Dynamics for a discrete competition and cooperation model of two enterprises with multiple delays and feedback controls

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Lu Lin

2017-03-01

Full Text Available This paper is concerned with a competition and cooperation model of two enterprises with multiple delays and feedback controls. With the aid of the difference inequality theory, we have obtained some sufficient conditions which guarantee the permanence of the model. Under a suitable condition, we prove that the system has global stable periodic solution. The paper ends with brief conclusions.

A Multiple-Iterated Dual Control Model for Groundwater Exploitation and Water Level Based on the Optimal Allocation Model of Water Resources

Directory of Open Access Journals (Sweden)

Junqiu Liu

2018-04-01

Full Text Available In order to mitigate environmental and ecological impacts resulting from groundwater overexploitation, we developed a multiple-iterated dual control model consisting of four modules for groundwater exploitation and water level. First, a water resources allocation model integrating calculation module of groundwater allowable withdrawal was built to predict future groundwater recharge and discharge. Then, the results were input into groundwater numerical model to simulate water levels. Groundwater exploitation was continuously optimized using the critical groundwater level as the feedback, and a groundwater multiple-iterated technique was applied to the feedback process. The proposed model was successfully applied to a typical region in Shenyang in northeast China. Results showed the groundwater numerical model was verified in simulating water levels, with a mean absolute error of 0.44 m, an average relative error of 1.33%, and a root-mean-square error of 0.46 m. The groundwater exploitation reduced from 290.33 million m3 to 116.76 million m3 and the average water level recovered from 34.27 m to 34.72 m in planning year. Finally, we proposed the strategies for water resources management in which the water levels should be controlled within the critical groundwater level. The developed model provides a promising approach for water resources allocation and sustainable groundwater management, especially for those regions with overexploited groundwater.

Modelling and controlling hydropower plants

CERN Document Server

Munoz-Hernandez, German Ardul; Jones, Dewi Ieuan

2013-01-01

Hydroelectric power stations are a major source of electricity around the world; understanding their dynamics is crucial to achieving good performance.  Modelling and Controlling Hydropower Plants discusses practical and well-documented cases of modelling and controlling hydropower station modelling and control, focussing on a pumped storage scheme based in Dinorwig, North Wales.  Single-input-single-output and multiple-input-multiple-output models, which cover the linear and nonlinear characteristics of pump-storage hydroelectric power stations, are reviewed. The most important dynamic features are discussed, and the verification of these models by hardware in the loop simulation is described. To show how the performance of a pump-storage hydroelectric power station can be improved, classical and modern controllers are applied to simulated models of the Dinorwig power plant. These include PID, fuzzy approximation, feed-forward and model-based predictive control with linear and hybrid prediction models. Mod...

Decentralized Model Predictive Control for Cooperative Multiple Vehicles Subject to Communication Loss

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Hojjat A. Izadi

2011-01-01

Full Text Available The decentralized model predictive control (DMPC of multiple cooperative vehicles with the possibility of communication loss/delay is investigated. The neighboring vehicles exchange their predicted trajectories at every sample time to maintain the cooperation objectives. In the event of a communication loss (packet dropout, the most recent available information, which is potentially delayed, is used. Then the communication loss problem changes to a cooperative problem when random large communication delays are present. Such large communication delays can lead to poor cooperation performance and unsafe behaviors such as collisions. A new DMPC approach is developed to improve the cooperation performance and achieve safety in the presence of the large communication delays. The proposed DMPC architecture estimates the tail of neighbor's trajectory which is not available due to the large communication delays for improving the performance. The concept of the tube MPC is also employed to provide the safety of the fleet against collisions, in the presence of large intervehicle communication delays. In this approach, a tube shaped trajectory set is assumed around the trajectory of the neighboring vehicles whose trajectory is delayed/lost. The radius of tube is a function of the communication delay and vehicle's maneuverability (in the absence of model uncertainty. The simulation of formation problem of multiple vehicles is employed to illustrate the effectiveness of the proposed approach.

Multiple model predictive control for optimal drug administration of mixed immunotherapy and chemotherapy of tumours.

Science.gov (United States)

Sharifi, N; Ozgoli, S; Ramezani, A

2017-06-01

Mixed immunotherapy and chemotherapy of tumours is one of the most efficient ways to improve cancer treatment strategies. However, it is important to 'design' an effective treatment programme which can optimize the ways of combining immunotherapy and chemotherapy to diminish their imminent side effects. Control engineering techniques could be used for this. The method of multiple model predictive controller (MMPC) is applied to the modified Stepanova model to induce the best combination of drugs scheduling under a better health criteria profile. The proposed MMPC is a feedback scheme that can perform global optimization for both tumour volume and immune competent cell density by performing multiple constraints. Although current studies usually assume that immunotherapy has no side effect, this paper presents a new method of mixed drug administration by employing MMPC, which implements several constraints for chemotherapy and immunotherapy by considering both drug toxicity and autoimmune. With designed controller we need maximum 57% and 28% of full dosage of drugs for chemotherapy and immunotherapy in some instances, respectively. Therefore, through the proposed controller less dosage of drugs are needed, which contribute to suitable results with a perceptible reduction in medicine side effects. It is observed that in the presence of MMPC, the amount of required drugs is minimized, while the tumour volume is reduced. The efficiency of the presented method has been illustrated through simulations, as the system from an initial condition in the malignant region of the state space (macroscopic tumour volume) transfers into the benign region (microscopic tumour volume) in which the immune system can control tumour growth. Copyright © 2017 Elsevier B.V. All rights reserved.

The Multiple Control of Verbal Behavior

Science.gov (United States)

Michael, Jack; Palmer, David C.; Sundberg, Mark L.

2011-01-01

Amid the novel terms and original analyses in Skinner's "Verbal Behavior", the importance of his discussion of multiple control is easily missed, but multiple control of verbal responses is the rule rather than the exception. In this paper we summarize and illustrate Skinner's analysis of multiple control and introduce the terms "convergent…

Damping-tunable energy-harvesting vehicle damper with multiple controlled generators: Design, modeling and experiments

Science.gov (United States)

Xie, Longhan; Li, Jiehong; Li, Xiaodong; Huang, Ledeng; Cai, Siqi

2018-01-01

Hydraulic dampers are used to decrease the vibration of a vehicle, where vibration energy is dissipated as heat. In addition to resulting in energy waste, the damping coefficient in hydraulic dampers cannot be changed during operation. In this paper, an energy-harvesting vehicle damper was proposed to replace traditional hydraulic dampers. The goal is not only to recover kinetic energy from suspension vibration but also to change the damping coefficient during operation according to road conditions. The energy-harvesting damper consists of multiple generators that are independently controlled by switches. One of these generators connects to a tunable resistor for fine tuning the damping coefficient, while the other generators are connected to a control and rectifying circuit, each of which both regenerates electricity and provides a constant damping coefficient. A mathematical model was built to investigate the performance of the energy-harvesting damper. By controlling the number of switched-on generators and adjusting the value of the external tunable resistor, the damping can be fine tuned according to the requirement. In addition to the capability of damping tuning, the multiple controlled generators can output a significant amount of electricity. A prototype was built to test the energy-harvesting damper design. Experiments on an MTS testing system were conducted, with results that validated the theoretical analysis. Experiments show that changing the number of switched-on generators can obviously tune the damping coefficient of the damper and simultaneously produce considerable electricity.

Second-Order Controllability of Multi-Agent Systems with Multiple Leaders

International Nuclear Information System (INIS)

Liu Bo; Han Xiao; Shi Yun-Tao; Su Hou-Sheng

2016-01-01

This paper proposes a new second-order continuous-time multi-agent model and analyzes the controllability of second-order multi-agent system with multiple leaders based on the asymmetric topology. This paper considers the more general case: velocity coupling topology is different from location coupling topology. Some sufficient and necessary conditions are presented for the controllability of the system with multiple leaders. In addition, the paper studies the controllability of the system with velocity damping gain. Simulation results are given to illustrate the correctness of theoretical results. (paper)

Multiple Model Adaptive Control Using Dual Youla-Kucera Factorisation

DEFF Research Database (Denmark)

Bendtsen, Jan Dimon; Trangbæk, Klaus

2012-01-01

We propose a multi-model adaptive control scheme for uncertain linear plants based on the concept of model unfalsification. The approach relies on examining the ability of a pre-computed set of plant-controller candidates and choosing the one that is best able to reproduce observed in- and output...

Multiple descriptions for packetized predictive control

DEFF Research Database (Denmark)

Østergaard, Jan; Quevedo, Daniel

2016-01-01

be reliably reconstructed at the plant side. For the particular case of LTI plant models and i.i.d. channels, we show that the overall system forms a Markov jump linear system. We provide conditions for mean square stability and derive upper bounds on the operational bit rate of the quantizer to guarantee......In this paper, we propose to use multiple descriptions (MDs) to achieve a high degree of robustness towards random packet delays and erasures in networked control systems. In particular, we consider the scenario, where a data-rate limited channel is located between the controller and the plant...

Stability analysis of multiple-robot control systems

Science.gov (United States)

Wen, John T.; Kreutz, Kenneth

1989-01-01

In a space telerobotic service scenario, cooperative motion and force control of multiple robot arms are of fundamental importance. Three paradigms to study this problem are proposed. They are distinguished by the set of variables used for control design. They are joint torques, arm tip force vectors, and an accelerated generalized coordinate set. Control issues related to each case are discussed. The latter two choices require complete model information, which presents practical modeling, computational, and robustness problems. Therefore, focus is on the joint torque control case to develop relatively model independent motion and internal force control laws. The rigid body assumption allows the motion and force control problems to be independently addressed. By using an energy motivated Lyapunov function, a simple proportional derivative plus gravity compensation type of motion control law is always shown to be stabilizing. The asymptotic convergence of the tracing error to zero requires the use of a generalized coordinate with the contact constraints taken into account. If a non-generalized coordinate is used, only convergence to a steady state manifold can be concluded. For the force control, both feedforward and feedback schemes are analyzed. The feedback control, if proper care has been taken, exhibits better robustness and transient performance.

Least squares reverse time migration of controlled order multiples

Science.gov (United States)

Liu, Y.

2016-12-01

Imaging using the reverse time migration of multiples generates inherent crosstalk artifacts due to the interference among different order multiples. Traditionally, least-square fitting has been used to address this issue by seeking the best objective function to measure the amplitude differences between the predicted and observed data. We have developed an alternative objective function by decomposing multiples into different orders to minimize the difference between Born modeling predicted multiples and specific-order multiples from observational data in order to attenuate the crosstalk. This method is denoted as the least-squares reverse time migration of controlled order multiples (LSRTM-CM). Our numerical examples demonstrated that the LSRTM-CM can significantly improve image quality compared with reverse time migration of multiples and least-square reverse time migration of multiples. Acknowledgments This research was funded by the National Nature Science Foundation of China (Grant Nos. 41430321 and 41374138).

Modeling Freedom From Progression for Standard-Risk Medulloblastoma: A Mathematical Tumor Control Model With Multiple Modes of Failure

International Nuclear Information System (INIS)

Brodin, N. Patrik; Vogelius, Ivan R.; Björk-Eriksson, Thomas; Munck af Rosenschöld, Per; Bentzen, Søren M.

2013-01-01

Purpose: As pediatric medulloblastoma (MB) is a relatively rare disease, it is important to extract the maximum information from trials and cohort studies. Here, a framework was developed for modeling tumor control with multiple modes of failure and time-to-progression for standard-risk MB, using published pattern of failure data. Methods and Materials: Outcome data for standard-risk MB published after 1990 with pattern of relapse information were used to fit a tumor control dose-response model addressing failures in both the high-dose boost volume and the elective craniospinal volume. Estimates of 5-year event-free survival from 2 large randomized MB trials were used to model the time-to-progression distribution. Uncertainty in freedom from progression (FFP) was estimated by Monte Carlo sampling over the statistical uncertainty in input data. Results: The estimated 5-year FFP (95% confidence intervals [CI]) for craniospinal doses of 15, 18, 24, and 36 Gy while maintaining 54 Gy to the posterior fossa was 77% (95% CI, 70%-81%), 78% (95% CI, 73%-81%), 79% (95% CI, 76%-82%), and 80% (95% CI, 77%-84%) respectively. The uncertainty in FFP was considerably larger for craniospinal doses below 18 Gy, reflecting the lack of data in the lower dose range. Conclusions: Estimates of tumor control and time-to-progression for standard-risk MB provides a data-driven setting for hypothesis generation or power calculations for prospective trials, taking the uncertainties into account. The presented methods can also be applied to incorporate further risk-stratification for example based on molecular biomarkers, when the necessary data become available

Reliability Analysis Multiple Redundancy Controller for Nuclear Safety Systems

International Nuclear Information System (INIS)

Son, Gwangseop; Kim, Donghoon; Son, Choulwoong

2013-01-01

This controller is configured for multiple modular redundancy (MMR) composed of dual modular redundancy (DMR) and triple modular redundancy (TMR). The architecture of MRC is briefly described, and the Markov model is developed. Based on the model, the reliability and Mean Time To Failure (MTTF) are analyzed. In this paper, the architecture of MRC for nuclear safety systems is described. The MRC is configured for multiple modular redundancy (MMR) composed of dual modular redundancy (DMR) and triple modular redundancy (TMR). Markov models for MRC architecture was developed, and then the reliability was analyzed by using the model. From the reliability analyses for the MRC, it is obtained that the failure rate of each module in the MRC should be less than 2 Χ 10 -4 /hour and the MTTF average increase rate depending on FCF increment, i. e. ΔMTTF/ΔFCF, is 4 months/0.1

MULTIPLE ECH LAUNCHER CONTROL SYSTEM

International Nuclear Information System (INIS)

GREEN, M.T.; PONCE, D.; GRUNLOH, H.J.; ELLIS, R.A.; GROSNICKLE, W.H.; HUMPHREY, R.L.

2004-03-01

OAK-B135 The addition of new, high power gyrotrons to the heating and current drive arsenal at DIII-D, required a system upgrade for control of fully steerable ECH Launchers. Each launcher contains two pointing mirrors with two degrees of mechanical freedom. The two flavors of motion are called facet and tilt. Therefore up to four channels of motion per launcher need to be controlled. The system utilizes absolute encoders to indicate mirror position and therefore direction of the microwave beam. The launcher movement is primarily controlled by PLC, but future iterations of design, may require this control to be accomplished by a CPU on fast bus such as Compact PCI. This will be necessary to accomplish real time position control. Safety of equipment and personnel is of primary importance when controlling a system of moving parts. Therefore multiple interlocks and fault status enunciators have been implemented. This paper addresses the design of a Multiple ECH Launcher Control System, and characterizes the flexibility needed to upgrade to a real time position control system in the future

Delegation control of multiple unmanned systems

Science.gov (United States)

Flaherty, Susan R.; Shively, Robert J.

2010-04-01

Maturing technologies and complex payloads coupled with a future objective to reduce the logistics burden of current unmanned aerial systems (UAS) operations require a change to the 2-crew employment paradigm. Increased automation and operator supervisory control of unmanned systems have been advocated to meet the objective of reducing the crew requirements, while managing future technologies. Specifically, a delegation control employment strategy has resulted in reduced workload and higher situation awareness for single operators controlling multiple unmanned systems in empirical studies1,2. Delegation control is characterized by the ability for an operator to call a single "play" that initiates prescribed default actions for each vehicle and associated sensor related to a common mission goal. Based upon the effectiveness of delegation control in simulation, the U.S. Army Aeroflightdynamics Directorate (AFDD) developed a Delegation Control (DelCon) operator interface with voice recognition implementation for play selection, real-time play modification, and play status with automation transparency to enable single operator control of multiple unmanned systems in flight. AFDD successfully demonstrated delegation control in a Troops-in-Contact mission scenario at Ft. Ord in 2009. This summary showcases the effort as a beneficial advance in single operator control of multiple UAS.

Mosaic model for sensorimotor learning and control.

Science.gov (United States)

Haruno, M; Wolpert, D M; Kawato, M

2001-10-01

Humans demonstrate a remarkable ability to generate accurate and appropriate motor behavior under many different and often uncertain environmental conditions. We previously proposed a new modular architecture, the modular selection and identification for control (MOSAIC) model, for motor learning and control based on multiple pairs of forward (predictor) and inverse (controller) models. The architecture simultaneously learns the multiple inverse models necessary for control as well as how to select the set of inverse models appropriate for a given environment. It combines both feedforward and feedback sensorimotor information so that the controllers can be selected both prior to movement and subsequently during movement. This article extends and evaluates the MOSAIC architecture in the following respects. The learning in the architecture was implemented by both the original gradient-descent method and the expectation-maximization (EM) algorithm. Unlike gradient descent, the newly derived EM algorithm is robust to the initial starting conditions and learning parameters. Second, simulations of an object manipulation task prove that the architecture can learn to manipulate multiple objects and switch between them appropriately. Moreover, after learning, the model shows generalization to novel objects whose dynamics lie within the polyhedra of already learned dynamics. Finally, when each of the dynamics is associated with a particular object shape, the model is able to select the appropriate controller before movement execution. When presented with a novel shape-dynamic pairing, inappropriate activation of modules is observed followed by on-line correction.

Robust Fault Tolerant Control for a Class of Time-Delay Systems with Multiple Disturbances

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Songyin Cao

2013-01-01

Full Text Available A robust fault tolerant control (FTC approach is addressed for a class of nonlinear systems with time delay, actuator faults, and multiple disturbances. The first part of the multiple disturbances is supposed to be an uncertain modeled disturbance and the second one represents a norm-bounded variable. First, a composite observer is designed to estimate the uncertain modeled disturbance and actuator fault simultaneously. Then, an FTC strategy consisting of disturbance observer based control (DOBC, fault accommodation, and a mixed H2/H∞ controller is constructed to reconfigure the considered systems with disturbance rejection and attenuation performance. Finally, simulations for a flight control system are given to show the efficiency of the proposed approach.

Control Strategies for Islanded Microgrid using Enhanced Hierarchical Control Structure with Multiple Current-Loop Damping Schemes

DEFF Research Database (Denmark)

Han, Yang; Shen, Pan; Zhao, Xin

2017-01-01

In this paper, the modeling, controller design, and stability analysis of the islanded microgrid (MG) using enhanced hierarchical control structure with multiple current loop damping schemes is proposed. The islanded MG is consisted of the parallel-connected voltage source inverters using LCL...... output filters, and the proposed control structure includes: the primary control with additional phase-shift loop, the secondary control for voltage amplitude and frequency restoration, the virtual impedance loops which contains virtual positive- and negative-sequence impedance loops at fundamental...... frequency, and virtual variable harmonic impedance loop at harmonic frequencies, and the inner voltage and current loop controllers. A small-signal model for the primary and secondary controls with additional phase-shift loop is presented, which shows an over-damped feature from eigenvalue analysis...

Flight controller design of unmanned airplane for radiation monitoring system via structured robust controller design using multiple model approach. Radiation monitoring flight in Namie-machi in Fukushima prefecture

International Nuclear Information System (INIS)

Sato, Masayuki; Muraoka, Koji; Hozumi, Koki; Sanada, Yukihisa; Yamada, Tsutomu; Torii, Tatsuo

2015-01-01

Due to the tragic accident of radioactive contaminant spread from Fukushima Dai-ichi nuclear power plant, the necessity of unmanned systems for radiation monitoring has been increasing. This paper concerns the flight controller design of an unmanned airplane which has been developed for radiation monitoring around the power plant. The flight controller consists of conventional control elements, i.e. Stability/Control Augmentation System (S/CAS) with PI controllers and guidance loops with PID controllers. The gains in these controllers are designed by minimizing appropriately defined cost functions for several possible models and disturbances to produce structured robust flight controllers. (This method is called as 'multiple model approach'.) Control performance of our flight controller was evaluated through flight tests and a primitive flight of radiation monitoring in Namie-machi in Fukushima prefecture was conducted in Jan. 2014. Flight results are included in this paper. (author)

Real-Time Optimal Flood Control Decision Making and Risk Propagation Under Multiple Uncertainties

Science.gov (United States)

Zhu, Feilin; Zhong, Ping-An; Sun, Yimeng; Yeh, William W.-G.

2017-12-01

Multiple uncertainties exist in the optimal flood control decision-making process, presenting risks involving flood control decisions. This paper defines the main steps in optimal flood control decision making that constitute the Forecast-Optimization-Decision Making (FODM) chain. We propose a framework for supporting optimal flood control decision making under multiple uncertainties and evaluate risk propagation along the FODM chain from a holistic perspective. To deal with uncertainties, we employ stochastic models at each link of the FODM chain. We generate synthetic ensemble flood forecasts via the martingale model of forecast evolution. We then establish a multiobjective stochastic programming with recourse model for optimal flood control operation. The Pareto front under uncertainty is derived via the constraint method coupled with a two-step process. We propose a novel SMAA-TOPSIS model for stochastic multicriteria decision making. Then we propose the risk assessment model, the risk of decision-making errors and rank uncertainty degree to quantify the risk propagation process along the FODM chain. We conduct numerical experiments to investigate the effects of flood forecast uncertainty on optimal flood control decision making and risk propagation. We apply the proposed methodology to a flood control system in the Daduhe River basin in China. The results indicate that the proposed method can provide valuable risk information in each link of the FODM chain and enable risk-informed decisions with higher reliability.

Conceptual design of multiple parallel switching controller

International Nuclear Information System (INIS)

Ugolini, D.; Yoshikawa, S.; Ozawa, K.

1996-01-01

This paper discusses the conceptual design and the development of a preliminary model of a multiple parallel switching (MPS) controller. The introduction of several advanced controllers has widened and improved the control capability of nonlinear dynamical systems. However, it is not possible to uniquely define a controller that always outperforms the others, and, in many situations, the controller providing the best control action depends on the operating conditions and on the intrinsic properties and behavior of the controlled dynamical system. The desire to combine the control action of several controllers with the purpose to continuously attain the best control action has motivated the development of the MPS controller. The MPS controller consists of a number of single controllers acting in parallel and of an artificial intelligence (AI) based selecting mechanism. The AI selecting mechanism analyzes the output of each controller and implements the one providing the best control performance. An inherent property of the MPS controller is the possibility to discard unreliable controllers while still being able to perform the control action. To demonstrate the feasibility and the capability of the MPS controller the simulation of the on-line operation control of a fast breeder reactor (FBR) evaporator is presented. (author)

Modeling, Control, and Numerical Simulations of a Novel Binary-Controlled Variable Stiffness Actuator (BcVSA

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Irfan Hussain

2018-06-01

Full Text Available This research work aims at realizing a new compliant robotic actuator for safe human-robotic interaction. In this paper, we present the modeling, control, and numerical simulations of a novel Binary-Controlled Variable Stiffness Actuator (BcVSA aiming to be used for the development of a novel compliant robotic manipulator. BcVSA is the proof of concept of the active revolute joint with the variable recruitment of series-parallel elastic elements. We briefly recall the basic design principle which is based on a stiffness varying mechanism consisting of a motor, three inline clutches, and three torsional springs with stiffness values (K0, 2K0, 4K0 connected to the load shaft and the motor shaft through two planetary sun gear trains with ratios (4:1, 4:1 respectively. We present the design concept, stiffness and dynamic modeling, and control of our BcVSA. We implemented three kinds of Multiple Model Predictive Control (MPC to control our actuator. The main motivation of choosing this controller lies in the fact that working principle of multiple MPC and multiple states space representation (stiffness level of our actuator share similar interests. In particular, we implemented Multiple MPC, Multiple Explicit MPC, and Approximated Multiple Explicit MPC. Numerical simulations are performed in order to evaluate their effectiveness for the future experiments on the prototype of our actuator. The simulation results showed that the Multiple MPC, and the Multiple Explicit MPC have similar results from the robustness point of view. On the other hand, the robustness performance of Approximated Multiple Explicit MPC is not good as compared to other controllers but it works in the offline framework while having the capability to compute the sub-optimal results. We also performed the comparison of MPC based controllers with the Computed Torque Control (CTC, and Linear Quadratic Regulator (LQR. In future, we are planning to test the presented approach on the

Nonresonant Multiple-Pulse Control of Molecular Motions in Liquid

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Nikiforov V.G.

2015-01-01

Full Text Available We propose the implementation of the multiple-pulse excitation for manipulation of the molecular contributions to the optically-heterodyne-detected optical-Kerr-effect. The key parameters controlling the specificity of the multiple-pulse excitation scenarios are the pulses durations, the delays between pulses, the relation between the pump pulses amplitudes and the pulses polarizations. We model the high-order optical responses and consider some principles of the scenarios construction. We show that it is possible to adjust the excitation scenario in such a way that the some responses can be removed from detected signal along with the enhancement of the interested response amplitude. The theoretical analysis and first experimental data reveal that the multiple-pulse excitation technique can be useful for the selective spectroscopy of the molecular vibrations and rotations in liquid.

Intraintestinal drainage as a damage control surgery adjunct in a hypothermic traumatic shock swine model with multiple bowel perforations.

Science.gov (United States)

Ji, Wu; Ding, Weiwei; Liu, Xingdong; Kao, Xiaomin; Xu, Xingwei; Li, Ning; Li, Jieshou

2014-11-01

Temporary bowel ligation (TL) has been proposed to prevent contamination as a damage control procedure in multiple bowel perforations. However, bacteria translocation and intestinal ischemia may develop in a prolonged duration. We here hypothesized that intraintestinal drainage combined with temporary ligation (D-TL) would decrease intestinal injury and improve survivals in a gunshot multiple bowel perforation swine model in the setting of a damage control surgery. The abdomen was shot one time with an experimental modified gun whereas pigs were hemorrhaged to a mean arterial pressure of 40 mm Hg and maintained in shock for 40 min. Cold lactated Ringer solution was gradually infused to induce hypothermia. Animals were randomized to primary anastomosis, TL and intraintestinal D-TL groups (n = 8). Animals were resuscitated for 12 h with the shed blood and lactated Ringer solution. Delayed anastomosis was performed in TL and D-TL animals after resuscitation. Surviving animals were humanely killed 24 h after operation. Systemic hemodynamic parameters were recorded and blood samples were obtained for biochemical assays. Intra-abdominal pressure, portal vein and peripheral vein bacterial cultures, small intestine hematoxylin-eosin staining, and transmission electron microscopy examination were performed at 0, 2, 6, 12, and 24 h after the surgery. All animals suffered extreme physiologic conditions as follows: hypothermia, severe acidosis, hypotension, and depressed cardiac output. Compared with the primary anastomosis and TL group, D-TL animals required less resuscitation fluid, suffered a lower intra-abdominal hypertension and bacterial translocation, normalized lactate levels faster, had lower serum creatine kinase, aspartate aminotransferase levels and tissue TNF-α level, and nuclear factor-kB activations and thus had greater early survival. Compared with primary intestinal anastomosis and TL, rapid bowel ligation combined with intraintestinal drainage as a damage

Robust control design verification using the modular modeling system

International Nuclear Information System (INIS)

Edwards, R.M.; Ben-Abdennour, A.; Lee, K.Y.

1991-01-01

The Modular Modeling System (B ampersand W MMS) is being used as a design tool to verify robust controller designs for improving power plant performance while also providing fault-accommodating capabilities. These controllers are designed based on optimal control theory and are thus model based controllers which are targeted for implementation in a computer based digital control environment. The MMS is being successfully used to verify that the controllers are tolerant of uncertainties between the plant model employed in the controller and the actual plant; i.e., that they are robust. The two areas in which the MMS is being used for this purpose is in the design of (1) a reactor power controller with improved reactor temperature response, and (2) the design of a multiple input multiple output (MIMO) robust fault-accommodating controller for a deaerator level and pressure control problem

Multiple-Vehicle Longitudinal Collision Mitigation by Coordinated Brake Control

Directory of Open Access Journals (Sweden)

Xiao-Yun Lu

2014-01-01

Full Text Available Rear-end collision often leads to serious casualties and traffic congestion. The consequences are even worse for multiple-vehicle collision. Many previous works focused on collision warning and avoidance strategies of two consecutive vehicles based on onboard sensor detection only. This paper proposes a centralized control strategy for multiple vehicles to minimize the impact of multiple-vehicle collision based on vehicle-to-vehicle communication technique. The system is defined as a coupled group of vehicles with wireless communication capability and short following distances. The safety relationship can be represented as lower bound limit on deceleration of the first vehicle and upper bound on maximum deceleration of the last vehicle. The objective is to determine the desired deceleration for each vehicle such that the total impact energy is minimized at each time step. The impact energy is defined as the relative kinetic energy between a consecutive pair of vehicles (approaching only. Model predictive control (MPC framework is used to formulate the problem to be constrained quadratic programming. Simulations show its effectiveness on collision mitigation. The developed algorithm has the potential to be used for progressive market penetration of connected vehicles in practice.

Development of Physics and Control of Multiple Forcing Mechanisms for the Alaska Tsunami Forecast Model

Science.gov (United States)

Bahng, B.; Whitmore, P.; Macpherson, K. A.; Knight, W. R.

2016-12-01

The Alaska Tsunami Forecast Model (ATFM) is a numerical model used to forecast propagation and inundation of tsunamis generated by earthquakes or other mechanisms in either the Pacific Ocean, Atlantic Ocean or Gulf of Mexico. At the U.S. National Tsunami Warning Center (NTWC), the use of the model has been mainly for tsunami pre-computation due to earthquakes. That is, results for hundreds of hypothetical events are computed before alerts, and are accessed and calibrated with observations during tsunamis to immediately produce forecasts. The model has also been used for tsunami hindcasting due to submarine landslides and due to atmospheric pressure jumps, but in a very case-specific and somewhat limited manner. ATFM uses the non-linear, depth-averaged, shallow-water equations of motion with multiply nested grids in two-way communications between domains of each parent-child pair as waves approach coastal waters. The shallow-water wave physics is readily applicable to all of the above tsunamis as well as to tides. Recently, the model has been expanded to include multiple forcing mechanisms in a systematic fashion, and to enhance the model physics for non-earthquake events.ATFM is now able to handle multiple source mechanisms, either individually or jointly, which include earthquake, submarine landslide, meteo-tsunami and tidal forcing. As for earthquakes, the source can be a single unit source or multiple, interacting source blocks. Horizontal slip contribution can be added to the sea-floor displacement. The model now includes submarine landslide physics, modeling the source either as a rigid slump, or as a viscous fluid. Additional shallow-water physics have been implemented for the viscous submarine landslides. With rigid slumping, any trajectory can be followed. As for meteo-tsunami, the forcing mechanism is capable of following any trajectory shape. Wind stress physics has also been implemented for the meteo-tsunami case, if required. As an example of multiple

A retrospective likelihood approach for efficient integration of multiple omics factors in case-control association studies.

