NASA Technical Reports Server (NTRS)

Quattrochi, D. A.; Lapenta, W. M.; Crosson, W. L.; Estes, M. G., Jr.; Limaye, A.; Kahn, M.

2006-01-01

Local and state agencies are responsible for developing state implementation plans to meet National Ambient Air Quality Standards. Numerical models used for this purpose simulate the transport and transformation of criteria pollutants and their precursors. The specification of land use/land cover (LULC) plays an important role in controlling modeled surface meteorology and emissions. NASA researchers have worked with partners and Atlanta stakeholders to incorporate an improved high-resolution LULC dataset for the Atlanta area within their modeling system and to assess meteorological and air quality impacts of Urban Heat Island (UHI) mitigation strategies. The new LULC dataset provides a more accurate representation of land use, has the potential to improve model accuracy, and facilitates prediction of LULC changes. Use of the new LULC dataset for two summertime episodes improved meteorological forecasts, with an existing daytime cold bias of approx. equal to 3 C reduced by 30%. Model performance for ozone prediction did not show improvement. In addition, LULC changes due to Atlanta area urbanization were predicted through 2030, for which model simulations predict higher urban air temperatures. The incorporation of UHI mitigation strategies partially offset this warming trend. The data and modeling methods used are generally applicable to other U.S. cities.

Seizure Prediction and its Applications

PubMed Central

Iasemidis, Leon D.

2011-01-01

Epilepsy is characterized by intermittent, paroxysmal, hypersynchronous electrical activity, that may remain localized and/or spread and severely disrupt the brain’s normal multi-task and multi-processing function. Epileptic seizures are the hallmarks of such activity and had been considered unpredictable. It is only recently that research on the dynamics of seizure generation by analysis of the brain’s electrographic activity (EEG) has shed ample light on the predictability of seizures, and illuminated the way to automatic, prospective, long-term prediction of seizures. The ability to issue warnings in real time of impending seizures (e.g., tens of minutes prior to seizure occurrence in the case of focal epilepsy), may lead to novel diagnostic tools and treatments for epilepsy. Applications may range from a simple warning to the patient, in order to avert seizure-associated injuries, to intervention by automatic timely administration of an appropriate stimulus, for example of a chemical nature like an anti-epileptic drug (AED), electromagnetic nature like vagus nerve stimulation (VNS), deep brain stimulation (DBS), transcranial direct current (TDC) or transcranial magnetic stimulation (TMS), and/or of another nature (e.g., ultrasonic, cryogenic, biofeedback operant conditioning). It is thus expected that seizure prediction could readily become an integral part of the treatment of epilepsy through neuromodulation, especially in the new generation of closed-loop seizure control systems. PMID:21939848

In-line and Real-time Monitoring of Resonant Acoustic Mixing by Near-infrared Spectroscopy Combined with Chemometric Technology for Process Analytical Technology Applications in Pharmaceutical Powder Blending Systems.

PubMed

Tanaka, Ryoma; Takahashi, Naoyuki; Nakamura, Yasuaki; Hattori, Yusuke; Ashizawa, Kazuhide; Otsuka, Makoto

2017-01-01

Resonant acoustic ® mixing (RAM) technology is a system that performs high-speed mixing by vibration through the control of acceleration and frequency. In recent years, real-time process monitoring and prediction has become of increasing interest, and process analytical technology (PAT) systems will be increasingly introduced into actual manufacturing processes. This study examined the application of PAT with the combination of RAM, near-infrared spectroscopy, and chemometric technology as a set of PAT tools for introduction into actual pharmaceutical powder blending processes. Content uniformity was based on a robust partial least squares regression (PLSR) model constructed to manage the RAM configuration parameters and the changing concentration of the components. As a result, real-time monitoring may be possible and could be successfully demonstrated for in-line real-time prediction of active pharmaceutical ingredients and other additives using chemometric technology. This system is expected to be applicable to the RAM method for the risk management of quality.

Regulation mechanisms in mixed and pure culture microbial fermentation.

PubMed

Hoelzle, Robert D; Virdis, Bernardino; Batstone, Damien J

2014-11-01

Mixed-culture fermentation is a key central process to enable next generation biofuels and biocommodity production due to economic and process advantages over application of pure cultures. However, a key limitation to the application of mixed-culture fermentation is predicting culture product response, related to metabolic regulation mechanisms. This is also a limitation in pure culture bacterial fermentation. This review evaluates recent literature in both pure and mixed culture studies with a focus on understanding how regulation and signaling mechanisms interact with metabolic routes and activity. In particular, we focus on how microorganisms balance electron sinking while maximizing catabolic energy generation. Analysis of these mechanisms and their effect on metabolism dynamics is absent in current models of mixed-culture fermentation. This limits process prediction and control, which in turn limits industrial application of mixed-culture fermentation. A key mechanism appears to be the role of internal electron mediating cofactors, and related regulatory signaling. This may determine direction of electrons towards either hydrogen or reduced organics as end-products and may form the basis for future mechanistic models. © 2014 Wiley Periodicals, Inc.

Verification and Validation of the BISON Fuel Performance Code for PCMI Applications

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

Gamble, Kyle Allan Lawrence; Novascone, Stephen Rhead; Gardner, Russell James

2016-06-01

BISON is a modern finite element-based nuclear fuel performance code that has been under development at Idaho National Laboratory (INL) since 2009. The code is applicable to both steady and transient fuel behavior and has been used to analyze a variety of fuel forms in 1D spherical, 2D axisymmetric, or 3D geometries. A brief overview of BISON’s computational framework, governing equations, and general material and behavioral models is provided. BISON code and solution verification procedures are described. Validation for application to light water reactor (LWR) PCMI problems is assessed by comparing predicted and measured rod diameter following base irradiation andmore » power ramps. Results indicate a tendency to overpredict clad diameter reduction early in life, when clad creepdown dominates, and more significantly overpredict the diameter increase late in life, when fuel expansion controls the mechanical response. Initial rod diameter comparisons have led to consideration of additional separate effects experiments to better understand and predict clad and fuel mechanical behavior. Results from this study are being used to define priorities for ongoing code development and validation activities.« less

Datamining approaches for modeling tumor control probability.

PubMed

Naqa, Issam El; Deasy, Joseph O; Mu, Yi; Huang, Ellen; Hope, Andrew J; Lindsay, Patricia E; Apte, Aditya; Alaly, James; Bradley, Jeffrey D

2010-11-01

Tumor control probability (TCP) to radiotherapy is determined by complex interactions between tumor biology, tumor microenvironment, radiation dosimetry, and patient-related variables. The complexity of these heterogeneous variable interactions constitutes a challenge for building predictive models for routine clinical practice. We describe a datamining framework that can unravel the higher order relationships among dosimetric dose-volume prognostic variables, interrogate various radiobiological processes, and generalize to unseen data before when applied prospectively. Several datamining approaches are discussed that include dose-volume metrics, equivalent uniform dose, mechanistic Poisson model, and model building methods using statistical regression and machine learning techniques. Institutional datasets of non-small cell lung cancer (NSCLC) patients are used to demonstrate these methods. The performance of the different methods was evaluated using bivariate Spearman rank correlations (rs). Over-fitting was controlled via resampling methods. Using a dataset of 56 patients with primary NCSLC tumors and 23 candidate variables, we estimated GTV volume and V75 to be the best model parameters for predicting TCP using statistical resampling and a logistic model. Using these variables, the support vector machine (SVM) kernel method provided superior performance for TCP prediction with an rs=0.68 on leave-one-out testing compared to logistic regression (rs=0.4), Poisson-based TCP (rs=0.33), and cell kill equivalent uniform dose model (rs=0.17). The prediction of treatment response can be improved by utilizing datamining approaches, which are able to unravel important non-linear complex interactions among model variables and have the capacity to predict on unseen data for prospective clinical applications.

Predicting physical activity and outcome expectations in cancer survivors: an application of Self-Determination Theory.

PubMed

Wilson, Philip M; Blanchard, Chris M; Nehl, Eric; Baker, Frank

2006-07-01

The purpose of this study was to examine the contributions of autonomous and controlled motives drawn from Self-Determination Theory (SDT; Intrinsic Motivation and Self-determination in Human Behavior. Plenum Press: New York, 1985; Handbook of Self-determination Research. University of Rochester Press: New York, 2002) towards predicting physical activity behaviours and outcome expectations in adult cancer survivors. Participants were cancer-survivors (N=220) and a non-cancer comparison cohort (N=220) who completed an adapted version of the Treatment Self-Regulation Questionnaire modified for physical activity behaviour (TSRQ-PA), an assessment of the number of minutes engaged in moderate-to-vigorous physical activity (MVPA) weekly, and the anticipated outcomes expected from regular physical activity (OE). Simultaneous multiple regression analyses indicated that autonomous motives was the dominant predictor of OEs across both cancer and non-cancer cohorts (R(2adj)=0.29-0.43), while MVPA was predicted by autonomous (beta's ranged from 0.21 to 0.34) and controlled (beta's ranged from -0.04 to -0.23) motives after controlling for demographic considerations. Cancer status (cancer versus no cancer) did not moderate the motivation-physical activity relationship. Collectively, these findings suggest that the distinction between autonomous and controlled motives is useful and compliments a growing body of evidence supporting SDT as a framework for understanding motivational processes in physical activity contexts with cancer survivors.

Prediction-Correction Algorithms for Time-Varying Constrained Optimization

DOE PAGES

Simonetto, Andrea; Dall'Anese, Emiliano

2017-07-26

This article develops online algorithms to track solutions of time-varying constrained optimization problems. Particularly, resembling workhorse Kalman filtering-based approaches for dynamical systems, the proposed methods involve prediction-correction steps to provably track the trajectory of the optimal solutions of time-varying convex problems. The merits of existing prediction-correction methods have been shown for unconstrained problems and for setups where computing the inverse of the Hessian of the cost function is computationally affordable. This paper addresses the limitations of existing methods by tackling constrained problems and by designing first-order prediction steps that rely on the Hessian of the cost function (and do notmore » require the computation of its inverse). In addition, the proposed methods are shown to improve the convergence speed of existing prediction-correction methods when applied to unconstrained problems. Numerical simulations corroborate the analytical results and showcase performance and benefits of the proposed algorithms. A realistic application of the proposed method to real-time control of energy resources is presented.« less

Lightweight deformable mirrors for future space telescopes

NASA Astrophysics Data System (ADS)

Patterson, Keith

This thesis presents a concept for ultra-lightweight deformable mirrors based on a thin substrate of optical surface quality coated with continuous active piezopolymer layers that provide modes of actuation and shape correction. This concept eliminates any kind of stiff backing structure for the mirror surface and exploits micro-fabrication technologies to provide a tight integration of the active materials into the mirror structure, to avoid actuator print-through effects. Proof-of-concept, 10-cm-diameter mirrors with a low areal density of about 0.5 kg/m2 have been designed, built and tested to measure their shape-correction performance and verify the models used for design. The low cost manufacturing scheme uses replication techniques, and strives for minimizing residual stresses that deviate the optical figure from the master mandrel. It does not require precision tolerancing, is lightweight, and is therefore potentially scalable to larger diameters for use in large, modular space telescopes. Other potential applications for such a laminate could include ground-based mirrors for solar energy collection, adaptive optics for atmospheric turbulence, laser communications, and other shape control applications. The immediate application for these mirrors is for the Autonomous Assembly and Reconfiguration of a Space Telescope (AAReST) mission, which is a university mission under development by Caltech, the University of Surrey, and JPL. The design concept, fabrication methodology, material behaviors and measurements, mirror modeling, mounting and control electronics design, shape control experiments, predictive performance analysis, and remaining challenges are presented herein. The experiments have validated numerical models of the mirror, and the mirror models have been used within a model of the telescope in order to predict the optical performance. A demonstration of this mirror concept, along with other new telescope technologies, is planned to take place during the AAReST mission.

Application of Solidification Theory to Rapid Solidification Processing

DTIC Science & Technology

1982-09-01

period were achieved in the following areas : Extended Solid Solubilities -- for Produetion of Alloys with New Compositions and Phases o At high growth... Areas where significant improvements In alloy properties can be produced by rapid solidification will be emphasized. Technical Problem and General...focussed on the science underlying areas where Improved materials can be obtained in order to provide such prediction and control. This work is both

Rapid analysis of inner and outer bark composition of southern yellow pine bark from industrial sources

Treesearch

Chi-Leung So; Thomas L. Eberhardt

2006-01-01

Differences in bark chemistry between inner and outer bark are well known and may affect the suitability of various bark supplies for a particular application. Accordingly, there is a need for quality control protocols to assess variability and predict product yields. Southern yellow pine bark samples from two industrial sources were separated into inner and outer bark...

Non-Cognitive Selected Students Do Not Outperform Lottery-Admitted Students in the Pre-Clinical Stage of Medical School

ERIC Educational Resources Information Center

Lucieer, Susanna M.; Stegers-Jager, Karen M.; Rikers, Remy M. J. P.; Themmen, Axel P. N.