Science.gov (United States)

Balliu, Brunilda; Tsonaka, Roula; Boehringer, Stefan; Houwing-Duistermaat, Jeanine

2015-03-01

Integrative omics, the joint analysis of outcome and multiple types of omics data, such as genomics, epigenomics, and transcriptomics data, constitute a promising approach for powerful and biologically relevant association studies. These studies often employ a case-control design, and often include nonomics covariates, such as age and gender, that may modify the underlying omics risk factors. An open question is how to best integrate multiple omics and nonomics information to maximize statistical power in case-control studies that ascertain individuals based on the phenotype. Recent work on integrative omics have used prospective approaches, modeling case-control status conditional on omics, and nonomics risk factors. Compared to univariate approaches, jointly analyzing multiple risk factors with a prospective approach increases power in nonascertained cohorts. However, these prospective approaches often lose power in case-control studies. In this article, we propose a novel statistical method for integrating multiple omics and nonomics factors in case-control association studies. Our method is based on a retrospective likelihood function that models the joint distribution of omics and nonomics factors conditional on case-control status. The new method provides accurate control of Type I error rate and has increased efficiency over prospective approaches in both simulated and real data. © 2015 Wiley Periodicals, Inc.

Use of wiener nonlinear MPC to control a CSTR with multiple steady state

OpenAIRE

Lusson Cervantes, A.; Agamennoni, O.E.; Figueroa, J.L.

2003-01-01

In this paper a Nonlinear Model Predictive Control based on a Wiener Model with a Piecewise Linear gain is presented. The major advantages of this algorithm is that it retains all the interesting properties of the classical linear MPC and the computations are easy to solve due to the canonical structure of the nonlinear gain. The proposed control scheme is applied to a nonlinear CSTR that presents multiple steady states.

Multiple Indicator Stationary Time Series Models.

Science.gov (United States)

Sivo, Stephen A.

2001-01-01

Discusses the propriety and practical advantages of specifying multivariate time series models in the context of structural equation modeling for time series and longitudinal panel data. For time series data, the multiple indicator model specification improves on classical time series analysis. For panel data, the multiple indicator model…

Multiple Property Cross Direction Control of Paper Machines

Directory of Open Access Journals (Sweden)

Markku Ohenoja

2011-07-01

Full Text Available Cross direction (CD control in sheet-forming process forms a challenging problem with high dimensions. Accounting the interactions between different properties and actuators, the dimensionality increases further and also computational issues arise. We present a multiple property controller feasible to be used especially with imaging measurements that provide high sampling frequency and therefore enable short control interval. The simulation results state the benefits of multiple property CD control over single property control and single property control using full feedforward compensation. The controller presented may also be tuned in automated manner and the results demonstrate the effect of tuning on input saturation.

Mathematical Modeling of Loop Heat Pipes with Multiple Capillary Pumps and Multiple Condensers. Part 1; Stead State Stimulations

Science.gov (United States)

Hoang, Triem T.; OConnell, Tamara; Ku, Jentung

2004-01-01

Loop Heat Pipes (LHPs) have proven themselves as reliable and robust heat transport devices for spacecraft thermal control systems. So far, the LHPs in earth-orbit satellites perform very well as expected. Conventional LHPs usually consist of a single capillary pump for heat acquisition and a single condenser for heat rejection. Multiple pump/multiple condenser LHPs have shown to function very well in ground testing. Nevertheless, the test results of a dual pump/condenser LHP also revealed that the dual LHP behaved in a complicated manner due to the interaction between the pumps and condensers. Thus it is redundant to say that more research is needed before they are ready for 0-g deployment. One research area that perhaps compels immediate attention is the analytical modeling of LHPs, particularly the transient phenomena. Modeling a single pump/single condenser LHP is difficult enough. Only a handful of computer codes are available for both steady state and transient simulations of conventional LHPs. No previous effort was made to develop an analytical model (or even a complete theory) to predict the operational behavior of the multiple pump/multiple condenser LHP systems. The current research project offered a basic theory of the multiple pump/multiple condenser LHP operation. From it, a computer code was developed to predict the LHP saturation temperature in accordance with the system operating and environmental conditions.

Robust anti-synchronization of uncertain chaotic systems based on multiple-kernel least squares support vector machine modeling

International Nuclear Information System (INIS)

Chen Qiang; Ren Xuemei; Na Jing

2011-01-01

Highlights: Model uncertainty of the system is approximated by multiple-kernel LSSVM. Approximation errors and disturbances are compensated in the controller design. Asymptotical anti-synchronization is achieved with model uncertainty and disturbances. Abstract: In this paper, we propose a robust anti-synchronization scheme based on multiple-kernel least squares support vector machine (MK-LSSVM) modeling for two uncertain chaotic systems. The multiple-kernel regression, which is a linear combination of basic kernels, is designed to approximate system uncertainties by constructing a multiple-kernel Lagrangian function and computing the corresponding regression parameters. Then, a robust feedback control based on MK-LSSVM modeling is presented and an improved update law is employed to estimate the unknown bound of the approximation error. The proposed control scheme can guarantee the asymptotic convergence of the anti-synchronization errors in the presence of system uncertainties and external disturbances. Numerical examples are provided to show the effectiveness of the proposed method.

Phase transitions in distributed control systems with multiplicative noise

Science.gov (United States)

Allegra, Nicolas; Bamieh, Bassam; Mitra, Partha; Sire, Clément

2018-01-01

Contemporary technological challenges often involve many degrees of freedom in a distributed or networked setting. Three aspects are notable: the variables are usually associated with the nodes of a graph with limited communication resources, hindering centralized control; the communication is subject to noise; and the number of variables can be very large. These three aspects make tools and techniques from statistical physics particularly suitable for the performance analysis of such networked systems in the limit of many variables (analogous to the thermodynamic limit in statistical physics). Perhaps not surprisingly, phase-transition like phenomena appear in these systems, where a sharp change in performance can be observed with a smooth parameter variation, with the change becoming discontinuous or singular in the limit of infinite system size. In this paper, we analyze the so called network consensus problem, prototypical of the above considerations, that has previously been analyzed mostly in the context of additive noise. We show that qualitatively new phase-transition like phenomena appear for this problem in the presence of multiplicative noise. Depending on dimensions, and on the presence or absence of a conservation law, the system performance shows a discontinuous change at a threshold value of the multiplicative noise strength. In the absence of the conservation law, and for graph spectral dimension less than two, the multiplicative noise threshold (the stability margin of the control problem) is zero. This is reminiscent of the absence of robust controllers for certain classes of centralized control problems. Although our study involves a ‘toy’ model, we believe that the qualitative features are generic, with implications for the robust stability of distributed control systems, as well as the effect of roundoff errors and communication noise on distributed algorithms.

The Dynamics and Sliding Mode Control of Multiple Cooperative Welding Robot Manipulators

Directory of Open Access Journals (Sweden)

Bin Zi

2012-08-01

Full Text Available This paper deals with the design, dynamic modelling and sliding mode control of multiple cooperative welding robot manipulators (MWRMs. The MWRMs can handle complex tasks that are difficult or even impossible for a single manipulator. The kinematics and dynamics of the MWRMs are studied on the basis of the Denavit-Hartenberg and Lagrange method. Following that, considering the MWRM system with nonlinear and unknown disturbances, a non-singular terminal sliding mode control strategy is designed. By means of the Lyapunov function, the stability of the controller is proved. Simulation results indicate that the good control performance of the MWRMs is achieved by the non-singular terminal sliding mode controller, which also illustrates the correctness of the dynamic modelling and effectiveness of the proposed control strategy.

Correlations in multiple production on nuclei and Glauber model of multiple scattering

International Nuclear Information System (INIS)

Zoller, V.R.; Nikolaev, N.N.

1982-01-01

Critical analysis of possibility for describing correlation phenomena during multiple production on nuclei within the framework of the Glauber multiple seattering model generalized for particle production processes with Capella, Krziwinski and Shabelsky has been performed. It was mainly concluded that the suggested generalization of the Glauber model gives dependences on Ng(Np) (where Ng-the number of ''grey'' tracess, and Np-the number of protons flying out of nucleus) and, eventually, on #betta# (where #betta#-the number of intranuclear interactions) contradicting experience. Independent of choice of relation between #betta# and Ng(Np) in the model the rapidity corrletor Rsub(eta) is overstated in the central region and understated in the region of nucleus fragmentation. In mean multiplicities these two contradictions of experience are disguised with random compensation and agreement with experience in Nsub(S) (function of Ng) cannot be an argument in favour of the model. It is concluded that eiconal model doesn't permit to quantitatively describe correlation phenomena during the multiple production on nuclei

Aspects of modelling and control of bioprocesses

Energy Technology Data Exchange (ETDEWEB)

Zhang, Xiachang

1995-12-31

The modelling and control of bioprocesses are the main subjects in this thesis. Different modelling approaches are proposed for different purposes in various bioprocesses. A conventional global model was constructed for a very complex mammalian cell culture process. A new concept of functional state and a multiple model (local models) approach were used for modelling the fed-batch baker`s yeast process for monitoring and control purposes. Finally, a combination of conventional electrical and biological models was used to simulate and to control a microbial fuel cell process. In the thesis, a yeast growth process was taken as an example to demonstrate the usefulness of the functional state concept and local models. The functional states were first defined according to the yeast metabolism. The process was then described by a set of simple local models. In different functional states, different local models were used. On the other hand, the on-line estimation of functional state and biomass of the process was discussed for process control purpose. As a consequence, both the functional state concept and the multiple model approach were applied for fuzzy logic control of yeast growth process. A fuzzy factor was calculated on the basis of a knowledge-based expert system and fuzzy logic rules. The factor was used to correct an ideal substrate feed rate. In the last part of the thesis, microbial fuel cell processes were studied. A microbial fuel cell is a device for direct conversion of chemical energy to electrical energy by using micro-organisms as catalysts. A combined model including conventional electrical and biological models was constructed for the process based on the biological and electrochemical phenomena

Aspects of modelling and control of bioprocesses

Energy Technology Data Exchange (ETDEWEB)

Zhang, Xiachang

1996-12-31

The modelling and control of bioprocesses are the main subjects in this thesis. Different modelling approaches are proposed for different purposes in various bioprocesses. A conventional global model was constructed for a very complex mammalian cell culture process. A new concept of functional state and a multiple model (local models) approach were used for modelling the fed-batch baker`s yeast process for monitoring and control purposes. Finally, a combination of conventional electrical and biological models was used to simulate and to control a microbial fuel cell process. In the thesis, a yeast growth process was taken as an example to demonstrate the usefulness of the functional state concept and local models. The functional states were first defined according to the yeast metabolism. The process was then described by a set of simple local models. In different functional states, different local models were used. On the other hand, the on-line estimation of functional state and biomass of the process was discussed for process control purpose. As a consequence, both the functional state concept and the multiple model approach were applied for fuzzy logic control of yeast growth process. A fuzzy factor was calculated on the basis of a knowledge-based expert system and fuzzy logic rules. The factor was used to correct an ideal substrate feed rate. In the last part of the thesis, microbial fuel cell processes were studied. A microbial fuel cell is a device for direct conversion of chemical energy to electrical energy by using micro-organisms as catalysts. A combined model including conventional electrical and biological models was constructed for the process based on the biological and electrochemical phenomena

Power Hardware-in-the-Loop Testing of Multiple Photovoltaic Inverters' Volt-Var Control with Real-Time Grid Model

Energy Technology Data Exchange (ETDEWEB)

Chakraborty, Sudipta; Nelson, Austin; Hoke, Anderson

2016-12-12

Traditional testing methods fall short in evaluating interactions between multiple smart inverters providing advanced grid support functions due to the fact that such interactions largely depend on their placements on the electric distribution systems with impedances between them. Even though significant concerns have been raised by the utilities on the effects of such interactions, little effort has been made to evaluate them. In this paper, power hardware-in-the-loop (PHIL) based testing was utilized to evaluate autonomous volt-var operations of multiple smart photovoltaic (PV) inverters connected to a simple distribution feeder model. The results provided in this paper show that depending on volt-var control (VVC) parameters and grid parameters, interaction between inverters and between the inverter and the grid is possible in some extreme cases with very high VVC slopes, fast response times and large VVC response delays.

Multiple sclerosis in the Faroe Islands. 7. Results of a case control questionnaire with multiple controls

DEFF Research Database (Denmark)

Kurtzke, J F; Hyllested, K; Arbuckle, J D

1997-01-01

Detailed questionnaires were completed in 1978-79 by 23 of the 28 then known resident Faroese multiple sclerosis (MS) patients and 127 controls. These controls were divided into 69 Group A (patient sibs and other relatives), 37 Group B (matched neighbor controls, their spouses and sibs, plus...... facilities, and nature of house construction or heating. Detailed dietary histories, available for half the subjects, revealed no differences, cases versus controls, for four age periods between age 0 and 30 years, and for 16 specified foodstuffs. Animal exposures showed overall no consistent differences...

Distributed Autonomous Control of Multiple Spacecraft During Close Proximity Operations

National Research Council Canada - National Science Library

McCamish, Shawn B

2007-01-01

This research contributes to multiple spacecraft control by developing an autonomous distributed control algorithm for close proximity operations of multiple spacecraft systems, including rendezvous...

Finite-time tracking control for multiple non-holonomic mobile robots based on visual servoing

Science.gov (United States)

Ou, Meiying; Li, Shihua; Wang, Chaoli

2013-12-01

This paper investigates finite-time tracking control problem of multiple non-holonomic mobile robots via visual servoing. It is assumed that the pinhole camera is fixed to the ceiling, and camera parameters are unknown. The desired reference trajectory is represented by a virtual leader whose states are available to only a subset of the followers, and the followers have only interaction. First, the camera-objective visual kinematic model is introduced by utilising the pinhole camera model for each mobile robot. Second, a unified tracking error system between camera-objective visual servoing model and desired reference trajectory is introduced. Third, based on the neighbour rule and by using finite-time control method, continuous distributed cooperative finite-time tracking control laws are designed for each mobile robot with unknown camera parameters, where the communication topology among the multiple mobile robots is assumed to be a directed graph. Rigorous proof shows that the group of mobile robots converges to the desired reference trajectory in finite time. Simulation example illustrates the effectiveness of our method.

Process control for sheet-metal stamping process modeling, controller design and shop-floor implementation

CERN Document Server

Lim, Yongseob; Ulsoy, A Galip

2014-01-01

Process Control for Sheet-Metal Stamping presents a comprehensive and structured approach to the design and implementation of controllers for the sheet metal stamping process. The use of process control for sheet-metal stamping greatly reduces defects in deep-drawn parts and can also yield large material savings from reduced scrap. Sheet-metal forming is a complex process and most often characterized by partial differential equations that are numerically solved using finite-element techniques. In this book, twenty years of academic research are reviewed and the resulting technology transitioned to the industrial environment. The sheet-metal stamping process is modeled in a manner suitable for multiple-input multiple-output control system design, with commercially available sensors and actuators. These models are then used to design adaptive controllers and real-time controller implementation is discussed. Finally, experimental results from actual shopfloor deployment are presented along with ideas for further...

Model predictive control of the solid oxide fuel cell stack temperature with models based on experimental data

Science.gov (United States)

Pohjoranta, Antti; Halinen, Matias; Pennanen, Jari; Kiviaho, Jari

2015-03-01

Generalized predictive control (GPC) is applied to control the maximum temperature in a solid oxide fuel cell (SOFC) stack and the temperature difference over the stack. GPC is a model predictive control method and the models utilized in this work are ARX-type (autoregressive with extra input), multiple input-multiple output, polynomial models that were identified from experimental data obtained from experiments with a complete SOFC system. The proposed control is evaluated by simulation with various input-output combinations, with and without constraints. A comparison with conventional proportional-integral-derivative (PID) control is also made. It is shown that if only the stack maximum temperature is controlled, a standard PID controller can be used to obtain output performance comparable to that obtained with the significantly more complex model predictive controller. However, in order to control the temperature difference over the stack, both the stack minimum and the maximum temperature need to be controlled and this cannot be done with a single PID controller. In such a case the model predictive controller provides a feasible and effective solution.

Linear systems with unstructured multiplicative uncertainty: Modeling and robust stability analysis.

Directory of Open Access Journals (Sweden)

Radek Matušů

Full Text Available This article deals with continuous-time Linear Time-Invariant (LTI Single-Input Single-Output (SISO systems affected by unstructured multiplicative uncertainty. More specifically, its aim is to present an approach to the construction of uncertain models based on the appropriate selection of a nominal system and a weight function and to apply the fundamentals of robust stability investigation for considered sort of systems. The initial theoretical parts are followed by three extensive illustrative examples in which the first order time-delay, second order and third order plants with parametric uncertainty are modeled as systems with unstructured multiplicative uncertainty and subsequently, the robust stability of selected feedback loops containing constructed models and chosen controllers is analyzed and obtained results are discussed.

Full-order optimal compensators for flow control: the multiple inputs case

Science.gov (United States)

Semeraro, Onofrio; Pralits, Jan O.

2018-03-01

Flow control has been the subject of numerous experimental and theoretical works. We analyze full-order, optimal controllers for large dynamical systems in the presence of multiple actuators and sensors. The full-order controllers do not require any preliminary model reduction or low-order approximation: this feature allows us to assess the optimal performance of an actuated flow without relying on any estimation process or further hypothesis on the disturbances. We start from the original technique proposed by Bewley et al. (Meccanica 51(12):2997-3014, 2016. https://doi.org/10.1007/s11012-016-0547-3), the adjoint of the direct-adjoint (ADA) algorithm. The algorithm is iterative and allows bypassing the solution of the algebraic Riccati equation associated with the optimal control problem, typically infeasible for large systems. In this numerical work, we extend the ADA iteration into a more general framework that includes the design of controllers with multiple, coupled inputs and robust controllers (H_{∞} methods). First, we demonstrate our results by showing the analytical equivalence between the full Riccati solutions and the ADA approximations in the multiple inputs case. In the second part of the article, we analyze the performance of the algorithm in terms of convergence of the solution, by comparing it with analogous techniques. We find an excellent scalability with the number of inputs (actuators), making the method a viable way for full-order control design in complex settings. Finally, the applicability of the algorithm to fluid mechanics problems is shown using the linearized Kuramoto-Sivashinsky equation and the Kármán vortex street past a two-dimensional cylinder.

Integrated production planning and control: A multi-objective optimization model

Directory of Open Access Journals (Sweden)

Cheng Wang

2013-09-01

Full Text Available Purpose: Production planning and control has crucial impact on the production and business activities of enterprise. Enterprise Resource Planning (ERP is the most popular resources planning and management system, however there are some shortcomings and deficiencies in the production planning and control because its core component is still the Material Requirements Planning (MRP. For the defects of ERP system, many local improvement and optimization schemes have been proposed, and improve the feasibility and practicality of the plan in some extent, but study considering the whole planning system optimization in the multiple performance management objectives and achieving better application performance is less. The purpose of this paper is to propose a multi-objective production planning optimization model Based on the point of view of the integration of production planning and control, in order to achieve optimization and control of enterprise manufacturing management. Design/methodology/approach: On the analysis of ERP planning system’s defects and disadvantages, and related research and literature, a multi-objective production planning optimization model is proposed, in addition to net demand and capacity, multiple performance management objectives, such as on-time delivery, production balance, inventory, overtime production, are considered incorporating into the examination scope of the model, so that the manufacturing process could be management and controlled Optimally between multiple objectives. The validity and practicability of the model will be verified by the instance in the last part of the paper. Findings: The main finding is that production planning management of manufacturing enterprise considers not only the capacity and materials, but also a variety of performance management objectives in the production process, and building a multi-objective optimization model can effectively optimize the management and control of enterprise

Testing for Nonuniform Differential Item Functioning with Multiple Indicator Multiple Cause Models

Science.gov (United States)

Woods, Carol M.; Grimm, Kevin J.

2011-01-01

In extant literature, multiple indicator multiple cause (MIMIC) models have been presented for identifying items that display uniform differential item functioning (DIF) only, not nonuniform DIF. This article addresses, for apparently the first time, the use of MIMIC models for testing both uniform and nonuniform DIF with categorical indicators. A…

Modeling, Control and Coordination of Helicopter Systems

CERN Document Server

Ren, Beibei; Chen, Chang; Fua, Cheng-Heng; Lee, Tong Heng

2012-01-01

Modeling, Control and Coordination of Helicopter Systems provides a comprehensive treatment of helicopter systems, ranging from related nonlinear flight dynamic modeling and stability analysis to advanced control design for single helicopter systems, and also covers issues related to the coordination and formation control of multiple helicopter systems to achieve high performance tasks. Ensuring stability in helicopter flight is a challenging problem for nonlinear control design and development. This book is a valuable reference on modeling, control and coordination of helicopter systems,providing readers with practical solutions for the problems that still plague helicopter system design and implementation. Readers will gain a complete picture of helicopters at the systems level, as well as a better understanding of the technical intricacies involved. This book also: Presents a complete picture of modeling, control and coordination for helicopter systems Provides a modeling platform for a general class of ro...

The reverse effects of random perturbation on discrete systems for single and multiple population models

International Nuclear Information System (INIS)

Kang, Li; Tang, Sanyi

2016-01-01

Highlights: • The discrete single species and multiple species models with random perturbation are proposed. • The complex dynamics and interesting bifurcation behavior have been investigated. • The reverse effects of random perturbation on discrete systems have been discussed and revealed. • The main results can be applied for pest control and resources management. - Abstract: The natural species are likely to present several interesting and complex phenomena under random perturbations, which have been confirmed by simple mathematical models. The important questions are: how the random perturbations influence the dynamics of the discrete population models with multiple steady states or multiple species interactions? and is there any different effects for single species and multiple species models with random perturbation? To address those interesting questions, we have proposed the discrete single species model with two stable equilibria and the host-parasitoid model with Holling type functional response functions to address how the random perturbation affects the dynamics. The main results indicate that the random perturbation does not change the number of blurred orbits of the single species model with two stable steady states compared with results for the classical Ricker model with same random perturbation, but it can strength the stability. However, extensive numerical investigations depict that the random perturbation does not influence the complexities of the host-parasitoid models compared with the results for the models without perturbation, while it does increase the period of periodic orbits doubly. All those confirm that the random perturbation has a reverse effect on the dynamics of the discrete single and multiple population models, which could be applied in reality including pest control and resources management.

Power Allocation in Multiple Access Networks: Implementation Aspects via Verhulst and Perron-Frobenius Models

Directory of Open Access Journals (Sweden)

Fábio Engel de Camargo

2012-11-01

Full Text Available In this work, the Verhulst model and the Perron-Frobenius theorem are applied on the power control problem which is a concern in multiple access communication networks due to the multiple access interference. This paper deals with the performance versus complexity tradeoff of both power control algorithm (PCA, as well as highlights the computational cost aspects regarding the implementability of distributed PCA (DPCA version for both algorithms. As a proof-of-concept the DPCA implementation is carried out deploying a commercial point-floating DSP platform. Numerical results in terms of DSP cycles and computational time as well indicate a feasibility of implementing the PCA-Verhulst model in 2G and 3G cellular systems; b high computational cost for the PCA-Perron-Frobenius model.

Drag reduction of a car model by linear genetic programming control

Science.gov (United States)

Li, Ruiying; Noack, Bernd R.; Cordier, Laurent; Borée, Jacques; Harambat, Fabien

2017-08-01

We investigate open- and closed-loop active control for aerodynamic drag reduction of a car model. Turbulent flow around a blunt-edged Ahmed body is examined at ReH≈ 3× 105 based on body height. The actuation is performed with pulsed jets at all trailing edges (multiple inputs) combined with a Coanda deflection surface. The flow is monitored with 16 pressure sensors distributed at the rear side (multiple outputs). We apply a recently developed model-free control strategy building on genetic programming in Dracopoulos and Kent (Neural Comput Appl 6:214-228, 1997) and Gautier et al. (J Fluid Mech 770:424-441, 2015). The optimized control laws comprise periodic forcing, multi-frequency forcing and sensor-based feedback including also time-history information feedback and combinations thereof. Key enabler is linear genetic programming (LGP) as powerful regression technique for optimizing the multiple-input multiple-output control laws. The proposed LGP control can select the best open- or closed-loop control in an unsupervised manner. Approximately 33% base pressure recovery associated with 22% drag reduction is achieved in all considered classes of control laws. Intriguingly, the feedback actuation emulates periodic high-frequency forcing. In addition, the control identified automatically the only sensor which listens to high-frequency flow components with good signal to noise ratio. Our control strategy is, in principle, applicable to all multiple actuators and sensors experiments.

Optimization of Inventories for Multiple Companies by Fuzzy Control Method

OpenAIRE

Kawase, Koichi; Konishi, Masami; Imai, Jun

2008-01-01

In this research, Fuzzy control theory is applied to the inventory control of the supply chain between multiple companies. The proposed control method deals with the amountof inventories expressing supply chain between multiple companies. Referring past demand and tardiness, inventory amounts of raw materials are determined by Fuzzy inference. The method that an appropriate inventory control becomes possible optimizing fuzzy control gain by using SA method for Fuzzy control. The variation of ...

Neural-adaptive control of single-master-multiple-slaves teleoperation for coordinated multiple mobile manipulators with time-varying communication delays and input uncertainties.

Science.gov (United States)

Li, Zhijun; Su, Chun-Yi

2013-09-01

In this paper, adaptive neural network control is investigated for single-master-multiple-slaves teleoperation in consideration of time delays and input dead-zone uncertainties for multiple mobile manipulators carrying a common object in a cooperative manner. Firstly, concise dynamics of teleoperation systems consisting of a single master robot, multiple coordinated slave robots, and the object are developed in the task space. To handle asymmetric time-varying delays in communication channels and unknown asymmetric input dead zones, the nonlinear dynamics of the teleoperation system are transformed into two subsystems through feedback linearization: local master or slave dynamics including the unknown input dead zones and delayed dynamics for the purpose of synchronization. Then, a model reference neural network control strategy based on linear matrix inequalities (LMI) and adaptive techniques is proposed. The developed control approach ensures that the defined tracking errors converge to zero whereas the coordination internal force errors remain bounded and can be made arbitrarily small. Throughout this paper, stability analysis is performed via explicit Lyapunov techniques under specific LMI conditions. The proposed adaptive neural network control scheme is robust against motion disturbances, parametric uncertainties, time-varying delays, and input dead zones, which is validated by simulation studies.

Model predictive control of a wind turbine modelled in Simpack

International Nuclear Information System (INIS)

Jassmann, U; Matzke, D; Reiter, M; Abel, D; Berroth, J; Schelenz, R; Jacobs, G

2014-01-01

Wind turbines (WT) are steadily growing in size to increase their power production, which also causes increasing loads acting on the turbine's components. At the same time large structures, such as the blades and the tower get more flexible. To minimize this impact, the classical control loops for keeping the power production in an optimum state are more and more extended by load alleviation strategies. These additional control loops can be unified by a multiple-input multiple-output (MIMO) controller to achieve better balancing of tuning parameters. An example for MIMO control, which has been paid more attention to recently by wind industry, is Model Predictive Control (MPC). In a MPC framework a simplified model of the WT is used to predict its controlled outputs. Based on a user-defined cost function an online optimization calculates the optimal control sequence. Thereby MPC can intrinsically incorporate constraints e.g. of actuators. Turbine models used for calculation within the MPC are typically simplified. For testing and verification usually multi body simulations, such as FAST, BLADED or FLEX5 are used to model system dynamics, but they are still limited in the number of degrees of freedom (DOF). Detailed information about load distribution (e.g. inside the gearbox) cannot be provided by such models. In this paper a Model Predictive Controller is presented and tested in a co-simulation with SlMPACK, a multi body system (MBS) simulation framework used for detailed load analysis. The analysis are performed on the basis of the IME6.0 MBS WT model, described in this paper. It is based on the rotor of the NREL 5MW WT and consists of a detailed representation of the drive train. This takes into account a flexible main shaft and its main bearings with a planetary gearbox, where all components are modelled flexible, as well as a supporting flexible main frame. The wind loads are simulated using the NREL AERODYN v13 code which has been implemented as a routine

Model predictive control of a wind turbine modelled in Simpack

Science.gov (United States)

Jassmann, U.; Berroth, J.; Matzke, D.; Schelenz, R.; Reiter, M.; Jacobs, G.; Abel, D.

2014-06-01

Wind turbines (WT) are steadily growing in size to increase their power production, which also causes increasing loads acting on the turbine's components. At the same time large structures, such as the blades and the tower get more flexible. To minimize this impact, the classical control loops for keeping the power production in an optimum state are more and more extended by load alleviation strategies. These additional control loops can be unified by a multiple-input multiple-output (MIMO) controller to achieve better balancing of tuning parameters. An example for MIMO control, which has been paid more attention to recently by wind industry, is Model Predictive Control (MPC). In a MPC framework a simplified model of the WT is used to predict its controlled outputs. Based on a user-defined cost function an online optimization calculates the optimal control sequence. Thereby MPC can intrinsically incorporate constraints e.g. of actuators. Turbine models used for calculation within the MPC are typically simplified. For testing and verification usually multi body simulations, such as FAST, BLADED or FLEX5 are used to model system dynamics, but they are still limited in the number of degrees of freedom (DOF). Detailed information about load distribution (e.g. inside the gearbox) cannot be provided by such models. In this paper a Model Predictive Controller is presented and tested in a co-simulation with SlMPACK, a multi body system (MBS) simulation framework used for detailed load analysis. The analysis are performed on the basis of the IME6.0 MBS WT model, described in this paper. It is based on the rotor of the NREL 5MW WT and consists of a detailed representation of the drive train. This takes into account a flexible main shaft and its main bearings with a planetary gearbox, where all components are modelled flexible, as well as a supporting flexible main frame. The wind loads are simulated using the NREL AERODYN v13 code which has been implemented as a routine to

A nuclear data acquisition system flow control model

International Nuclear Information System (INIS)

Hack, S.N.

1988-01-01

A general Petri Net representation of a nuclear data acquisition system model is presented. This model provides for the unique requirements of a nuclear data acquisition system including the capabilities of concurrently acquiring asynchronous and synchronous data, of providing multiple priority levels of flow control arbitration, and of permitting multiple input sources to reside at the same priority without the problem of channel lockout caused by a high rate data source. Finally, a previously implemented gamma camera/physiological signal data acquisition system is described using the models presented

Coordinated voltage control for multiple wind plants in Eastern Wyoming. Analysis, field experience and validation

Energy Technology Data Exchange (ETDEWEB)

Miller, Nicholas; MacDowell, Jason; Chmiel, Gary; Konopinski, Ryan; Gautam, Durga [GE Energy, Schenectady, NY (United States); Laughter, Grant; Hagen, Dave [PacifiCorp., Salt Lake City, UT (United States)

2012-07-01

At high levels of wind power penetration, multiple wind plants may be the predominant generation resource over large geographic areas. Thus, not only do wind plants need to provide a high level of functionality, they must coordinate properly with each other. This paper describes the analysis and field testing of wind plant voltage controllers designed to improve system voltage performance through passive coordination. The described wind power plant controls can coordinate the real and reactive power response of multiple wind turbines and thereby make the plant function as a single ''grid friendly'' power generation source. For this application, involving seven large wind plants with predominantly GE wind turbines in Eastern Wyoming, the voltage portion of the controllers were configured and tuned to allow the collective reactive power response of multiple wind plants in the region to work well together. This paper presents the results of the initial configuration and tuning study, and the results of the subsequent field tuning and testing of the modified controls. The paper also presents some comparisons of the measured field performance with the stability simulation models, which show that the available wind plant models provide accurate, high fidelity results for actual operating conditions of commercial wind power plants. (orig.)

Stator for a rotating electrical machine having multiple control windings

Science.gov (United States)

Shah, Manoj R.; Lewandowski, Chad R.

2001-07-17

A rotating electric machine is provided which includes multiple independent control windings for compensating for rotor imbalances and for levitating/centering the rotor. The multiple independent control windings are placed at different axial locations along the rotor to oppose forces created by imbalances at different axial locations along the rotor. The multiple control windings can also be used to levitate/center the rotor with a relatively small magnetic field per unit area since the rotor and/or the main power winding provides the bias field.

Controller Synthesis using Qualitative Models and Constraints

OpenAIRE

Ramamoorthy, Subramanian; Kuipers, Benjamin J

2004-01-01

Many engineering systems require the synthesis of global behaviors in nonlinear dynamical systems. Multiple model approaches to control design make it possible to synthesize robust and optimal versions of such global behaviors. We propose a methodology called Qualitative Heterogeneous Control that enables this type of control design. This methodology is based on a separation of concerns between qualitative correctness and quantitative optimization. Qualitative sufficient conditions are derive...

Finite-Control-Set Model Predictive Control (FCS-MPC) for Islanded Hybrid Microgrids

OpenAIRE

Yi, Zhehan; Babqi, Abdulrahman J.; Wang, Yishen; Shi, Di; Etemadi, Amir H.; Wang, Zhiwei; Huang, Bibin

2018-01-01

Microgrids consisting of multiple distributed energy resources (DERs) provide a promising solution to integrate renewable energies, e.g., solar photovoltaic (PV) systems. Hybrid AC/DC microgrids leverage the merits of both AC and DC power systems. In this paper, a control strategy for islanded multi-bus hybrid microgrids is proposed based on the Finite-Control-Set Model Predictive Control (FCS-MPC) technologies. The control loops are expedited by predicting the future states and determining t...

All Set! Evidence of Simultaneous Attentional Control Settings for Multiple Target Colors

Science.gov (United States)

Irons, Jessica L.; Folk, Charles L.; Remington, Roger W.

2012-01-01

Although models of visual search have often assumed that attention can only be set for a single feature or property at a time, recent studies have suggested that it may be possible to maintain more than one attentional control setting. The aim of the present study was to investigate whether spatial attention could be guided by multiple attentional…

Modeling and optimization of a utility system containing multiple extractions steam turbines

International Nuclear Information System (INIS)

Luo, Xianglong; Zhang, Bingjian; Chen, Ying; Mo, Songping

2011-01-01

Complex turbines with multiple controlled and/or uncontrolled extractions are popularly used in the processing industry and cogeneration plants to provide steam of different levels, electric power, and driving power. To characterize thermodynamic behavior under varying conditions, nonlinear mathematical models are developed based on energy balance, thermodynamic principles, and semi-empirical equations. First, the complex turbine is decomposed into several simple turbines from the controlled extraction stages and modeled in series. THM (The turbine hardware model) developing concept is applied to predict the isentropic efficiency of the decomposed simple turbines. Stodola's formulation is also used to simulate the uncontrolled extraction steam parameters. The thermodynamic properties of steam and water are regressed through linearization or piece-wise linearization. Second, comparison between the simulated results using the proposed model and the data in the working condition diagram provided by the manufacturer is conducted over a wide range of operations. The simulation results yield small deviation from the data in the working condition diagram where the maximum modeling error is 0.87% among the compared seven operation conditions. Last, the optimization model of a utility system containing multiple extraction turbines is established and a detailed case is analyzed. Compared with the conventional operation strategy, a maximum of 5.47% of the total operation cost is saved using the proposed optimization model. -- Highlights: → We develop a complete simulation model for steam turbine with multiple extractions. → We test the simulation model using the performance data of commercial turbines. → The simulation error of electric power generation is no more than 0.87%. → We establish a utility system operational optimization model. → The optimal industrial operation scheme featured with 5.47% of cost saving.

Cognitive process modelling of controllers in en route air traffic control.

Science.gov (United States)

Inoue, Satoru; Furuta, Kazuo; Nakata, Keiichi; Kanno, Taro; Aoyama, Hisae; Brown, Mark

2012-01-01

In recent years, various efforts have been made in air traffic control (ATC) to maintain traffic safety and efficiency in the face of increasing air traffic demands. ATC is a complex process that depends to a large degree on human capabilities, and so understanding how controllers carry out their tasks is an important issue in the design and development of ATC systems. In particular, the human factor is considered to be a serious problem in ATC safety and has been identified as a causal factor in both major and minor incidents. There is, therefore, a need to analyse the mechanisms by which errors occur due to complex factors and to develop systems that can deal with these errors. From the cognitive process perspective, it is essential that system developers have an understanding of the more complex working processes that involve the cooperative work of multiple controllers. Distributed cognition is a methodological framework for analysing cognitive processes that span multiple actors mediated by technology. In this research, we attempt to analyse and model interactions that take place in en route ATC systems based on distributed cognition. We examine the functional problems in an ATC system from a human factors perspective, and conclude by identifying certain measures by which to address these problems. This research focuses on the analysis of air traffic controllers' tasks for en route ATC and modelling controllers' cognitive processes. This research focuses on an experimental study to gain a better understanding of controllers' cognitive processes in air traffic control. We conducted ethnographic observations and then analysed the data to develop a model of controllers' cognitive process. This analysis revealed that strategic routines are applicable to decision making.

Model predictive control classical, robust and stochastic

CERN Document Server

Kouvaritakis, Basil

2016-01-01

For the first time, a textbook that brings together classical predictive control with treatment of up-to-date robust and stochastic techniques. Model Predictive Control describes the development of tractable algorithms for uncertain, stochastic, constrained systems. The starting point is classical predictive control and the appropriate formulation of performance objectives and constraints to provide guarantees of closed-loop stability and performance. Moving on to robust predictive control, the text explains how similar guarantees may be obtained for cases in which the model describing the system dynamics is subject to additive disturbances and parametric uncertainties. Open- and closed-loop optimization are considered and the state of the art in computationally tractable methods based on uncertainty tubes presented for systems with additive model uncertainty. Finally, the tube framework is also applied to model predictive control problems involving hard or probabilistic constraints for the cases of multiplic...

Distributed Model Predictive Control for Active Power Control of Wind Farm

DEFF Research Database (Denmark)

Zhao, Haoran; Wu, Qiuwei; Rasmussen, Claus Nygaard

2014-01-01

This paper presents the active power control of a wind farm using the Distributed Model Predictive Controller (D- MPC) via dual decomposition. Different from the conventional centralized wind farm control, multiple objectives such as power reference tracking performance and wind turbine load can...... be considered to achieve a trade-off between them. Additionally, D- MPC is based on communication among the subsystems. Through the interaction among the neighboring subsystems, the global optimization could be achieved, which significantly reduces the computation burden. It is suitable for the modern large......-scale wind farm control....

Modeling Rabbit Responses to Single and Multiple Aerosol ...

Science.gov (United States)

Journal Article Survival models are developed here to predict response and time-to-response for mortality in rabbits following exposures to single or multiple aerosol doses of Bacillus anthracis spores. Hazard function models were developed for a multiple dose dataset to predict the probability of death through specifying dose-response functions and the time between exposure and the time-to-death (TTD). Among the models developed, the best-fitting survival model (baseline model) has an exponential dose-response model with a Weibull TTD distribution. Alternative models assessed employ different underlying dose-response functions and use the assumption that, in a multiple dose scenario, earlier doses affect the hazard functions of each subsequent dose. In addition, published mechanistic models are analyzed and compared with models developed in this paper. None of the alternative models that were assessed provided a statistically significant improvement in fit over the baseline model. The general approach utilizes simple empirical data analysis to develop parsimonious models with limited reliance on mechanistic assumptions. The baseline model predicts TTDs consistent with reported results from three independent high-dose rabbit datasets. More accurate survival models depend upon future development of dose-response datasets specifically designed to assess potential multiple dose effects on response and time-to-response. The process used in this paper to dev

Should researchers use single indicators, best indicators, or multiple indicators in structural equation models?

Directory of Open Access Journals (Sweden)

Hayduk Leslie A

2012-10-01

Full Text Available Abstract Background Structural equation modeling developed as a statistical melding of path analysis and factor analysis that obscured a fundamental tension between a factor preference for multiple indicators and path modeling’s openness to fewer indicators. Discussion Multiple indicators hamper theory by unnecessarily restricting the number of modeled latents. Using the few best indicators – possibly even the single best indicator of each latent – encourages development of theoretically sophisticated models. Additional latent variables permit stronger statistical control of potential confounders, and encourage detailed investigation of mediating causal mechanisms. Summary We recommend the use of the few best indicators. One or two indicators are often sufficient, but three indicators may occasionally be helpful. More than three indicators are rarely warranted because additional redundant indicators provide less research benefit than single indicators of additional latent variables. Scales created from multiple indicators can introduce additional problems, and are prone to being less desirable than either single or multiple indicators.

Multilateral Telecoordinated Control of Multiple Robots With Uncertain Kinematics.

Science.gov (United States)

Zhai, Di-Hua; Xia, Yuanqing

2017-06-06

This paper addresses the telecoordinated control of multiple robots in the simultaneous presence of asymmetric time-varying delays, nonpassive external forces, and uncertain kinematics/dynamics. To achieve the control objective, a neuroadaptive controller with utilizing prescribed performance control and switching control technique is developed, where the basic idea is to employ the concept of motion synchronization in each pair of master-slave robots and among all slave robots. By using the multiple Lyapunov-Krasovskii functionals method, the state-independent input-to-output practical stability of the closed-loop system is established. Compared with the previous approaches, the new design is straightforward and easier to implement and is applicable to a wider area. Simulation results on three pairs of three degrees-of-freedom robots confirm the theoretical findings.

Smart Control of Multiple Evaporator Systems with Wireless Sensor and Actuator Networks

Directory of Open Access Journals (Sweden)

Apolinar González-Potes

2016-02-01

Full Text Available This paper describes the complete integration of a fuzzy control of multiple evaporator systems with the IEEE 802.15.4 standard, in which we study several important aspects for this kind of system, like a detailed analysis of the end-to-end real-time flows over wireless sensor and actuator networks (WSAN, a real-time kernel with an earliest deadline first (EDF scheduler, periodic and aperiodic tasking models for the nodes, lightweight and flexible compensation-based control algorithms for WSAN that exhibit packet dropouts, an event-triggered sampling scheme and design methodologies. We address the control problem of the multi-evaporators with the presence of uncertainties, which was tackled through a wireless fuzzy control approach, showing the advantages of this concept where it can easily perform the optimization for a set of multiple evaporators controlled by the same smart controller, which should have an intelligent and flexible architecture based on multi-agent systems (MAS that allows one to add or remove new evaporators online, without the need for reconfiguring, while maintaining temporal and functional restrictions in the system. We show clearly how we can get a greater scalability, the self-configuration of the network and the least overhead with a non-beacon or unslotted mode of the IEEE 802.15.4 protocol, as well as wireless communications and distributed architectures, which could be extremely helpful in the development process of networked control systems in large spatially-distributed plants, which involve many sensors and actuators. For this purpose, a fuzzy scheme is used to control a set of parallel evaporator air-conditioning systems, with temperature and relative humidity control as a multi-input and multi-output closed loop system; in addition, a general architecture is presented, which implements multiple control loops closed over a communication network, integrating the analysis and validation method for multi

Modeling and Control of the Redundant Parallel Adjustment Mechanism on a Deployable Antenna Panel

Directory of Open Access Journals (Sweden)

Lili Tian

2016-10-01

Full Text Available With the aim of developing multiple input and multiple output (MIMO coupling systems with a redundant parallel adjustment mechanism on the deployable antenna panel, a structural control integrated design methodology is proposed in this paper. Firstly, the modal information from the finite element model of the structure of the antenna panel is extracted, and then the mathematical model is established with the Hamilton principle; Secondly, the discrete Linear Quadratic Regulator (LQR controller is added to the model in order to control the actuators and adjust the shape of the panel. Finally, the engineering practicality of the modeling and control method based on finite element analysis simulation is verified.

Adaptive PID and Model Reference Adaptive Control Switch Controller for Nonlinear Hydraulic Actuator

Directory of Open Access Journals (Sweden)

Xin Zuo

2017-01-01

Full Text Available Nonlinear systems are modeled as piecewise linear systems at multiple operating points, where the operating points are modeled as switches between constituent linearized systems. In this paper, adaptive piecewise linear switch controller is proposed for improving the response time and tracking performance of the hydraulic actuator control system, which is essentially piecewise linear. The controller composed of PID and Model Reference Adaptive Control (MRAC adaptively chooses the proportion of these two components and makes the designed system have faster response time at the transient phase and better tracking performance, simultaneously. Then, their stability and tracking performance are analyzed and evaluated by the hydraulic actuator control system, the hydraulic actuator is controlled by the electrohydraulic system, and its model is built, which has piecewise linear characteristic. Then the controller results are compared between PID and MRAC and the switch controller designed in this paper is applied to the hydraulic actuator; it is obvious that adaptive switch controller has better effects both on response time and on tracking performance.

Multi-Model Adaptive Fuzzy Controller for a CSTR Process

Directory of Open Access Journals (Sweden)

Shubham Gogoria

2015-09-01

Full Text Available Continuous Stirred Tank Reactors are intensively used to control exothermic reactions in chemical industries. It is a very complex multi-variable system with non-linear characteristics. This paper deals with linearization of the mathematical model of a CSTR Process. Multi model adaptive fuzzy controller has been designed to control the reactor concentration and temperature of CSTR process. This method combines the output of multiple Fuzzy controllers, which are operated at various operating points. The proposed solution is a straightforward implementation of Fuzzy controller with gain scheduler to control the linearly inseparable parameters of a highly non-linear process.

Introducing Model Predictive Control for Improving Power Plant Portfolio Performance

DEFF Research Database (Denmark)

Edlund, Kristian Skjoldborg; Bendtsen, Jan Dimon; Børresen, Simon

2008-01-01

This paper introduces a model predictive control (MPC) approach for construction of a controller for balancing the power generation against consumption in a power system. The objective of the controller is to coordinate a portfolio consisting of multiple power plant units in the effort to perform...

Contrast Gain Control Model Fits Masking Data

Science.gov (United States)

Watson, Andrew B.; Solomon, Joshua A.; Null, Cynthia H. (Technical Monitor)

1994-01-01

We studied the fit of a contrast gain control model to data of Foley (JOSA 1994), consisting of thresholds for a Gabor patch masked by gratings of various orientations, or by compounds of two orientations. Our general model includes models of Foley and Teo & Heeger (IEEE 1994). Our specific model used a bank of Gabor filters with octave bandwidths at 8 orientations. Excitatory and inhibitory nonlinearities were power functions with exponents of 2.4 and 2. Inhibitory pooling was broad in orientation, but narrow in spatial frequency and space. Minkowski pooling used an exponent of 4. All of the data for observer KMF were well fit by the model. We have developed a contrast gain control model that fits masking data. Unlike Foley's, our model accepts images as inputs. Unlike Teo & Heeger's, our model did not require multiple channels for different dynamic ranges.

Geometrical model of multiple production

International Nuclear Information System (INIS)

Chikovani, Z.E.; Jenkovszky, L.L.; Kvaratshelia, T.M.; Struminskij, B.V.

1988-01-01

The relation between geometrical and KNO-scaling and their violation is studied in a geometrical model of multiple production of hadrons. Predictions concerning the behaviour of correlation coefficients at future accelerators are given

A multiple-time-scale approach to the control of ITBs on JET

International Nuclear Information System (INIS)

Laborde, L.; Mazon, D.; Moreau, D.; Moreau, D.; Ariola, M.; Cordoliani, V.; Tala, T.

2005-01-01

The simultaneous real-time control of the current and temperature gradient profiles could lead to the steady state sustainment of an internal transport barrier (ITB) and so to a stationary optimized plasma regime. Recent experiments in JET have demonstrated significant progress in achieving such a control: different current and temperature gradient target profiles have been reached and sustained for several seconds using a controller based on a static linear model. It's worth noting that the inverse safety factor profile evolves on a slow time scale (resistive time) while the normalized electron temperature gradient reacts on a faster one (confinement time). Moreover these experiments have shown that the controller was sensitive to rapid plasma events such as transient ITBs during the safety factor profile evolution or MHD instabilities which modify the pressure profiles on the confinement time scale. In order to take into account the different dynamics of the controlled profiles and to better react to rapid plasma events the control technique is being improved by using a multiple-time-scale approximation. The paper describes the theoretical analysis and closed-loop simulations using a control algorithm based on two-time-scale state-space model. These closed-loop simulations using the full dynamic but linear model used for the controller design to simulate the plasma response have demonstrated that this new controller allows the normalized electron temperature gradient target profile to be reached faster than the one used in previous experiments. (A.C.)

A multiple-time-scale approach to the control of ITBs on JET

Energy Technology Data Exchange (ETDEWEB)

Laborde, L.; Mazon, D.; Moreau, D. [EURATOM-CEA Association (DSM-DRFC), CEA Cadarache, 13 - Saint Paul lez Durance (France); Moreau, D. [Culham Science Centre, EFDA-JET, Abingdon, OX (United Kingdom); Ariola, M. [EURATOM/ENEA/CREATE Association, Univ. Napoli Federico II, Napoli (Italy); Cordoliani, V. [Ecole Polytechnique, 91 - Palaiseau (France); Tala, T. [EURATOM-Tekes Association, VTT Processes (Finland)

2005-07-01

The simultaneous real-time control of the current and temperature gradient profiles could lead to the steady state sustainment of an internal transport barrier (ITB) and so to a stationary optimized plasma regime. Recent experiments in JET have demonstrated significant progress in achieving such a control: different current and temperature gradient target profiles have been reached and sustained for several seconds using a controller based on a static linear model. It's worth noting that the inverse safety factor profile evolves on a slow time scale (resistive time) while the normalized electron temperature gradient reacts on a faster one (confinement time). Moreover these experiments have shown that the controller was sensitive to rapid plasma events such as transient ITBs during the safety factor profile evolution or MHD instabilities which modify the pressure profiles on the confinement time scale. In order to take into account the different dynamics of the controlled profiles and to better react to rapid plasma events the control technique is being improved by using a multiple-time-scale approximation. The paper describes the theoretical analysis and closed-loop simulations using a control algorithm based on two-time-scale state-space model. These closed-loop simulations using the full dynamic but linear model used for the controller design to simulate the plasma response have demonstrated that this new controller allows the normalized electron temperature gradient target profile to be reached faster than the one used in previous experiments. (A.C.)

Optimization of inverse model identification for multi-axial test rig control

Directory of Open Access Journals (Sweden)

Müller Tino

2016-01-01

Full Text Available Laboratory testing of multi-axial fatigue situations improves repeatability and allows a time condensing of tests which can be carried out until component failure, compared to field testing. To achieve realistic and convincing durability results, precise load data reconstruction is necessary. Cross-talk and a high number of degrees of freedom negatively affect the control accuracy. Therefore a multiple input/multiple output (MIMO model of the system, capturing all inherent cross-couplings is identified. In a first step the model order is estimated based on the physical fundamentals of a one channel hydraulic-servo system. Subsequently, the structure of the MIMO model is optimized using correlation of the outputs, to increase control stability and reduce complexity of the parameter optimization. The identification process is successfully applied to the iterative control of a multi-axial suspension rig. The results show accurate control, with increased stability compared to control without structure optimization.

Neural-Based Compensation of Nonlinearities in an Airplane Longitudinal Model with Dynamic-Inversion Control

Directory of Open Access Journals (Sweden)

YanBin Liu

2017-01-01

Full Text Available The inversion design approach is a very useful tool for the complex multiple-input-multiple-output nonlinear systems to implement the decoupling control goal, such as the airplane model and spacecraft model. In this work, the flight control law is proposed using the neural-based inversion design method associated with the nonlinear compensation for a general longitudinal model of the airplane. First, the nonlinear mathematic model is converted to the equivalent linear model based on the feedback linearization theory. Then, the flight control law integrated with this inversion model is developed to stabilize the nonlinear system and relieve the coupling effect. Afterwards, the inversion control combined with the neural network and nonlinear portion is presented to improve the transient performance and attenuate the uncertain effects on both external disturbances and model errors. Finally, the simulation results demonstrate the effectiveness of this controller.

Relative efficiency of joint-model and full-conditional-specification multiple imputation when conditional models are compatible: The general location model.

Science.gov (United States)

Seaman, Shaun R; Hughes, Rachael A

2018-06-01

Estimating the parameters of a regression model of interest is complicated by missing data on the variables in that model. Multiple imputation is commonly used to handle these missing data. Joint model multiple imputation and full-conditional specification multiple imputation are known to yield imputed data with the same asymptotic distribution when the conditional models of full-conditional specification are compatible with that joint model. We show that this asymptotic equivalence of imputation distributions does not imply that joint model multiple imputation and full-conditional specification multiple imputation will also yield asymptotically equally efficient inference about the parameters of the model of interest, nor that they will be equally robust to misspecification of the joint model. When the conditional models used by full-conditional specification multiple imputation are linear, logistic and multinomial regressions, these are compatible with a restricted general location joint model. We show that multiple imputation using the restricted general location joint model can be substantially more asymptotically efficient than full-conditional specification multiple imputation, but this typically requires very strong associations between variables. When associations are weaker, the efficiency gain is small. Moreover, full-conditional specification multiple imputation is shown to be potentially much more robust than joint model multiple imputation using the restricted general location model to mispecification of that model when there is substantial missingness in the outcome variable.

Application of model predictive control for optimal operation of wind turbines

Science.gov (United States)

Yuan, Yuan; Cao, Pei; Tang, J.

2017-04-01

For large-scale wind turbines, reducing maintenance cost is a major challenge. Model predictive control (MPC) is a promising approach to deal with multiple conflicting objectives using the weighed sum approach. In this research, model predictive control method is applied to wind turbine to find an optimal balance between multiple objectives, such as the energy capture, loads on turbine components, and the pitch actuator usage. The actuator constraints are integrated into the objective function at the control design stage. The analysis is carried out in both the partial load region and full load region, and the performances are compared with those of a baseline gain scheduling PID controller. The application of this strategy achieves enhanced balance of component loads, the average power and actuator usages in partial load region.

An Adaptive Model for Calculating the Correlation Degree of Multiple Adjacent Signalized Intersections

Directory of Open Access Journals (Sweden)

Linhong Wang

2013-01-01

Full Text Available As an important component of the urban adaptive traffic control system, subarea partition algorithm divides the road network into some small subareas and then determines the optimal signal control mode for each signalized intersection. Correlation model is the core of subarea partition algorithm because it can quantify the correlation degree of adjacent signalized intersections and decides whether these intersections can be grouped into one subarea. In most cases, there are more than two intersections in one subarea. However, current researches only focus on the correlation model for two adjacent intersections. The objective of this study is to develop a model which can calculate the correlation degree of multiple intersections adaptively. The cycle lengths, link lengths, number of intersections, and path flow between upstream and downstream coordinated phases were selected as the contributing factors of the correlation model. Their jointly impacts on the performance of the coordinated control mode relative to the isolated control mode were further studied using numerical experiments. The paper then proposed a correlation index (CI as an alternative to relative performance. The relationship between CI and the four contributing factors was established in order to predict the correlation, which determined whether adjacent intersections could be partitioned into one subarea. A value of 0 was set as the threshold of CI. If CI was larger than 0, multiple intersections could be partitioned into one subarea; otherwise, they should be separated. Finally, case studies were conducted in a real-life signalized network to evaluate the performance of the model. The results show that the CI simulates the relative performance well and could be a reliable index for subarea partition.

Integration of multiple, excess, backup, and expected covering models

OpenAIRE

M S Daskin; K Hogan; C ReVelle

1988-01-01

The concepts of multiple, excess, backup, and expected coverage are defined. Model formulations using these constructs are reviewed and contrasted to illustrate the relationships between them. Several new formulations are presented as is a new derivation of the expected covering model which indicates more clearly the relationship of the model to other multi-state covering models. An expected covering model with multiple time standards is also presented.

Evolving Four Part Harmony Using a Multiple Worlds Model

DEFF Research Database (Denmark)

Scirea, Marco; Brown, Joseph Alexander

2015-01-01

This application of the Multiple Worlds Model examines a collaborative fitness model for generating four part harmonies. In this model we have multiple populations and the fitness of the individuals is based on the ability of a member from each population to work with the members of other...

Simultaneous small-sample comparisons in longitudinal or multi-endpoint trials using multiple marginal models

DEFF Research Database (Denmark)

Pallmann, Philip; Ritz, Christian; Hothorn, Ludwig A

2018-01-01

, however only asymptotically. In this paper, we show how to make the approach also applicable to small-sample data problems. Specifically, we discuss the computation of adjusted P values and simultaneous confidence bounds for comparisons of randomised treatment groups as well as for levels......Simultaneous inference in longitudinal, repeated-measures, and multi-endpoint designs can be onerous, especially when trying to find a reasonable joint model from which the interesting effects and covariances are estimated. A novel statistical approach known as multiple marginal models greatly...... simplifies the modelling process: the core idea is to "marginalise" the problem and fit multiple small models to different portions of the data, and then estimate the overall covariance matrix in a subsequent, separate step. Using these estimates guarantees strong control of the family-wise error rate...

Double-multiple streamtube model for Darrieus in turbines

Science.gov (United States)

Paraschivoiu, I.

1981-01-01

An analytical model is proposed for calculating the rotor performance and aerodynamic blade forces for Darrieus wind turbines with curved blades. The method of analysis uses a multiple-streamtube model, divided into two parts: one modeling the upstream half-cycle of the rotor and the other, the downstream half-cycle. The upwind and downwind components of the induced velocities at each level of the rotor were obtained using the principle of two actuator disks in tandem. Variation of the induced velocities in the two parts of the rotor produces larger forces in the upstream zone and smaller forces in the downstream zone. Comparisons of the overall rotor performance with previous methods and field test data show the important improvement obtained with the present model. The calculations were made using the computer code CARDAA developed at IREQ. The double-multiple streamtube model presented has two major advantages: it requires a much shorter computer time than the three-dimensional vortex model and is more accurate than multiple-streamtube model in predicting the aerodynamic blade loads.

Characteristic Model-Based Robust Model Predictive Control for Hypersonic Vehicles with Constraints

Directory of Open Access Journals (Sweden)

Jun Zhang

2017-06-01

Full Text Available Designing robust control for hypersonic vehicles in reentry is difficult, due to the features of the vehicles including strong coupling, non-linearity, and multiple constraints. This paper proposed a characteristic model-based robust model predictive control (MPC for hypersonic vehicles with reentry constraints. First, the hypersonic vehicle is modeled by a characteristic model composed of a linear time-varying system and a lumped disturbance. Then, the identification data are regenerated by the accumulative sum idea in the gray theory, which weakens effects of the random noises and strengthens regularity of the identification data. Based on the regenerated data, the time-varying parameters and the disturbance are online estimated according to the gray identification. At last, the mixed H2/H∞ robust predictive control law is proposed based on linear matrix inequalities (LMIs and receding horizon optimization techniques. Using active tackling system constraints of MPC, the input and state constraints are satisfied in the closed-loop control system. The validity of the proposed control is verified theoretically according to Lyapunov theory and illustrated by simulation results.

Semi-active control of a cable-stayed bridge under multiple-support excitations.

Science.gov (United States)

Dai, Ze-Bing; Huang, Jin-Zhi; Wang, Hong-Xia

2004-03-01

This paper presents a semi-active strategy for seismic protection of a benchmark cable-stayed bridge with consideration of multiple-support excitations. In this control strategy, Magnetorheological (MR) dampers are proposed as control devices, a LQG-clipped-optimal control algorithm is employed. An active control strategy, shown in previous researches to perform well at controlling the benchmark bridge when uniform earthquake motion was assumed, is also used in this study to control this benchmark bridge with consideration of multiple-support excitations. The performance of active control system is compared to that of the presented semi-active control strategy. Because the MR fluid damper is a controllable energy- dissipation device that cannot add mechanical energy to the structural system, the proposed control strategy is fail-safe in that bounded-input, bounded-output stability of the controlled structure is guaranteed. The numerical results demonstrated that the performance of the presented control design is nearly the same as that of the active control system; and that the MR dampers can effectively be used to control seismically excited cable-stayed bridges with multiple-support excitations.

Modeling and control for closed environment plant production systems

Science.gov (United States)

Fleisher, David H.; Ting, K. C.; Janes, H. W. (Principal Investigator)

2002-01-01

A computer program was developed to study multiple crop production and control in controlled environment plant production systems. The program simulates crop growth and development under nominal and off-nominal environments. Time-series crop models for wheat (Triticum aestivum), soybean (Glycine max), and white potato (Solanum tuberosum) are integrated with a model-based predictive controller. The controller evaluates and compensates for effects of environmental disturbances on crop production scheduling. The crop models consist of a set of nonlinear polynomial equations, six for each crop, developed using multivariate polynomial regression (MPR). Simulated data from DSSAT crop models, previously modified for crop production in controlled environments with hydroponics under elevated atmospheric carbon dioxide concentration, were used for the MPR fitting. The model-based predictive controller adjusts light intensity, air temperature, and carbon dioxide concentration set points in response to environmental perturbations. Control signals are determined from minimization of a cost function, which is based on the weighted control effort and squared-error between the system response and desired reference signal.

Occupational stress and psychopathology in health professionals: an explorative study with the multiple indicators multiple causes (MIMIC) model approach.

Science.gov (United States)

Iliceto, Paolo; Pompili, Maurizio; Spencer-Thomas, Sally; Ferracuti, Stefano; Erbuto, Denise; Lester, David; Candilera, Gabriella; Girardi, Paolo

2013-03-01

Occupational stress is a multivariate process involving sources of pressure, psycho-physiological distress, locus of control, work dissatisfaction, depression, anxiety, mental health disorders, hopelessness, and suicide ideation. Healthcare professionals are known for higher rates of occupational-related distress (burnout and compassion fatigue) and higher rates of suicide. The purpose of this study was to explain the relationships between occupational stress and some psychopathological dimensions in a sample of health professionals. We investigated 156 nurses and physicians, 62 males and 94 females, who were administered self-report questionnaires to assess occupational stress [occupational stress inventory (OSI)], temperament (temperament evaluation of Memphis, Pisa, Paris, and San Diego autoquestionnaire), and hopelessness (Beck hopelessness scale). The best Multiple Indicators Multiple Causes model with five OSI predictors yielded the following results: χ2(9) = 14.47 (p = 0.11); χ2/df = 1.60; comparative fit index = 0.99; root mean square error of approximation = 0.05. This model provided a good fit to the empirical data, showing a strong direct influence of casual variables such as work dissatisfaction, absence of type A behavior, and especially external locus of control, psychological and physiological distress on latent variable psychopathology. Occupational stress is in a complex relationship with temperament and hopelessness and also common among healthcare professionals.