2016-01-01

Medical schools all over the world select applicants using non-cognitive and cognitive criteria. The predictive value of these different types of selection criteria has however never been investigated within the same curriculum while using a control group. We therefore set up a study that enabled us to compare the academic performance of three…

Predictive Flow Control to Minimize Convective Time Delays

DTIC Science & Technology

2013-08-19

simulation. The CFO solver used is Cobalt, an unstructured finite-volume code developed for the solution of the compress- ible Navier-Stokes...cell-centered fin ite volume approach applicable to arbitrary cell topologies (e.g, hexahedra, prisms, tetrahedra). The spatial operator uses a Riemann ... solver , least squares gradient calculations using QR factorizati on to provide second order accuracy in space. A point implicit method using

The vibrational properties of the bee-killer imidacloprid insecticide: A molecular description

NASA Astrophysics Data System (ADS)

Moreira, Antônio A. G.; De Lima-Neto, Pedro; Caetano, Ewerton W. S.; Barroso-Neto, Ito L.; Freire, Valder N.

2017-10-01

The chemical imidacloprid belongs to the neonicotinoids insecticide class, widely used for insect pest control mainly for crop protection. However, imidacloprid is a non-selective agrochemical to the insects and it is able to kill the most important pollinators, the bees. The high toxicity of imidacloprid requires controlled release and continuous monitoring. For this purpose, high performance liquid chromatography (HPLC) is usually employed; infrared and Raman spectroscopy, however, are simple and viable techniques that can be adapted to portable devices for field application. In this communication, state-of-the-art quantum level simulations were used to predict the infrared and Raman spectra of the most stable conformer of imidacloprid. Four molecular geometries were investigated in vacuum and solvated within the Density Functional Theory (DFT) approach employing the hybrid meta functional M06-2X and the hybrid functional B3LYP. The M062X/PCM model proved to be the best to predict structural features, while the values of harmonic vibrational frequencies were predicted more accurately using the B3LYP functional.

Electronic Structure Control of Sub-nanometer 1D SnTe via Nanostructuring within Single-Walled Carbon Nanotubes.

PubMed

Vasylenko, Andrij; Marks, Samuel; Wynn, Jamie M; Medeiros, Paulo V C; Ramasse, Quentin M; Morris, Andrew J; Sloan, Jeremy; Quigley, David

2018-05-25

Nanostructuring, e. g., reduction of dimensionality in materials, offers a viable route toward regulation of materials electronic and hence functional properties. Here, we present the extreme case of nanostructuring, exploiting the capillarity of single-walled carbon nanotubes (SWCNTs) for the synthesis of the smallest possible SnTe nanowires with cross sections as thin as a single atom column. We demonstrate that by choosing the appropriate diameter of a template SWCNT, we can manipulate the structure of the quasi-one-dimensional (1D) SnTe to design electronic behavior. From first principles, we predict the structural re-formations that SnTe undergoes in varying encapsulations and confront the prediction with TEM imagery. To further illustrate the control of physical properties by nanostructuring, we study the evolution of transport properties in a homologous series of models of synthesized and isolated SnTe nanowires varying only in morphology and atomic layer thickness. This extreme scaling is predicted to significantly enhance thermoelectric performance of SnTe, offering a prospect for further experimental studies and future applications.

Numerical prediction on the dispersion of pollutant particles

NASA Astrophysics Data System (ADS)

Osman, Kahar; Ali, Zairi; Ubaidullah, S.; Zahid, M. N.

2012-06-01

The increasing concern on air pollution has led people around the world to find more efficient ways to control the problem. Air dispersion modeling is proven to be one of the alternatives that provide economical ways to control the growing threat of air pollution. The objective of this research is to develop a practical numerical algorithm to predict the dispersion of pollutant particles around a specific source of emission. The source selected was a rubber wood manufacturing plant. Gaussian-plume model were used as air dispersion model due to its simplicity and generic application. Results of this study show the concentrations of the pollutant particles on ground level reached approximately 90μg/m3, compared with other software. This value surpasses the limit of 50μg/m3 stipulated by the National Ambient Air Quality Standard (NAAQS) and Recommended Malaysian Guidelines (RMG) set by Environment Department of Malaysia. The results also show high concentration of pollutant particles reading during dru seasons as compared to that of rainy seasons. In general, the developed algorithm is proven to be able to predict particles distribution around emitted source with acceptable accuracy.

Determining the potential productivity of food crops in controlled environments

NASA Technical Reports Server (NTRS)

Bugbee, Bruce

1992-01-01

The quest to determine the maximum potential productivity of food crops is greatly benefitted by crop growth models. Many models have been developed to analyze and predict crop growth in the field, but it is difficult to predict biological responses to stress conditions. Crop growth models for the optimal environments of a Controlled Environment Life Support System (CELSS) can be highly predictive. This paper discusses the application of a crop growth model to CELSS; the model is used to evaluate factors limiting growth. The model separately evaluates the following four physiological processes: absorption of PPF by photosynthetic tissue, carbon fixation (photosynthesis), carbon use (respiration), and carbon partitioning (harvest index). These constituent processes determine potentially achievable productivity. An analysis of each process suggests that low harvest index is the factor most limiting to yield. PPF absorption by plant canopies and respiration efficiency are also of major importance. Research concerning productivity in a CELSS should emphasize: (1) the development of gas exchange techniques to continuously monitor plant growth rates and (2) environmental techniques to reduce plant height in communities.

PREFACE: European Workshop on Advanced Control and Diagnosis

NASA Astrophysics Data System (ADS)

Schulte, Horst; Georg, Sören

2014-12-01

The European Workshop on Advanced Control and Diagnosis is an annual event that has been organised since 2003 by Control Engineering departments of several European universities in Germany, France, the UK, Poland, Italy, Hungary and Denmark. The overall planning of the workshops is conducted by the Intelligent Control and Diagnosis (ICD) steering committee. This year's ACD workshop took place at HTW Berlin (University of Applied Sciences) and was organised by the Control Engineering group of School of Engineering I of HTW Berlin. 38 papers were presented at ACD 2014, with contributions spanning a variety of fields in modern control science: Discrete control, nonlinear control, model predictive control, system identification, fault diagnosis and fault-tolerant control, control applications, applications of fuzzy logic, as well as modelling and simulation, the latter two forming a basis for all tasks in modern control. Three interesting and high-quality plenary lectures were delivered. The first plenary speaker was Wolfgang Weber from Pepperl+Fuchs, a German manufacturer of state-of-the-art industrial sensors and process interfaces. The second and third plenary speakers were two internationally high-ranked researchers in their respective fields, Prof. Didier Theilliol from Université de Lorraine and Prof. Carsten Scherer from Universität Stuttgart. Taken together, the three plenary lectures sought to contribute to closing the gap between theory and applications. On behalf of the whole ACD 2014 organising committee, we would like to thank all those who submitted papers and participated in the workshop. We hope it was a fruitful and memorable event for all. Together we are looking forward to the next ACD workshop in 2015 in Pilsen, Czech Republic. Horst Schulte (General Chair), Sören Georg (Programme Chair)

New Predictive Filters for Compensating the Transport Delay on a Flight Simulator

NASA Technical Reports Server (NTRS)

Guo, Liwen; Cardullo, Frank M.; Houck, Jacob A.; Kelly, Lon C.; Wolters, Thomas E.

2004-01-01

The problems of transport delay in a flight simulator, such as its sources and effects, are reviewed. Then their effects on a pilot-in-the-loop control system are investigated with simulations. Three current prominent delay compensators the lead/lag filter, McFarland filter, and the Sobiski/Cardullo filter were analyzed and compared. This paper introduces two novel delay compensation techniques an adaptive predictor using the Kalman estimator and a state space predictive filter using a reference aerodynamic model. Applications of these two new compensators on recorded data from the NASA Langley Research Center Visual Motion Simulator show that they achieve better compensation over the current ones.

Progress and Challenges in Short to Medium Range Coupled Prediction

NASA Technical Reports Server (NTRS)

Brassington, G. B.; Martin, M. J.; Tolman, H. L.; Akella, Santha; Balmeseda, M.; Chambers, C. R. S.; Cummings, J. A.; Drillet, Y.; Jansen, P. A. E. M.; Laloyaux, P.;

Applications of system identification methods to the prediction of helicopter stability, control and handling characteristics

NASA Technical Reports Server (NTRS)

Padfield, G. D.; Duval, R. K.

1982-01-01

A set of results on rotorcraft system identification is described. Flight measurements collected on an experimental Puma helicopter are reviewed and some notable characteristics highlighted. Following a brief review of previous work in rotorcraft system identification, the results of state estimation and model structure estimation processes applied to the Puma data are presented. The results, which were obtained using NASA developed software, are compared with theoretical predictions of roll, yaw and pitching moment derivatives for a 6 degree of freedom model structure. Anomalies are reported. The theoretical methods used are described. A framework for reduced order modelling is outlined.

Electrical Properties and Power Considerations of a Piezoelectric Actuator

NASA Technical Reports Server (NTRS)

Jordan, T.; Ounaies, Z.; Tripp, J.; Tcheng, P.

1999-01-01

This paper assesses the electrical characteristics of piezoelectric wafers for use in aeronautical applications such as active noise control in aircraft. Determination of capacitive behavior and power consumption is necessary to optimize the system configuration and to design efficient driving electronics. Empirical relations are developed from experimental data to predict the capacitance and loss tangent of a PZT5A ceramic as nonlinear functions of both applied peak voltage and driving frequency. Power consumed by the PZT is the rate of energy required to excite the piezoelectric system along with power dissipated due to dielectric loss and mechanical and structural damping. Overall power consumption is thus quantified as a function of peak applied voltage and driving frequency. It was demonstrated that by incorporating the variation of capacitance and power loss with voltage and frequency, satisfactory estimates of power requirements can be obtained. These relations allow general guidelines in selection and application of piezoelectric actuators and driving electronics for active control applications.

Controlling herding in minority game systems

NASA Astrophysics Data System (ADS)

Zhang, Ji-Qiang; Huang, Zi-Gang; Wu, Zhi-Xi; Su, Riqi; Lai, Ying-Cheng

2016-02-01

Resource allocation takes place in various types of real-world complex systems such as urban traffic, social services institutions, economical and ecosystems. Mathematically, the dynamical process of resource allocation can be modeled as minority games. Spontaneous evolution of the resource allocation dynamics, however, often leads to a harmful herding behavior accompanied by strong fluctuations in which a large majority of agents crowd temporarily for a few resources, leaving many others unused. Developing effective control methods to suppress and eliminate herding is an important but open problem. Here we develop a pinning control method, that the fluctuations of the system consist of intrinsic and systematic components allows us to design a control scheme with separated control variables. A striking finding is the universal existence of an optimal pinning fraction to minimize the variance of the system, regardless of the pinning patterns and the network topology. We carry out a generally applicable theory to explain the emergence of optimal pinning and to predict the dependence of the optimal pinning fraction on the network topology. Our work represents a general framework to deal with the broader problem of controlling collective dynamics in complex systems with potential applications in social, economical and political systems.

Flyback CCM inverter for AC module applications: iterative learning control and convergence analysis

NASA Astrophysics Data System (ADS)

Lee, Sung-Ho; Kim, Minsung

2017-12-01

This paper presents an iterative learning controller (ILC) for an interleaved flyback inverter operating in continuous conduction mode (CCM). The flyback CCM inverter features small output ripple current, high efficiency, and low cost, and hence it is well suited for photovoltaic power applications. However, it exhibits the non-minimum phase behaviour, because its transfer function from control duty to output current has the right-half-plane (RHP) zero. Moreover, the flyback CCM inverter suffers from the time-varying grid voltage disturbance. Thus, conventional control scheme results in inaccurate output tracking. To overcome these problems, the ILC is first developed and applied to the flyback inverter operating in CCM. The ILC makes use of both predictive and current learning terms which help the system output to converge to the reference trajectory. We take into account the nonlinear averaged model and use it to construct the proposed controller. It is proven that the system output globally converges to the reference trajectory in the absence of state disturbances, output noises, or initial state errors. Numerical simulations are performed to validate the proposed control scheme, and experiments using 400-W AC module prototype are carried out to demonstrate its practical feasibility.

Reverse iontophoresis of urea in health and chronic kidney disease: a potential diagnostic and monitoring tool?

PubMed Central

Ebah, Leonard M; Read, Ian; Sayce, Andrew; Morgan, Jane; Chaloner, Christopher; Brenchley, Paul; Mitra, Sandip

2012-01-01

Background Patients with chronic kidney disease (CKD) need regular monitoring, usually by blood urea and creatinine measurements, needing venepuncture, frequent attendances and a healthcare professional, with significant inconvenience. Noninvasive monitoring will potentially simplify and improve monitoring. We tested the potential of transdermal reverse iontophoresis of urea in patients with CKD and healthy controls. Methods Using a MIC 2® Iontophoresis Controller, reverse iontophoresis was applied on the forearm of five healthy subjects (controls) and 18 patients with CKD for 3–5 h. Urea extracted at the cathode was measured and compared with plasma urea. Results Reverse iontophoresis at 250 μA was entirely safe for the duration. Cathodal buffer urea linearly correlated with plasma urea after 2 h (r = 0·82, P < 0·0001), to 3·5 h current application (r = 0·89, P = 0·007). The linear equations y = 0·24x + 1 and y = 0·21x + 4·63 predicted plasma urea (y) from cathodal urea after 2 and 3 h, respectively. Cathodal urea concentration in controls was significantly lower than in patients with CKD after a minimum current application of 2 h (P < 0·0001), with the separation between the two groups becoming more apparent with longer application (P = 0·003). A cathodal urea cut-off of 30 μM gave a sensitivity of 83·3% and positive predictive value of 87% CKD. During haemodialysis, the fall in cathodal urea was able to track that of blood urea. Conclusion Reverse iontophoresis is safe, can potentially discriminate patients with CKD and healthy subjects and is able to track blood urea changes on dialysis. Further development of the technology for routine use can lead to an exciting opportunity for its use in diagnostics and monitoring. PMID:22409780

Accurate prediction of cardiorespiratory fitness using cycle ergometry in minimally disabled persons with relapsing-remitting multiple sclerosis.

PubMed

Motl, Robert W; Fernhall, Bo

2012-03-01

To examine the accuracy of predicting peak oxygen consumption (VO(2peak)) primarily from peak work rate (WR(peak)) recorded during a maximal, incremental exercise test on a cycle ergometer among persons with relapsing-remitting multiple sclerosis (RRMS) who had minimal disability. Cross-sectional study. Clinical research laboratory. Women with RRMS (n=32) and sex-, age-, height-, and weight-matched healthy controls (n=16) completed an incremental exercise test on a cycle ergometer to volitional termination. Not applicable. Measured and predicted VO(2peak) and WR(peak). There were strong, statistically significant associations between measured and predicted VO(2peak) in the overall sample (R(2)=.89, standard error of the estimate=127.4 mL/min) and subsamples with (R(2)=.89, standard error of the estimate=131.3 mL/min) and without (R(2)=.85, standard error of the estimate=126.8 mL/min) multiple sclerosis (MS) based on the linear regression analyses. Based on the 95% confidence limits for worst-case errors, the equation predicted VO(2peak) within 10% of its true value in 95 of every 100 subjects with MS. Peak VO(2) can be accurately predicted in persons with RRMS who have minimal disability as it is in controls by using established equations and WR(peak) recorded from a maximal, incremental exercise test on a cycle ergometer. Copyright © 2012 American Congress of Rehabilitation Medicine. Published by Elsevier Inc. All rights reserved.

Perspectives for geographically oriented management of fusarium mycotoxins in the cereal supply chain.

PubMed

van der Fels-Klerx, H J; Booij, C J H

2010-06-01

This article provides an overview of available systems for management of Fusarium mycotoxins in the cereal grain supply chain, with an emphasis on the use of predictive mathematical modeling. From the state of the art, it proposes future developments in modeling and management and their challenges. Mycotoxin contamination in cereal grain-based feed and food products is currently managed and controlled by good agricultural practices, good manufacturing practices, hazard analysis critical control points, and by checking and more recently by notification systems and predictive mathematical models. Most of the predictive models for Fusarium mycotoxins in cereal grains focus on deoxynivalenol in wheat and aim to help growers make decisions about the application of fungicides during cultivation. Future developments in managing Fusarium mycotoxins should include the linkage between predictive mathematical models and geographical information systems, resulting into region-specific predictions for mycotoxin occurrence. The envisioned geographically oriented decision support system may incorporate various underlying models for specific users' demands and regions and various related databases to feed the particular models with (geographically oriented) input data. Depending on the user requirements, the system selects the best fitting model and available input information. Future research areas include organizing data management in the cereal grain supply chain, developing predictive models for other stakeholders (taking into account the period up to harvest), other Fusarium mycotoxins, and cereal grain types, and understanding the underlying effects of the regional component in the models.

Microbial burden prediction model for unmanned planetary spacecraft

NASA Technical Reports Server (NTRS)

Hoffman, A. R.; Winterburn, D. A.

1972-01-01

The technical development of a computer program for predicting microbial burden on unmanned planetary spacecraft is outlined. The discussion includes the derivation of the basic analytical equations, the selection of a method for handling several random variables, the macrologic of the computer programs and the validation and verification of the model. The prediction model was developed to (1) supplement the biological assays of a spacecraft by simulating the microbial accretion during periods when assays are not taken; (2) minimize the necessity for a large number of microbiological assays; and (3) predict the microbial loading on a lander immediately prior to sterilization and other non-lander equipment prior to launch. It is shown that these purposes not only were achieved but also that the prediction results compare favorably to the estimates derived from the direct assays. The computer program can be applied not only as a prediction instrument but also as a management and control tool. The basic logic of the model is shown to have possible applicability to other sequential flow processes, such as food processing.

Predicting sugar consumption: Application of an integrated dual-process, dual-phase model.

PubMed

Hagger, Martin S; Trost, Nadine; Keech, Jacob J; Chan, Derwin K C; Hamilton, Kyra

2017-09-01

Excess consumption of added dietary sugars is related to multiple metabolic problems and adverse health conditions. Identifying the modifiable social cognitive and motivational constructs that predict sugar consumption is important to inform behavioral interventions aimed at reducing sugar intake. We tested the efficacy of an integrated dual-process, dual-phase model derived from multiple theories to predict sugar consumption. Using a prospective design, university students (N = 90) completed initial measures of the reflective (autonomous and controlled motivation, intentions, attitudes, subjective norm, perceived behavioral control), impulsive (implicit attitudes), volitional (action and coping planning), and behavioral (past sugar consumption) components of the proposed model. Self-reported sugar consumption was measured two weeks later. A structural equation model revealed that intentions, implicit attitudes, and, indirectly, autonomous motivation to reduce sugar consumption had small, significant effects on sugar consumption. Attitudes, subjective norm, and, indirectly, autonomous motivation to reduce sugar consumption predicted intentions. There were no effects of the planning constructs. Model effects were independent of the effects of past sugar consumption. The model identified the relative contribution of reflective and impulsive components in predicting sugar consumption. Given the prominent role of the impulsive component, interventions that assist individuals in managing cues-to-action and behavioral monitoring are likely to be effective in regulating sugar consumption. Copyright © 2017 Elsevier Ltd. All rights reserved.

Design of optimal hyperthermia protocols for prostate cancer by controlling HSP expression through computer modeling (Invited Paper)

NASA Astrophysics Data System (ADS)

Rylander, Marissa N.; Feng, Yusheng; Diller, Kenneth; Bass, J.

2005-04-01

Heat shock proteins (HSP) are critical components of a complex defense mechanism essential for preserving cell survival under adverse environmental conditions. It is inevitable that hyperthermia will enhance tumor tissue viability, due to HSP expression in regions where temperatures are insufficient to coagulate proteins, and would likely increase the probability of cancer recurrence. Although hyperthermia therapy is commonly used in conjunction with radiotherapy, chemotherapy, and gene therapy to increase therapeutic effectiveness, the efficacy of these therapies can be substantially hindered due to HSP expression when hyperthermia is applied prior to these procedures. Therefore, in planning hyperthermia protocols, prediction of the HSP response of the tumor must be incorporated into the treatment plan to optimize the thermal dose delivery and permit prediction of overall tissue response. In this paper, we present a highly accurate, adaptive, finite element tumor model capable of predicting the HSP expression distribution and tissue damage region based on measured cellular data when hyperthermia protocols are specified. Cubic spline representations of HSP27 and HSP70, and Arrhenius damage models were integrated into the finite element model to enable prediction of the HSP expression and damage distribution in the tissue following laser heating. Application of the model can enable optimized treatment planning by controlling of the tissue response to therapy based on accurate prediction of the HSP expression and cell damage distribution.

Preliminary Application of WCX Magnetic Bead-Based Matrix-Assisted Laser Desorption Ionization Time-of-Flight Mass Spectrometry in Analyzing the Urine of Renal Clear Cell Carcinoma.

PubMed

Dong, De-Xin; Ji, Zhi-Gang; Li, Han-Zhong; Yan, Wei-Gang; Zhang, Yu-Shi

2017-12-30

Objective To evaluate the application of weak cation exchange (WCX) magnetic bead-based Matrix-Assisted Laser Desorption Ionization Time-of-Flight Mass Spectrometry (MALDI-TOF MS) in detecting differentially expressed proteins in the urine of renal clear cell carcinoma (RCCC) and its value in the early diagnosis of RCCC.Methods Eleven newly diagnosed patients (10 males and 1 female, aged 46-78, mean 63 years) of renal clear cell carcinoma by biopsy and 10 healthy volunteers (all males, aged 25-32, mean 29.7 years) were enrolled in this study. Urine samples of the RCCC patients and healthy controls were collected in the morning. Weak cation exchange (WCX) bead-based MALDI-TOF MS technique was applied in detecting differential protein peaks in the urine of RCCC. ClinProTools2.2 software was utilized to determine the characteristic proteins in the urine of RCCC patients for the predictive model of RCCC. Results The technique identified 160 protein peaks in the urine that were different between RCCC patients and health controls; and among them, there was one peak (molecular weight of 2221.71 Da) with statistical significance (P=0.0304). With genetic algorithms and the support vector machine, we screened out 13 characteristic protein peaks for the predictive model. Conclusions The application of WCX magnetic bead-based MALDI-TOF MS in detecting differentially expressed proteins in urine may have potential value for the early diagnosis of RCCC.

ERPs and Psychopathology. I. Behavioral process issues.

PubMed

Roth, W T; Tecce, J J; Pfefferbaum, A; Rosenbloom, M; Callaway, E

1984-01-01

The clinical study of ERPs has an inherent defect--a self-selection of clinical populations that hampers equating of clinically defined groups on factors extraneous to the independent variables. Such ex post facto studies increase the likelihood of confounding variables in the interpretation of findings. Hence, the development of lawful relationships between clinical variables and ERPs is impeded and the fulfillment of description, explanation, prediction, and control in brain science is thwarted. Proper methodologies and theory development can increase the likelihood of establishing these lawful relationships. One methodology of potential value in the clinical application of ERPs, particularly in studies of aging, is that of divided attention. Two promising theoretical developments in the understanding of brain functioning and aging are the distraction-arousal hypothesis and the controlled-automatic attention model. The evaluation of ERPs in the study of brain-behavior relations in clinical populations might be facilitated by the differentiation of concurrent, predictive, content, and construct validities.

Payload/orbiter contamination control requirement study: Spacelab configuration contamination study

NASA Technical Reports Server (NTRS)

Bareiss, L. E.; Hetrick, M. A.; Ress, E. B.; Strange, D. A.

1976-01-01

The assessment of the Spacelab carrier induced contaminant environment was continued, and the ability of Spacelab to meet established contamination control criteria for the space transportation system program was determined. The primary areas considered included: (1) updating, refining, and improving the Spacelab contamination computer model and contamination analysis methodology, (2) establishing the resulting adjusted induced environment predictions for comparison with the applicable criteria, (3) determining the Spacelab design and operational requirements necessary to meet the criteria, (4) conducting mission feasibility analyses of the combined Spacelab/Orbiter contaminant environment for specific proposed mission and payload mixes, and (5) establishing a preliminary Spacelab mission support plan as well as model interface requirements; A summary of those activities conducted to date with respect to the modelling, analysis, and predictions of the induced environment, including any modifications in approach or methodology utilized in the contamination assessment of the Spacelab carrier, was presented.

Amnesic patients show superior generalization in category learning.

PubMed

O'Connell, Garret; Myers, Catherine E; Hopkins, Ramona O; McLaren, R P; Gluck, Mark A; Wills, Andy J

2016-11-01

Generalization is the application of existing knowledge to novel situations. Questions remain about the precise role of the hippocampus in this facet of learning, but a connectionist model by Gluck and Myers (1993) predicts that generalization should be enhanced following hippocampal damage. In a two-category learning task, a group of amnesic patients (n = 9) learned the training items to a similar level of accuracy as matched controls (n = 9). Both groups then classified new items at various levels of distortion. The amnesic group showed significantly more accurate generalization to high-distortion novel items, a difference also present compared to a larger group of unmatched controls (n = 33). The model prediction of a broadening of generalization gradients in amnesia, at least for items near category boundaries, was supported by the results. Our study shows for the first time that amnesia can sometimes improve generalization. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

Artificial neural network study on organ-targeting peptides

NASA Astrophysics Data System (ADS)

Jung, Eunkyoung; Kim, Junhyoung; Choi, Seung-Hoon; Kim, Minkyoung; Rhee, Hokyoung; Shin, Jae-Min; Choi, Kihang; Kang, Sang-Kee; Lee, Nam Kyung; Choi, Yun-Jaie; Jung, Dong Hyun

2010-01-01

We report a new approach to studying organ targeting of peptides on the basis of peptide sequence information. The positive control data sets consist of organ-targeting peptide sequences identified by the peroral phage-display technique for four organs, and the negative control data are prepared from random sequences. The capacity of our models to make appropriate predictions is validated by statistical indicators including sensitivity, specificity, enrichment curve, and the area under the receiver operating characteristic (ROC) curve (the ROC score). VHSE descriptor produces statistically significant training models and the models with simple neural network architectures show slightly greater predictive power than those with complex ones. The training and test set statistics indicate that our models could discriminate between organ-targeting and random sequences. We anticipate that our models will be applicable to the selection of organ-targeting peptides for generating peptide drugs or peptidomimetics.

Numerical Analysis of the Cavity Flow subjected to Passive Controls Techniques

NASA Astrophysics Data System (ADS)

Melih Guleren, Kursad; Turk, Seyfettin; Mirza Demircan, Osman; Demir, Oguzhan

2018-03-01

Open-source flow solvers are getting more and more popular for the analysis of challenging flow problems in aeronautical and mechanical engineering applications. They are offered under the GNU General Public License and can be run, examined, shared and modified according to user’s requirements. SU2 and OpenFOAM are the two most popular open-source solvers in Computational Fluid Dynamics (CFD) community. In the present study, some passive control methods on the high-speed cavity flows are numerically simulated using these open-source flow solvers along with one commercial flow solver called ANSYS/Fluent. The results are compared with the available experimental data. The solver SU2 are seen to predict satisfactory the mean streamline velocity but not turbulent kinetic energy and overall averaged sound pressure level (OASPL). Whereas OpenFOAM predicts all these parameters nearly as the same levels of ANSYS/Fluent.