Cooperative Control of Multiple Unmanned Autonomous Vehicles

Science.gov (United States)

2005-06-03

I I Final Report 4. TITLE AND SUBTITLE 5. FUNDING NUMBERS Cooperative Control of Multiple Unmanned Autonomous Vehicles F49620-01-1-0337 6. AUTHOR(S... Autonomous Vehicles Final Report Kendall E. Nygard Department of Computer Science and Operations Research North Dakota State University Fargo, ND 58105-5164

Relative null controllability of linear systems with multiple delays in ...

African Journals Online (AJOL)

varying multiple delays in state and control are developed. If the uncontrolled system is uniformly asymptotically stable, and if the linear system is controllable, then the linear system is null controllable. Journal of the Nigerian Association of ...

An agent-based negotiation approach for balancing multiple coupled control domains

DEFF Research Database (Denmark)

Umair, Aisha; Clausen, Anders; Jørgensen, Bo Nørregaard

2015-01-01

Solving multi-objective multi-issue negotiation problems involving interdependent issues distributed among multiple control domains is inherent to most non-trivial cyber-physical systems. In these systems, the coordinated operation of interconnected subsystems performing autonomous control....... The proposed approach can solve negotiation problems with interdependent issues across multiple coupled control domains. We demonstrate our approach by solving a coordination problem where a Combined Heat and Power Plant must allocate electricity for three commercial greenhouses to ensure the required plant...

Performance effect of multiple control forms in a Lean organization

DEFF Research Database (Denmark)

Kristensen, Thomas Borup; Israelsen, Poul

2012-01-01

Over the last decades Lean has developed into a prominent management philosophy reaching beyond shop floor tools. However, substantial support of performance effects from Lean is still scarce and at best with mixed results. Recently, research has turned its focus towards perceiving Lean...... as a control package. In this paper we present statistical support for enhanced performance coming from Lean. Furthermore, our results strongly support the perception of Lean as a set of multiple control forms (output, behavioral, and social controls) that complement each other. Therefore, performance...... is increased if the average level of control forms is increased, and performance is further increased if the control forms are balanced at the same level representing a complementary effect between them. Our data are archival data spanning multiple years in a strong Lean organization. The dependent performance...

Design of clinical trials involving multiple hypothesis tests with a common control.

Science.gov (United States)

Schou, I Manjula; Marschner, Ian C

2017-07-01

Randomized clinical trials comparing several treatments to a common control are often reported in the medical literature. For example, multiple experimental treatments may be compared with placebo, or in combination therapy trials, a combination therapy may be compared with each of its constituent monotherapies. Such trials are typically designed using a balanced approach in which equal numbers of individuals are randomized to each arm, however, this can result in an inefficient use of resources. We provide a unified framework and new theoretical results for optimal design of such single-control multiple-comparator studies. We consider variance optimal designs based on D-, A-, and E-optimality criteria, using a general model that allows for heteroscedasticity and a range of effect measures that include both continuous and binary outcomes. We demonstrate the sensitivity of these designs to the type of optimality criterion by showing that the optimal allocation ratios are systematically ordered according to the optimality criterion. Given this sensitivity to the optimality criterion, we argue that power optimality is a more suitable approach when designing clinical trials where testing is the objective. Weighted variance optimal designs are also discussed, which, like power optimal designs, allow the treatment difference to play a major role in determining allocation ratios. We illustrate our methods using two real clinical trial examples taken from the medical literature. Some recommendations on the use of optimal designs in single-control multiple-comparator trials are also provided. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

ASSISTments Dataset from Multiple Randomized Controlled Experiments

Science.gov (United States)

Selent, Douglas; Patikorn, Thanaporn; Heffernan, Neil

2016-01-01

In this paper, we present a dataset consisting of data generated from 22 previously and currently running randomized controlled experiments inside the ASSISTments online learning platform. This dataset provides data mining opportunities for researchers to analyze ASSISTments data in a convenient format across multiple experiments at the same time.…

Multiple single-board-computer system for the KEK positron generator control

International Nuclear Information System (INIS)

Nakahara, Kazuo; Abe, Isamu; Enomoto, Atsushi; Otake, Yuji; Urano, Takao

1986-01-01

The KEK positron generator is controlled by means of a distributed microprocessor network. The control system is composed of three kinds of equipment: device controllers for the linac equipment, operation management stations and a communication network. Individual linac equipment has its own microprocessor-based controller. A multiple single board computer (SBC) system is used for communication control and for equipment surveillance; it has a database containing communication and linac equipment status information. The linac operation management that should be the most soft part in the control system, is separated from the multiple SBC system and is carried out by work-stations. The principle that every processor executes only one task is maintained throughout the control system. This made the software architecture very simple. (orig.)

Multiple model cardinalized probability hypothesis density filter

Science.gov (United States)

Georgescu, Ramona; Willett, Peter

2011-09-01

The Probability Hypothesis Density (PHD) filter propagates the first-moment approximation to the multi-target Bayesian posterior distribution while the Cardinalized PHD (CPHD) filter propagates both the posterior likelihood of (an unlabeled) target state and the posterior probability mass function of the number of targets. Extensions of the PHD filter to the multiple model (MM) framework have been published and were implemented either with a Sequential Monte Carlo or a Gaussian Mixture approach. In this work, we introduce the multiple model version of the more elaborate CPHD filter. We present the derivation of the prediction and update steps of the MMCPHD particularized for the case of two target motion models and proceed to show that in the case of a single model, the new MMCPHD equations reduce to the original CPHD equations.

Pointright: a system to redirect mouse and keyboard control among multiple machines

Science.gov (United States)

Johanson, Bradley E [Palo Alto, CA; Winograd, Terry A [Stanford, CA; Hutchins, Gregory M [Mountain View, CA

2008-09-30

The present invention provides a software system, PointRight, that allows for smooth and effortless control of pointing and input devices among multiple displays. With PointRight, a single free-floating mouse and keyboard can be used to control multiple screens. When the cursor reaches the edge of a screen it seamlessly moves to the adjacent screen and keyboard control is simultaneously redirected to the appropriate machine. Laptops may also redirect their keyboard and pointing device, and multiple pointers are supported simultaneously. The system automatically reconfigures itself as displays go on, go off, or change the machine they display.

Mean multiplicity in the Regge models with rising cross sections

International Nuclear Information System (INIS)

Chikovani, Z.E.; Kobylisky, N.A.; Martynov, E.S.

1979-01-01

Behaviour of the mean multiplicity and the total cross section σsub(t) of hadron-hadron interactions is considered in the framework of the Regge models at high energies. Generating function was plotted for models of dipole and froissaron, and the mean multiplicity and multiplicity moments were calculated. It is shown that approximately ln 2 S (energy square) in the dipole model, which is in good agreement with the experiment. It is also found that in various Regge models approximately σsub(t)lnS

Rapidity correlations at fixed multiplicity in cluster emission models

CERN Document Server

Berger, M C

1975-01-01

Rapidity correlations in the central region among hadrons produced in proton-proton collisions of fixed final state multiplicity n at NAL and ISR energies are investigated in a two-step framework in which clusters of hadrons are emitted essentially independently, via a multiperipheral-like model, and decay isotropically. For n>or approximately=/sup 1///sub 2/(n), these semi-inclusive distributions are controlled by the reaction mechanism which dominates production in the central region. Thus, data offer cleaner insight into the properties of this mechanism than can be obtained from fully inclusive spectra. A method of experimental analysis is suggested to facilitate the extraction of new dynamical information. It is shown that the n independence of the magnitude of semi-inclusive correlation functions reflects directly the structure of the internal cluster multiplicity distribution. This conclusion is independent of certain assumptions concerning the form of the single cluster density in rapidity space. (23 r...

Auditory decision aiding in supervisory control of multiple unmanned aerial vehicles.

Science.gov (United States)

Donmez, Birsen; Cummings, M L; Graham, Hudson D

2009-10-01

This article is an investigation of the effectiveness of sonifications, which are continuous auditory alerts mapped to the state of a monitored task, in supporting unmanned aerial vehicle (UAV) supervisory control. UAV supervisory control requires monitoring a UAV across multiple tasks (e.g., course maintenance) via a predominantly visual display, which currently is supported with discrete auditory alerts. Sonification has been shown to enhance monitoring performance in domains such as anesthesiology by allowing an operator to immediately determine an entity's (e.g., patient) current and projected states, and is a promising alternative to discrete alerts in UAV control. However, minimal research compares sonification to discrete alerts, and no research assesses the effectiveness of sonification for monitoring multiple entities (e.g., multiple UAVs). The authors conducted an experiment with 39 military personnel, using a simulated setup. Participants controlled single and multiple UAVs and received sonifications or discrete alerts based on UAV course deviations and late target arrivals. Regardless of the number of UAVs supervised, the course deviation sonification resulted in reactions to course deviations that were 1.9 s faster, a 19% enhancement, compared with discrete alerts. However, course deviation sonifications interfered with the effectiveness of discrete late arrival alerts in general and with operator responses to late arrivals when supervising multiple vehicles. Sonifications can outperform discrete alerts when designed to aid operators to predict future states of monitored tasks. However, sonifications may mask other auditory alerts and interfere with other monitoring tasks that require divided attention. This research has implications for supervisory control display design.

Determination of osteoporosis risk factors using a multiple logistic regression model in postmenopausal Turkish women.

Science.gov (United States)

Akkus, Zeki; Camdeviren, Handan; Celik, Fatma; Gur, Ali; Nas, Kemal

2005-09-01

To determine the risk factors of osteoporosis using a multiple binary logistic regression method and to assess the risk variables for osteoporosis, which is a major and growing health problem in many countries. We presented a case-control study, consisting of 126 postmenopausal healthy women as control group and 225 postmenopausal osteoporotic women as the case group. The study was carried out in the Department of Physical Medicine and Rehabilitation, Dicle University, Diyarbakir, Turkey between 1999-2002. The data from the 351 participants were collected using a standard questionnaire that contains 43 variables. A multiple logistic regression model was then used to evaluate the data and to find the best regression model. We classified 80.1% (281/351) of the participants using the regression model. Furthermore, the specificity value of the model was 67% (84/126) of the control group while the sensitivity value was 88% (197/225) of the case group. We found the distribution of residual values standardized for final model to be exponential using the Kolmogorow-Smirnow test (p=0.193). The receiver operating characteristic curve was found successful to predict patients with risk for osteoporosis. This study suggests that low levels of dietary calcium intake, physical activity, education, and longer duration of menopause are independent predictors of the risk of low bone density in our population. Adequate dietary calcium intake in combination with maintaining a daily physical activity, increasing educational level, decreasing birth rate, and duration of breast-feeding may contribute to healthy bones and play a role in practical prevention of osteoporosis in Southeast Anatolia. In addition, the findings of the present study indicate that the use of multivariate statistical method as a multiple logistic regression in osteoporosis, which maybe influenced by many variables, is better than univariate statistical evaluation.

Noise-Induced Transition in a Voltage-Controlled Oscillator Neuron Model

International Nuclear Information System (INIS)

Xie Huizhang; Liu Xuemei; Li Zhibing; Ai Baoquan; Liu Lianggang

2008-01-01

In the presence of Gaussian white noise, we study the properties of voltage-controlled oscillator neuron model and discuss the effects of the additive and multiplicative noise. It is found that the additive noise can accelerate and counterwork the firing of neuron, which depends on the value of central frequency of neuron itself, while multiplicative noise can induce the continuous change or mutation of membrane potential

Bayesian models based on test statistics for multiple hypothesis testing problems.

Science.gov (United States)

Ji, Yuan; Lu, Yiling; Mills, Gordon B

2008-04-01

We propose a Bayesian method for the problem of multiple hypothesis testing that is routinely encountered in bioinformatics research, such as the differential gene expression analysis. Our algorithm is based on modeling the distributions of test statistics under both null and alternative hypotheses. We substantially reduce the complexity of the process of defining posterior model probabilities by modeling the test statistics directly instead of modeling the full data. Computationally, we apply a Bayesian FDR approach to control the number of rejections of null hypotheses. To check if our model assumptions for the test statistics are valid for various bioinformatics experiments, we also propose a simple graphical model-assessment tool. Using extensive simulations, we demonstrate the performance of our models and the utility of the model-assessment tool. In the end, we apply the proposed methodology to an siRNA screening and a gene expression experiment.

A versatile method for confirmatory evaluation of the effects of a covariate in multiple models

DEFF Research Database (Denmark)

Pipper, Christian Bressen; Ritz, Christian; Bisgaard, Hans

2012-01-01

to provide a fine-tuned control of the overall type I error in a wide range of epidemiological experiments where in reality no other useful alternative exists. The methodology proposed is applied to a multiple-end-point study of the effect of neonatal bacterial colonization on development of childhood asthma.......Modern epidemiology often requires testing of the effect of a covariate on multiple end points from the same study. However, popular state of the art methods for multiple testing require the tests to be evaluated within the framework of a single model unifying all end points. This severely limits...

Introducing Model Predictive Control for Improving Power Plant Portfolio Performance

DEFF Research Database (Denmark)

Edlund, Kristian Skjoldborg; Bendtsen, Jan Dimon; Børresen, Simon

2008-01-01

This paper introduces a model predictive control (MPC) approach for construction of a controller for balancing the power generation against consumption in a power system. The objective of the controller is to coordinate a portfolio consisting of multiple power plant units in the effort to perform...... reference tracking and disturbance rejection in an economically optimal way. The performance function is chosen as a mixture of the `1-norm and a linear weighting to model the economics of the system. Simulations show a significant improvement of the performance of the MPC compared to the current...

Aviation Safety Risk Modeling: Lessons Learned From Multiple Knowledge Elicitation Sessions

Science.gov (United States)

Luxhoj, J. T.; Ancel, E.; Green, L. L.; Shih, A. T.; Jones, S. M.; Reveley, M. S.

2014-01-01

Aviation safety risk modeling has elements of both art and science. In a complex domain, such as the National Airspace System (NAS), it is essential that knowledge elicitation (KE) sessions with domain experts be performed to facilitate the making of plausible inferences about the possible impacts of future technologies and procedures. This study discusses lessons learned throughout the multiple KE sessions held with domain experts to construct probabilistic safety risk models for a Loss of Control Accident Framework (LOCAF), FLightdeck Automation Problems (FLAP), and Runway Incursion (RI) mishap scenarios. The intent of these safety risk models is to support a portfolio analysis of NASA's Aviation Safety Program (AvSP). These models use the flexible, probabilistic approach of Bayesian Belief Networks (BBNs) and influence diagrams to model the complex interactions of aviation system risk factors. Each KE session had a different set of experts with diverse expertise, such as pilot, air traffic controller, certification, and/or human factors knowledge that was elicited to construct a composite, systems-level risk model. There were numerous "lessons learned" from these KE sessions that deal with behavioral aggregation, conditional probability modeling, object-oriented construction, interpretation of the safety risk results, and model verification/validation that are presented in this paper.

H-infty Control of systems with multiple i/o delays

NARCIS (Netherlands)

Agoes Ariffin Moelja, A.A.; Meinsma, Gjerrit; Mirkin, Leonid

2003-01-01

In this paper the standard (four-block) H-infty control problem for systems with multiple i/o delays in the feedback loop is studied. The central idea is to see the multiple delay operator as a special series connection of elementary delay operators, called the adobe delay operators. The adobe delay

Design of Xen Hybrid Multiple Police Model

Science.gov (United States)

Sun, Lei; Lin, Renhao; Zhu, Xianwei

2017-10-01

Virtualization Technology has attracted more and more attention. As a popular open-source virtualization tools, XEN is used more and more frequently. Xsm, XEN security model, has also been widespread concern. The safety status classification has not been established in the XSM, and it uses the virtual machine as a managed object to make Dom0 a unique administrative domain that does not meet the minimum privilege. According to these questions, we design a Hybrid multiple police model named SV_HMPMD that organically integrates multiple single security policy models include DTE,RBAC,BLP. It can fullfill the requirement of confidentiality and integrity for security model and use different particle size to different domain. In order to improve BLP’s practicability, the model introduce multi-level security labels. In order to divide the privilege in detail, we combine DTE with RBAC. In order to oversize privilege, we limit the privilege of domain0.

Modeling the Effects of Multiple Intervention Strategies on Controlling Foot-and-Mouth Disease

Directory of Open Access Journals (Sweden)

Steady Mushayabasa

2015-01-01

Full Text Available Foot-and-mouth disease (FMD is a threat to economic security and infrastructure as well as animal health, in both developed and developing countries. We propose and analyze an optimal control problem where the control system is a mathematical model for FMD that incorporates vaccination and culling of infectious animals. The control functions represent the fraction of animals that are vaccinated during an outbreak, infectious symptomatic animals that are detected and culled, and infectious nonsymptomatic animals that are detected and culled. Our aim was to study how these control measures should be implemented for a certain time period, in order to reduce or eliminate FMD in the community, while minimizing the interventions implementation costs. A cost-effectiveness analysis is carried out, to compare the application of each one of the control measures, separately or in combination.

Decentralized fuzzy control of multiple nonholonomic vehicles

Energy Technology Data Exchange (ETDEWEB)

Driessen, B.J.; Feddema, J.T.; Kwok, K.S.

1997-09-01

This work considers the problem of controlling multiple nonholonomic vehicles so that they converge to a scent source without colliding with each other. Since the control is to be implemented on simple 8-bit microcontrollers, fuzzy control rules are used to simplify a linear quadratic regulator control design. The inputs to the fuzzy controllers for each vehicle are the (noisy) direction to the source, the distance to the closest neighbor vehicle, and the direction to the closest vehicle. These directions are discretized into four values: Forward, Behind, Left, and Right, and the distance into three values: Near, Far, Gone. The values of the control at these discrete values are obtained based on the collision-avoidance repulsive forces and the change of variables that reduces the motion control problem of each nonholonomic vehicle to a nonsingular one with two degrees of freedom, instead of three. A fuzzy inference system is used to obtain control values for inputs between the small number of discrete input values. Simulation results are provided which demonstrate that the fuzzy control law performs well compared to the exact controller. In fact, the fuzzy controller demonstrates improved robustness to noise.

A study of pilot modeling in multi-controller tasks

Science.gov (United States)

Whitbeck, R. F.; Knight, J. R.

1972-01-01

A modeling approach, which utilizes a matrix of transfer functions to describe the human pilot in multiple input, multiple output control situations, is studied. The approach used was to extend a well established scalar Wiener-Hopf minimization technique to the matrix case and then study, via a series of experiments, the data requirements when only finite record lengths are available. One of these experiments was a two-controller roll tracking experiment designed to force the pilot to use rudder in order to coordinate and reduce the effects of aileron yaw. One model was computed for the case where the signals used to generate the spectral matrix are error and bank angle while another model was computed for the case where error and yaw angle are the inputs. Several anomalies were observed to be present in the experimental data. These are defined by the descriptive terms roll up, break up, and roll down. Due to these algorithm induced anomalies, the frequency band over which reliable estimates of power spectra can be achieved is considerably less than predicted by the sampling theorem.

Merging for Particle-Mesh Complex Particle Kinetic Modeling of the Multiple Plasma Beams

Science.gov (United States)

Lipatov, Alexander S.

2011-01-01

We suggest a merging procedure for the Particle-Mesh Complex Particle Kinetic (PMCPK) method in case of inter-penetrating flow (multiple plasma beams). We examine the standard particle-in-cell (PIC) and the PMCPK methods in the case of particle acceleration by shock surfing for a wide range of the control numerical parameters. The plasma dynamics is described by a hybrid (particle-ion-fluid-electron) model. Note that one may need a mesh if modeling with the computation of an electromagnetic field. Our calculations use specified, time-independent electromagnetic fields for the shock, rather than self-consistently generated fields. While a particle-mesh method is a well-verified approach, the CPK method seems to be a good approach for multiscale modeling that includes multiple regions with various particle/fluid plasma behavior. However, the CPK method is still in need of a verification for studying the basic plasma phenomena: particle heating and acceleration by collisionless shocks, magnetic field reconnection, beam dynamics, etc.

Supersymmetric U(1)' model with multiple dark matters

International Nuclear Information System (INIS)

Hur, Taeil; Lee, Hye-Sung; Nasri, Salah

2008-01-01

We consider a scenario where a supersymmetric model has multiple dark matter particles. Adding a U(1) ' gauge symmetry is a well-motivated extension of the minimal supersymmetric standard model (MSSM). It can cure the problems of the MSSM such as the μ problem or the proton decay problem with high-dimensional lepton number and baryon number violating operators which R parity allows. An extra parity (U parity) may arise as a residual discrete symmetry after U(1) ' gauge symmetry is spontaneously broken. The lightest U-parity particle (LUP) is stable under the new parity becoming a new dark matter candidate. Up to three massive particles can be stable in the presence of the R parity and the U parity. We numerically illustrate that multiple stable particles in our model can satisfy both constraints from the relic density and the direct detection, thus providing a specific scenario where a supersymmetric model has well-motivated multiple dark matters consistent with experimental constraints. The scenario provides new possibilities in the present and upcoming dark matter searches in the direct detection and collider experiments

Multiple Social Networks, Data Models and Measures for

DEFF Research Database (Denmark)

Magnani, Matteo; Rossi, Luca

2017-01-01

Multiple Social Network Analysis is a discipline defining models, measures, methodologies, and algorithms to study multiple social networks together as a single social system. It is particularly valuable when the networks are interconnected, e.g., the same actors are present in more than one...

Multiple Response Regression for Gaussian Mixture Models with Known Labels.

Science.gov (United States)

Lee, Wonyul; Du, Ying; Sun, Wei; Hayes, D Neil; Liu, Yufeng

2012-12-01

Multiple response regression is a useful regression technique to model multiple response variables using the same set of predictor variables. Most existing methods for multiple response regression are designed for modeling homogeneous data. In many applications, however, one may have heterogeneous data where the samples are divided into multiple groups. Our motivating example is a cancer dataset where the samples belong to multiple cancer subtypes. In this paper, we consider modeling the data coming from a mixture of several Gaussian distributions with known group labels. A naive approach is to split the data into several groups according to the labels and model each group separately. Although it is simple, this approach ignores potential common structures across different groups. We propose new penalized methods to model all groups jointly in which the common and unique structures can be identified. The proposed methods estimate the regression coefficient matrix, as well as the conditional inverse covariance matrix of response variables. Asymptotic properties of the proposed methods are explored. Through numerical examples, we demonstrate that both estimation and prediction can be improved by modeling all groups jointly using the proposed methods. An application to a glioblastoma cancer dataset reveals some interesting common and unique gene relationships across different cancer subtypes.

SDG and qualitative trend based model multiple scale validation

Science.gov (United States)

Gao, Dong; Xu, Xin; Yin, Jianjin; Zhang, Hongyu; Zhang, Beike

2017-09-01

Verification, Validation and Accreditation (VV&A) is key technology of simulation and modelling. For the traditional model validation methods, the completeness is weak; it is carried out in one scale; it depends on human experience. The SDG (Signed Directed Graph) and qualitative trend based multiple scale validation is proposed. First the SDG model is built and qualitative trends are added to the model. And then complete testing scenarios are produced by positive inference. The multiple scale validation is carried out by comparing the testing scenarios with outputs of simulation model in different scales. Finally, the effectiveness is proved by carrying out validation for a reactor model.

A Multiple Items EPQ/EOQ Model for a Vendor and Multiple Buyers System with Considering Continuous and Discrete Demand Simultaneously

Science.gov (United States)

Jonrinaldi; Rahman, T.; Henmaidi; Wirdianto, E.; Zhang, D. Z.

2018-03-01

This paper proposed a mathematical model for multiple items Economic Production and Order Quantity (EPQ/EOQ) with considering continuous and discrete demand simultaneously in a system consisting of a vendor and multiple buyers. This model is used to investigate the optimal production lot size of the vendor and the number of shipments policy of orders to multiple buyers. The model considers the multiple buyers’ holding cost as well as transportation cost, which minimize the total production and inventory costs of the system. The continuous demand from any other customers can be fulfilled anytime by the vendor while the discrete demand from multiple buyers can be fulfilled by the vendor using the multiple delivery policy with a number of shipments of items in the production cycle time. A mathematical model is developed to illustrate the system based on EPQ and EOQ model. Solution procedures are proposed to solve the model using a Mixed Integer Non Linear Programming (MINLP) and algorithm methods. Then, the numerical example is provided to illustrate the system and results are discussed.

Calcium Intervention Ameliorates Experimental Model of Multiple Sclerosis

Directory of Open Access Journals (Sweden)

Dariush Haghmorad

2014-05-01

Full Text Available Objective: Multiple sclerosis (MS is the most common inflammatory disease of the CNS. Experimental autoimmune encephalomyelitis (EAE is a widely used model for MS. In the present research, our aim was to test the therapeutic efficacy of Calcium (Ca in an experimental model of MS. Methods: In this study the experiment was done on C57BL/6 mice. EAE was induced using 200 μg of the MOG35-55 peptide emulsified in CFA and injected subcutaneously on day 0 over two flank areas. In addition, 250 ng of pertussis toxin was injected on days 0 and 2. In the treatment group, 30 mg/kg Ca was administered intraperitoneally four times at regular 48 hour intervals. The mice were sacrificed 21 days after EAE induction and blood samples were taken from their hearts. The brains of mice were removed for histological analysis and their isolated splenocytes were cultured. Results: Our results showed that treatment with Ca caused a significant reduction in the severity of the EAE. Histological analysis indicated that there was no plaque in brain sections of Ca treated group of mice whereas 4 ± 1 plaques were detected in brain sections of controls. The density of mononuclear infiltration in the CNS of Ca treated mice was lower than in controls. The serum level of Nitric Oxide in the treatment group was lower than in the control group but was not significant. Moreover, the levels of IFN-γ in cell culture supernatant of splenocytes in treated mice were significantly lower than in the control group. Conclusion: The data indicates that Ca intervention can effectively attenuate EAE progression.

Modeling, control and optimization of water systems systems engineering methods for control and decision making tasks

CERN Document Server

2016-01-01

This book provides essential background knowledge on the development of model-based real-world solutions in the field of control and decision making for water systems. It presents system engineering methods for modelling surface water and groundwater resources as well as water transportation systems (rivers, channels and pipelines). The models in turn provide information on both the water quantity (flow rates, water levels) of surface water and groundwater and on water quality. In addition, methods for modelling and predicting water demand are described. Sample applications of the models are presented, such as a water allocation decision support system for semi-arid regions, a multiple-criteria control model for run-of-river hydropower plants, and a supply network simulation for public services.

Multiple commodities in statistical microeconomics: Model and market

Science.gov (United States)

Baaquie, Belal E.; Yu, Miao; Du, Xin

2016-11-01

A statistical generalization of microeconomics has been made in Baaquie (2013). In Baaquie et al. (2015), the market behavior of single commodities was analyzed and it was shown that market data provides strong support for the statistical microeconomic description of commodity prices. The case of multiple commodities is studied and a parsimonious generalization of the single commodity model is made for the multiple commodities case. Market data shows that the generalization can accurately model the simultaneous correlation functions of up to four commodities. To accurately model five or more commodities, further terms have to be included in the model. This study shows that the statistical microeconomics approach is a comprehensive and complete formulation of microeconomics, and which is independent to the mainstream formulation of microeconomics.

Dynamics modeling and periodic control of horizontal-axis wind turbines

Science.gov (United States)

Stol, Karl Alexander

2001-07-01

The development of large multi-megawatt wind turbines has increased the need for active feedback control to meet multiple performance objectives. Power regulation is still of prime concern but there is an increasing interest in mitigating loads for these very large, dynamically soft and highly integrated power systems. This work explores the opportunities for utilizing state space modeling, modal analysis, and multi-objective controllers in advanced horizontal-axis wind turbines. A linear state-space representation of a generic, multiple degree-of-freedom wind turbine is developed to test various control methods and paradigms. The structural model, SymDyn, provides for limited flexibility in the tower, drive train and blades assuming a rigid component architecture with joint springs and dampers. Equations of motion are derived symbolically, verified by numerical simulation, and implemented in the Matlab with Simulink computational environment. AeroDyn, an industry-standard aerodynamics package for wind turbines, provides the aerodynamic load data through interfaced subroutines. Linearization of the structural model produces state equations with periodic coefficients due to the interaction of rotating and non-rotating components. Floquet theory is used to extract the necessary modal properties and several parametric studies identify the damping levels and dominant dynamic coupling influences. Two separate issues of control design are investigated: full-state feedback and state estimation. Periodic gains are developed using time-varying LQR techniques and many different time-invariant control designs are constructed, including a classical PID controller. Disturbance accommodating control (DAC) allows the estimation of wind speed for minimization of the disturbance effects on the system. Controllers are tested in simulation for multiple objectives using measurement of rotor position and rotor speed only and actuation of independent blade pitch. It is found that

AgMIP Training in Multiple Crop Models and Tools

Science.gov (United States)

Boote, Kenneth J.; Porter, Cheryl H.; Hargreaves, John; Hoogenboom, Gerrit; Thornburn, Peter; Mutter, Carolyn

2015-01-01

The Agricultural Model Intercomparison and Improvement Project (AgMIP) has the goal of using multiple crop models to evaluate climate impacts on agricultural production and food security in developed and developing countries. There are several major limitations that must be overcome to achieve this goal, including the need to train AgMIP regional research team (RRT) crop modelers to use models other than the ones they are currently familiar with, plus the need to harmonize and interconvert the disparate input file formats used for the various models. Two activities were followed to address these shortcomings among AgMIP RRTs to enable them to use multiple models to evaluate climate impacts on crop production and food security. We designed and conducted courses in which participants trained on two different sets of crop models, with emphasis on the model of least experience. In a second activity, the AgMIP IT group created templates for inputting data on soils, management, weather, and crops into AgMIP harmonized databases, and developed translation tools for converting the harmonized data into files that are ready for multiple crop model simulations. The strategies for creating and conducting the multi-model course and developing entry and translation tools are reviewed in this chapter.

Efficient Adoption and Assessment of Multiple Process Improvement Reference Models

Directory of Open Access Journals (Sweden)

Simona Jeners

2013-06-01

Full Text Available A variety of reference models such as CMMI, COBIT or ITIL support IT organizations to improve their processes. These process improvement reference models (IRMs cover different domains such as IT development, IT Services or IT Governance but also share some similarities. As there are organizations that address multiple domains and need to coordinate their processes in their improvement we present MoSaIC, an approach to support organizations to efficiently adopt and conform to multiple IRMs. Our solution realizes a semantic integration of IRMs based on common meta-models. The resulting IRM integration model enables organizations to efficiently implement and asses multiple IRMs and to benefit from synergy effects.

Advanced topics in control and estimation of state-multiplicative noisy systems

CERN Document Server

Gershon, Eli

2013-01-01

Advanced Topics in Control and Estimation of State-Multiplicative Noisy Systems begins with an introduction and extensive literature survey. The text proceeds to cover solutions of measurement-feedback control and state problems and the formulation of the Bounded Real Lemma for both continuous- and discrete-time systems. The continuous-time reduced-order and stochastic-tracking control problems for delayed systems are then treated. Ideas of nonlinear stability are introduced for infinite-horizon systems, again, in both the continuous- and discrete-time cases. The reader is introduced to six practical examples of noisy state-multiplicative control and filtering associated with various fields of control engineering. The book is rounded out by a three-part appendix containing stochastic tools necessary for a proper appreciation of the text: a basic introduction to nonlinear stochastic differential equations and aspects of switched systems and peak to peak  optimal control and filtering. Advanced Topics in Contr...