Hygienic food handling behaviours. An application of the Theory of Planned Behaviour.

PubMed

Mullan, Barbara A; Wong, Cara L

2009-06-01

It is estimated that 5.4 million Australians get sick annually from eating contaminated food and that up to 20% of this illness results from food handling behaviour. A study was undertaken to investigate the efficacy of the Theory of Planned Behaviour (TPB) including past behaviour in predicting safe food handling intention and behaviour. One hundred and nine participants completed questionnaires regarding their attitudes, perceived behavioural control (PBC), subjective norm, intentions and past behaviour. Behaviour was measured 4 weeks later. The TPB predicted a high proportion of variance in both intentions and behaviour, and past behaviour/habit was found to be the strongest predictor of behaviour. The results of the present study suggest interventions aimed at increasing safe food handling intentions should focus on the impact of normative influences and perceptions of control over their food handling environment; whereas interventions to change actual behaviour should attempt to increase hygienic food handling as a habitual behaviour.

Near-field noise prediction for aircraft in cruising flight: Methods manual. [laminar flow control noise effects analysis

NASA Technical Reports Server (NTRS)

Tibbetts, J. G.

1979-01-01

Methods for predicting noise at any point on an aircraft while the aircraft is in a cruise flight regime are presented. Developed for use in laminar flow control (LFC) noise effects analyses, they can be used in any case where aircraft generated noise needs to be evaluated at a location on an aircraft while under high altitude, high speed conditions. For each noise source applicable to the LFC problem, a noise computational procedure is given in algorithm format, suitable for computerization. Three categories of noise sources are covered: (1) propulsion system, (2) airframe, and (3) LFC suction system. In addition, procedures are given for noise modifications due to source soundproofing and the shielding effects of the aircraft structure wherever needed. Sample cases, for each of the individual noise source procedures, are provided to familiarize the user with typical input and computed data.

Background Noise Analysis in a Few-Photon-Level Qubit Memory

NASA Astrophysics Data System (ADS)

Mittiga, Thomas; Kupchak, Connor; Jordaan, Bertus; Namazi, Mehdi; Nolleke, Christian; Figeroa, Eden

2014-05-01

We have developed an Electromagnetically Induced Transparency based polarization qubit memory. The device is composed of a dual-rail probe field polarization setup colinear with an intense control field to store and retrieve any arbitrary polarization state by addressing a Λ-type energy level scheme in a 87Rb vapor cell. To achieve a signal-to-background ratio at the few photon level sufficient for polarization tomography of the retrieved state, the intense control field is filtered out through an etalon filtrating system. We have developed an analytical model predicting the influence of the signal-to-background ratio on the fidelities and compared it to experimental data. Experimentally measured global fidelities have been found to follow closely the theoretical prediction as signal-to-background decreases. These results suggest the plausibility of employing room temperature memories to store photonic qubits at the single photon level and for future applications in long distance quantum communication schemes.

Vulnerability of recently recharged groundwater in principal aquifers of the United States to nitrate contamination

USGS Publications Warehouse

Gurdak, Jason J.; Qi, Sharon L.

2012-01-01

Recently recharged water (defined here as <60 years old) is generally the most vulnerable part of a groundwater resource to nonpoint-source nitrate contamination. Understanding at the appropriate scale the interactions of natural and anthropogenic controlling factors that influence nitrate occurrence in recently recharged groundwater is critical to support best management and policy decisions that are often made at the aquifer to subaquifer scale. New logistic regression models were developed using data from the U.S. Geological Survey's National Water-Quality Assessment (NAWQA) program and National Water Information System for 17 principal aquifers of the U.S. to identify important source, transport, and attenuation factors that control nonpoint source nitrate concentrations greater than relative background levels in recently recharged groundwater and were used to predict the probability of detecting elevated nitrate in areas beyond the sampling network. Results indicate that dissolved oxygen, crops and irrigated cropland, fertilizer application, seasonally high water table, and soil properties that affect infiltration and denitrification are among the most important factors in predicting elevated nitrate concentrations. Important differences in controlling factors and spatial predictions were identified in the principal aquifer and national-scale models and support the conclusion that similar spatial scales are needed between informed groundwater management and model development.

2-D Circulation Control Airfoil Benchmark Experiments Intended for CFD Code Validation

NASA Technical Reports Server (NTRS)

Englar, Robert J.; Jones, Gregory S.; Allan, Brian G.; Lin, Johb C.

2009-01-01

A current NASA Research Announcement (NRA) project being conducted by Georgia Tech Research Institute (GTRI) personnel and NASA collaborators includes the development of Circulation Control (CC) blown airfoils to improve subsonic aircraft high-lift and cruise performance. The emphasis of this program is the development of CC active flow control concepts for both high-lift augmentation, drag control, and cruise efficiency. A collaboration in this project includes work by NASA research engineers, whereas CFD validation and flow physics experimental research are part of NASA s systematic approach to developing design and optimization tools for CC applications to fixed-wing aircraft. The design space for CESTOL type aircraft is focusing on geometries that depend on advanced flow control technologies that include Circulation Control aerodynamics. The ability to consistently predict advanced aircraft performance requires improvements in design tools to include these advanced concepts. Validation of these tools will be based on experimental methods applied to complex flows that go beyond conventional aircraft modeling techniques. This paper focuses on recent/ongoing benchmark high-lift experiments and CFD efforts intended to provide 2-D CFD validation data sets related to NASA s Cruise Efficient Short Take Off and Landing (CESTOL) study. Both the experimental data and related CFD predictions are discussed.

Advective transport in heterogeneous aquifers: Are proxy models predictive?

NASA Astrophysics Data System (ADS)

Fiori, A.; Zarlenga, A.; Gotovac, H.; Jankovic, I.; Volpi, E.; Cvetkovic, V.; Dagan, G.

2015-12-01

We examine the prediction capability of two approximate models (Multi-Rate Mass Transfer (MRMT) and Continuous Time Random Walk (CTRW)) of non-Fickian transport, by comparison with accurate 2-D and 3-D numerical simulations. Both nonlocal in time approaches circumvent the need to solve the flow and transport equations by using proxy models to advection, providing the breakthrough curves (BTC) at control planes at any x, depending on a vector of five unknown parameters. Although underlain by different mechanisms, the two models have an identical structure in the Laplace Transform domain and have the Markovian property of independent transitions. We show that also the numerical BTCs enjoy the Markovian property. Following the procedure recommended in the literature, along a practitioner perspective, we first calibrate the parameters values by a best fit with the numerical BTC at a control plane at x1, close to the injection plane, and subsequently use it for prediction at further control planes for a few values of σY2≤8. Due to a similar structure and Markovian property, the two methods perform equally well in matching the numerical BTC. The identified parameters are generally not unique, making their identification somewhat arbitrary. The inverse Gaussian model and the recently developed Multi-Indicator Model (MIM), which does not require any fitting as it relates the BTC to the permeability structure, are also discussed. The application of the proxy models for prediction requires carrying out transport field tests of large plumes for a long duration.

Demand theory of gene regulation. II. Quantitative application to the lactose and maltose operons of Escherichia coli.

PubMed Central

Savageau, M A

1998-01-01

Induction of gene expression can be accomplished either by removing a restraining element (negative mode of control) or by providing a stimulatory element (positive mode of control). According to the demand theory of gene regulation, which was first presented in qualitative form in the 1970s, the negative mode will be selected for the control of a gene whose function is in low demand in the organism's natural environment, whereas the positive mode will be selected for the control of a gene whose function is in high demand. This theory has now been further developed in a quantitative form that reveals the importance of two key parameters: cycle time C, which is the average time for a gene to complete an ON/OFF cycle, and demand D, which is the fraction of the cycle time that the gene is ON. Here we estimate nominal values for the relevant mutation rates and growth rates and apply the quantitative demand theory to the lactose and maltose operons of Escherichia coli. The results define regions of the C vs. D plot within which selection for the wild-type regulatory mechanisms is realizable, and these in turn provide the first estimates for the minimum and maximum values of demand that are required for selection of the positive and negative modes of gene control found in these systems. The ratio of mutation rate to selection coefficient is the most relevant determinant of the realizable region for selection, and the most influential parameter is the selection coefficient that reflects the reduction in growth rate when there is superfluous expression of a gene. The quantitative theory predicts the rate and extent of selection for each mode of control. It also predicts three critical values for the cycle time. The predicted maximum value for the cycle time C is consistent with the lifetime of the host. The predicted minimum value for C is consistent with the time for transit through the intestinal tract without colonization. Finally, the theory predicts an optimum value of C that is in agreement with the observed frequency for E. coli colonizing the human intestinal tract. PMID:9691028

Computing exact bundle compliance control charts via probability generating functions.

PubMed

Chen, Binchao; Matis, Timothy; Benneyan, James

2016-06-01

Compliance to evidenced-base practices, individually and in 'bundles', remains an important focus of healthcare quality improvement for many clinical conditions. The exact probability distribution of composite bundle compliance measures used to develop corresponding control charts and other statistical tests is based on a fairly large convolution whose direct calculation can be computationally prohibitive. Various series expansions and other approximation approaches have been proposed, each with computational and accuracy tradeoffs, especially in the tails. This same probability distribution also arises in other important healthcare applications, such as for risk-adjusted outcomes and bed demand prediction, with the same computational difficulties. As an alternative, we use probability generating functions to rapidly obtain exact results and illustrate the improved accuracy and detection over other methods. Numerical testing across a wide range of applications demonstrates the computational efficiency and accuracy of this approach.

Giant Faraday Rotation of High-Order Plasmonic Modes in Graphene-Covered Nanowires.

PubMed

Kuzmin, Dmitry A; Bychkov, Igor V; Shavrov, Vladimir G; Temnov, Vasily V

2016-07-13

Plasmonic Faraday rotation in nanowires manifests itself in the rotation of the spatial intensity distribution of high-order surface plasmon polariton (SPP) modes around the nanowire axis. Here we predict theoretically the giant Faraday rotation for SPPs propagating on graphene-coated magneto-optically active nanowires. Upon the reversal of the external magnetic field pointing along the nanowire axis some high-order plasmonic modes may be rotated by up to ∼100° on the length scale of about 500 nm at mid-infrared frequencies. Tuning the carrier concentration in graphene by chemical doping or gate voltage allows for controlling SPP-properties and notably the rotation angle of high-order azimuthal modes. Our results open the door to novel plasmonic applications ranging from nanowire-based Faraday isolators to the magnetic control in quantum-optical applications.

Charge transfer in ultracold gases via Feshbach resonances

NASA Astrophysics Data System (ADS)

Gacesa, Marko; Côté, Robin

2017-06-01

We investigate the prospects of using magnetic Feshbach resonance to control charge exchange in ultracold collisions of heteroisotopic combinations of atoms and ions of the same element. The proposed treatment, readily applicable to alkali or alkaline-earth metals, is illustrated on cold collisions of +9Be and 10Be. Feshbach resonances are characterized by quantum scattering calculations in a coupled-channel formalism that includes non-Born-Oppenheimer terms originating from the nuclear kinetic operator. Near a resonance predicted at 322 G, we find the charge exchange rate coefficient to rise from practically zero to values greater than 10-12cm3 /s. Our results suggest controllable charge exchange processes between different isotopes of suitable atom-ion pairs, with potential applications to quantum systems engineered to study charge diffusion in trapped cold atom-ion mixtures and emulate many-body physics.

Optimal control of photoelectron emission by realistic waveforms

NASA Astrophysics Data System (ADS)

Solanpää, J.; Ciappina, M. F.; Räsänen, E.

2017-09-01

Recent experimental techniques in multicolor waveform synthesis allow the temporal shaping of strong femtosecond laser pulses with applications in the control of quantum mechanical processes in atoms, molecules, and nanostructures. Prediction of the shapes of the optimal waveforms can be done computationally using quantum optimal control theory. In this work we demonstrate the control of above-threshold photoemission of one-dimensional hydrogen model with pulses feasible for experimental waveform synthesis. By mixing different spectral channels and thus lowering the intensity requirements for individual channels, the resulting optimal pulses can extend the cutoff energies by at least up to 50% and bring up the electron yield by several orders of magnitude. Insights into the electron dynamics for optimized photoelectron emission are obtained with a semiclassical two-step model.

Fiber Optic Wing Shape Sensing on NASA's Ikhana UAV

NASA Technical Reports Server (NTRS)

Richards, Lance; Parker, Allen R.; Ko, William L.; Piazza, Anthony

2008-01-01

This document discusses the development of fiber optic wing shape sensing on NASA's Ikhana vehicle. The Dryden Flight Research Center's Aerostructures Branch initiated fiber-optic instrumentation development efforts in the mid-1990s. Motivated by a failure to control wing dihedral resulting in a mishap with the Helios aircraft, new wing displacement techniques were developed. Research objectives for Ikhana included validating fiber optic sensor measurements and real-time wing shape sensing predictions; the validation of fiber optic mathematical models and design tools; assessing technical viability and, if applicable, developing methodology and approaches to incorporate wing shape measurements within the vehicle flight control system; and, developing and flight validating approaches to perform active wing shape control using conventional control surfaces and active material concepts.

Optimization of Control Strategies for Non-Domiciliated Triatoma dimidiata, Chagas Disease Vector in the Yucatán Peninsula, Mexico

PubMed Central

Barbu, Corentin; Dumonteil, Eric; Gourbière, Sébastien

2009-01-01

Background Chagas disease is the most important vector-borne disease in Latin America. Regional initiatives based on residual insecticide spraying have successfully controlled domiciliated vectors in many regions. Non-domiciliated vectors remain responsible for a significant transmission risk, and their control is now a key challenge for disease control. Methodology/Principal Findings A mathematical model was developed to predict the temporal variations in abundance of non-domiciliated vectors inside houses. Demographic parameters were estimated by fitting the model to two years of field data from the Yucatan peninsula, Mexico. The predictive value of the model was tested on an independent data set before simulations examined the efficacy of control strategies based on residual insecticide spraying, insect screens, and bednets. The model accurately fitted and predicted field data in the absence and presence of insecticide spraying. Pyrethroid spraying was found effective when 50 mg/m2 were applied yearly within a two-month period matching the immigration season. The >80% reduction in bug abundance was not improved by larger doses or more frequent interventions, and it decreased drastically for different timing and lower frequencies of intervention. Alternatively, the use of insect screens consistently reduced bug abundance proportionally to the reduction of the vector immigration rate. Conclusion/Significance Control of non-domiciliated vectors can hardly be achieved by insecticide spraying, because it would require yearly application and an accurate understanding of the temporal pattern of immigration. Insect screens appear to offer an effective and sustainable alternative, which may be part of multi-disease interventions for the integrated control of neglected vector-borne diseases. PMID:19365542

Geomorphically based predictive mapping of soil thickness in upland watersheds

NASA Astrophysics Data System (ADS)

Pelletier, Jon D.; Rasmussen, Craig

2009-09-01

The hydrologic response of upland watersheds is strongly controlled by soil (regolith) thickness. Despite the need to quantify soil thickness for input into hydrologic models, there is currently no widely used, geomorphically based method for doing so. In this paper we describe and illustrate a new method for predictive mapping of soil thicknesses using high-resolution topographic data, numerical modeling, and field-based calibration. The model framework works directly with input digital elevation model data to predict soil thicknesses assuming a long-term balance between soil production and erosion. Erosion rates in the model are quantified using one of three geomorphically based sediment transport models: nonlinear slope-dependent transport, nonlinear area- and slope-dependent transport, and nonlinear depth- and slope-dependent transport. The model balances soil production and erosion locally to predict a family of solutions corresponding to a range of values of two unconstrained model parameters. A small number of field-based soil thickness measurements can then be used to calibrate the local value of those unconstrained parameters, thereby constraining which solution is applicable at a particular study site. As an illustration, the model is used to predictively map soil thicknesses in two small, ˜0.1 km2, drainage basins in the Marshall Gulch watershed, a semiarid drainage basin in the Santa Catalina Mountains of Pima County, Arizona. Field observations and calibration data indicate that the nonlinear depth- and slope-dependent sediment transport model is the most appropriate transport model for this site. The resulting framework provides a generally applicable, geomorphically based tool for predictive mapping of soil thickness using high-resolution topographic data sets.

Tunable Optical Filters for Space Exploration

NASA Technical Reports Server (NTRS)

Crandall, Charles; Clark, Natalie; Davis, Patricia P.

2007-01-01

Spectrally tunable liquid crystal filters provide numerous advantages and several challenges in space applications. We discuss the tradeoffs in design elements for tunable liquid crystal birefringent filters with special consideration required for space exploration applications. In this paper we present a summary of our development of tunable filters for NASA space exploration. In particular we discuss the application of tunable liquid crystals in guidance navigation and control in space exploration programs. We present a summary of design considerations for improving speed, field of view, transmission of liquid crystal tunable filters for space exploration. In conclusion, the current state of the art of several NASA LaRC assembled filters is presented and their performance compared to the predicted spectra using our PolarTools modeling software.

Display/control requirements for automated VTOL aircraft

NASA Technical Reports Server (NTRS)

Hoffman, W. C.; Kleinman, D. L.; Young, L. R.

1976-01-01

A systematic design methodology for pilot displays in advanced commercial VTOL aircraft was developed and refined. The analyst is provided with a step-by-step procedure for conducting conceptual display/control configurations evaluations for simultaneous monitoring and control pilot tasks. The approach consists of three phases: formulation of information requirements, configuration evaluation, and system selection. Both the monitoring and control performance models are based upon the optimal control model of the human operator. Extensions to the conventional optimal control model required in the display design methodology include explicit optimization of control/monitoring attention; simultaneous monitoring and control performance predictions; and indifference threshold effects. The methodology was applied to NASA's experimental CH-47 helicopter in support of the VALT program. The CH-47 application examined the system performance of six flight conditions. Four candidate configurations are suggested for evaluation in pilot-in-the-loop simulations and eventual flight tests.

Using OPC technology to support the study of advanced process control.

PubMed

Mahmoud, Magdi S; Sabih, Muhammad; Elshafei, Moustafa

2015-03-01

OPC, originally the Object Linking and Embedding (OLE) for Process Control, brings a broad communication opportunity between different kinds of control systems. This paper investigates the use of OPC technology for the study of distributed control systems (DCS) as a cost effective and flexible research tool for the development and testing of advanced process control (APC) techniques in university research centers. Co-Simulation environment based on Matlab, LabVIEW and TCP/IP network is presented here. Several implementation issues and OPC based client/server control application have been addressed for TCP/IP network. A nonlinear boiler model is simulated as OPC server and OPC client is used for closed loop model identification, and to design a Model Predictive Controller. The MPC is able to control the NOx emissions in addition to drum water level and steam pressure. Copyright © 2014 ISA. Published by Elsevier Ltd. All rights reserved.

Snap evaporation of droplets on smooth topographies.

PubMed

Wells, Gary G; Ruiz-Gutiérrez, Élfego; Le Lirzin, Youen; Nourry, Anthony; Orme, Bethany V; Pradas, Marc; Ledesma-Aguilar, Rodrigo

2018-04-11

Droplet evaporation on solid surfaces is important in many applications including printing, micro-patterning and cooling. While seemingly simple, the configuration of evaporating droplets on solids is difficult to predict and control. This is because evaporation typically proceeds as a "stick-slip" sequence-a combination of pinning and de-pinning events dominated by static friction or "pinning", caused by microscopic surface roughness. Here we show how smooth, pinning-free, solid surfaces of non-planar topography promote a different process called snap evaporation. During snap evaporation a droplet follows a reproducible sequence of configurations, consisting of a quasi-static phase-change controlled by mass diffusion interrupted by out-of-equilibrium snaps. Snaps are triggered by bifurcations of the equilibrium droplet shape mediated by the underlying non-planar solid. Because the evolution of droplets during snap evaporation is controlled by a smooth topography, and not by surface roughness, our ideas can inspire programmable surfaces that manage liquids in heat- and mass-transfer applications.

Echinococcosis: Control and Prevention.

PubMed

Craig, P S; Hegglin, D; Lightowlers, M W; Torgerson, P R; Wang, Q

2017-01-01

Human cystic echinococcosis (CE) has been eliminated or significantly reduced as a public health problem in several previously highly endemic regions. This has been achieved by the long-term application of prevention and control measures primarily targeted to deworming dogs, health education, meat inspection, and effective surveillance in livestock and human populations. Human CE, however, remains a serious neglected zoonotic disease in many resource-poor pastoral regions. The incidence of human alveolar echinococcosis (AE) has increased in continental Europe and is a major public health problem in parts of Eurasia. Better understanding of wildlife ecology for fox and small mammal hosts has enabled targeted anthelmintic baiting of fox populations and development of spatially explicit models to predict population dynamics for key intermediate host species and human AE risk in endemic landscapes. Challenges that remain for echinococcosis control include effective intervention in resource-poor communities, better availability of surveillance tools, optimal application of livestock vaccination, and management and ecology of dog and wildlife host populations. Copyright © 2017 Elsevier Ltd. All rights reserved.

A fast implementation of MPC-based motion cueing algorithms for mid-size road vehicle motion simulators

NASA Astrophysics Data System (ADS)

Bruschetta, M.; Maran, F.; Beghi, A.

2017-06-01

The use of dynamic driving simulators is constantly increasing in the automotive community, with applications ranging from vehicle development to rehab and driver training. The effectiveness of such devices is related to their capabilities of well reproducing the driving sensations, hence it is crucial that the motion control strategies generate both realistic and feasible inputs to the platform. Such strategies are called motion cueing algorithms (MCAs). In recent years several MCAs based on model predictive control (MPC) techniques have been proposed. The main drawback associated with the use of MPC is its computational burden, that may limit their application to high performance dynamic simulators. In the paper, a fast, real-time implementation of an MPC-based MCA for 9 DOF, high performance platform is proposed. Effectiveness of the approach in managing the available working area is illustrated by presenting experimental results from an implementation on a real device with a 200 Hz control frequency.

Dimension-controlled formation of crease patterns on soft solids.

PubMed

Tang, Shan; Gao, Bo; Zhou, Zhiheng; Gu, Qiang; Guo, Tianfu

2017-01-18

Soft solids such as PDMS or silicone are widely needed in many advanced applications such as flexible electronics and medical engineering. The ability to control the structure and properties of the surface of soft solids provides new opportunities in these applications. In particular, mechanical loading induced elastic instability is a convenient method to control the surface morphology. The critical strain at which the crease nucleates is experimentally measured under plane strain conditions, and is found to be consistent with that predicted by nonlinear large deformation theory of creases. Under compressive loading, we find that silicone undergoes a transition of creasing pattern from a single channeling or double channeling crease to an unchanneling crease, depending on the specimen's width and height. Finite element simulations are performed to better understand the underlying mechanism of creasing, wherein a relationship between the depth and spacing of the creases is established. It is found to be in good agreement with the experimental data obtained.

Structural insights into Cydia pomonella pheromone binding protein 2 mediated prediction of potentially active semiochemicals

NASA Astrophysics Data System (ADS)

Tian, Zhen; Liu, Jiyuan; Zhang, Yalin

2016-03-01

Given the advantages of behavioral disruption application in pest control and the damage of Cydia pomonella, due progresses have not been made in searching active semiochemicals for codling moth. In this research, 31 candidate semiochemicals were ranked for their binding potential to Cydia pomonella pheromone binding protein 2 (CpomPBP2) by simulated docking, and this sorted result was confirmed by competitive binding assay. This high predicting accuracy of virtual screening led to the construction of a rapid and viable method for semiochemicals searching. By reference to binding mode analyses, hydrogen bond and hydrophobic interaction were suggested to be two key factors in determining ligand affinity, so is the length of molecule chain. So it is concluded that semiochemicals of appropriate chain length with hydroxyl group or carbonyl group at one head tended to be favored by CpomPBP2. Residues involved in binding with each ligand were pointed out as well, which were verified by computational alanine scanning mutagenesis. Progress made in the present study helps establish an efficient method for predicting potentially active compounds and prepares for the application of high-throughput virtual screening in searching semiochemicals by taking insights into binding mode analyses.

Predicting indoor pollutant concentrations, and applications to air quality management

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

Lorenzetti, David M.

Because most people spend more than 90% of their time indoors, predicting exposure to airborne pollutants requires models that incorporate the effect of buildings. Buildings affect the exposure of their occupants in a number of ways, both by design (for example, filters in ventilation systems remove particles) and incidentally (for example, sorption on walls can reduce peak concentrations, but prolong exposure to semivolatile organic compounds). Furthermore, building materials and occupant activities can generate pollutants. Indoor air quality depends not only on outdoor air quality, but also on the design, maintenance, and use of the building. For example, ''sick building'' symptomsmore » such as respiratory problems and headaches have been related to the presence of air-conditioning systems, to carpeting, to low ventilation rates, and to high occupant density (1). The physical processes of interest apply even in simple structures such as homes. Indoor air quality models simulate the processes, such as ventilation and filtration, that control pollutant concentrations in a building. Section 2 describes the modeling approach, and the important transport processes in buildings. Because advection usually dominates among the transport processes, Sections 3 and 4 describe methods for predicting airflows. The concluding section summarizes the application of these models.« less

Fully Ab-Initio Determination of the Thermoelectric Properties of Half-Heusler NiTiSn: Crucial Role of Interstitial Ni Defects.

PubMed

Berche, Alexandre; Jund, Philippe

2018-05-23

For thermoelectric applications, ab initio methods generally fail to predict the transport properties of the materials because of their inability to predict properly the carrier concentrations that control the electronic properties. In this work, a methodology to fill in this gap is applied on the NiTiSn half Heusler phase. For that, we show that the main defects act as donor of electrons and are responsible of the electronic properties of the material. Indeed, the presence of Ni i interstitial defects explains the experimental valence band spectrum and its associated band gap reported in the literature. Moreover, combining the DOS of the solid solutions with the determination of the energy of formation of charged defects, we show that Ni i defects are also responsible of the measured carrier concentration in experimentally supposed "pure" NiTiSn compounds. Subsequently the thermoelectric properties of NiTiSn can be calculated using a fully ab initio description and an overall correct agreement with experiments is obtained. This methodology can be extended to predict the result of extrinsic doping and thus to select the most efficient dopant for specific thermoelectric applications.