Dinucleotide controlled null models for comparative RNA gene prediction.

Science.gov (United States)

Gesell, Tanja; Washietl, Stefan

2008-05-27

Comparative prediction of RNA structures can be used to identify functional noncoding RNAs in genomic screens. It was shown recently by Babak et al. [BMC Bioinformatics. 8:33] that RNA gene prediction programs can be biased by the genomic dinucleotide content, in particular those programs using a thermodynamic folding model including stacking energies. As a consequence, there is need for dinucleotide-preserving control strategies to assess the significance of such predictions. While there have been randomization algorithms for single sequences for many years, the problem has remained challenging for multiple alignments and there is currently no algorithm available. We present a program called SISSIz that simulates multiple alignments of a given average dinucleotide content. Meeting additional requirements of an accurate null model, the randomized alignments are on average of the same sequence diversity and preserve local conservation and gap patterns. We make use of a phylogenetic substitution model that includes overlapping dependencies and site-specific rates. Using fast heuristics and a distance based approach, a tree is estimated under this model which is used to guide the simulations. The new algorithm is tested on vertebrate genomic alignments and the effect on RNA structure predictions is studied. In addition, we directly combined the new null model with the RNAalifold consensus folding algorithm giving a new variant of a thermodynamic structure based RNA gene finding program that is not biased by the dinucleotide content. SISSIz implements an efficient algorithm to randomize multiple alignments preserving dinucleotide content. It can be used to get more accurate estimates of false positive rates of existing programs, to produce negative controls for the training of machine learning based programs, or as standalone RNA gene finding program. Other applications in comparative genomics that require randomization of multiple alignments can be considered. SISSIz

Dinucleotide controlled null models for comparative RNA gene prediction

Directory of Open Access Journals (Sweden)

Gesell Tanja

2008-05-01

Full Text Available Abstract Background Comparative prediction of RNA structures can be used to identify functional noncoding RNAs in genomic screens. It was shown recently by Babak et al. [BMC Bioinformatics. 8:33] that RNA gene prediction programs can be biased by the genomic dinucleotide content, in particular those programs using a thermodynamic folding model including stacking energies. As a consequence, there is need for dinucleotide-preserving control strategies to assess the significance of such predictions. While there have been randomization algorithms for single sequences for many years, the problem has remained challenging for multiple alignments and there is currently no algorithm available. Results We present a program called SISSIz that simulates multiple alignments of a given average dinucleotide content. Meeting additional requirements of an accurate null model, the randomized alignments are on average of the same sequence diversity and preserve local conservation and gap patterns. We make use of a phylogenetic substitution model that includes overlapping dependencies and site-specific rates. Using fast heuristics and a distance based approach, a tree is estimated under this model which is used to guide the simulations. The new algorithm is tested on vertebrate genomic alignments and the effect on RNA structure predictions is studied. In addition, we directly combined the new null model with the RNAalifold consensus folding algorithm giving a new variant of a thermodynamic structure based RNA gene finding program that is not biased by the dinucleotide content. Conclusion SISSIz implements an efficient algorithm to randomize multiple alignments preserving dinucleotide content. It can be used to get more accurate estimates of false positive rates of existing programs, to produce negative controls for the training of machine learning based programs, or as standalone RNA gene finding program. Other applications in comparative genomics that require

A network control theory approach to modeling and optimal control of zoonoses: case study of brucellosis transmission in sub-Saharan Africa.

Science.gov (United States)

Roy, Sandip; McElwain, Terry F; Wan, Yan

2011-10-01

Developing control policies for zoonotic diseases is challenging, both because of the complex spread dynamics exhibited by these diseases, and because of the need for implementing complex multi-species surveillance and control efforts using limited resources. Mathematical models, and in particular network models, of disease spread are promising as tools for control-policy design, because they can provide comprehensive quantitative representations of disease transmission. A layered dynamical network model for the transmission and control of zoonotic diseases is introduced as a tool for analyzing disease spread and designing cost-effective surveillance and control. The model development is achieved using brucellosis transmission among wildlife, cattle herds, and human sub-populations in an agricultural system as a case study. Precisely, a model that tracks infection counts in interacting animal herds of multiple species (e.g., cattle herds and groups of wildlife for brucellosis) and in human subpopulations is introduced. The model is then abstracted to a form that permits comprehensive targeted design of multiple control capabilities as well as model identification from data. Next, techniques are developed for such quantitative design of control policies (that are directed to both the animal and human populations), and for model identification from snapshot and time-course data, by drawing on recent results in the network control community. The modeling approach is shown to provide quantitative insight into comprehensive control policies for zoonotic diseases, and in turn to permit policy design for mitigation of these diseases. For the brucellosis-transmission example in particular, numerous insights are obtained regarding the optimal distribution of resources among available control capabilities (e.g., vaccination, surveillance and culling, pasteurization of milk) and points in the spread network (e.g., transhumance vs. sedentary herds). In addition, a preliminary

A network control theory approach to modeling and optimal control of zoonoses: case study of brucellosis transmission in sub-Saharan Africa.

Directory of Open Access Journals (Sweden)

Sandip Roy

2011-10-01

Full Text Available BACKGROUND: Developing control policies for zoonotic diseases is challenging, both because of the complex spread dynamics exhibited by these diseases, and because of the need for implementing complex multi-species surveillance and control efforts using limited resources. Mathematical models, and in particular network models, of disease spread are promising as tools for control-policy design, because they can provide comprehensive quantitative representations of disease transmission. METHODOLOGY/PRINCIPAL FINDINGS: A layered dynamical network model for the transmission and control of zoonotic diseases is introduced as a tool for analyzing disease spread and designing cost-effective surveillance and control. The model development is achieved using brucellosis transmission among wildlife, cattle herds, and human sub-populations in an agricultural system as a case study. Precisely, a model that tracks infection counts in interacting animal herds of multiple species (e.g., cattle herds and groups of wildlife for brucellosis and in human subpopulations is introduced. The model is then abstracted to a form that permits comprehensive targeted design of multiple control capabilities as well as model identification from data. Next, techniques are developed for such quantitative design of control policies (that are directed to both the animal and human populations, and for model identification from snapshot and time-course data, by drawing on recent results in the network control community. CONCLUSIONS/SIGNIFICANCE: The modeling approach is shown to provide quantitative insight into comprehensive control policies for zoonotic diseases, and in turn to permit policy design for mitigation of these diseases. For the brucellosis-transmission example in particular, numerous insights are obtained regarding the optimal distribution of resources among available control capabilities (e.g., vaccination, surveillance and culling, pasteurization of milk and points in

A test for the parameters of multiple linear regression models ...

African Journals Online (AJOL)

A test for the parameters of multiple linear regression models is developed for conducting tests simultaneously on all the parameters of multiple linear regression models. The test is robust relative to the assumptions of homogeneity of variances and absence of serial correlation of the classical F-test. Under certain null and ...

A mathematical model for incorporating biofeedback into human postural control

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Ersal Tulga

2013-02-01

Full Text Available Abstract Background Biofeedback of body motion can serve as a balance aid and rehabilitation tool. To date, mathematical models considering the integration of biofeedback into postural control have represented this integration as a sensory addition and limited their application to a single degree-of-freedom representation of the body. This study has two objectives: 1 to develop a scalable method for incorporating biofeedback into postural control that is independent of the model’s degrees of freedom, how it handles sensory integration, and the modeling of its postural controller; and 2 to validate this new model using multidirectional perturbation experimental results. Methods Biofeedback was modeled as an additional torque to the postural controller torque. For validation, this biofeedback modeling approach was applied to a vibrotactile biofeedback device and incorporated into a two-link multibody model with full-state-feedback control that represents the dynamics of bipedal stance. Average response trajectories of body sway and center of pressure (COP to multidirectional surface perturbations of subjects with vestibular deficits were used for model parameterization and validation in multiple perturbation directions and for multiple display resolutions. The quality of fit was quantified using average error and cross-correlation values. Results The mean of the average errors across all tactor configurations and perturbations was 0.24° for body sway and 0.39 cm for COP. The mean of the cross-correlation value was 0.97 for both body sway and COP. Conclusions The biofeedback model developed in this study is capable of capturing experimental response trajectory shapes with low average errors and high cross-correlation values in both the anterior-posterior and medial-lateral directions for all perturbation directions and spatial resolution display configurations considered. The results validate that biofeedback can be modeled as an additional

A mathematical model for incorporating biofeedback into human postural control

Science.gov (United States)

2013-01-01

Background Biofeedback of body motion can serve as a balance aid and rehabilitation tool. To date, mathematical models considering the integration of biofeedback into postural control have represented this integration as a sensory addition and limited their application to a single degree-of-freedom representation of the body. This study has two objectives: 1) to develop a scalable method for incorporating biofeedback into postural control that is independent of the model’s degrees of freedom, how it handles sensory integration, and the modeling of its postural controller; and 2) to validate this new model using multidirectional perturbation experimental results. Methods Biofeedback was modeled as an additional torque to the postural controller torque. For validation, this biofeedback modeling approach was applied to a vibrotactile biofeedback device and incorporated into a two-link multibody model with full-state-feedback control that represents the dynamics of bipedal stance. Average response trajectories of body sway and center of pressure (COP) to multidirectional surface perturbations of subjects with vestibular deficits were used for model parameterization and validation in multiple perturbation directions and for multiple display resolutions. The quality of fit was quantified using average error and cross-correlation values. Results The mean of the average errors across all tactor configurations and perturbations was 0.24° for body sway and 0.39 cm for COP. The mean of the cross-correlation value was 0.97 for both body sway and COP. Conclusions The biofeedback model developed in this study is capable of capturing experimental response trajectory shapes with low average errors and high cross-correlation values in both the anterior-posterior and medial-lateral directions for all perturbation directions and spatial resolution display configurations considered. The results validate that biofeedback can be modeled as an additional torque to the postural

Parametric modeling for damped sinusoids from multiple channels

DEFF Research Database (Denmark)

Zhou, Zhenhua; So, Hing Cheung; Christensen, Mads Græsbøll

2013-01-01

frequencies and damping factors are then computed with the multi-channel weighted linear prediction method. The estimated sinusoidal poles are then matched to each channel according to the extreme value theory of distribution of random fields. Simulations are performed to show the performance advantages......The problem of parametric modeling for noisy damped sinusoidal signals from multiple channels is addressed. Utilizing the shift invariance property of the signal subspace, the number of distinct sinusoidal poles in the multiple channels is first determined. With the estimated number, the distinct...... of the proposed multi-channel sinusoidal modeling methodology compared with existing methods....

A model for diagnosing and explaining multiple disorders.

Science.gov (United States)

Jamieson, P W

1991-08-01

The ability to diagnose multiple interacting disorders and explain them in a coherent causal framework has only partially been achieved in medical expert systems. This paper proposes a causal model for diagnosing and explaining multiple disorders whose key elements are: physician-directed hypotheses generation, object-oriented knowledge representation, and novel explanation heuristics. The heuristics modify and link the explanations to make the physician aware of diagnostic complexities. A computer program incorporating the model currently is in use for diagnosing peripheral nerve and muscle disorders. The program successfully diagnoses and explains interactions between diseases in terms of underlying pathophysiologic concepts. The model offers a new architecture for medical domains where reasoning from first principles is difficult but explanation of disease interactions is crucial for the system's operation.

The Multiplicity of Controls and the Making of Innovation

DEFF Research Database (Denmark)

Revellino, Silvana; Mouritsen, Jan

2009-01-01

are mediated by unique sets of technologies of control. In this process the innovation changes and adapts. This thesis is drawn from the case of Italian Autostrade's innovation Telepass which was an automatic toll collection devise developed to make traffic fast, safe and fluid. Throughout its development...... satisfaction, productivity and highly pointed achievement targets. This multiplicity of controls changed and adapted to the innovation as the innovation unfolds. The controls were part of the innovation more likely than an external device to make it transparent. They engaged the individual trials and changed...

Hybrid Multiple Soft-Sensor Models of Grinding Granularity Based on Cuckoo Searching Algorithm and Hysteresis Switching Strategy

Directory of Open Access Journals (Sweden)

Jie-Sheng Wang

2015-01-01

Full Text Available According to the characteristics of grinding process and accuracy requirements of technical indicators, a hybrid multiple soft-sensor modeling method of grinding granularity is proposed based on cuckoo searching (CS algorithm and hysteresis switching (HS strategy. Firstly, a mechanism soft-sensor model of grinding granularity is deduced based on the technique characteristics and a lot of experimental data of grinding process. Meanwhile, the BP neural network soft-sensor model and wavelet neural network (WNN soft-sensor model are set up. Then, the hybrid multiple soft-sensor model based on the hysteresis switching strategy is realized. That is to say, the optimum model is selected as the current predictive model according to the switching performance index at each sampling instant. Finally the cuckoo searching algorithm is adopted to optimize the performance parameters of hysteresis switching strategy. Simulation results show that the proposed model has better generalization results and prediction precision, which can satisfy the real-time control requirements of grinding classification process.

Autonomous and controlled motivational regulations for multiple health-related behaviors: between- and within-participants analyses

Science.gov (United States)

Hagger, M.S.; Hardcastle, S.J.; Chater, A.; Mallett, C.; Pal, S.; Chatzisarantis, N.L.D.

2014-01-01

Self-determination theory has been applied to the prediction of a number of health-related behaviors with self-determined or autonomous forms of motivation generally more effective in predicting health behavior than non-self-determined or controlled forms. Research has been confined to examining the motivational predictors in single health behaviors rather than comparing effects across multiple behaviors. The present study addressed this gap in the literature by testing the relative contribution of autonomous and controlling motivation to the prediction of a large number of health-related behaviors, and examining individual differences in self-determined motivation as a moderator of the effects of autonomous and controlling motivation on health behavior. Participants were undergraduate students (N = 140) who completed measures of autonomous and controlled motivational regulations and behavioral intention for 20 health-related behaviors at an initial occasion with follow-up behavioral measures taken four weeks later. Path analysis was used to test a process model for each behavior in which motivational regulations predicted behavior mediated by intentions. Some minor idiosyncratic findings aside, between-participants analyses revealed significant effects for autonomous motivational regulations on intentions and behavior across the 20 behaviors. Effects for controlled motivation on intentions and behavior were relatively modest by comparison. Intentions mediated the effect of autonomous motivation on behavior. Within-participants analyses were used to segregate the sample into individuals who based their intentions on autonomous motivation (autonomy-oriented) and controlled motivation (control-oriented). Replicating the between-participants path analyses for the process model in the autonomy- and control-oriented samples did not alter the relative effects of the motivational orientations on intention and behavior. Results provide evidence for consistent effects

Application of Multiple Evaluation Models in Brazil

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Rafael Victal Saliba

2008-07-01

Full Text Available Based on two different samples, this article tests the performance of a number of Value Drivers commonly used for evaluating companies by finance practitioners, through simple regression models of cross-section type which estimate the parameters associated to each Value Driver, denominated Market Multiples. We are able to diagnose the behavior of several multiples in the period 1994-2004, with an outlook also on the particularities of the economic activities performed by the sample companies (and their impacts on the performance through a subsequent analysis with segregation of companies in the sample by sectors. Extrapolating simple multiples evaluation standards from analysts of the main financial institutions in Brazil, we find that adjusting the ratio formulation to allow for an intercept does not provide satisfactory results in terms of pricing errors reduction. Results found, in spite of evidencing certain relative and absolute superiority among the multiples, may not be generically representative, given samples limitation.

Design of a model predictive load-following controller by discrete optimization of control rod speed for PWRs

International Nuclear Information System (INIS)

Kim, Jae Hwan; Park, Soon Ho; Na, Man Gyun

2014-01-01

Highlights: • A model predictive controller for load-following operation was developed. • Genetic algorithm optimizes the five nonlinear discrete control rod speeds. • The boron concentration is adjusted with automatic adjustment logic. • The proposed controller reflects the realistic control rod drive mechanism movement. • The performance was confirmed to be satisfactory by simulation from BOC to EOC. - Abstract: Currently, most existing nuclear power plants alter the reactor power by adjusting the boron concentration in the coolant because it has a smaller effect on the reactor power distribution. Frequent control rod movements for load-following operation induce xenon-oscillation. Therefore, a controller that can subdue this phenomenon effectively is needed. At an APR1400 nuclear power plant which is a pressurized water reactor (PWR), the reactor power is controlled automatically using a Reactor Regulating System (RRS) but the power distribution is controlled manually by operators. Therefore, for APR+ nuclear power plants which is an improved version of APR1400 nuclear reactor, a new concept of a reactor controller is needed to control both the reactor power and power distribution automatically. The model predictive control (MPC) method is applicable to multiple-input multiple-output control, and can be applied for complex and nonlinear systems, such as the nuclear power plants. In this study, an MPC controller was developed by applying a genetic algorithm to optimize the discrete control rod speeds and by reflecting the realistic movement of the control rod drive mechanism that moves at only five discrete speeds. The performance of the proposed controller was confirmed to be satisfactory by simulating the load-following operation of an APR+ nuclear power plant through interface with KISPAC-1D code

Vibration control of uncertain multiple launch rocket system using radial basis function neural network

Science.gov (United States)

Li, Bo; Rui, Xiaoting

2018-01-01

Poor dispersion characteristics of rockets due to the vibration of Multiple Launch Rocket System (MLRS) have always restricted the MLRS development for several decades. Vibration control is a key technique to improve the dispersion characteristics of rockets. For a mechanical system such as MLRS, the major difficulty in designing an appropriate control strategy that can achieve the desired vibration control performance is to guarantee the robustness and stability of the control system under the occurrence of uncertainties and nonlinearities. To approach this problem, a computed torque controller integrated with a radial basis function neural network is proposed to achieve the high-precision vibration control for MLRS. In this paper, the vibration response of a computed torque controlled MLRS is described. The azimuth and elevation mechanisms of the MLRS are driven by permanent magnet synchronous motors and supposed to be rigid. First, the dynamic model of motor-mechanism coupling system is established using Lagrange method and field-oriented control theory. Then, in order to deal with the nonlinearities, a computed torque controller is designed to control the vibration of the MLRS when it is firing a salvo of rockets. Furthermore, to compensate for the lumped uncertainty due to parametric variations and un-modeled dynamics in the design of the computed torque controller, a radial basis function neural network estimator is developed to adapt the uncertainty based on Lyapunov stability theory. Finally, the simulated results demonstrate the effectiveness of the proposed control system and show that the proposed controller is robust with regard to the uncertainty.

Accelerated spike resampling for accurate multiple testing controls.

Science.gov (United States)

Harrison, Matthew T

2013-02-01

Controlling for multiple hypothesis tests using standard spike resampling techniques often requires prohibitive amounts of computation. Importance sampling techniques can be used to accelerate the computation. The general theory is presented, along with specific examples for testing differences across conditions using permutation tests and for testing pairwise synchrony and precise lagged-correlation between many simultaneously recorded spike trains using interval jitter.

Study of system dynamics model and control of a high-power LED lighting luminaire

International Nuclear Information System (INIS)

Huang, B.-J.; Hsu, P.-C.; Wu, M.-S.; Tang, C.-W.

2007-01-01

The purpose of the present study is to design a current control system which is robust to the system dynamics uncertainty and the disturbance of ambient temperature to assure a stable optical output property of LED. The system dynamics model of the LED lighting system was first derived. A 96 W high-power LED luminaire was designed and built in the present study. The linearly perturbed system dynamics model for the LED luminaire is derived experimentally. The dynamics model of LED lighting system is of a multiple-input-multiple-output (MIMO) system with two inputs (applied voltage and ambient temperature) and two outputs (forward current and heat conducting body temperature). A step response test method was employed to the 96 W LED luminaire to identify the system dynamics model. It is found that the current model is just a constant gain (resistance) and the disturbance model is of first order, both changing with operating conditions (voltage and ambient temperature). A feedback control system using PI algorithm was designed using the results of the system dynamics model. The control system was implemented on a PIC microprocessor. Experimental results show that the control system can stably and accurately control the LED current to a constant value at the variation of ambient temperature up to 40 o C. The control system is shown to have a robust property with respect to the plant uncertainty and the ambient temperature disturbance

Deterministic integer multiple firing depending on initial state in Wang model

Energy Technology Data Exchange (ETDEWEB)

Xie Yong [Institute of Nonlinear Dynamics, MSSV, Department of Engineering Mechanics, Xi' an Jiaotong University, Xi' an 710049 (China)]. E-mail: yxie@mail.xjtu.edu.cn; Xu Jianxue [Institute of Nonlinear Dynamics, MSSV, Department of Engineering Mechanics, Xi' an Jiaotong University, Xi' an 710049 (China); Jiang Jun [Institute of Nonlinear Dynamics, MSSV, Department of Engineering Mechanics, Xi' an Jiaotong University, Xi' an 710049 (China)

2006-12-15

We investigate numerically dynamical behaviour of the Wang model, which describes the rhythmic activities of thalamic relay neurons. The model neuron exhibits Type I excitability from a global view, but Type II excitability from a local view. There exists a narrow range of bistability, in which a subthreshold oscillation and a suprathreshold firing behaviour coexist. A special firing pattern, integer multiple firing can be found in the certain part of the bistable range. The characteristic feature of such firing pattern is that the histogram of interspike intervals has a multipeaked structure, and the peaks are located at about integer multiples of a basic interspike interval. Since the Wang model is noise-free, the integer multiple firing is a deterministic firing pattern. The existence of bistability leads to the deterministic integer multiple firing depending on the initial state of the model neuron, i.e., the initial values of the state variables.

Deterministic integer multiple firing depending on initial state in Wang model

International Nuclear Information System (INIS)

Xie Yong; Xu Jianxue; Jiang Jun

2006-01-01

We investigate numerically dynamical behaviour of the Wang model, which describes the rhythmic activities of thalamic relay neurons. The model neuron exhibits Type I excitability from a global view, but Type II excitability from a local view. There exists a narrow range of bistability, in which a subthreshold oscillation and a suprathreshold firing behaviour coexist. A special firing pattern, integer multiple firing can be found in the certain part of the bistable range. The characteristic feature of such firing pattern is that the histogram of interspike intervals has a multipeaked structure, and the peaks are located at about integer multiples of a basic interspike interval. Since the Wang model is noise-free, the integer multiple firing is a deterministic firing pattern. The existence of bistability leads to the deterministic integer multiple firing depending on the initial state of the model neuron, i.e., the initial values of the state variables

Multiple regression and beyond an introduction to multiple regression and structural equation modeling

CERN Document Server

Keith, Timothy Z

2014-01-01

Multiple Regression and Beyond offers a conceptually oriented introduction to multiple regression (MR) analysis and structural equation modeling (SEM), along with analyses that flow naturally from those methods. By focusing on the concepts and purposes of MR and related methods, rather than the derivation and calculation of formulae, this book introduces material to students more clearly, and in a less threatening way. In addition to illuminating content necessary for coursework, the accessibility of this approach means students are more likely to be able to conduct research using MR or SEM--and more likely to use the methods wisely. Covers both MR and SEM, while explaining their relevance to one another Also includes path analysis, confirmatory factor analysis, and latent growth modeling Figures and tables throughout provide examples and illustrate key concepts and techniques For additional resources, please visit: http://tzkeith.com/.

Attacking the mosquito on multiple fronts: Insights from the Vector Control Optimization Model (VCOM for malaria elimination.

Directory of Open Access Journals (Sweden)

Samson S Kiware

Full Text Available Despite great achievements by insecticide-treated nets (ITNs and indoor residual spraying (IRS in reducing malaria transmission, it is unlikely these tools will be sufficient to eliminate malaria transmission on their own in many settings today. Fortunately, field experiments indicate that there are many promising vector control interventions that can be used to complement ITNs and/or IRS by targeting a wide range of biological and environmental mosquito resources. The majority of these experiments were performed to test a single vector control intervention in isolation; however, there is growing evidence and consensus that effective vector control with the goal of malaria elimination will require a combination of interventions.We have developed a model of mosquito population dynamic to describe the mosquito life and feeding cycles and to optimize the impact of vector control intervention combinations at suppressing mosquito populations. The model simulations were performed for the main three malaria vectors in sub-Saharan Africa, Anopheles gambiae s.s, An. arabiensis and An. funestus. We considered areas having low, moderate and high malaria transmission, corresponding to entomological inoculation rates of 10, 50 and 100 infective bites per person per year, respectively. In all settings, we considered baseline ITN coverage of 50% or 80% in addition to a range of other vector control tools to interrupt malaria transmission. The model was used to sweep through parameters space to select the best optimal intervention packages. Sample model simulations indicate that, starting with ITNs at a coverage of 50% (An. gambiae s.s. and An. funestus or 80% (An. arabiensis and adding interventions that do not require human participation (e.g. larviciding at 80% coverage, endectocide treated cattle at 50% coverage and attractive toxic sugar baits at 50% coverage may be sufficient to suppress all the three species to an extent required to achieve local malaria

New Hybrid Variational Recovery Model for Blurred Images with Multiplicative Noise

DEFF Research Database (Denmark)

Dong, Yiqiu; Zeng, Tieyong

2013-01-01

A new hybrid variational model for recovering blurred images in the presence of multiplicative noise is proposed. Inspired by previous work on multiplicative noise removal, an I-divergence technique is used to build a strictly convex model under a condition that ensures the uniqueness...

On decentralized adaptive full-order sliding mode control of multiple UAVs.

Science.gov (United States)

Xiang, Xianbo; Liu, Chao; Su, Housheng; Zhang, Qin

2017-11-01

In this study, a novel decentralized adaptive full-order sliding mode control framework is proposed for the robust synchronized formation motion of multiple unmanned aerial vehicles (UAVs) subject to system uncertainty. First, a full-order sliding mode surface in a decentralized manner is designed to incorporate both the individual position tracking error and the synchronized formation error while the UAV group is engaged in building a certain desired geometric pattern in three dimensional space. Second, a decentralized virtual plant controller is constructed which allows the embedded low-pass filter to attain the chattering free property of the sliding mode controller. In addition, robust adaptive technique is integrated in the decentralized chattering free sliding control design in order to handle unknown bounded uncertainties, without requirements for assuming a priori knowledge of bounds on the system uncertainties as stated in conventional chattering free control methods. Subsequently, system robustness as well as stability of the decentralized full-order sliding mode control of multiple UAVs is synthesized. Numerical simulation results illustrate the effectiveness of the proposed control framework to achieve robust 3D formation flight of the multi-UAV system. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.

Patch models and their applications to multivehicle command and control.

Science.gov (United States)

Rao, Venkatesh G; D'Andrea, Raffaello

2007-06-01

We introduce patch models, a computational modeling formalism for multivehicle combat domains, based on spatiotemporal abstraction methods developed in the computer science community. The framework yields models that are expressive enough to accommodate nontrivial controlled vehicle dynamics while being within the representational capabilities of common artificial intelligence techniques used in the construction of autonomous systems. The framework allows several key design requirements of next-generation network-centric command and control systems, such as maintenance of shared situation awareness, to be achieved. Major features include support for multiple situation models at each decision node and rapid mission plan adaptation. We describe the formal specification of patch models and our prototype implementation, i.e., Patchworks. The capabilities of patch models are validated through a combat mission simulation in Patchworks, which involves two defending teams protecting a camp from an enemy attacking team.

Developing Access Control Model of Web OLAP over Trusted and Collaborative Data Warehouses

Science.gov (United States)

Fugkeaw, Somchart; Mitrpanont, Jarernsri L.; Manpanpanich, Piyawit; Juntapremjitt, Sekpon

This paper proposes the design and development of Role- based Access Control (RBAC) model for the Single Sign-On (SSO) Web-OLAP query spanning over multiple data warehouses (DWs). The model is based on PKI Authentication and Privilege Management Infrastructure (PMI); it presents a binding model of RBAC authorization based on dimension privilege specified in attribute certificate (AC) and user identification. Particularly, the way of attribute mapping between DW user authentication and privilege of dimensional access is illustrated. In our approach, we apply the multi-agent system to automate flexible and effective management of user authentication, role delegation as well as system accountability. Finally, the paper culminates in the prototype system A-COLD (Access Control of web-OLAP over multiple DWs) that incorporates the OLAP features and authentication and authorization enforcement in the multi-user and multi-data warehouse environment.

Combustion Model and Control Parameter Optimization Methods for Single Cylinder Diesel Engine

Directory of Open Access Journals (Sweden)

Bambang Wahono

2014-01-01

Full Text Available This research presents a method to construct a combustion model and a method to optimize some control parameters of diesel engine in order to develop a model-based control system. The construction purpose of the model is to appropriately manage some control parameters to obtain the values of fuel consumption and emission as the engine output objectives. Stepwise method considering multicollinearity was applied to construct combustion model with the polynomial model. Using the experimental data of a single cylinder diesel engine, the model of power, BSFC, NOx, and soot on multiple injection diesel engines was built. The proposed method succesfully developed the model that describes control parameters in relation to the engine outputs. Although many control devices can be mounted to diesel engine, optimization technique is required to utilize this method in finding optimal engine operating conditions efficiently beside the existing development of individual emission control methods. Particle swarm optimization (PSO was used to calculate control parameters to optimize fuel consumption and emission based on the model. The proposed method is able to calculate control parameters efficiently to optimize evaluation item based on the model. Finally, the model which added PSO then was compiled in a microcontroller.

A generic model for camera based intelligent road crowd control ...

African Journals Online (AJOL)

This research proposes a model for intelligent traffic flow control by implementing camera based surveillance and feedback system. A series of cameras are set minimum three signals ahead from the target junction. The complete software system is developed to help integrating the multiple camera on road as feedback to ...

Sliding-mode control of single input multiple output DC-DC converter

Science.gov (United States)

Zhang, Libo; Sun, Yihan; Luo, Tiejian; Wan, Qiyang

2016-10-01

Various voltage levels are required in the vehicle mounted power system. A conventional solution is to utilize an independent multiple output DC-DC converter whose cost is high and control scheme is complicated. In this paper, we design a novel SIMO DC-DC converter with sliding mode controller. The proposed converter can boost the voltage of a low-voltage input power source to a controllable high-voltage DC bus and middle-voltage output terminals, which endow the converter with characteristics of simple structure, low cost, and convenient control. In addition, the sliding mode control (SMC) technique applied in our converter can enhance the performances of a certain SIMO DC-DC converter topology. The high-voltage DC bus can be regarded as the main power source to the high-voltage facility of the vehicle mounted power system, and the middle-voltage output terminals can supply power to the low-voltage equipment on an automobile. In the respect of control algorithm, it is the first time to propose the SMC-PID (Proportion Integration Differentiation) control algorithm, in which the SMC algorithm is utilized and the PID control is attended to the conventional SMC algorithm. The PID control increases the dynamic ability of the SMC algorithm by establishing the corresponding SMC surface and introducing the attached integral of voltage error, which endow the sliding-control system with excellent dynamic performance. At last, we established the MATLAB/SIMULINK simulation model, tested performance of the system, and built the hardware prototype based on Digital Signal Processor (DSP). Results show that the sliding mode control is able to track a required trajectory, which has robustness against the uncertainties and disturbances.