Structural insights into Cydia pomonella pheromone binding protein 2 mediated prediction of potentially active semiochemicals

PubMed Central

Tian, Zhen; Liu, Jiyuan; Zhang, Yalin

2016-01-01

Given the advantages of behavioral disruption application in pest control and the damage of Cydia pomonella, due progresses have not been made in searching active semiochemicals for codling moth. In this research, 31 candidate semiochemicals were ranked for their binding potential to Cydia pomonella pheromone binding protein 2 (CpomPBP2) by simulated docking, and this sorted result was confirmed by competitive binding assay. This high predicting accuracy of virtual screening led to the construction of a rapid and viable method for semiochemicals searching. By reference to binding mode analyses, hydrogen bond and hydrophobic interaction were suggested to be two key factors in determining ligand affinity, so is the length of molecule chain. So it is concluded that semiochemicals of appropriate chain length with hydroxyl group or carbonyl group at one head tended to be favored by CpomPBP2. Residues involved in binding with each ligand were pointed out as well, which were verified by computational alanine scanning mutagenesis. Progress made in the present study helps establish an efficient method for predicting potentially active compounds and prepares for the application of high-throughput virtual screening in searching semiochemicals by taking insights into binding mode analyses. PMID:26928635

Adaptive Network Dynamics - Modeling and Control of Time-Dependent Social Contacts

PubMed Central

Schwartz, Ira B.; Shaw, Leah B.; Shkarayev, Maxim S.

2013-01-01

Real networks consisting of social contacts do not possess static connections. That is, social connections may be time dependent due to a variety of individual behavioral decisions based on current network connections. Examples of adaptive networks occur in epidemics, where information about infectious individuals may change the rewiring of healthy people, or in the recruitment of individuals to a cause or fad, where rewiring may optimize recruitment of susceptible individuals. In this paper, we will review some of the dynamical properties of adaptive networks, and show how they predict novel phenomena as well as yield insight into new controls. The applications will be control of epidemic outbreaks and terrorist recruitment modeling. PMID:25414913

Neural-fuzzy control system application for monitoring process response and control of anaerobic hybrid reactor in wastewater treatment and biogas production.

PubMed

Waewsak, Chaiwat; Nopharatana, Annop; Chaiprasert, Pawinee

2010-01-01

Based on the developed neural-fuzzy control system for anaerobic hybrid reactor (AHR) in wastewater treatment and biogas production, the neural network with backpropagation algorithm for prediction of the variables pH, alkalinity (Alk) and total volatile acids (TVA) at present day time t was used as input data for the fuzzy logic to calculate the influent feed flow rate that was applied to control and monitor the process response at different operations in the initial, overload influent feeding and the recovery phases. In all three phases, this neural-fuzzy control system showed great potential to control AHR in high stability and performance and quick response. Although in the overloading operation phase II with two fold calculating influent flow rate together with a two fold organic loading rate (OLR), this control system had rapid response and was sensitive to the intended overload. When the influent feeding rate was followed by the calculation of control system in the initial operation phase I and the recovery operation phase III, it was found that the neural-fuzzy control system application was capable of controlling the AHR in a good manner with the pH close to 7, TVA/Alk < 0.4 and COD removal > 80% with biogas and methane yields at 0.45 and 0.30 m3/kg COD removed.

Model Selection for Solving Kinematic Problems

DTIC Science & Technology

1990-09-01

Bundy78] A. Bundy. Will it Reach the Top? Prediction in the Mechanics World. Aritificial Intelligence , 10:111-122, 1978. [Bundy,Luger,Mellish&Pamer78] A...ELEMENT. PfOJECT. TASK Artificial Intelligence Laboratory AREA 4 WORK UNIT NUMBERS 545 Technology Square Cambridge, MA 02139 It. CONTROLLiNG OFFICE...tificial Intelligence community, particularly in its application to diagnosis and trou- bleshooting. The core issue in this thesis, simply put, is, model

The robust model predictive control based on mixed H2/H∞ approach with separated performance formulations and its ISpS analysis

NASA Astrophysics Data System (ADS)

Li, Dewei; Li, Jiwei; Xi, Yugeng; Gao, Furong

2017-12-01

In practical applications, systems are always influenced by parameter uncertainties and external disturbance. Both the H2 performance and the H∞ performance are important for the real applications. For a constrained system, the previous designs of mixed H2/H∞ robust model predictive control (RMPC) optimise one performance with the other performance requirement as a constraint. But the two performances cannot be optimised at the same time. In this paper, an improved design of mixed H2/H∞ RMPC for polytopic uncertain systems with external disturbances is proposed to optimise them simultaneously. In the proposed design, the original uncertain system is decomposed into two subsystems by the additive character of linear systems. Two different Lyapunov functions are used to separately formulate the two performance indices for the two subsystems. Then, the proposed RMPC is designed to optimise both the two performances by the weighting method with the satisfaction of the H∞ performance requirement. Meanwhile, to make the design more practical, a simplified design is also developed. The recursive feasible conditions of the proposed RMPC are discussed and the closed-loop input state practical stable is proven. The numerical examples reflect the enlarged feasible region and the improved performance of the proposed design.

The impact of social cognitive and personality factors on teachers' reported inclusive behaviour.

PubMed

Wilson, Claire; Woolfson, Lisa Marks; Durkin, Kevin; Elliott, Mark A

2016-09-01

Inclusive education of children with intellectual disabilities (ID) is intended to maximize their educational experience within the mainstream school setting. While policy mandates inclusion, it is classroom teachers' behaviours that determine its success. This study provided a novel application of the theory of planned behaviour (TPB) in this setting. It examined the effect of TPB variables and personality on reported inclusive teaching behaviours for learners with ID. The sample comprised 145 primary school teachers (85% female) from mainstream schools across Scotland. Participants completed a TPB questionnaire assessing attitudes (instrumental and affective), subjective norms (injunctive and descriptive norms), perceptions of control (self-efficacy and controllability), and behavioural intentions towards using inclusive strategies. The Big Five Personality Index, measuring extraversion, conscientiousness, openness, neuroticism, and agreeableness, was also completed. Teaching practices were reported 2 weeks later. Instrumental attitudes, descriptive norm, self-efficacy, and neuroticism predicted teachers' intentions to use inclusive strategies. Further, conscientiousness had indirect effects on intentions through TPB variables. These intentions, however, did not predict reported behaviour expected by TPB. Instead, self-efficacy was the only significant predictor of reported behaviour. This study demonstrates the application of TPB to an educational setting and contributes to the understanding of teachers' reported use of inclusive strategies for children with ID. © 2016 The British Psychological Society.

Closed-Loop Control of Vortex Formation in Separated Flows with Application to Micro Air Vehicles

DTIC Science & Technology

2010-10-25

ruich. roll, «nd phasgi. innmt.yi of th« wwtg m tnpnap» lo die nnHriiiy fin—n nant flow r 1 faA fhiif—irm ■IIIIUIJ wah gutting fnxjBfju flow wa...a» ■ Altar kernel to predict the retpone of Ihe »nig lo mote complex actuator omul »pails A «oic. of caonvTkn of incrcaaang eornpkxirv were <toa>gard... lo rupracis bit Muctuatioru m puffing condition. The mow robust controller» were «Me to suppre« lift fluctuation» associated with • broadband

An overview of current Navy programs to develop thrust augmenting ejectors

NASA Technical Reports Server (NTRS)

Green, K. A.

1979-01-01

The primary objective of Navy sponsored research in thrust augmentation is the development of an improved augmenter for V/STOL application. In support of this goal, a data base is being established to provide an accurate prediction capability for use in ejector design. A general technology development of ejectors and associated effects presently is split into the more specific areas of lift and control, since thrust augmenting ejectors may be suitable for both. Research areas examined include advanced diffuser and end wall design; advanced primary nozzles; analytic studies; augmenting reaction controls; and nozzle design.

Interesting examples of supervised continuous variable systems

NASA Technical Reports Server (NTRS)

Chase, Christopher; Serrano, Joe; Ramadge, Peter

1990-01-01

The authors analyze two simple deterministic flow models for multiple buffer servers which are examples of the supervision of continuous variable systems by a discrete controller. These systems exhibit what may be regarded as the two extremes of complexity of the closed loop behavior: one is eventually periodic, the other is chaotic. The first example exhibits chaotic behavior that could be characterized statistically. The dual system, the switched server system, exhibits very predictable behavior, which is modeled by a finite state automaton. This research has application to multimodal discrete time systems where the controller can choose from a set of transition maps to implement.

Towards integrated pest management in red clover seed production.

PubMed

Lundin, Ola; Rundlöf, Maj; Smith, Henrik G; Bommarco, Riccardo

2012-10-01

The development of integrated pest management is hampered by lack of information on how insect pest abundances relate to yield losses, and how pests are affected by control measures. In this study, we develop integrated pest management tactics for Apion spp. weevils (Coleoptera: Brentidae) in seed production of red clover, Trifolium pratense L. We tested a method to forecast pest damage, quantified the relationship between pest abundance and yield, and evaluated chemical and biological pest control in 29 Swedish red clover fields in 2008 and 2011. Pest inflorescence abundance, which had a highly negative effect on yield, could be predicted with pan trap catches of adult pests. In 2008, chemical control with typically one application of pyrethroids was ineffective both in decreasing pest abundances and in increasing yields. In 2011, when chemical control included applications of the neonicotinoid thiacloprid, pest abundances decreased and yields increased considerably in treated field zones. A post hoc analysis indicated that using pyrethroids in addition to thiacloprid was largely redundant. Infestation rates by parasitoids was higher and reached average levels of around 40% in insecticide treated field zones in 2011, which is a level of interest for biological pest control. Based on the data presented, an economic threshold for chemical control is developed, and guidelines are provided on minimum effective chemical pest control.

Experimentation and analysis of mechanical behavior modification of titanium matrix composites through controlled fiber placement

NASA Astrophysics Data System (ADS)

Bowman, Cheryl Lynne

Titanium composites reinforced with SiC fibers in a uniaxial direction are being considered for various high temperature applications which require high specific strength or stiffness in the primary loading direction. However the very low tensile and creep strength of these composites in the transverse direction (loading perpendicular to the fiber axis) limits their use in many practical applications. Recent advances in composite fabrication techniques have provided not only better control of fiber volume fraction and distribution, but also the ability to control the relative fiber placement. The goal of this research was produce continuously reinforced SiC/Ti composites with precise fiber arrangement in order to ascertain the significance of fiber arrangements on transverse mechanical properties. In this study, TIMETAL 21S and Ti-6-4 composites reinforced with SCS-6 SiC fibers were produced with six distinct fiber placement arrangements. The effect of fiber placement on uniaxial tensile and creep behaviors was assessed and the results compared to analytical predictions. Consistent with analytical predictions, the fiber arrangements used in this study did not significantly change the longitudinal tensile behavior, but differences were obtained in the transverse loading response. For example, a diamond (non-equilateral triangle) fiber packing was found to have a higher transverse ultimate tensile strength and better transverse creep resistance than a rectangular fiber packing arrangement for a given volume fraction and fiber spacing (within-ply vs. between-ply). Initially this result appeared to be in contrast to previous computational and analytical simulations which predicted more favorable mechanical behavior for rectangular-type arrangements. However, this experimental/predictive conflict was resolved, in part, by simply defining a fiber spacing ratio which could describe both rectangular type and diamond-type arrangements. The computationally efficient Micromechanical Analysis Code based on the Generalized Method of Cells captured the correct behavior trends for these fiber arrangements and thus can be used to estimate the optimum fiber arrangement for a given materials system. Although this research utilized SiC/titanium alloy composites, the results should be relevant to any composite with a continuous reinforcement, a ductile matrix, and a finite fiber/matrix interfacial bond strength.

Use of Remote Sensing/Geographical Information Systems (RS/GIS) to Identify the Distributional Limits of Soil-Transmitted Helminths (STHs) and Their Association to Prevalence of Intestinal Infection in School-Age Children in Four Rural Communities in Boaco, Nicaragua

NASA Technical Reports Server (NTRS)

Moreno, Max J.; Al-Hamdan, Mohammad Z.; Parajon, David G.; Rickman, Douglas L.; Luvall, Jeffrey; Parajon, Laura C.; Martinez, Roberto A.; Estes, Sue

2011-01-01

STHs can infect all members of a population but school-age children living in poverty are at greater risk. Infection can be controlled with drug treatment, health education and sanitation. Helminth control programs often lack resources and reliable information to identify areas of highest risk to guide interventions and to monitor progress. Objectives: To use RS/GIS to identify the environmental variables that correlate with the ecology of STHs and with the prevalence of STH infections. Methods: Geo-referenced in situ prevalence data will be overlaid over an ecological map derived from the RS environmental data using ESRI s ArcGIS 9.3. Prevalence data and RS environmental data matching at the same geographical location will be analyzed for correlation and those RS environmental variables that better correlate with prevalence data will be included in a multivariate regression model. Temperature, vegetation, and distance to bodies of water will be inferred using data from the Moderate-Resolution Imaging Spectroradiometer (MODIS) onboard the Terra and Aqua satellites, and Thematic Mapper (TM) and Enhance Thematic Mapper Plus (ETM+) satellite sensors onboard Landsat 5 and Landsat 7 respectively. Elevation will be estimated with data from The Shuttle Radar Topography Mission (SRTM). Prevalence and intensity of infections will be determined by parasitological survey (Kato Katz) of children enrolled in rural schools in Boaco, Nicaragua, in the communities of El Roblar, Cumaica Norte, Malacatoya 1, and Malacatoya 2). Expected Results: Associations between RS environmental data and prevalence in situ data will be determined and their applications to public health will be discussed. Discussion/Conclusions: The use of RS/GIS data to predict the prevalence of STH infections could be useful for helminth control programs, providing improved geographical guidance of interventions while increasing cost-effectiveness. Learning Objectives: (1) To identify the RS environmental variables that can help predict the prevalence of STH infections. (2) To understand potential applications of RS/GIS to national helminth control programs. (3) To asses the applicability of RS/GIS to control STH infections.

Prediction of pilot opinion ratings using an optimal pilot model. [of aircraft handling qualities in multiaxis tasks

NASA Technical Reports Server (NTRS)

Hess, R. A.

1977-01-01

A brief review of some of the more pertinent applications of analytical pilot models to the prediction of aircraft handling qualities is undertaken. The relative ease with which multiloop piloting tasks can be modeled via the optimal control formulation makes the use of optimal pilot models particularly attractive for handling qualities research. To this end, a rating hypothesis is introduced which relates the numerical pilot opinion rating assigned to a particular vehicle and task to the numerical value of the index of performance resulting from an optimal pilot modeling procedure as applied to that vehicle and task. This hypothesis is tested using data from piloted simulations and is shown to be reasonable. An example concerning a helicopter landing approach is introduced to outline the predictive capability of the rating hypothesis in multiaxis piloting tasks.

Applying Social Psychological Models to Predicting HIV-Related Sexual Risk Behaviors Among African Americans

PubMed Central

Cochran, Susan D.; Mays, Vickie M.

2011-01-01

Existing models of attitude-behavior relationships, including the Health Belief Model, the Theory of Reasoned Action, and the Self-Efficacy Theory, are increasingly being used by psychologists to predict human immunodeficiency virus (HIV)-related risk behaviors. The authors briefly highlight some of the difficulties that might arise in applying these models to predicting the risk behaviors of African Americans. These social psychological models tend to emphasize the importance of individualistic, direct control of behavioral choices and deemphasize factors, such as racism and poverty, particularly relevant to that segment of the African American population most at risk for HIV infection. Applications of these models without taking into account the unique issues associated with behavioral choices within the African American community may fail to capture the relevant determinants of risk behaviors. PMID:23529205

The application of parameter estimation to flight measurements to obtain lateral-directional stability derivatives of an augmented jet-flap STOL airplane

NASA Technical Reports Server (NTRS)

Stephenson, J. D.

1983-01-01

Flight experiments with an augmented jet flap STOL aircraft provided data from which the lateral directional stability and control derivatives were calculated by applying a linear regression parameter estimation procedure. The tests, which were conducted with the jet flaps set at a 65 deg deflection, covered a large range of angles of attack and engine power settings. The effect of changing the angle of the jet thrust vector was also investigated. Test results are compared with stability derivatives that had been predicted. The roll damping derived from the tests was significantly larger than had been predicted, whereas the other derivatives were generally in agreement with the predictions. Results obtained using a maximum likelihood estimation procedure are compared with those from the linear regression solutions.

Forecast Method of Solar Irradiance with Just-In-Time Modeling

NASA Astrophysics Data System (ADS)

Suzuki, Takanobu; Goto, Yusuke; Terazono, Takahiro; Wakao, Shinji; Oozeki, Takashi

PV power output mainly depends on the solar irradiance which is affected by various meteorological factors. So, it is required to predict solar irradiance in the future for the efficient operation of PV systems. In this paper, we develop a novel approach for solar irradiance forecast, in which we introduce to combine the black-box model (JIT Modeling) with the physical model (GPV data). We investigate the predictive accuracy of solar irradiance over wide controlled-area of each electric power company by utilizing the measured data on the 44 observation points throughout Japan offered by JMA and the 64 points around Kanto by NEDO. Finally, we propose the application forecast method of solar irradiance to the point which is difficulty in compiling the database. And we consider the influence of different GPV default time on solar irradiance prediction.

A machine learning approach to triaging patients with chronic obstructive pulmonary disease

PubMed Central

Qirko, Klajdi; Smith, Ted; Corcoran, Ethan; Wysham, Nicholas G.; Bazaz, Gaurav; Kappel, George; Gerber, Anthony N.

2017-01-01

COPD patients are burdened with a daily risk of acute exacerbation and loss of control, which could be mitigated by effective, on-demand decision support tools. In this study, we present a machine learning-based strategy for early detection of exacerbations and subsequent triage. Our application uses physician opinion in a statistically and clinically comprehensive set of patient cases to train a supervised prediction algorithm. The accuracy of the model is assessed against a panel of physicians each triaging identical cases in a representative patient validation set. Our results show that algorithm accuracy and safety indicators surpass all individual pulmonologists in both identifying exacerbations and predicting the consensus triage in a 101 case validation set. The algorithm is also the top performer in sensitivity, specificity, and ppv when predicting a patient’s need for emergency care. PMID:29166411

Fatigue Behavior of AM60B Subjected to Variable Amplitude Loading

NASA Astrophysics Data System (ADS)

Kang, H.; Kari, K.; Khosrovaneh, A. K.; Nayaki, R.; Su, X.; Zhang, L.; Lee, Y.-L.

Magnesium alloys are considered as an alternative material to reduce vehicle weight due to their weight which are 33% lighter than aluminum alloys. There has been a significant expansion in the applications of magnesium alloys in automotives components in an effort to improve fuel efficiency through vehicle mass reduction. In this project, a simple front shock tower of passenger vehicle is constructed with various magnesium alloys. To predict the fatigue behavior of the structure, fatigue properties of the magnesium alloy (AM60B) were determined from strain controlled fatigue tests. Notched specimens were also tested with three different variable amplitude loading profiles obtained from the shock tower of the similar size of vehicle. The test results were compared with various fatigue prediction results. The effect of mean stress and fatigue prediction method were discussed.

Strategies for concurrent processing of complex algorithms in data driven architectures

NASA Technical Reports Server (NTRS)

Stoughton, John W.; Mielke, Roland R.; Som, Sukhamony

1990-01-01

The performance modeling and enhancement for periodic execution of large-grain, decision-free algorithms in data flow architectures is examined. Applications include real-time implementation of control and signal processing algorithms where performance is required to be highly predictable. The mapping of algorithms onto the specified class of data flow architectures is realized by a marked graph model called ATAMM (Algorithm To Architecture Mapping Model). Performance measures and bounds are established. Algorithm transformation techniques are identified for performance enhancement and reduction of resource (computing element) requirements. A systematic design procedure is described for generating operating conditions for predictable performance both with and without resource constraints. An ATAMM simulator is used to test and validate the performance prediction by the design procedure. Experiments on a three resource testbed provide verification of the ATAMM model and the design procedure.

Strategies for concurrent processing of complex algorithms in data driven architectures

NASA Technical Reports Server (NTRS)

Som, Sukhamoy; Stoughton, John W.; Mielke, Roland R.

1990-01-01

Performance modeling and performance enhancement for periodic execution of large-grain, decision-free algorithms in data flow architectures are discussed. Applications include real-time implementation of control and signal processing algorithms where performance is required to be highly predictable. The mapping of algorithms onto the specified class of data flow architectures is realized by a marked graph model called algorithm to architecture mapping model (ATAMM). Performance measures and bounds are established. Algorithm transformation techniques are identified for performance enhancement and reduction of resource (computing element) requirements. A systematic design procedure is described for generating operating conditions for predictable performance both with and without resource constraints. An ATAMM simulator is used to test and validate the performance prediction by the design procedure. Experiments on a three resource testbed provide verification of the ATAMM model and the design procedure.

Data-Based Predictive Control with Multirate Prediction Step

NASA Technical Reports Server (NTRS)

Barlow, Jonathan S.

2010-01-01

Data-based predictive control is an emerging control method that stems from Model Predictive Control (MPC). MPC computes current control action based on a prediction of the system output a number of time steps into the future and is generally derived from a known model of the system. Data-based predictive control has the advantage of deriving predictive models and controller gains from input-output data. Thus, a controller can be designed from the outputs of complex simulation code or a physical system where no explicit model exists. If the output data happens to be corrupted by periodic disturbances, the designed controller will also have the built-in ability to reject these disturbances without the need to know them. When data-based predictive control is implemented online, it becomes a version of adaptive control. One challenge of MPC is computational requirements increasing with prediction horizon length. This paper develops a closed-loop dynamic output feedback controller that minimizes a multi-step-ahead receding-horizon cost function with multirate prediction step. One result is a reduced influence of prediction horizon and the number of system outputs on the computational requirements of the controller. Another result is an emphasis on portions of the prediction window that are sampled more frequently. A third result is the ability to include more outputs in the feedback path than in the cost function.

Affinity and Efficacy of Copper Following an Algicide Exposure: Application of the Critical Burden Concept for Lyngbya wollei Control in Lay Lake, AL

NASA Astrophysics Data System (ADS)

Bishop, West M.; Willis, Ben E.; Horton, C. Todd

2015-04-01

Accurate predictions of nuisance algae responses to algicide exposures are needed to guide management decisions. Copper sorption and responses of Lyngbya wollei (Farlow ex Gomont) Speziale and Dyck were measured in the laboratory and two areas in Lay Lake (AL, USA) to treatments of Captain® XTR (SePRO Corporation; chelated copper algicide) and a sequential treatment of GreenClean® Liquid (BioSafe Systems, LLC; peroxygen algicide) combined with Hydrothol® 191 (United Phosphorus, Inc.; endothall algicide) followed by Captain XTR. Measured filament viability in laboratory exposures predicted Captain XTR alone could control L. wollei in Lay Lake, with 2 mg Cu/g algae EC75. This produced a targeted field treatment of 9.7 kg Cu/ha which was divided into three applications of 0.3 mg Cu/L as Captain XTR in the treatment areas. Laboratory and field experiments indicated treatments of Captain XTR alone and the combination treatment resulted in comparable copper sorption and responses of L. wollei. Copper adsorbed greater to L. wollei in laboratory experiments than in the treated areas of Lay Lake with comparable exposures (2 mg Cu/g L. wollei). However, responses and infused copper were similar and correlated in laboratory experiments and treated areas of Lay Lake indicating infused copper is critical for governing toxicity. Laboratory exposures as mg Cu/g algae accurately predicted the necessary algicide exposure required to attain the critical burden of infused copper and elicit desired responses of L. wollei in treated areas of Lay Lake.

Morphing Compression Garments for Space Medicine and Extravehicular Activity Using Active Materials.

PubMed

Holschuh, Bradley T; Newman, Dava J

2016-02-01

Compression garments tend to be difficult to don/doff, due to their intentional function of squeezing the wearer. This is especially true for compression garments used for space medicine and for extravehicular activity (EVA). We present an innovative solution to this problem by integrating shape changing materials-NiTi shape memory alloy (SMA) coil actuators formed into modular, 3D-printed cartridges-into compression garments to produce garments capable of constricting on command. A parameterized, 2-spring analytic counterpressure model based on 12 garment and material inputs was developed to inform garment design. A methodology was developed for producing novel SMA cartridge systems to enable active compression garment construction. Five active compression sleeve prototypes were manufactured and tested: each sleeve was placed on a rigid cylindrical object and counterpressure was measured as a function of spatial location and time before, during, and after the application of a step voltage input. Controllable active counterpressures were measured up to 34.3 kPa, exceeding the requirement for EVA life support (29.6 kPa). Prototypes which incorporated fabrics with linear properties closely matched analytic model predictions (4.1%/-10.5% error in passive/active pressure predictions); prototypes using nonlinear fabrics did not match model predictions (errors >100%). Pressure non-uniformities were observed due to friction and the rigid SMA cartridge structure. To our knowledge this is the first demonstration of controllable compression technology incorporating active materials, a novel contribution to the field of compression garment design. This technology could lead to easy-to-don compression garments with widespread space and terrestrial applications.

Fuzzy logic modeling of the resistivity parameter and topography features for aquifer assessment in hydrogeological investigation of a crystalline basement complex

NASA Astrophysics Data System (ADS)

Adabanija, M. A.; Omidiora, E. O.; Olayinka, A. I.

2008-05-01

A linguistic fuzzy logic system (LFLS)-based expert system model has been developed for the assessment of aquifers for the location of productive water boreholes in a crystalline basement complex. The model design employed a multiple input/single output (MISO) approach with geoelectrical parameters and topographic features as input variables and control crisp value as the output. The application of the method to the data acquired in Khondalitic terrain, a basement complex in Vizianagaram District, south India, shows that potential groundwater resource zones that have control output values in the range 0.3295-0.3484 have a yield greater than 6,000 liters per hour (LPH). The range 0.3174-0.3226 gives a yield less than 4,000 LPH. The validation of the control crisp value using data acquired from Oban Massif, a basement complex in southeastern Nigeria, indicates a yield less than 3,000 LPH for control output values in the range 0.2938-0.3065. This validation corroborates the ability of control output values to predict a yield, thereby vindicating the applicability of linguistic fuzzy logic system in siting productive water boreholes in a basement complex.

Real-time control of focused ultrasound heating based on rapid MR thermometry.