A Multiple Agent Model of Human Performance in Automated Air Traffic Control and Flight Management Operations

Science.gov (United States)

Corker, Kevin; Pisanich, Gregory; Condon, Gregory W. (Technical Monitor)

1995-01-01

A predictive model of human operator performance (flight crew and air traffic control (ATC)) has been developed and applied in order to evaluate the impact of automation developments in flight management and air traffic control. The model is used to predict the performance of a two person flight crew and the ATC operators generating and responding to clearances aided by the Center TRACON Automation System (CTAS). The purpose of the modeling is to support evaluation and design of automated aids for flight management and airspace management and to predict required changes in procedure both air and ground in response to advancing automation in both domains. Additional information is contained in the original extended abstract.

A Bayesian Hierarchical Model for Relating Multiple SNPs within Multiple Genes to Disease Risk

Directory of Open Access Journals (Sweden)

Lewei Duan

2013-01-01

Full Text Available A variety of methods have been proposed for studying the association of multiple genes thought to be involved in a common pathway for a particular disease. Here, we present an extension of a Bayesian hierarchical modeling strategy that allows for multiple SNPs within each gene, with external prior information at either the SNP or gene level. The model involves variable selection at the SNP level through latent indicator variables and Bayesian shrinkage at the gene level towards a prior mean vector and covariance matrix that depend on external information. The entire model is fitted using Markov chain Monte Carlo methods. Simulation studies show that the approach is capable of recovering many of the truly causal SNPs and genes, depending upon their frequency and size of their effects. The method is applied to data on 504 SNPs in 38 candidate genes involved in DNA damage response in the WECARE study of second breast cancers in relation to radiotherapy exposure.

Predictive performance models and multiple task performance

Science.gov (United States)

Wickens, Christopher D.; Larish, Inge; Contorer, Aaron

1989-01-01

Five models that predict how performance of multiple tasks will interact in complex task scenarios are discussed. The models are shown in terms of the assumptions they make about human operator divided attention. The different assumptions about attention are then empirically validated in a multitask helicopter flight simulation. It is concluded from this simulation that the most important assumption relates to the coding of demand level of different component tasks.

The implementation of multiple intelligences based teaching model to improve mathematical problem solving ability for student of junior high school

Science.gov (United States)

Fasni, Nurli; Fatimah, Siti; Yulanda, Syerli

2017-05-01

This research aims to achieve some purposes such as: to know whether mathematical problem solving ability of students who have learned mathematics using Multiple Intelligences based teaching model is higher than the student who have learned mathematics using cooperative learning; to know the improvement of the mathematical problem solving ability of the student who have learned mathematics using Multiple Intelligences based teaching model., to know the improvement of the mathematical problem solving ability of the student who have learned mathematics using cooperative learning; to know the attitude of the students to Multiple Intelligences based teaching model. The method employed here is quasi-experiment which is controlled by pre-test and post-test. The population of this research is all of VII grade in SMP Negeri 14 Bandung even-term 2013/2014, later on two classes of it were taken for the samples of this research. A class was taught using Multiple Intelligences based teaching model and the other one was taught using cooperative learning. The data of this research were gotten from the test in mathematical problem solving, scale questionnaire of the student attitudes, and observation. The results show the mathematical problem solving of the students who have learned mathematics using Multiple Intelligences based teaching model learning is higher than the student who have learned mathematics using cooperative learning, the mathematical problem solving ability of the student who have learned mathematics using cooperative learning and Multiple Intelligences based teaching model are in intermediate level, and the students showed the positive attitude in learning mathematics using Multiple Intelligences based teaching model. As for the recommendation for next author, Multiple Intelligences based teaching model can be tested on other subject and other ability.

MFAM: Multiple Frequency Adaptive Model-Based Indoor Localization Method.

Science.gov (United States)

Tuta, Jure; Juric, Matjaz B

2018-03-24

This paper presents MFAM (Multiple Frequency Adaptive Model-based localization method), a novel model-based indoor localization method that is capable of using multiple wireless signal frequencies simultaneously. It utilizes indoor architectural model and physical properties of wireless signal propagation through objects and space. The motivation for developing multiple frequency localization method lies in the future Wi-Fi standards (e.g., 802.11ah) and the growing number of various wireless signals present in the buildings (e.g., Wi-Fi, Bluetooth, ZigBee, etc.). Current indoor localization methods mostly rely on a single wireless signal type and often require many devices to achieve the necessary accuracy. MFAM utilizes multiple wireless signal types and improves the localization accuracy over the usage of a single frequency. It continuously monitors signal propagation through space and adapts the model according to the changes indoors. Using multiple signal sources lowers the required number of access points for a specific signal type while utilizing signals, already present in the indoors. Due to the unavailability of the 802.11ah hardware, we have evaluated proposed method with similar signals; we have used 2.4 GHz Wi-Fi and 868 MHz HomeMatic home automation signals. We have performed the evaluation in a modern two-bedroom apartment and measured mean localization error 2.0 to 2.3 m and median error of 2.0 to 2.2 m. Based on our evaluation results, using two different signals improves the localization accuracy by 18% in comparison to 2.4 GHz Wi-Fi-only approach. Additional signals would improve the accuracy even further. We have shown that MFAM provides better accuracy than competing methods, while having several advantages for real-world usage.

MFAM: Multiple Frequency Adaptive Model-Based Indoor Localization Method

Directory of Open Access Journals (Sweden)

Jure Tuta

2018-03-01

Full Text Available This paper presents MFAM (Multiple Frequency Adaptive Model-based localization method, a novel model-based indoor localization method that is capable of using multiple wireless signal frequencies simultaneously. It utilizes indoor architectural model and physical properties of wireless signal propagation through objects and space. The motivation for developing multiple frequency localization method lies in the future Wi-Fi standards (e.g., 802.11ah and the growing number of various wireless signals present in the buildings (e.g., Wi-Fi, Bluetooth, ZigBee, etc.. Current indoor localization methods mostly rely on a single wireless signal type and often require many devices to achieve the necessary accuracy. MFAM utilizes multiple wireless signal types and improves the localization accuracy over the usage of a single frequency. It continuously monitors signal propagation through space and adapts the model according to the changes indoors. Using multiple signal sources lowers the required number of access points for a specific signal type while utilizing signals, already present in the indoors. Due to the unavailability of the 802.11ah hardware, we have evaluated proposed method with similar signals; we have used 2.4 GHz Wi-Fi and 868 MHz HomeMatic home automation signals. We have performed the evaluation in a modern two-bedroom apartment and measured mean localization error 2.0 to 2.3 m and median error of 2.0 to 2.2 m. Based on our evaluation results, using two different signals improves the localization accuracy by 18% in comparison to 2.4 GHz Wi-Fi-only approach. Additional signals would improve the accuracy even further. We have shown that MFAM provides better accuracy than competing methods, while having several advantages for real-world usage.

Realtime control of multiple-focus phased array heating patterns based on noninvasive ultrasound thermography.

Science.gov (United States)

Casper, Andrew; Liu, Dalong; Ebbini, Emad S

2012-01-01

A system for the realtime generation and control of multiple-focus ultrasound phased-array heating patterns is presented. The system employs a 1-MHz, 64-element array and driving electronics capable of fine spatial and temporal control of the heating pattern. The driver is integrated with a realtime 2-D temperature imaging system implemented on a commercial scanner. The coordinates of the temperature control points are defined on B-mode guidance images from the scanner, together with the temperature set points and controller parameters. The temperature at each point is controlled by an independent proportional, integral, and derivative controller that determines the focal intensity at that point. Optimal multiple-focus synthesis is applied to generate the desired heating pattern at the control points. The controller dynamically reallocates the power available among the foci from the shared power supply upon reaching the desired temperature at each control point. Furthermore, anti-windup compensation is implemented at each control point to improve the system dynamics. In vitro experiments in tissue-mimicking phantom demonstrate the robustness of the controllers for short (2-5 s) and longer multiple-focus high-intensity focused ultrasound exposures. Thermocouple measurements in the vicinity of the control points confirm the dynamics of the temperature variations obtained through noninvasive feedback. © 2011 IEEE

Realization of quantum gates with multiple control qubits or multiple target qubits in a cavity

Science.gov (United States)

Waseem, Muhammad; Irfan, Muhammad; Qamar, Shahid

2015-06-01

We propose a scheme to realize a three-qubit controlled phase gate and a multi-qubit controlled NOT gate of one qubit simultaneously controlling n-target qubits with a four-level quantum system in a cavity. The implementation time for multi-qubit controlled NOT gate is independent of the number of qubit. Three-qubit phase gate is generalized to n-qubit phase gate with multiple control qubits. The number of steps reduces linearly as compared to conventional gate decomposition method. Our scheme can be applied to various types of physical systems such as superconducting qubits coupled to a resonator and trapped atoms in a cavity. Our scheme does not require adjustment of level spacing during the gate implementation. We also show the implementation of Deutsch-Joza algorithm. Finally, we discuss the imperfections due to cavity decay and the possibility of physical implementation of our scheme.

Memory-guided attention: Control from multiple memory systems

OpenAIRE

Hutchinson, J. Benjamin; Turk-Browne, Nicholas B.

2012-01-01

Attention is strongly influenced by both external stimuli and internal goals. However, this useful dichotomy does not readily capture the ubiquitous and often automatic contribution of past experience stored in memory. We review recent evidence about how multiple memory systems control attention, consider how such interactions are manifested in the brain, and highlight how this framework for ‘memory-guided attention’ might help systematize previous findings and guide future research.

Control of the exercise hyperpnoea in humans: a modeling perspective.

Science.gov (United States)

Ward, S A

2000-09-01

Models of the exercise hyperpnoea have classically incorporated elements of proportional feedback (carotid and medullary chemosensory) and feedforward (central and/or peripheral neurogenic) control. However, the precise details of the control process remain unresolved, reflecting in part both technical and interpretational limitations inherent in isolating putative control mechanisms in the intact human, and also the challenges to linear control theory presented by multiple-input integration, especially with regard to the ventilatory and gas-exchange complexities encountered at work rates which engender a metabolic acidosis. While some combination of neurogenic, chemoreflex and circulatory-coupled processes are likely to contribute to the control, the system appears to evidence considerable redundancy. This, coupled with the lack of appreciable error signals in the mean levels of arterial blood gas tensions and pH over a wide range of work rates, has motivated the formulation of innovative control models that reflect not only spatial interactions but also temporal interactions (i.e. memory). The challenge is to discriminate between robust competing control models that: (a) integrate such processes within plausible physiological equivalents; and (b) account for both the dynamic and steady-state system response over a range of exercise intensities. Such models are not yet available.

Multiple Model-Based Synchronization Approaches for Time Delayed Slaving Data in a Space Launch Vehicle Tracking System

Directory of Open Access Journals (Sweden)

Haryong Song

2016-01-01

Full Text Available Due to the inherent characteristics of the flight mission of a space launch vehicle (SLV, which is required to fly over very large distances and have very high fault tolerances, in general, SLV tracking systems (TSs comprise multiple heterogeneous sensors such as radars, GPS, INS, and electrooptical targeting systems installed over widespread areas. To track an SLV without interruption and to hand over the measurement coverage between TSs properly, the mission control system (MCS transfers slaving data to each TS through mission networks. When serious network delays occur, however, the slaving data from the MCS can lead to the failure of the TS. To address this problem, in this paper, we propose multiple model-based synchronization (MMS approaches, which take advantage of the multiple motion models of an SLV. Cubic spline extrapolation, prediction through an α-β-γ filter, and a single model Kalman filter are presented as benchmark approaches. We demonstrate the synchronization accuracy and effectiveness of the proposed MMS approaches using the Monte Carlo simulation with the nominal trajectory data of Korea Space Launch Vehicle-I.

Mechanistic Fermentation Models for Process Design, Monitoring, and Control

DEFF Research Database (Denmark)

Mears, Lisa; Stocks, Stuart M.; Albæk, Mads Orla

2017-01-01

Mechanistic models require a significant investment of time and resources, but their application to multiple stages of fermentation process development and operation can make this investment highly valuable. This Opinion article discusses how an established fermentation model may be adapted...... for application to different stages of fermentation process development: planning, process design, monitoring, and control. Although a longer development time is required for such modeling methods in comparison to purely data-based model techniques, the wide range of applications makes them a highly valuable tool...... for fermentation research and development. In addition, in a research environment, where collaboration is important, developing mechanistic models provides a platform for knowledge sharing and consolidation of existing process understanding....

Multiple Scattering Model for Optical Coherence Tomography with Rytov Approximation

KAUST Repository

Li, Muxingzi

2017-01-01

of speckles due to multiple scatterers within the coherence length, and other random noise. Motivated by the above two challenges, a multiple scattering model based on Rytov approximation and Gaussian beam optics is proposed for the OCT setup. Some previous

Stability Properties of Network Diversity Multiple Access with Multiple-Antenna Reception and Imperfect Collision Multiplicity Estimation

Directory of Open Access Journals (Sweden)

Ramiro Samano-Robles

2013-01-01

Full Text Available In NDMA (network diversity multiple access, protocol-controlled retransmissions are used to create a virtual MIMO (multiple-input multiple-output system, where collisions can be resolved via source separation. By using this retransmission diversity approach for collision resolution, NDMA is the family of random access protocols with the highest potential throughput. However, several issues remain open today in the modeling and design of this type of protocol, particularly in terms of dynamic stable performance and backlog delay. This paper attempts to partially fill this gap by proposing a Markov model for the study of the dynamic-stable performance of a symmetrical and non-blind NDMA protocol assisted by a multiple-antenna receiver. The model is useful in the study of stability aspects in terms of the backlog-user distribution and average backlog delay. It also allows for the investigation of the different states of the system and the transition probabilities between them. Unlike previous works, the proposed approach considers the imperfect estimation of the collision multiplicity, which is a crucial process to the performance of NDMA. The results suggest that NDMA improves not only the throughput performance over previous solutions, but also the average number of backlogged users, the average backlog delay and, in general, the stability of random access protocols. It is also shown that when multiuser detection conditions degrade, ALOHA-type backlog retransmission becomes relevant to the stable operation of NDMA.

A New Attribute Control Chart using Multiple Dependent State Repetitive Sampling

KAUST Repository

Aldosari, Mansour Sattam; Aslam, Muhammad; Jun, Chi-Hyuck

2017-01-01

In this manuscript, a new attribute control chart using multiple dependent state repetitive sampling is designed. The operational procedure and structure of the proposed control chart is given. The required measures to determine the average run length (ARL) for in-control and out-of-control processes are given. Tables of ARLs are reported for various control chart parameters. The proposed control chart is more sensitive in detecting a small shift in the process as compared to the existing attribute control charts. The simulation study shows the efficiency of the proposed chart over the existing charts. An example is given for the illustration purpose.

A New Attribute Control Chart using Multiple Dependent State Repetitive Sampling

KAUST Repository

Aldosari, Mansour Sattam

2017-03-25

In this manuscript, a new attribute control chart using multiple dependent state repetitive sampling is designed. The operational procedure and structure of the proposed control chart is given. The required measures to determine the average run length (ARL) for in-control and out-of-control processes are given. Tables of ARLs are reported for various control chart parameters. The proposed control chart is more sensitive in detecting a small shift in the process as compared to the existing attribute control charts. The simulation study shows the efficiency of the proposed chart over the existing charts. An example is given for the illustration purpose.

MODEL PENSKORAN PARTIAL CREDIT PADA BUTIR MULTIPLE TRUE-FALSE BIDANG FISIKA

Directory of Open Access Journals (Sweden)

Wasis Wasis

2013-01-01

Full Text Available Tujuan penelitian ini menghasilkan model penskoran politomus untuk respons butir multiple true-false, sehingga dapat mengestimasi secara lebih akurat kemampuan di bidang fisika. Pengembangan penskoran menggunakan Four-D model dan diuji akurasinya melalui penelitian empiris dan simulasi. Penelitian empiris menggunakan 15 butir multiple true-false yang diambil dari soal UMPTN tahun 1996-2006 dan dikenakan pada 410 mahasiswa baru FMIPA Universitas Negeri Surabaya angkatan tahun 2007. Respons peserta tes diskor dengan tiga model partial credit (PCM I; II; dan III dan secara dikotomus. Hasil penskoran dianalisis dengan program Quest untuk mendapat-kan estimasi tingkat kesukaran butir (δ dan estimasi ke-mampuan peserta (θ untuk menentukan nilai fungsi informasi tes dan kesalahan baku estimasi. Penelitian simulasi mengguna-kan data bangkitan berdasarkan parameter empiris (δ dan θ memakai program statistik SAS dan akurasi estimasinya di-analisis dengan metode root mean squared error (RMSE. Hasil penelitian ini menunjukkan: (i Penskoran PCM dengan pem-bobotan mampu mengestimasi kemampuan lebih akurat di-bandingkan tanpa pembobotan maupun secara dikotomus; (ii Semakin banyak jumlah kategori dalam penskoran partial credit, semakin akurat. Kata kunci: model penskoran partial credit, butir multiple true-false ____________________________________________________________ THE PARTIAL CREDIT SCORING MODEL FOR THE MULTIPLE TRUE-FALSE BUTIRS IN PHYSICS Abstract This study is an attempt to overcome the weaknesses. This study aims to produce a polytomous scoring model for responses to multiple true-false butirs in order to get a more accurate estimation of abilities in physics. It adopts the Four-D model and its accuracy is assessed through empirical and simulation studies. The empirical study employed 15 multiple true-false butirs taken from the New Students Entrance Test of State University the year of 1996–2006. It administered to 410 new students enrolled

Multiple-Ring Digital Communication Network

Science.gov (United States)

Kirkham, Harold

1992-01-01

Optical-fiber digital communication network to support data-acquisition and control functions of electric-power-distribution networks. Optical-fiber links of communication network follow power-distribution routes. Since fiber crosses open power switches, communication network includes multiple interconnected loops with occasional spurs. At each intersection node is needed. Nodes of communication network include power-distribution substations and power-controlling units. In addition to serving data acquisition and control functions, each node acts as repeater, passing on messages to next node(s). Multiple-ring communication network operates on new AbNET protocol and features fiber-optic communication.

A collaborative scheduling model for the supply-hub with multiple suppliers and multiple manufacturers.

Science.gov (United States)

Li, Guo; Lv, Fei; Guan, Xu

2014-01-01

This paper investigates a collaborative scheduling model in the assembly system, wherein multiple suppliers have to deliver their components to the multiple manufacturers under the operation of Supply-Hub. We first develop two different scenarios to examine the impact of Supply-Hub. One is that suppliers and manufacturers make their decisions separately, and the other is that the Supply-Hub makes joint decisions with collaborative scheduling. The results show that our scheduling model with the Supply-Hub is a NP-complete problem, therefore, we propose an auto-adapted differential evolution algorithm to solve this problem. Moreover, we illustrate that the performance of collaborative scheduling by the Supply-Hub is superior to separate decision made by each manufacturer and supplier. Furthermore, we also show that the algorithm proposed has good convergence and reliability, which can be applicable to more complicated supply chain environment.

A Technique of Fuzzy C-Mean in Multiple Linear Regression Model toward Paddy Yield

Science.gov (United States)

Syazwan Wahab, Nur; Saifullah Rusiman, Mohd; Mohamad, Mahathir; Amira Azmi, Nur; Che Him, Norziha; Ghazali Kamardan, M.; Ali, Maselan

2018-04-01

In this paper, we propose a hybrid model which is a combination of multiple linear regression model and fuzzy c-means method. This research involved a relationship between 20 variates of the top soil that are analyzed prior to planting of paddy yields at standard fertilizer rates. Data used were from the multi-location trials for rice carried out by MARDI at major paddy granary in Peninsular Malaysia during the period from 2009 to 2012. Missing observations were estimated using mean estimation techniques. The data were analyzed using multiple linear regression model and a combination of multiple linear regression model and fuzzy c-means method. Analysis of normality and multicollinearity indicate that the data is normally scattered without multicollinearity among independent variables. Analysis of fuzzy c-means cluster the yield of paddy into two clusters before the multiple linear regression model can be used. The comparison between two method indicate that the hybrid of multiple linear regression model and fuzzy c-means method outperform the multiple linear regression model with lower value of mean square error.

Presentation of Malaria Epidemics Using Multiple Optimal Controls

Directory of Open Access Journals (Sweden)

Abid Ali Lashari

2012-01-01

Full Text Available An existing model is extended to assess the impact of some antimalaria control measures, by re-formulating the model as an optimal control problem. This paper investigates the fundamental role of three type of controls, personal protection, treatment, and mosquito reduction strategies in controlling the malaria. We work in the nonlinear optimal control framework. The existence and the uniqueness results of the solution are discussed. A characterization of the optimal control via adjoint variables is established. The optimality system is solved numerically by a competitive Gauss-Seidel-like implicit difference method. Finally, numerical simulations of the optimal control problem, using a set of reasonable parameter values, are carried out to investigate the effectiveness of the proposed control measures.

Chance Events in Career Development: Influence, Control and Multiplicity

Science.gov (United States)

Bright, Jim E. H.; Pryor, Robert G. L.; Chan, Eva Wing Man; Rijanto, Jeniyanti

2009-01-01

This article reports three studies on the nature and impact of chance events. The first study investigated chance events in terms of the dimensions of influence and control. The second and third studies investigated the effects of multiplicity of chance events on career development are in terms of respondents' own careers and then in terms of…

Reduction of bias in neutron multiplicity assay using a weighted point model

Energy Technology Data Exchange (ETDEWEB)

Geist, W. H. (William H.); Krick, M. S. (Merlyn S.); Mayo, D. R. (Douglas R.)

2004-01-01

Accurate assay of most common plutonium samples was the development goal for the nondestructive assay technique of neutron multiplicity counting. Over the past 20 years the technique has been proven for relatively pure oxides and small metal items. Unfortunately, the technique results in large biases when assaying large metal items. Limiting assumptions, such as unifoh multiplication, in the point model used to derive the multiplicity equations causes these biases for large dense items. A weighted point model has been developed to overcome some of the limitations in the standard point model. Weighting factors are detemiined from Monte Carlo calculations using the MCNPX code. Monte Carlo calculations give the dependence of the weighting factors on sample mass and geometry, and simulated assays using Monte Carlo give the theoretical accuracy of the weighted-point-model assay. Measured multiplicity data evaluated with both the standard and weighted point models are compared to reference values to give the experimental accuracy of the assay. Initial results show significant promise for the weighted point model in reducing or eliminating biases in the neutron multiplicity assay of metal items. The negative biases observed in the assay of plutonium metal samples are caused by variations in the neutron multiplication for neutrons originating in various locations in the sample. The bias depends on the mass and shape of the sample and depends on the amount and energy distribution of the ({alpha},n) neutrons in the sample. When the standard point model is used, this variable-multiplication bias overestimates the multiplication and alpha values of the sample, and underestimates the plutonium mass. The weighted point model potentially can provide assay accuracy of {approx}2% (1 {sigma}) for cylindrical plutonium metal samples < 4 kg with {alpha} < 1 without knowing the exact shape of the samples, provided that the ({alpha},n) source is uniformly distributed throughout the

Assessment of Personality Types and Locus of Control in Multiple Sclerosis Patients

Directory of Open Access Journals (Sweden)

Sh. Mazaheri

2008-07-01

Full Text Available Introduction & Objective: Multiple sclerosis (MS is an autoimmune disease with unknown cause. MS is one of the disabling neurologic diseases in adult especially young range that myelin part of central nervous system (CNS is destructed. The aim of this study was assessment of types A and B personality and internal and external locus of control in multiple sclerosis (MS patients and comparison of the results with control group.Materials & Methods: In a case-control study, 30 patients with MS and 30 normal persons as control group evaluated with neurological examination, Rotter locus of control test and Friedman-Rosenman questionnaire for detection of types A and B personality. We employed to analyze the results.Results: 43 percent and 57 percent of MS patients had internal and external locus of control respectively. 63 percent and 37 percent of MS patients had type A and B personality respectively. 60 percent and 40 percent of control group had internal and external locus of control respectively. 20 percent and 80 percent of control group had type A and B personality respectively. Difference between personality type in two groups was significant (P<0.01.Conclusions: In this study, MS patients had more type A personality in comparison to control group.

A simple optical fibre-linked remote control system for multiple devices

Indian Academy of Sciences (India)

We report on the development of a simple control system which can handle multiple devices through an optical fibre data link. The devices are controlled using a set of DACs through serial data communication via a serial port of a PC. Serial data from the PC get converted to parallel mode using a homemade “serial in ...

Active control of multiple resistive wall modes

International Nuclear Information System (INIS)

Brunsell, P. R.; Yadikin, D.; Gregoratto, D.; Paccagnella, R.; Liu, Y. Q.; Bolzonella, T.; Cecconello, M.; Drake, J. R.; Kuldkepp, M.; Manduchi, G.; Marchiori, G.; Marrelli, L.; Partin, P.; Menmuir, S.; Ortolani, S.; Rachlew, E.; Spizzo, S.; Zanca, P.

2005-01-01

Active magnetic feedback suppression of resistive wall modes is of common interest for several fusion concepts relying on close conducting walls for stabilization of ideal magnetohydrodynamic (MHD) modes. In the advanced tokamak without plasma rotation the kink mode is not completely stabilized, but rather converted into an unstable resistive wall mode (RWM) with a growth time comparable to the wall magnetic flux penetration time. The reversed field pinch (RFP) is similar to the advanced tokamak in the sense that it uses a conducting wall for kink mode stabilization. Also both configurations are susceptible to resonant field error amplification of marginally stable modes. However, the RFP has a different RWM spectrum and, in general, a range of modes is unstable. Hence, the requirement for simultaneous feedback stabilization of multiple independent RWMs arises for the RFP configuration. Recent experiments on RWM feedback stabilization, performed in the RFP device EXTRAP T2R [1], are presented. The experimental results obtained are the first demonstration of simultaneous feedback control of multiple independent RWMs [2]. Using an array of active magnetic coils, a reproducible suppression of several RWMs is achieved for the duration of the discharge, 3-5 wall times, through feedback action. An array with 64 active saddle coils at 4 poloidal times 16 toroidal positions is used. The important issues of side band generation by the active coil array and the accompanying coupling of different unstable modes through the feedback action are addressed in this study. Open loop control experiments have been carried out to quantitatively study resonant field error amplification. (Author)

Infinite Multiple Membership Relational Modeling for Complex Networks

DEFF Research Database (Denmark)

Mørup, Morten; Schmidt, Mikkel Nørgaard; Hansen, Lars Kai

Learning latent structure in complex networks has become an important problem fueled by many types of networked data originating from practically all fields of science. In this paper, we propose a new non-parametric Bayesian multiplemembership latent feature model for networks. Contrary to existing...... multiplemembership models that scale quadratically in the number of vertices the proposedmodel scales linearly in the number of links admittingmultiple-membership analysis in large scale networks. We demonstrate a connection between the single membership relational model and multiple membership models and show...

Internal-Model-Principle-Based Specific Harmonics Repetitive Controller for Grid-Connected PWM Inverters

Directory of Open Access Journals (Sweden)

Wenzhou Lu

2016-01-01

Full Text Available This paper analyzes the general properties of IMP-based controller and presents an internal-model-principle-based (IMP-based specific harmonics repetitive control (SHRC scheme. The proposed SHRC is effective for specific nk±m order harmonics, with n>m≥0 and k=0,1,2,…. Using the properties of exponential function, SHRC can also be rewritten into the format of multiple resonant controllers in parallel, where the control gain of SHRC is n/2 multiple of that of conventional RC (CRC. Therefore, including SHRC in a stable closed-loop feedback control system, asymptotic disturbance eliminating, or reference tracking for any periodic signal only including these specific harmonic components at n/2 times faster error convergence rate compared with CRC can be achieved. Application examples of SHRC controlled three-phase/single-phase grid-connected PWM inverters demonstrate the effectiveness and advantages of the proposed SHRC scheme.

Optimization of the Darrieus wind turbines with double-multiple-streamtube model

International Nuclear Information System (INIS)

Paraschivoiu, I.

1985-01-01

This paper discusses a new improvement of the double-multiple-stream tube model by considering the stream tube expansion effects on the Darrieus wind turbine. These effects, allowing a more realistic modeling of the upwind/downwind flow field asymmetries inherent in the Darrieus rotor, were calculated by using CARDAAX computer code. When the dynamic stall is introduced in the double-multiple-stream tube model, the aerodynamic loads and performance show significant changes in the range of low tip-speed ratio

Application of multiple objective models to water resources planning and management

International Nuclear Information System (INIS)

North, R.M.

1993-01-01

Over the past 30 years, we have seen the birth and growth of multiple objective analysis from an idea without tools to one with useful applications. Models have been developed and applications have been researched to address the multiple purposes and objectives inherent in the development and management of water resources. A practical approach to multiple objective modelling incorporates macroeconomic-based policies and expectations in order to optimize the results from both engineering (structural) and management (non-structural) alternatives, while taking into account the economic and environmental trade-offs. (author). 27 refs, 4 figs, 3 tabs

Modelling and Control of Robotic Leg as Assistive Device

Science.gov (United States)

Jingye, Yee; Zain, Badrul Aisham bin Md

2017-10-01

The ageing population (people older than 60 years old) is expected to constitute 21.8% of global population by year 2050. When human ages, bodily function including locomotors will deteriorate. Besides, there are hundreds of thousands of victims who suffer from multiple health conditions worldwide that leads to gait impairment. A promising solution will be the lower limb powered-exoskeleton. This study is to be a start-up platform to design a lower limb powered-exoskeleton for a normal Malaysian male, by designing and simulating the dynamic model of a 2-link robotic leg to observe its behaviour under different input conditions with and without a PID controller. Simulink in MATLAB software is used as the dynamic modelling and simulation software for this study. It is observed that the 2-links robotic leg behaved differently under different input conditions, and perform the best when it is constrained and controlled by PID controller. Simulink model is formed as a foundation for the upcoming researches and can be modified and utilised by the future researchers.

A Collaborative Scheduling Model for the Supply-Hub with Multiple Suppliers and Multiple Manufacturers

Directory of Open Access Journals (Sweden)

Guo Li

2014-01-01

Full Text Available This paper investigates a collaborative scheduling model in the assembly system, wherein multiple suppliers have to deliver their components to the multiple manufacturers under the operation of Supply-Hub. We first develop two different scenarios to examine the impact of Supply-Hub. One is that suppliers and manufacturers make their decisions separately, and the other is that the Supply-Hub makes joint decisions with collaborative scheduling. The results show that our scheduling model with the Supply-Hub is a NP-complete problem, therefore, we propose an auto-adapted differential evolution algorithm to solve this problem. Moreover, we illustrate that the performance of collaborative scheduling by the Supply-Hub is superior to separate decision made by each manufacturer and supplier. Furthermore, we also show that the algorithm proposed has good convergence and reliability, which can be applicable to more complicated supply chain environment.