PubMed

Vimeux, F C; De Zwart, J A; Palussiére, J; Fawaz, R; Delalande, C; Canioni, P; Grenier, N; Moonen, C T

1999-03-01

Real-time control of the heating procedure is essential for hyperthermia applications of focused ultrasound (FUS). The objective of this study is to demonstrate the feasibility of MRI-controlled FUS. An automatic control system was developed using a dedicated interface between the MR system control computer and the FUS wave generator. Two algorithms were used to regulate FUS power to maintain the focal point temperature at a desired level. Automatic control of FUS power level was demonstrated ex vivo at three target temperature levels (increase of 5 degrees C, 10 degrees C, and 30 degrees C above room temperature) during 30-minute hyperthermic periods. Preliminary in vivo results on rat leg muscle confirm that necrosis estimate, calculated on-line during FUS sonication, allows prediction of tissue damage. CONCLUSIONS. The feasibility of fully automatic FUS control based on MRI thermometry has been demonstrated.

Active Mirror Predictive and Requirements Verification Software (AMP-ReVS)

NASA Technical Reports Server (NTRS)

Basinger, Scott A.

2012-01-01

This software is designed to predict large active mirror performance at various stages in the fabrication lifecycle of the mirror. It was developed for 1-meter class powered mirrors for astronomical purposes, but is extensible to other geometries. The package accepts finite element model (FEM) inputs and laboratory measured data for large optical-quality mirrors with active figure control. It computes phenomenological contributions to the surface figure error using several built-in optimization techniques. These phenomena include stresses induced in the mirror by the manufacturing process and the support structure, the test procedure, high spatial frequency errors introduced by the polishing process, and other process-dependent deleterious effects due to light-weighting of the mirror. Then, depending on the maturity of the mirror, it either predicts the best surface figure error that the mirror will attain, or it verifies that the requirements for the error sources have been met once the best surface figure error has been measured. The unique feature of this software is that it ties together physical phenomenology with wavefront sensing and control techniques and various optimization methods including convex optimization, Kalman filtering, and quadratic programming to both generate predictive models and to do requirements verification. This software combines three distinct disciplines: wavefront control, predictive models based on FEM, and requirements verification using measured data in a robust, reusable code that is applicable to any large optics for ground and space telescopes. The software also includes state-of-the-art wavefront control algorithms that allow closed-loop performance to be computed. It allows for quantitative trade studies to be performed for optical systems engineering, including computing the best surface figure error under various testing and operating conditions. After the mirror manufacturing process and testing have been completed, the software package can be used to verify that the underlying requirements have been met.

Exploration of crystal simulation potential by fluconazole isomorphism and its application in improvement of pharmaceutical properties

NASA Astrophysics Data System (ADS)

Thakur, Amitha; Kumar, Dinesh; Thipparaboina, Rajesh; Shastri, Nalini R.

2014-11-01

Control of crystal morphology during crystallization is a paramount challenge in pharmaceutical processing. Hence, there is need to introduce computational methods for morphology prediction to manage production cost of drugs and improve related pharmaceutical and biopharmaceutical properties. Layer docking approach with molecular dynamics opens a new avenue for crystal habit prediction in presence of solvent. In the present study, attempts were made to correlate predicted and experimental crystal habits of fluconazole considering solvent interactions using layer docking approach. Simulated results from layer docking approach with methanol as solvent gave two dominant facets (0 1 1) and (1 0 1) with a surface area 22.43% and 19.82% respectively, which were in agreement with the experimental results. Experimentally grown modified crystal habit of fluconazole in methanol showed enhanced dissolution rate (p<0.05) when compared to plain drug. This was attributed to the increased surface area on the specified facets caused by interactions with the solvent. Furthermore, Differential Scanning Calorimetry, Fourier Transform Infrared (FTIR) Spectroscopy and powder X-ray Diffraction of recrystallized samples confirmed only a habit change and absence of any polymorphs, hydrates or solvates. Flow and compressibility of fluconazole recrystallized in methanol was significantly improved when compared to plain drug. This study demonstrates a methodical approach using computational tools for prediction and modification of crystal habit, to enhance dissolution of poorly soluble drugs, for future pharmaceutical applications.

Adaptive PIF Control for Permanent Magnet Synchronous Motors Based on GPC

PubMed Central

Lu, Shaowu; Tang, Xiaoqi; Song, Bao

2013-01-01

To enhance the control performance of permanent magnet synchronous motors (PMSMs), a generalized predictive control (GPC)-based proportional integral feedforward (PIF) controller is proposed for the speed control system. In this new approach, firstly, based on the online identification of controlled model parameters, a simplified GPC law supplies the PIF controller with suitable control parameters according to the uncertainties in the operating conditions. Secondly, the speed reference curve for PMSMs is usually required to be continuous and continuously differentiable according to the general servo system design requirements, so the adaptation of the speed reference is discussed in details in this paper. Hence, the performance of the speed control system using a GPC-based PIF controller is improved for tracking some specified signals. The main motivation of this paper is the extension of GPC law to replace the traditional PI or PIF controllers in industrial applications. The efficacy and usefulness of the proposed controller are verified through experimental results. PMID:23262481

Adaptive PIF control for permanent magnet synchronous motors based on GPC.

PubMed

Lu, Shaowu; Tang, Xiaoqi; Song, Bao

2012-12-24

To enhance the control performance of permanent magnet synchronous motors (PMSMs), a generalized predictive control (GPC)-based proportional integral feedforward (PIF) controller is proposed for the speed control system. In this new approach, firstly, based on the online identification of controlled model parameters, a simplified GPC law supplies the PIF controller with suitable control parameters according to the uncertainties in the operating conditions. Secondly, the speed reference curve for PMSMs is usually required to be continuous and continuously differentiable according to the general servo system design requirements, so the adaptation of the speed reference is discussed in details in this paper. Hence, the performance of the speed control system using a GPC-based PIF controller is improved for tracking some specified signals. The main motivation of this paper is the extension of GPC law to replace the traditional PI or PIF controllers in industrial applications. The efficacy and usefulness of the proposed controller are verified through experimental results.

Novel Applications of Magnetic Fields for Fluid Flow Control and for Simulating Variable Gravity Conditions

NASA Technical Reports Server (NTRS)

Ramachandran, N.

2005-01-01

Static and dynamic magnetic fields have been used to control convection in many materials processing applications. In most of the applications, convection control (damping or enhancement) is achieved through the Lorentz force that can be tailored to counteract/assist dominant system flows. This technique has been successfully applied to liquids that are electrically conducting, such as high temperature melts of semiconductors, metals and alloys, etc. In liquids with low electrical conductivity such as ionic solutions of salts in water, the Lorentz force is weak and hence not very effective and alternate ways of flow control are necessary. If the salt in solution is paramagnetic then the variation of magnetic susceptibility with temperature and/or concentration can be used for flow control. For thermal buoyancy driven flows this can be accomplished in a temperature range below the Curie point of the salt. The magnetic force is proportional to the magnetic susceptibility and the product of the magnetic field and its gradient. By suitably positioning the experiment cell in the magnet, system flows can be assisted or countered, as desired. A similar approach can be extended to diamagnetic substances and fluids but the required magnetic force is considerably larger than that required for paramagnetic substances. The presentation will provide an overview of work to date on a NASA fluid physics sponsored project that aims to test the hypothesis of convective flow control using strong magnetic fields in protein crystal growth. The objective is to understand the nature of the various forces that come into play, delineate causative factors for fluid flow and to quantify them through experiments, analysis, and numerical modeling. The seminar will report specifically on the experimental results using paramagnetic salts and solutions in magnetic fields and compare them to analytical predictions. Applications of the concept to protein crystallization studies will be discussed. The use of strong magnetic fields for terrestrially simulating variable gravity environments and applications supporting the NASA Exploration Initiative will also be briefly discussed.

A Constitutive Model for Strain-Controlled Strength Degradation of Rockmasses (SDR)

NASA Astrophysics Data System (ADS)

Kalos, A.; Kavvadas, M.

2017-11-01

The paper describes a continuum, rate-independent, incremental plasticity constitutive model applicable in weak rocks and heavily fractured rockmasses, where mechanical behaviour is controlled by rockmass strength rather than structural features (discontinuities). The model describes rockmass structure by a generalised Hoek-Brown Structure Envelope (SE) in the stress space. Stress paths inside the SE are nonlinear and irreversible to better simulate behaviour at strains up to peak strength and under stress reversals. Stress paths on the SE have user-controlled volume dilatancy (gradually reducing to zero at large shear strains) and can model post-peak strain softening of brittle rockmasses via a structure degradation (damage) mechanism triggered by accumulated plastic shear strains. As the SE may strain harden with plastic strains, ductile behaviour can also be modelled. The model was implemented in the Finite Element Code Simulia ABAQUS and was applied in plane strain (2D) excavation of a cylindrical cavity (tunnel) to predict convergence-confinement curves. It is shown that small-strain nonlinearity, variable volume dilatancy and post-peak hardening/softening strongly affect the predicted curves, resulting in corresponding differences of lining pressures in real tunnel excavations.

Notched fatigue of single crystal PWA 1480 at turbine attachment temperatures

NASA Technical Reports Server (NTRS)

Meyer, T. G.; Nissley, D. M.; Swanson, G. A.

1989-01-01

The focus is on the lower temperature, uncoated and notched features of gas turbine blades. Constitutive and fatigue life prediction models applicable to these regions are being developed. Fatigue results are presented which were obtained thus far. Fatigue tests are being conducted on PWA 1480 single crystal material using smooth strain controlled specimens and three different notched specimens. Isothermal fatigue tests were conducted at 1200, 1400, and 1600 F. The bulk of the tests were conducted at 1200 F. The strain controlled tests were conducted at 0.4 percent per second strain rate and the notched tests were cycled at 1.0 cycle per second. A clear orientation dependence is observed in the smooth strain controlled fatigue results. The fatigue lifes of the thin, mild notched specimens agree fairly well with this smooth data when elastic stress range is used as a correlating parameter. Finite element analyses were used to calculate notch stresses. Fatigue testing will continue to further explore the trends observed thus far. Constitutive and life prediction models are being developed.

A dynamic feedforward neural network based on gaussian particle swarm optimization and its application for predictive control.

PubMed

Han, Min; Fan, Jianchao; Wang, Jun

2011-09-01

A dynamic feedforward neural network (DFNN) is proposed for predictive control, whose adaptive parameters are adjusted by using Gaussian particle swarm optimization (GPSO) in the training process. Adaptive time-delay operators are added in the DFNN to improve its generalization for poorly known nonlinear dynamic systems with long time delays. Furthermore, GPSO adopts a chaotic map with Gaussian function to balance the exploration and exploitation capabilities of particles, which improves the computational efficiency without compromising the performance of the DFNN. The stability of the particle dynamics is analyzed, based on the robust stability theory, without any restrictive assumption. A stability condition for the GPSO+DFNN model is derived, which ensures a satisfactory global search and quick convergence, without the need for gradients. The particle velocity ranges could change adaptively during the optimization process. The results of a comparative study show that the performance of the proposed algorithm can compete with selected algorithms on benchmark problems. Additional simulation results demonstrate the effectiveness and accuracy of the proposed combination algorithm in identifying and controlling nonlinear systems with long time delays.

Intelligence rules of hysteresis in the feedforward trajectory control of piezoelectrically-driven nanostagers

NASA Astrophysics Data System (ADS)

Bashash, Saeid; Jalili, Nader

2007-02-01

Piezoelectrically-driven nanostagers have limited performance in a variety of feedforward and feedback positioning applications because of their nonlinear hysteretic response to input voltage. The hysteresis phenomenon is well known for its complex and multi-path behavior. To realize the underlying physics of this phenomenon and to develop an efficient compensation strategy, the intelligence properties of hysteresis with the effects of non-local memories are discussed here. Through performing a set of experiments on a piezoelectrically-driven nanostager with a high resolution capacitive position sensor, it is shown that for the precise prediction of the hysteresis path, certain memory units are required to store the previous hysteresis trajectory data. Based on the experimental observations, a constitutive memory-based mathematical modeling framework is developed and trained for the precise prediction of the hysteresis path for arbitrarily assigned input profiles. Using the inverse hysteresis model, a feedforward control strategy is then developed and implemented on the nanostager to compensate for the ever-present nonlinearity. Experimental results demonstrate that the controller remarkably eliminates the nonlinear effect, if memory units are sufficiently chosen for the inverse model.

Protective resources and long-term recovery from alcohol use disorders.

PubMed

Moos, Rudolf H; Moos, Bernice S

2007-01-05

This study examined indices of personal and social resources drawn from social learning, behavioral economics, and social control theories as predictors of medium- and long-term alcohol use disorder outcomes. Individuals (N = 461) who initiated help-seeking for alcohol-related problems were surveyed at baseline and 1, 3, 8, and 16 years later. At baseline and each follow-up, participants provided information about their personal and social resources and alcohol-related and psychosocial functioning. In general, protective resources associated with social learning (self-efficacy and approach coping), behavioral economics (health and financial resources and resources associated with Alcoholics Anonymous), and social control theory (bonding with family members, friends, and coworkers) predicted better alcohol-related and psychosocial outcomes. A summary index of protective resources associated with all three theories significantly predicted remission. Protective resources strengthened the positive influence of treatment on short-term remission and partially mediated the association between treatment and remission. Application of social learning, behavior economic, and social control theories may help to identify predictors of remission and thus to allocate treatment more efficiently.