A Collaborative Scheduling Model for the Supply-Hub with Multiple Suppliers and Multiple Manufacturers

Science.gov (United States)

Lv, Fei; Guan, Xu

2014-01-01

This paper investigates a collaborative scheduling model in the assembly system, wherein multiple suppliers have to deliver their components to the multiple manufacturers under the operation of Supply-Hub. We first develop two different scenarios to examine the impact of Supply-Hub. One is that suppliers and manufacturers make their decisions separately, and the other is that the Supply-Hub makes joint decisions with collaborative scheduling. The results show that our scheduling model with the Supply-Hub is a NP-complete problem, therefore, we propose an auto-adapted differential evolution algorithm to solve this problem. Moreover, we illustrate that the performance of collaborative scheduling by the Supply-Hub is superior to separate decision made by each manufacturer and supplier. Furthermore, we also show that the algorithm proposed has good convergence and reliability, which can be applicable to more complicated supply chain environment. PMID:24892104

Multiple Time Series Ising Model for Financial Market Simulations

International Nuclear Information System (INIS)

Takaishi, Tetsuya

2015-01-01

In this paper we propose an Ising model which simulates multiple financial time series. Our model introduces the interaction which couples to spins of other systems. Simulations from our model show that time series exhibit the volatility clustering that is often observed in the real financial markets. Furthermore we also find non-zero cross correlations between the volatilities from our model. Thus our model can simulate stock markets where volatilities of stocks are mutually correlated

Modeling and Sensitivity Study of Consensus Algorithm-Based Distributed Hierarchical Control for DC Microgrids

DEFF Research Database (Denmark)

Meng, Lexuan; Dragicevic, Tomislav; Roldan Perez, Javier

2016-01-01

Distributed control methods based on consensus algorithms have become popular in recent years for microgrid (MG) systems. These kinds of algorithms can be applied to share information in order to coordinate multiple distributed generators within a MG. However, stability analysis becomes a challen......Distributed control methods based on consensus algorithms have become popular in recent years for microgrid (MG) systems. These kinds of algorithms can be applied to share information in order to coordinate multiple distributed generators within a MG. However, stability analysis becomes...... in the communication network, continuous-time methods can be inaccurate for this kind of dynamic study. Therefore, this paper aims at modeling a complete DC MG using a discrete-time approach in order to perform a sensitivity analysis taking into account the effects of the consensus algorithm. To this end......, a generalized modeling method is proposed and the influence of key control parameters, the communication topology and the communication speed are studied in detail. The theoretical results obtained with the proposed model are verified by comparing them with the results obtained with a detailed switching...

Advanced Models and Controls for Prediction and Extension of Battery Lifetime (Presentation)

Energy Technology Data Exchange (ETDEWEB)

Smith, K.; Wood, E.; Santhanagopalan, S.; Kim, G.; Pesaran, A.

2014-02-01

Predictive models of capacity and power fade must consider a multiplicity of degradation modes experienced by Li-ion batteries in the automotive environment. Lacking accurate models and tests, lifetime uncertainty must presently be absorbed by overdesign and excess warranty costs. To reduce these costs and extend life, degradation models are under development that predict lifetime more accurately and with less test data. The lifetime models provide engineering feedback for cell, pack and system designs and are being incorporated into real-time control strategies.

Impulse control disorders are associated with multiple psychiatric symptoms in Parkinson's disease.

Science.gov (United States)

Jaakkola, Elina; Kaasinen, Valtteri; Siri, Chiara; Martikainen, Kirsti; Cilia, Roberto; Niemelä, Solja; Joutsa, Juho

2014-01-01

Impulse control disorders can have serious adverse consequences to the life of a patient with Parkinson's disease. Although impulse control disorders are common, a possible psychiatric comorbidity has not been fully characterized. The aim of this study was to investigate the psychiatric symptoms exhibited by Parkinson's disease patients with impulse control disorders. The study was conducted as a postal survey to patients in the registry of the Finnish Parkinson Association. A total of 290 Parkinson's disease patients were evaluated for impulse control disorders using the Questionnaire for Impulsive-Compulsive Disorders in Parkinson's Disease. Psychiatric symptoms were systematically screened using the Symptom Checklist 90. We found that 108 of the evaluated patients had one or more impulse control disorders. Patients with impulse control disorders had markedly higher scores for symptoms of psychoticism (Bonferroni corrected p disorder (p impulse control disorders. Impulse control disorders were shown to be independently associated with these symptoms. Patients with multiple impulse control disorders had higher scores for depression and obsessive-compulsive symptoms when compared with patients that exhibited only one impulse control disorder. COUNCLUSIONS: Our results confirm the previous observations that impulse control disorders in Parkinson's disease are linked with multiple psychiatric symptoms, including psychoticism, interpersonal sensitivity, obsessive-compulsive symptoms and depression. Clinicians treating these patients should acknowledge the concomitant psychiatric symptoms.

Synthesis for robust synchronization of chaotic systems under output feedback control with multiple random delays

International Nuclear Information System (INIS)

Wen Guilin; Wang Qingguo; Lin Chong; Han Xu; Li Guangyao

2006-01-01

Synchronization under output feedback control with multiple random time delays is studied, using the paradigm in nonlinear physics-Chua's circuit. Compared with other synchronization control methods, output feedback control with multiple random delay is superior for a realistic synchronization application to secure communications. Sufficient condition for global stability of delay-dependent synchronization is established based on the LMI technique. Numerical simulations fully support the analytical approach, in spite of the random delays

Alternative approaches to reliability modeling of a multiple engineered barrier system

International Nuclear Information System (INIS)

Ananda, M.M.A.; Singh, A.K.

1994-01-01

The lifetime of the engineered barrier system used for containment of high-level radioactive waste will significantly impact the total performance of a geological repository facility. Currently two types of designs are under consideration for an engineered barrier system, single engineered barrier system and multiple engineered barrier system. Multiple engineered barrier system consists of several metal barriers and the waste form (cladding). Some recent work show that a significant improvement of performance can be achieved by utilizing multiple engineered barrier systems. Considering sequential failures for each barrier, we model the reliability of the multiple engineered barrier system. Weibull and exponential lifetime distributions are used through out the analysis. Furthermore, the number of failed engineered barrier systems in a repository at a given time is modeled using a poisson approximation

Semi-empirical neural network models of controlled dynamical systems

Directory of Open Access Journals (Sweden)

Mihail V. Egorchev

2017-12-01

Full Text Available A simulation approach is discussed for maneuverable aircraft motion as nonlinear controlled dynamical system under multiple and diverse uncertainties including knowledge imperfection concerning simulated plant and its environment exposure. The suggested approach is based on a merging of theoretical knowledge for the plant with training tools of artificial neural network field. The efficiency of this approach is demonstrated using the example of motion modeling and the identification of the aerodynamic characteristics of a maneuverable aircraft. A semi-empirical recurrent neural network based model learning algorithm is proposed for multi-step ahead prediction problem. This algorithm sequentially states and solves numerical optimization subproblems of increasing complexity, using each solution as initial guess for subsequent subproblem. We also consider a procedure for representative training set acquisition that utilizes multisine control signals.

Reserve-building activities in multiple sclerosis patients and healthy controls: a descriptive study.

Science.gov (United States)

Schwartz, Carolyn E; Ayandeh, Armon; Ramanathan, Murali; Benedict, Ralph; Dwyer, Michael G; Weinstock-Guttman, Bianca; Zivadinov, Robert

2015-08-12

Cognitive reserve has been implicated as a possible protective factor in multiple sclerosis (MS) but to date no study has compared reserve-building activities across disease course or to healthy controls. This study aims to describe differences in reserve-building activities across the MS disease course and healthy controls. Secondary analysis of a cross-sectional cohort study that included 276 healthy controls, and subjects with clinically isolated syndrome (CIS; n = 67), relapsing-remitting MS (RRMS; n = 358) and secondary progressive MS (PMS; n = 109). Past reserve-building activities were operationalized as occupational attainment and education. Current activities comprised 6 strenuous and 6 non-strenuous activities, including 5 reserve-building activities and television-watching. Multivariate Analysis of Variance models examined group differences in past and current activities, after adjusting for covariates. There were group differences in past and current reserve-building activities. SPMS patients had lower past reserve-building activities than healthy controls. All forms of MS engaged in fewer strenuous current reserve-building pursuits than healthy controls. RRMS read less than healthy controls. SPMS engaged in fewer job-related non-strenuous activities. All MS groups watched more television than healthy controls. MS patients show significantly fewer past and present reserve-building activities. Although it is difficult to establish causality without future prospective studies, lifestyle-modifying interventions should prioritize expanding MS patients' repertoire of strenuous and non-strenuous activities.

Feedback structure based entropy approach for multiple-model estimation

Institute of Scientific and Technical Information of China (English)

Shen-tu Han; Xue Anke; Guo Yunfei

2013-01-01

The variable-structure multiple-model (VSMM) approach, one of the multiple-model (MM) methods, is a popular and effective approach in handling problems with mode uncertainties. The model sequence set adaptation (MSA) is the key to design a better VSMM. However, MSA methods in the literature have big room to improve both theoretically and practically. To this end, we propose a feedback structure based entropy approach that could find the model sequence sets with the smallest size under certain conditions. The filtered data are fed back in real time and can be used by the minimum entropy (ME) based VSMM algorithms, i.e., MEVSMM. Firstly, the full Markov chains are used to achieve optimal solutions. Secondly, the myopic method together with particle filter (PF) and the challenge match algorithm are also used to achieve sub-optimal solutions, a trade-off between practicability and optimality. The numerical results show that the proposed algorithm provides not only refined model sets but also a good robustness margin and very high accuracy.

A PDP model of the simultaneous perception of multiple objects

Science.gov (United States)

Henderson, Cynthia M.; McClelland, James L.

2011-06-01

Illusory conjunctions in normal and simultanagnosic subjects are two instances where the visual features of multiple objects are incorrectly 'bound' together. A connectionist model explores how multiple objects could be perceived correctly in normal subjects given sufficient time, but could give rise to illusory conjunctions with damage or time pressure. In this model, perception of two objects benefits from lateral connections between hidden layers modelling aspects of the ventral and dorsal visual pathways. As with simultanagnosia, simulations of dorsal lesions impair multi-object recognition. In contrast, a large ventral lesion has minimal effect on dorsal functioning, akin to dissociations between simple object manipulation (retained in visual form agnosia and semantic dementia) and object discrimination (impaired in these disorders) [Hodges, J.R., Bozeat, S., Lambon Ralph, M.A., Patterson, K., and Spatt, J. (2000), 'The Role of Conceptual Knowledge: Evidence from Semantic Dementia', Brain, 123, 1913-1925; Milner, A.D., and Goodale, M.A. (2006), The Visual Brain in Action (2nd ed.), New York: Oxford]. It is hoped that the functioning of this model might suggest potential processes underlying dorsal and ventral contributions to the correct perception of multiple objects.

MODEL PENSKORAN PARTIAL CREDIT PADA BUTIR MULTIPLE TRUE-FALSE BIDANG FISIKA

OpenAIRE

Wasis Wasis

2013-01-01

Tujuan penelitian ini menghasilkan model penskoran politomus untuk respons butir multiple true-false, sehingga dapat mengestimasi secara lebih akurat kemampuan di bidang fisika. Pengembangan penskoran menggunakan Four-D model dan diuji akurasinya melalui penelitian empiris dan simulasi. Penelitian empiris menggunakan 15 butir multiple true-false yang diambil dari soal UMPTN tahun 1996-2006 dan dikenakan pada 410 mahasiswa baru FMIPA Universitas Negeri Surabaya angkatan tahun 2007. Respons pes...

Economic model predictive control theory, formulations and chemical process applications

CERN Document Server

Ellis, Matthew; Christofides, Panagiotis D

2017-01-01

This book presents general methods for the design of economic model predictive control (EMPC) systems for broad classes of nonlinear systems that address key theoretical and practical considerations including recursive feasibility, closed-loop stability, closed-loop performance, and computational efficiency. Specifically, the book proposes: Lyapunov-based EMPC methods for nonlinear systems; two-tier EMPC architectures that are highly computationally efficient; and EMPC schemes handling explicitly uncertainty, time-varying cost functions, time-delays and multiple-time-scale dynamics. The proposed methods employ a variety of tools ranging from nonlinear systems analysis, through Lyapunov-based control techniques to nonlinear dynamic optimization. The applicability and performance of the proposed methods are demonstrated through a number of chemical process examples. The book presents state-of-the-art methods for the design of economic model predictive control systems for chemical processes. In addition to being...

H-Shaped Multiple Linear Motor Drive Platform Control System Design Based on an Inverse System Method

Directory of Open Access Journals (Sweden)

Caiyan Qin

2017-12-01

Full Text Available Due to its simple mechanical structure and high motion stability, the H-shaped platform has been increasingly widely used in precision measuring, numerical control machining and semiconductor packaging equipment, etc. The H-shaped platform is normally driven by multiple (three permanent magnet synchronous linear motors. The main challenges for H-shaped platform-control include synchronous control between the two linear motors in the Y direction as well as total positioning error of the platform mover, a combination of position deviation in X and Y directions. To deal with the above challenges, this paper proposes a control strategy based on the inverse system method through state feedback and dynamic decoupling of the thrust force. First, mechanical dynamics equations have been deduced through the analysis of system coupling based on the platform structure. Second, the mathematical model of the linear motors and the relevant coordinate transformation between dq-axis currents and ABC-phase currents are analyzed. Third, after the main concept of inverse system method being explained, the inverse system model of the platform control system has been designed after defining relevant system variables. Inverse system model compensates the original nonlinear coupled system into pseudo-linear decoupled linear system, for which typical linear control methods, like PID, can be adopted to control the system. The simulation model of the control system is built in MATLAB/Simulink and the simulation result shows that the designed control system has both small synchronous deviation and small total trajectory tracking error. Furthermore, the control program has been run on NI controller for both fixed-loop-time and free-loop-time modes, and the test result shows that the average loop computation time needed is rather small, which makes it suitable for real industrial applications. Overall, it proves that the proposed new control strategy can be used in

Hybrid approaches for multiple-species stochastic reaction–diffusion models

International Nuclear Information System (INIS)

Spill, Fabian; Guerrero, Pilar; Alarcon, Tomas; Maini, Philip K.; Byrne, Helen

2015-01-01

Reaction–diffusion models are used to describe systems in fields as diverse as physics, chemistry, ecology and biology. The fundamental quantities in such models are individual entities such as atoms and molecules, bacteria, cells or animals, which move and/or react in a stochastic manner. If the number of entities is large, accounting for each individual is inefficient, and often partial differential equation (PDE) models are used in which the stochastic behaviour of individuals is replaced by a description of the averaged, or mean behaviour of the system. In some situations the number of individuals is large in certain regions and small in others. In such cases, a stochastic model may be inefficient in one region, and a PDE model inaccurate in another. To overcome this problem, we develop a scheme which couples a stochastic reaction–diffusion system in one part of the domain with its mean field analogue, i.e. a discretised PDE model, in the other part of the domain. The interface in between the two domains occupies exactly one lattice site and is chosen such that the mean field description is still accurate there. In this way errors due to the flux between the domains are small. Our scheme can account for multiple dynamic interfaces separating multiple stochastic and deterministic domains, and the coupling between the domains conserves the total number of particles. The method preserves stochastic features such as extinction not observable in the mean field description, and is significantly faster to simulate on a computer than the pure stochastic model. - Highlights: • A novel hybrid stochastic/deterministic reaction–diffusion simulation method is given. • Can massively speed up stochastic simulations while preserving stochastic effects. • Can handle multiple reacting species. • Can handle moving boundaries

Hybrid approaches for multiple-species stochastic reaction–diffusion models

Energy Technology Data Exchange (ETDEWEB)

Spill, Fabian, E-mail: fspill@bu.edu [Department of Biomedical Engineering, Boston University, 44 Cummington Street, Boston, MA 02215 (United States); Department of Mechanical Engineering, Massachusetts Institute of Technology, 77 Massachusetts Avenue, Cambridge, MA 02139 (United States); Guerrero, Pilar [Department of Mathematics, University College London, Gower Street, London WC1E 6BT (United Kingdom); Alarcon, Tomas [Centre de Recerca Matematica, Campus de Bellaterra, Edifici C, 08193 Bellaterra (Barcelona) (Spain); Departament de Matemàtiques, Universitat Atonòma de Barcelona, 08193 Bellaterra (Barcelona) (Spain); Maini, Philip K. [Wolfson Centre for Mathematical Biology, Mathematical Institute, University of Oxford, Oxford OX2 6GG (United Kingdom); Byrne, Helen [Wolfson Centre for Mathematical Biology, Mathematical Institute, University of Oxford, Oxford OX2 6GG (United Kingdom); Computational Biology Group, Department of Computer Science, University of Oxford, Oxford OX1 3QD (United Kingdom)

2015-10-15

Reaction–diffusion models are used to describe systems in fields as diverse as physics, chemistry, ecology and biology. The fundamental quantities in such models are individual entities such as atoms and molecules, bacteria, cells or animals, which move and/or react in a stochastic manner. If the number of entities is large, accounting for each individual is inefficient, and often partial differential equation (PDE) models are used in which the stochastic behaviour of individuals is replaced by a description of the averaged, or mean behaviour of the system. In some situations the number of individuals is large in certain regions and small in others. In such cases, a stochastic model may be inefficient in one region, and a PDE model inaccurate in another. To overcome this problem, we develop a scheme which couples a stochastic reaction–diffusion system in one part of the domain with its mean field analogue, i.e. a discretised PDE model, in the other part of the domain. The interface in between the two domains occupies exactly one lattice site and is chosen such that the mean field description is still accurate there. In this way errors due to the flux between the domains are small. Our scheme can account for multiple dynamic interfaces separating multiple stochastic and deterministic domains, and the coupling between the domains conserves the total number of particles. The method preserves stochastic features such as extinction not observable in the mean field description, and is significantly faster to simulate on a computer than the pure stochastic model. - Highlights: • A novel hybrid stochastic/deterministic reaction–diffusion simulation method is given. • Can massively speed up stochastic simulations while preserving stochastic effects. • Can handle multiple reacting species. • Can handle moving boundaries.

Modeling a Single SEP Event from Multiple Vantage Points Using the iPATH Model

Science.gov (United States)

Hu, Junxiang; Li, Gang; Fu, Shuai; Zank, Gary; Ao, Xianzhi

2018-02-01

Using the recently extended 2D improved Particle Acceleration and Transport in the Heliosphere (iPATH) model, we model an example gradual solar energetic particle event as observed at multiple locations. Protons and ions that are energized via the diffusive shock acceleration mechanism are followed at a 2D coronal mass ejection-driven shock where the shock geometry varies across the shock front. The subsequent transport of energetic particles, including cross-field diffusion, is modeled by a Monte Carlo code that is based on a stochastic differential equation method. Time intensity profiles and particle spectra at multiple locations and different radial distances, separated in longitudes, are presented. The results shown here are relevant to the upcoming Parker Solar Probe mission.

Computational Models Used to Assess US Tobacco Control Policies.

Science.gov (United States)

Feirman, Shari P; Glasser, Allison M; Rose, Shyanika; Niaura, Ray; Abrams, David B; Teplitskaya, Lyubov; Villanti, Andrea C

2017-11-01

Simulation models can be used to evaluate existing and potential tobacco control interventions, including policies. The purpose of this systematic review was to synthesize evidence from computational models used to project population-level effects of tobacco control interventions. We provide recommendations to strengthen simulation models that evaluate tobacco control interventions. Studies were eligible for review if they employed a computational model to predict the expected effects of a non-clinical US-based tobacco control intervention. We searched five electronic databases on July 1, 2013 with no date restrictions and synthesized studies qualitatively. Six primary non-clinical intervention types were examined across the 40 studies: taxation, youth prevention, smoke-free policies, mass media campaigns, marketing/advertising restrictions, and product regulation. Simulation models demonstrated the independent and combined effects of these interventions on decreasing projected future smoking prevalence. Taxation effects were the most robust, as studies examining other interventions exhibited substantial heterogeneity with regard to the outcomes and specific policies examined across models. Models should project the impact of interventions on overall tobacco use, including nicotine delivery product use, to estimate preventable health and cost-saving outcomes. Model validation, transparency, more sophisticated models, and modeling policy interactions are also needed to inform policymakers to make decisions that will minimize harm and maximize health. In this systematic review, evidence from multiple studies demonstrated the independent effect of taxation on decreasing future smoking prevalence, and models for other tobacco control interventions showed that these strategies are expected to decrease smoking, benefit population health, and are reasonable to implement from a cost perspective. Our recommendations aim to help policymakers and researchers minimize harm and

Modeling and Inverse Controller Design for an Unmanned Aerial Vehicle Based on the Self-Organizing Map

Science.gov (United States)

Cho, Jeongho; Principe, Jose C.; Erdogmus, Deniz; Motter, Mark A.

2005-01-01

The next generation of aircraft will have dynamics that vary considerably over the operating regime. A single controller will have difficulty to meet the design specifications. In this paper, a SOM-based local linear modeling scheme of an unmanned aerial vehicle (UAV) is developed to design a set of inverse controllers. The SOM selects the operating regime depending only on the embedded output space information and avoids normalization of the input data. Each local linear model is associated with a linear controller, which is easy to design. Switching of the controllers is done synchronously with the active local linear model that tracks the different operating conditions. The proposed multiple modeling and control strategy has been successfully tested in a simulator that models the LoFLYTE UAV.

Improved model predictive control of resistive wall modes by error field estimator in EXTRAP T2R

Science.gov (United States)

Setiadi, A. C.; Brunsell, P. R.; Frassinetti, L.

2016-12-01

Many implementations of a model-based approach for toroidal plasma have shown better control performance compared to the conventional type of feedback controller. One prerequisite of model-based control is the availability of a control oriented model. This model can be obtained empirically through a systematic procedure called system identification. Such a model is used in this work to design a model predictive controller to stabilize multiple resistive wall modes in EXTRAP T2R reversed-field pinch. Model predictive control is an advanced control method that can optimize the future behaviour of a system. Furthermore, this paper will discuss an additional use of the empirical model which is to estimate the error field in EXTRAP T2R. Two potential methods are discussed that can estimate the error field. The error field estimator is then combined with the model predictive control and yields better radial magnetic field suppression.

Dealing with Multiple Solutions in Structural Vector Autoregressive Models.

Science.gov (United States)

Beltz, Adriene M; Molenaar, Peter C M

2016-01-01

Structural vector autoregressive models (VARs) hold great potential for psychological science, particularly for time series data analysis. They capture the magnitude, direction of influence, and temporal (lagged and contemporaneous) nature of relations among variables. Unified structural equation modeling (uSEM) is an optimal structural VAR instantiation, according to large-scale simulation studies, and it is implemented within an SEM framework. However, little is known about the uniqueness of uSEM results. Thus, the goal of this study was to investigate whether multiple solutions result from uSEM analysis and, if so, to demonstrate ways to select an optimal solution. This was accomplished with two simulated data sets, an empirical data set concerning children's dyadic play, and modifications to the group iterative multiple model estimation (GIMME) program, which implements uSEMs with group- and individual-level relations in a data-driven manner. Results revealed multiple solutions when there were large contemporaneous relations among variables. Results also verified several ways to select the correct solution when the complete solution set was generated, such as the use of cross-validation, maximum standardized residuals, and information criteria. This work has immediate and direct implications for the analysis of time series data and for the inferences drawn from those data concerning human behavior.

Dynamic Bus Travel Time Prediction Models on Road with Multiple Bus Routes.

Science.gov (United States)

Bai, Cong; Peng, Zhong-Ren; Lu, Qing-Chang; Sun, Jian

2015-01-01

Accurate and real-time travel time information for buses can help passengers better plan their trips and minimize waiting times. A dynamic travel time prediction model for buses addressing the cases on road with multiple bus routes is proposed in this paper, based on support vector machines (SVMs) and Kalman filtering-based algorithm. In the proposed model, the well-trained SVM model predicts the baseline bus travel times from the historical bus trip data; the Kalman filtering-based dynamic algorithm can adjust bus travel times with the latest bus operation information and the estimated baseline travel times. The performance of the proposed dynamic model is validated with the real-world data on road with multiple bus routes in Shenzhen, China. The results show that the proposed dynamic model is feasible and applicable for bus travel time prediction and has the best prediction performance among all the five models proposed in the study in terms of prediction accuracy on road with multiple bus routes.

Dynamic Bus Travel Time Prediction Models on Road with Multiple Bus Routes

Science.gov (United States)

Bai, Cong; Peng, Zhong-Ren; Lu, Qing-Chang; Sun, Jian

2015-01-01

Accurate and real-time travel time information for buses can help passengers better plan their trips and minimize waiting times. A dynamic travel time prediction model for buses addressing the cases on road with multiple bus routes is proposed in this paper, based on support vector machines (SVMs) and Kalman filtering-based algorithm. In the proposed model, the well-trained SVM model predicts the baseline bus travel times from the historical bus trip data; the Kalman filtering-based dynamic algorithm can adjust bus travel times with the latest bus operation information and the estimated baseline travel times. The performance of the proposed dynamic model is validated with the real-world data on road with multiple bus routes in Shenzhen, China. The results show that the proposed dynamic model is feasible and applicable for bus travel time prediction and has the best prediction performance among all the five models proposed in the study in terms of prediction accuracy on road with multiple bus routes. PMID:26294903

Green communication: The enabler to multiple business models

DEFF Research Database (Denmark)

Lindgren, Peter; Clemmensen, Suberia; Taran, Yariv

2010-01-01

Companies stand at the forefront of a new business model reality with new potentials - that will change their basic understanding and practice of running their business models radically. One of the drivers to this change is green communication, its strong relation to green business models and its...... possibility to enable lower energy consumption. This paper shows how green communication enables innovation of green business models and multiple business models running simultaneously in different markets to different customers.......Companies stand at the forefront of a new business model reality with new potentials - that will change their basic understanding and practice of running their business models radically. One of the drivers to this change is green communication, its strong relation to green business models and its...

An extension of the multiple-trapping model

International Nuclear Information System (INIS)

Shkilev, V. P.

2012-01-01

The hopping charge transport in disordered semiconductors is considered. Using the concept of the transport energy level, macroscopic equations are derived that extend a multiple-trapping model to the case of semiconductors with both energy and spatial disorders. It is shown that, although both types of disorder can cause dispersive transport, the frequency dependence of conductivity is determined exclusively by the spatial disorder.

Exploring the relationship between socioeconomic status, control beliefs and exercise behavior: a multiple mediator model.

Science.gov (United States)

Murray, Terra C; Rodgers, Wendy M; Fraser, Shawn N

2012-02-01

The purpose of this study was to examine the relationship between control beliefs, socioeconomic status and exercise intentions and behavior. Specifically, we examined whether distal and proximal control beliefs mediated the association between socioeconomic status and exercise intentions and behavior. A one time, cross sectional mail out survey (N = 350) was conducted in a large urban Canadian city. Distal (i.e., personal constraints) and proximal (i.e., scheduling self-efficacy) control beliefs mediated the association between socioeconomic status and exercise, explaining approximately 30% of the variance. Proximal control beliefs (i.e., scheduling self-efficacy) partially mediated the association between socioeconomic status and intentions, with the models explaining approximately 50% of the variance. Compared to individuals with lower socioeconomic status, individuals with higher socioeconomic status reported more exercise and stronger intentions to exercise. This was at least partly because higher socioeconomic status respondents reported fewer barriers in their lives, and were more confident to cope with the scheduling demands of exercise.

A full scope nuclear power plant simulator for multiple reactor types with virtual control panels

International Nuclear Information System (INIS)

Yonezawa, Hisanori; Ueda, Hiroki; Kato, Takahisa

2017-01-01

This paper summarizes a full scope nuclear power plant simulator for multiple reactor types with virtual control panels which Toshiba developed and delivered. After the Fukushima DAIICHI nuclear power plants accident, it is required that all the people who are engaged in the design, manufacturing, operation, maintenance, management and regulation for the nuclear power plant should learn the wide and deep knowledge about the nuclear power plant design including the severe accident. For this purpose, the training with a full scope simulator is one of the most suitable ways. However the existing full scope simulators which are consist of the control panels replica of the referenced plants are costly and they are hard to remodel to fit to the real plant of the latest condition. That's why Toshiba developed and delivered the new concept simulator system which covers multiple referenced plants even though they have different design like BWR and PWR. The control panels of the simulator are made by combining 69 large Liquid Crystal Display (LCD) panels with touch screen instead of a control panel replica of referenced plant. The screen size of the each panel is 42 inches and 3 displays are arranged in tandem for one unit and 23 units are connected together. Each panel displays switches, indicators, recorders and lamps with the Computer Graphics (CG) and trainees operate them with touch operations. The simulator includes a BWR and a PWR simulator model, which enable trainees to learn the wide and deep knowledge about the nuclear power plant of BWR and PWR reactor types. (author)

A Multiple Model Prediction Algorithm for CNC Machine Wear PHM

Directory of Open Access Journals (Sweden)

Huimin Chen

2011-01-01

Full Text Available The 2010 PHM data challenge focuses on the remaining useful life (RUL estimation for cutters of a high speed CNC milling machine using measurements from dynamometer, accelerometer, and acoustic emission sensors. We present a multiple model approach for wear depth estimation of milling machine cutters using the provided data. The feature selection, initial wear estimation and multiple model fusion components of the proposed algorithm are explained in details and compared with several alternative methods using the training data. The final submission ranked #2 among professional and student participants and the method is applicable to other data driven PHM problems.

An inventory control model for biomass dependent production systems

International Nuclear Information System (INIS)

Grado, S.C.; Strauss, C.H.

1993-01-01

The financial performance of a biomass dependent production system was critiqued based on the development and validation of an inventory control model. Dynamic programming was used to examine the constraints and capabilities of producing ethanol from various biomass crops. In particular, the model evaluated the plantation, harvest, and manufacturing components of a woody biomass supply system. The optimum wood to ethanol production scheme produced 38 million litres of ethanol in the harvest year, at 13.6 million litre increase over the least optimal policy as demonstrated in the dynamic programming results. The system produced ethanol at a delivered cost of $0.38 L -1 which was consistent with the unit costs from other studies. Nearly 60% of the delivered costs were in ethanol production. The remaining costs were attributed to growing biomass (14%), harvest and shipment of the crop (18%), storage of the raw material and finished product (7%) and open-quotes lost salesclose quotes (2%). Inventory control, in all phases of production, proved to be an important cost consideration throughout the model. The model also analyzed the employment of alternative harvesting policies and the use of different or multiple feedstocks. A comparison between the least cost wood system and an even cut wood system further revealed the benefits of using an inventory control system

Analysis of the immune system of multiple myeloma patients achieving long-term disease control by multidimensional flow cytometry

Science.gov (United States)

Pessoa de Magalhães, Roberto J.; Vidriales, María-Belén; Paiva, Bruno; Fernandez-Gimenez, Carlos; García-Sanz, Ramón; Mateos, Maria-Victoria; Gutierrez, Norma C.; Lecrevisse, Quentin; Blanco, Juan F; Hernández, Jose; de las Heras, Natalia; Martinez-Lopez, Joaquin; Roig, Monica; Costa, Elaine Sobral; Ocio, Enrique M.; Perez-Andres, Martin; Maiolino, Angelo; Nucci, Marcio; De La Rubia, Javier; Lahuerta, Juan-Jose; San-Miguel, Jesús F.; Orfao, Alberto

2013-01-01

Multiple myeloma remains largely incurable. However, a few patients experience more than 10 years of relapse-free survival and can be considered as operationally cured. Interestingly, long-term disease control in multiple myeloma is not restricted to patients with a complete response, since some patients revert to having a profile of monoclonal gammopathy of undetermined significance. We compared the distribution of multiple compartments of lymphocytes and dendritic cells in the bone marrow and peripheral blood of multiple myeloma patients with long-term disease control (n=28), patients with newly diagnosed monoclonal gammopathy of undetermined significance (n=23), patients with symptomatic multiple myeloma (n=23), and age-matched healthy adults (n=10). Similarly to the patients with monoclonal gammopathy of undetermined significance and symptomatic multiple myeloma, patients with long-term disease control showed an expansion of cytotoxic CD8+ T cells and natural killer cells. However, the numbers of bone marrow T-regulatory cells were lower in patients with long-term disease control than in those with symptomatic multiple myeloma. It is noteworthy that B cells were depleted in patients with monoclonal gammopathy of undetermined significance and in those with symptomatic multiple myeloma, but recovered in both the bone marrow and peripheral blood of patients with long-term disease control, due to an increase in normal bone marrow B-cell precursors and plasma cells, as well as pre-germinal center peripheral blood B cells. The number of bone marrow dendritic cells and tissue macrophages differed significantly between patients with long-term disease control and those with symptomatic multiple myeloma, with a trend to cell count recovering in the former group of patients towards levels similar to those found in healthy adults. In summary, our results indicate that multiple myeloma patients with long-term disease control have a constellation of unique immune changes

Multiple-state based power control for multi-radio multi-channel wireless mesh networks

CSIR Research Space (South Africa)

Olwal, TO

2009-01-01

Full Text Available Multi-Radio Multi-Channel (MRMC) systems are key to power control problems in wireless mesh networks (WMNs). In this paper, we present asynchronous multiple-state based power control for MRMC WMNs. First, WMN is represented as a set of disjoint...

Second-order sliding mode controller with model reference adaptation for automatic train operation

Science.gov (United States)

Ganesan, M.; Ezhilarasi, D.; Benni, Jijo

2017-11-01

In this paper, a new approach to model reference based adaptive second-order sliding mode control together with adaptive state feedback is presented to control the longitudinal dynamic motion of a high speed train for automatic train operation with the objective of minimal jerk travel by the passengers. The nonlinear dynamic model for the longitudinal motion of the train comprises of a locomotive and coach subsystems is constructed using multiple point-mass model by considering the forces acting on the vehicle. An adaptation scheme using Lyapunov criterion is derived to tune the controller gains by considering a linear, stable reference model that ensures the stability of the system in closed loop. The effectiveness of the controller tracking performance is tested under uncertain passenger load, coupler-draft gear parameters, propulsion resistance coefficients variations and environmental disturbances due to side wind and wet rail conditions. The results demonstrate improved tracking performance of the proposed control scheme with a least jerk under maximum parameter uncertainties when compared to constant gain second-order sliding mode control.

Optimal Exponential Synchronization of Chaotic Systems with Multiple Time Delays via Fuzzy Control

Directory of Open Access Journals (Sweden)

Feng-Hsiag Hsiao

2013-01-01

Full Text Available This study presents an effective approach to realize the optimal exponential synchronization of multiple time-delay chaotic (MTDC systems. First, a neural network (NN model is employed to approximate the MTDC system. Then, a linear differential inclusion (LDI state-space representation is established for the dynamics of the NN model. Based on this LDI state-space representation, this study proposes a delay-dependent exponential stability criterion of the error system derived in terms of Lyapunov’s direct method to ensure that the trajectories of the slave system can approach those of the master system. Subsequently, the stability condition of this criterion is reformulated into a linear matrix inequality (LMI. Based on the LMI, a fuzzy controller is synthesized not only to realize the exponential synchronization but also to achieve the optimal performance by minimizing the disturbance attenuation level. Finally, a numerical example with simulations is provided to illustrate the concepts discussed throughout this work.

Selecting Tools to Model Integer and Binomial Multiplication

Science.gov (United States)

Pratt, Sarah Smitherman; Eddy, Colleen M.

2017-01-01

Mathematics teachers frequently provide concrete manipulatives to students during instruction; however, the rationale for using certain manipulatives in conjunction with concepts may not be explored. This article focuses on area models that are currently used in classrooms to provide concrete examples of integer and binomial multiplication. The…

The impact of comorbidity on mortality in multiple myeloma

DEFF Research Database (Denmark)

Gregersen, Henrik; Vangsted, Annette Juul; Abildgaard, Niels

2017-01-01

To describe the prevalence of comorbidity and its impact on survival in newly diagnosed multiple myeloma patients compared with population controls. Cases of newly diagnosed symptomatic multiple myeloma during the 2005-2012 period were identified in the Danish National Multiple Myeloma Registry....... For each myeloma patient, 10 members of the general population matched by age and sex were chosen from the national Civil Registration System. Data on comorbidity in the myeloma patients and the general population comparison cohort were collected by linkage to the Danish National Patient Registry (DNPR......). Cox proportional hazards regression models were used to evaluate the prognostic significance of comorbidity. The study included 2190 cases of multiple myeloma and 21,900 population controls. The comorbidity was increased in multiple myeloma patients compared with population controls, odds ratio (OR) 1...

Comparative study between a QCD inspired model and a multiple diffraction model

International Nuclear Information System (INIS)

Luna, E.G.S.; Martini, A.F.; Menon, M.J.

2003-01-01

A comparative study between a QCD Inspired Model (QCDIM) and a Multiple Diffraction Model (MDM) is presented, with focus on the results for pp differential cross section at √s = 52.8 GeV. It is shown that the MDM predictions are in agreement with experimental data, except for the dip region and that the QCDIM describes only the diffraction peak region. Interpretations in terms of the corresponding eikonals are also discussed. (author)

PWR hybrid computer model for assessing the safety implications of control systems

International Nuclear Information System (INIS)

Smith, O.L.; Renier, J.P.; Difilippo, F.C.; Clapp, N.E.; Sozer, A.; Booth, R.S.; Craddick, W.G.; Morris, D.G.

1986-03-01

The ORNL study of safety-related aspects of nuclear power plant control systems consists of two interrelated tasks: (1) failure mode and effects analysis (FMEA) that identified single and multiple component failures that might lead to significant plant upsets and (2) computer models that used these failures as initial conditions and traced the dynamic impact on the control system and remainder of the plant. This report describes the simulation of Oconee Unit 1, the first plant analyzed. A first-principles, best-estimate model was developed and implemented on a hybrid computer consisting of AD-4 analog and PDP-10 digital machines. Controls were placed primarily on the analog to use its interactive capability to simulate operator action. 48 refs., 138 figs., 15 tabs

Femtosecond coherent control of absorption and free induction decay in a GaAs multiple quantum well

CERN Document Server

Yee, D S

2000-01-01

Excitonic polarizations are coherently excited using two phase-locked pulses. By probing the linear propagation of the pulses through a GaAs/AlGaAs multiple quantum well sample, we directly demonstrate the intriguing interaction between the coherent exciton polarizations and the controlling pulses. It is shown that the second pulse can be either strongly amplified by taking up energy gained from the destruction of the exciton polarization or drastically decreased by giving up all its energy to excitons. The temporal signatures of the transmitted pulse shapes agree well with model calculations.

Therapeutic effects of D-aspartate in a mouse model of multiple sclerosis

Directory of Open Access Journals (Sweden)

Sanaz Afraei

2017-07-01

Full Text Available Experimental autoimmune encephalomyelitis (EAE is an animal model of multiple sclerosis. EAE is mainly mediated by adaptive and innate immune responses that leads to an inflammatory demyelization and axonal damage. The aim of the present research was to examine the therapeutic efficacy of D-aspartic acid (D-Asp on a mouse EAE model. EAE induction was performed in female C57BL/6 mice by myelin 40 oligodendrocyte glycoprotein (35-55 in a complete Freund's adjuvant emulsion, and D-Asp was used to test its efficiency in the reduction of EAE. During the course of study, clinical evaluation was assessed, and on Day 21, post-immunization blood samples were taken from the heart of mice for the evaluation of interleukin 6 and other chemical molecules. The mice were sacrificed, and their brain and cerebellum were removed for histological analysis. Our findings indicated that D-Asp had beneficial effects on EAE by attenuation in the severity and delay in the onset of the disease. Histological analysis showed that treatment with D-Asp can reduce inflammation. Moreover, in D-Asp-treated mice, the serum level of interleukin 6 was significantly lower than that in control animals, whereas the total antioxidant capacity was significantly higher. The data indicates that D-Asp possess neuroprotective property to prevent the onset of the multiple sclerosis.

A novel variational Bayes multiple locus Z-statistic for genome-wide association studies with Bayesian model averaging

Science.gov (United States)

Logsdon, Benjamin A.; Carty, Cara L.; Reiner, Alexander P.; Dai, James Y.; Kooperberg, Charles

2012-01-01

Motivation: For many complex traits, including height, the majority of variants identified by genome-wide association studies (GWAS) have small effects, leaving a significant proportion of the heritable variation unexplained. Although many penalized multiple regression methodologies have been proposed to increase the power to detect associations for complex genetic architectures, they generally lack mechanisms for false-positive control and diagnostics for model over-fitting. Our methodology is the first penalized multiple regression approach that explicitly controls Type I error rates and provide model over-fitting diagnostics through a novel normally distributed statistic defined for every marker within the GWAS, based on results from a variational Bayes spike regression algorithm. Results: We compare the performance of our method to the lasso and single marker analysis on simulated data and demonstrate that our approach has superior performance in terms of power and Type I error control. In addition, using the Women's Health Initiative (WHI) SNP Health Association Resource (SHARe) GWAS of African-Americans, we show that our method has power to detect additional novel associations with body height. These findings replicate by reaching a stringent cutoff of marginal association in a larger cohort. Availability: An R-package, including an implementation of our variational Bayes spike regression (vBsr) algorithm, is available at http://kooperberg.fhcrc.org/soft.html. Contact: blogsdon@fhcrc.org Supplementary information: Supplementary data are available at Bioinformatics online. PMID:22563072

Nash Bargaining Game-Theoretic Framework for Power Control in Distributed Multiple-Radar Architecture Underlying Wireless Communication System

Directory of Open Access Journals (Sweden)

Chenguang Shi

2018-04-01

Full Text Available This paper presents a novel Nash bargaining solution (NBS-based cooperative game-theoretic framework for power control in a distributed multiple-radar architecture underlying a wireless communication system. Our primary objective is to minimize the total power consumption of the distributed multiple-radar system (DMRS with the protection of wireless communication user’s transmission, while guaranteeing each radar’s target detection requirement. A unified cooperative game-theoretic framework is proposed for the optimization problem, where interference power constraints (IPCs are imposed to protect the communication user’s transmission, and a minimum signal-to-interference-plus-noise ratio (SINR requirement is employed to provide reliable target detection for each radar. The existence, uniqueness and fairness of the NBS to this cooperative game are proven. An iterative Nash bargaining power control algorithm with low computational complexity and fast convergence is developed and is shown to converge to a Pareto-optimal equilibrium for the cooperative game model. Numerical simulations and analyses are further presented to highlight the advantages and testify to the efficiency of our proposed cooperative game algorithm. It is demonstrated that the distributed algorithm is effective for power control and could protect the communication system with limited implementation overhead.

Towards Integration of CAx Systems and a Multiple-View Product Modeller in Mechanical Design

Directory of Open Access Journals (Sweden)

H. Song

2005-01-01

Full Text Available This paper deals with the development of an integration framework and its implementation for the connexion of CAx systems and multiple-view product modelling. The integration framework is presented regarding its conceptual level and the implementation level is described currently with the connexion of a functional modeller, a multiple-view product modeller, an optimisation module and a CAD system. The integration between the multiple-view product modeller and CATIA V5 based on the STEP standard is described in detail. Finally, the presented works are discussed and future research developments are suggested. 

Nurse-led immunotreatment DEcision Coaching In people with Multiple Sclerosis (DECIMS) - Feasibility testing, pilot randomised controlled trial and mixed methods process evaluation.

Science.gov (United States)

Rahn, A C; Köpke, S; Backhus, I; Kasper, J; Anger, K; Untiedt, B; Alegiani, A; Kleiter, I; Mühlhauser, I; Heesen, C

2018-02-01

Treatment decision-making is complex for people with multiple sclerosis. Profound information on available options is virtually not possible in regular neurologist encounters. The "nurse decision coach model" was developed to redistribute health professionals' tasks in supporting immunotreatment decision-making following the principles of informed shared decision-making. To test the feasibility of a decision coaching programme and recruitment strategies to inform the main trial. Feasibility testing and parallel pilot randomised controlled trial, accompanied by a mixed methods process evaluation. Two German multiple sclerosis university centres. People with suspected or relapsing-remitting multiple sclerosis facing immunotreatment decisions on first line drugs were recruited. Randomisation to the intervention (n = 38) or control group (n = 35) was performed on a daily basis. Quantitative and qualitative process data were collected from people with multiple sclerosis, nurses and physicians. We report on the development and piloting of the decision coaching programme. It comprises a training course for multiple sclerosis nurses and the coaching intervention. The intervention consists of up to three structured nurse-led decision coaching sessions, access to an evidence-based online information platform (DECIMS-Wiki) and a final physician consultation. After feasibility testing, a pilot randomised controlled trial was performed. People with multiple sclerosis were randomised to the intervention or control group. The latter had also access to the DECIMS-Wiki, but received otherwise care as usual. Nurses were not blinded to group assignment, while people with multiple sclerosis and physicians were. The primary outcome was 'informed choice' after six months including the sub-dimensions' risk knowledge (after 14 days), attitude concerning immunotreatment (after physician consultation), and treatment uptake (after six months). Quantitative process evaluation data

Optimized production planning model for a multi-plant cultivation system under uncertainty

Science.gov (United States)

Ke, Shunkui; Guo, Doudou; Niu, Qingliang; Huang, Danfeng

2015-02-01

An inexact multi-constraint programming model under uncertainty was developed by incorporating a production plan algorithm into the crop production optimization framework under the multi-plant collaborative cultivation system. In the production plan, orders from the customers are assigned to a suitable plant under the constraints of plant capabilities and uncertainty parameters to maximize profit and achieve customer satisfaction. The developed model and solution method were applied to a case study of a multi-plant collaborative cultivation system to verify its applicability. As determined in the case analysis involving different orders from customers, the period of plant production planning and the interval between orders can significantly affect system benefits. Through the analysis of uncertain parameters, reliable and practical decisions can be generated using the suggested model of a multi-plant collaborative cultivation system.

Identifying multiple timescale rainfall controls on Mojave Desert ecohydrology using an integrated data and modeling approach for Larrea tridentata

Science.gov (United States)

Ng, Gene-Hua Crystal; Bedford, David R.; Miller, David M.

2015-01-01

The perennial shrub Larrea tridentata is widely successful in North American warm deserts but is also susceptible to climatic perturbations. Understanding its response to rainfall variability requires consideration of multiple timescales. We examine intra-annual to multi-year relationships using model simulations of soil moisture and vegetation growth over 50 years in the Mojave National Preserve in southeastern California (USA). Ecohydrological model parameters are conditioned on field and remote sensing data using an ensemble Kalman filter. Although no specific periodicities were detected in the rainfall record, simulated leaf-area-index exhibits multi-year dynamics that are driven by multi-year (∼3-years) rains, but with up to a 1-year delay in peak response. Within a multi-year period, Larrea tridentata is more sensitive to winter rains than summer. In the most active part of the root zone (above ∼80 cm), >1-year average soil moisture drives vegetation growth, but monthly average soil moisture is controlled by root uptake. Moisture inputs reach the lower part of the root zone (below ∼80 cm) infrequently, but once there they can persist over a year to help sustain plant growth. Parameter estimates highlight efficient plant physiological properties facilitating persistent growth and high soil hydraulic conductivity allowing deep soil moisture stores. We show that soil moisture as an ecological indicator is complicated by bidirectional interactions with vegetation that depend on timescale and depth. Under changing climate, Larrea tridentata will likely be relatively resilient to shorter-term moisture variability but will exhibit higher sensitivity to shifts in seasonal to multi-year moisture inputs.

An Overview on SDN Architectures with Multiple Controllers

Directory of Open Access Journals (Sweden)

Othmane Blial

2016-01-01

Full Text Available Software-defined networking offers several benefits for networking by separating the control plane from the data plane. However, networks’ scalability, reliability, and availability remain as a big issue. Accordingly, multicontroller architectures are important for SDN-enabled networks. This paper gives a comprehensive overview of SDN multicontroller architectures. It presents SDN and its main instantiation OpenFlow. Then, it explains in detail the differences between multiple types of multicontroller architectures, like the distribution method and the communication system. Furthermore, it provides already implemented and under research examples of multicontroller architectures by describing their design, their communication process, and their performance results.

MATHEMATICAL MODELING AND SIMULATION OF AUTOMATIC CONTROL FOR QUINTUPLE EFFECT EVAPORATION OF CENTRAL SUGAR “EL PALMAR” IN VENEZUELA

Directory of Open Access Journals (Sweden)

Lisoviett Pérez Pinto

2015-04-01

Full Text Available In this paper, the mathematical modeling and simulation of the automatic control of the quintuple effect of evaporation of a sugar mill “El Palmar” in Venezuela is made. The multiple effect consist of 5 evaporators Robert type, with equal characteristics, connected in series. Starting from the desired operating conditions and control requirements: level in each evaporator vessel, cane syrup concentration and pressure in the fifth evaporator vessel using mass balances, balance on solids for each evaporator and energy to the barometric condenser is present at the output of the fifth vessel, the nonlinear model of the process is obtained, resulting in a system of multiple inputs and multiple outputs, with strong interactions between variables. In the design of the system of the automatic process control, we are interested in maintaining the variables that characterize the performance of it and they are regulated in an operating point; we proceed to linearize the model around an equilibrium point, resulting in a new model in terms of the variables variations around an environment from that point. Then, it is processed the model obtained in terms of input and output relations, based on the characterization of it in terms of variables and transfer relationships in the complex frequency domain. Finally, the evaporation process is simulated, establishing the adequacy of the model to the real process.

Optically controlled multiple switching operations of DNA biopolymer devices

International Nuclear Information System (INIS)

Hung, Chao-You; Tu, Waan-Ting; Lin, Yi-Tzu; Fruk, Ljiljana; Hung, Yu-Chueh

2015-01-01

We present optically tunable operations of deoxyribonucleic acid (DNA) biopolymer devices, where a single high-resistance state, write-once read-many-times memory state, write-read-erase memory state, and single low-resistance state can be achieved by controlling UV irradiation time. The device is a simple sandwich structure with a spin-coated DNA biopolymer layer sandwiched by two electrodes. Upon irradiation, the electrical properties of the device are adjusted owing to a phototriggered synthesis of silver nanoparticles in DNA biopolymer, giving rise to multiple switching scenarios. This technique, distinct from the strategy of doping of pre-formed nanoparticles, enables a post-film fabrication process for achieving optically controlled memory device operations, which provides a more versatile platform to fabricate organic memory and optoelectronic devices

Optically controlled multiple switching operations of DNA biopolymer devices

Energy Technology Data Exchange (ETDEWEB)

Hung, Chao-You; Tu, Waan-Ting; Lin, Yi-Tzu [Institute of Photonics Technologies, National Tsing Hua University, Hsinchu 30013, Taiwan (China); Fruk, Ljiljana [Department of Chemical Engineering and Biotechnology, University of Cambridge, Pembroke Street, Cambridge CB2 3RA (United Kingdom); Hung, Yu-Chueh, E-mail: ychung@ee.nthu.edu.tw [Institute of Photonics Technologies, National Tsing Hua University, Hsinchu 30013, Taiwan (China); Department of Electrical Engineering, National Tsing Hua University, Hsinchu 30013, Taiwan (China)

2015-12-21

We present optically tunable operations of deoxyribonucleic acid (DNA) biopolymer devices, where a single high-resistance state, write-once read-many-times memory state, write-read-erase memory state, and single low-resistance state can be achieved by controlling UV irradiation time. The device is a simple sandwich structure with a spin-coated DNA biopolymer layer sandwiched by two electrodes. Upon irradiation, the electrical properties of the device are adjusted owing to a phototriggered synthesis of silver nanoparticles in DNA biopolymer, giving rise to multiple switching scenarios. This technique, distinct from the strategy of doping of pre-formed nanoparticles, enables a post-film fabrication process for achieving optically controlled memory device operations, which provides a more versatile platform to fabricate organic memory and optoelectronic devices.

Circadian phase resetting via single and multiple control targets.

Directory of Open Access Journals (Sweden)

Neda Bagheri

2008-07-01

Full Text Available 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.

Mathematical Modelling, Simulation, and Optimal Control of the 2014 Ebola Outbreak in West Africa

Directory of Open Access Journals (Sweden)

Amira Rachah

2015-01-01

it is crucial to modelize the virus and simulate it. In this paper, we begin by studying a simple mathematical model that describes the 2014 Ebola outbreak in Liberia. Then, we use numerical simulations and available data provided by the World Health Organization to validate the obtained mathematical model. Moreover, we develop a new mathematical model including vaccination of individuals. We discuss different cases of vaccination in order to predict the effect of vaccination on the infected individuals over time. Finally, we apply optimal control to study the impact of vaccination on the spread of the Ebola virus. The optimal control problem is solved numerically by using a direct multiple shooting method.

Internet-based home training is capable to improve balance in multiple sclerosis: a randomized controlled trial.

Science.gov (United States)

Frevel, D; Mäurer, M

2015-02-01

Balance disorders are common in multiple sclerosis. Aim of the study is to investigate the effectiveness of an Internet-based home training program (e-Training) to improve balance in patients with multiple sclerosis. A randomized, controlled study. Academic teaching hospital in cooperation with the therapeutic riding center Gut Üttingshof, Bad Mergentheim. Eighteen multiple sclerosis patients (mean EDSS 3,5) took part in the trial. Outcome of patients using e-Training (N.=9) was compared to the outcome of patients receiving hippotherapy (N.=9), which can be considered as an advanced concept for the improvement of balance and postural control in multiple sclerosis. After simple random allocation patients received hippotherapy or Internet-based home training (balance, postural control and strength training) twice a week for 12 weeks. Assessments were done before and after the intervention and included static and dynamic balance (primary outcome). Isometric muscle strength of the knee and trunk extension/flexion (dynamometer), walking capacity, fatigue and quality of life served as secondary outcome parameters. Both intervention groups showed comparable and highly significant improvement in static and dynamic balance capacity, no difference was seen between the both intervention groups. However looking at fatigue and quality of life only the group receiving hippotherapy improved significantly. Since e-Training shows even comparable effects to hippotherapy to improve balance, we believe that the established Internet-based home training program, specialized on balance and postural control training, is feasible for a balance and strength training in persons with multiple sclerosis. We demonstrated that Internet-based home training is possible in patients with multiple sclerosis.

Temperature uniformity control in RTP using multivariable adaptive control

Energy Technology Data Exchange (ETDEWEB)

Morales, S.; Dahhou, B.; Dilhac, J.M. [Centre National de la Recherche Scientifique (CNRS), 31 - Toulouse (France); Morales, S.

1995-12-31

In Rapid Thermal Processing (RTP) control of the wafer temperature during all processing to get good trajectory following, together with spatial temperature uniformity, is essential. It is well know as RTP process is nonlinear, classical control laws are not very efficient. In this work, the authors aim at studying the applicability of MIMO (Multiple Inputs Multiple Outputs) adaptive techniques to solve the temperature control problems in RTP. A multivariable linear discrete time CARIMA (Controlled Auto Regressive Integrating Moving Average) model of the highly non-linear process is identified on-line using a robust identification technique. The identified model is used to compute an infinite time LQ (Linear Quadratic) based control law, with a partial state reference model. This reference model smooths the original setpoint sequence, and at the same time gives a tracking capability to the LQ control law. After an experimental open-loop investigation, the results of the application of the adaptive control law are presented. Finally, some comments on the future difficulties and developments of the application of adaptive control in RTP are given. (author) 13 refs.

Active control: Wind turbine model

Energy Technology Data Exchange (ETDEWEB)

Bindner, Henrik

1999-07-01

This report is a part of the reporting of the work done in the project `Active Control of Wind Turbines`. This project aim is to develop a simulation model for design of control systems for turbines with pitch control and to use that model to design controllers. This report describes the model developed for controller design and analysis. Emphasis has been put on establishment of simple models describing the dynamic behavior of the wind turbine in adequate details for controller design. This has been done with extensive use of measurements as the basis for selection of model complexity and model validation as well as parameter estimation. The model includes a simple model of the structure of the turbine including tower and flapwise blade bending, a detailed model of the gear box and induction generator, a linearized aerodynamic model including modelling of induction lag and actuator and sensor models. The models are all formulated as linear differential equations. The models are validated through comparisons with measurements performed on a Vestas WD 34 400 kW wind turbine. It is shown from a control point of view simple linear models can be used to describe the dynamic behavior of a pitch controlled wind turbine. The model and the measurements corresponds well in the relevant frequency range. The developed model is therefore applicable for controller design. (au) EFP-91. 18 ills., 22 refs.

Natural killer cell lines preferentially kill clonogenic multiple myeloma cells and decrease myeloma engraftment in a bioluminescent xenograft mouse model.

Science.gov (United States)

Swift, Brenna E; Williams, Brent A; Kosaka, Yoko; Wang, Xing-Hua; Medin, Jeffrey A; Viswanathan, Sowmya; Martinez-Lopez, Joaquin; Keating, Armand

2012-07-01

Novel therapies capable of targeting drug resistant clonogenic MM cells are required for more effective treatment of multiple myeloma. This study investigates the cytotoxicity of natural killer cell lines against bulk and clonogenic multiple myeloma and evaluates the tumor burden after NK cell therapy in a bioluminescent xenograft mouse model. The cytotoxicity of natural killer cell lines was evaluated against bulk multiple myeloma cell lines using chromium release and flow cytometry cytotoxicity assays. Selected activating receptors on natural killer cells were blocked to determine their role in multiple myeloma recognition. Growth inhibition of clonogenic multiple myeloma cells was assessed in a methylcellulose clonogenic assay in combination with secondary replating to evaluate the self-renewal of residual progenitors after natural killer cell treatment. A bioluminescent mouse model was developed using the human U266 cell line transduced to express green fluorescent protein and luciferase (U266eGFPluc) to monitor disease progression in vivo and assess bone marrow engraftment after intravenous NK-92 cell therapy. Three multiple myeloma cell lines were sensitive to NK-92 and KHYG-1 cytotoxicity mediated by NKp30, NKp46, NKG2D and DNAM-1 activating receptors. NK-92 and KHYG-1 demonstrated 2- to 3-fold greater inhibition of clonogenic multiple myeloma growth, compared with killing of the bulk tumor population. In addition, the residual colonies after treatment formed significantly fewer colonies compared to the control in a secondary replating for a cumulative clonogenic inhibition of 89-99% at the 20:1 effector to target ratio. Multiple myeloma tumor burden was reduced by NK-92 in a xenograft mouse model as measured by bioluminescence imaging and reduction in bone marrow engraftment of U266eGFPluc cells by flow cytometry. This study demonstrates that NK-92 and KHYG-1 are capable of killing clonogenic and bulk multiple myeloma cells. In addition, multiple myeloma

Multiple Imputation of Predictor Variables Using Generalized Additive Models

NARCIS (Netherlands)

de Jong, Roel; van Buuren, Stef; Spiess, Martin

2016-01-01

The sensitivity of multiple imputation methods to deviations from their distributional assumptions is investigated using simulations, where the parameters of scientific interest are the coefficients of a linear regression model, and values in predictor variables are missing at random. The

Model Seleksi Premi Asuransi Jiwa Dwiguna untuk Kasus Multiple Decrement

OpenAIRE

Cita, Devi Ramana; Pane, Rolan; ', Harison

2015-01-01

This article discusses a select survival model for the case of multiple decrements in evaluating endowment life insurance premium for person currently aged ( + ) years, who is selected at age with ℎ years selection period. The case of multiple decrements in this case is limited to two cases. The calculation of the annual premium is done by prior evaluating of the single premium, and the present value of annuity depends on theconstant force assumption.

A multiple shock model for common cause failures using discrete Markov chain

International Nuclear Information System (INIS)

Chung, Dae Wook; Kang, Chang Soon

1992-01-01

The most widely used models in common cause analysis are (single) shock models such as the BFR, and the MFR. But, single shock model can not treat the individual common cause separately and has some irrational assumptions. Multiple shock model for common cause failures is developed using Markov chain theory. This model treats each common cause shock as separately and sequently occuring event to implicate the change in failure probability distribution due to each common cause shock. The final failure probability distribution is evaluated and compared with that from the BFR model. The results show that multiple shock model which minimizes the assumptions in the BFR model is more realistic and conservative than the BFR model. The further work for application is the estimations of parameters such as common cause shock rate and component failure probability given a shock,p, through the data analysis

Prediction Model of Battery State of Charge and Control Parameter Optimization for Electric Vehicle

Directory of Open Access Journals (Sweden)

Bambang Wahono

2015-07-01

Full Text Available This paper presents the construction of a battery state of charge (SOC prediction model and the optimization method of the said model to appropriately control the number of parameters in compliance with the SOC as the battery output objectives. Research Centre for Electrical Power and Mechatronics, Indonesian Institute of Sciences has tested its electric vehicle research prototype on the road, monitoring its voltage, current, temperature, time, vehicle velocity, motor speed, and SOC during the operation. Using this experimental data, the prediction model of battery SOC was built. Stepwise method considering multicollinearity was able to efficiently develops the battery prediction model that describes the multiple control parameters in relation to the characteristic values such as SOC. It was demonstrated that particle swarm optimization (PSO succesfully and efficiently calculated optimal control parameters to optimize evaluation item such as SOC based on the model.

Experimental Autoimmune Encephalomyelitis (EAE) as Animal Models of Multiple Sclerosis (MS).

Science.gov (United States)

Glatigny, Simon; Bettelli, Estelle

2018-01-08

Multiple sclerosis (MS) is a multifocal demyelinating disease of the central nervous system (CNS) leading to the progressive destruction of the myelin sheath surrounding axons. It can present with variable clinical and pathological manifestations, which might reflect the involvement of distinct pathogenic processes. Although the mechanisms leading to the development of the disease are not fully understood, numerous evidences indicate that MS is an autoimmune disease, the initiation and progression of which are dependent on an autoimmune response against myelin antigens. In addition, genetic susceptibility and environmental triggers likely contribute to the initiation of the disease. At this time, there is no cure for MS, but several disease-modifying therapies (DMTs) are available to control and slow down disease progression. A good number of these DMTs were identified and tested using animal models of MS referred to as experimental autoimmune encephalomyelitis (EAE). In this review, we will recapitulate the characteristics of EAE models and discuss how they help shed light on MS pathogenesis and help test new treatments for MS patients. Copyright © 2018 Cold Spring Harbor Laboratory Press; all rights reserved.

The Answering Process for Multiple-Choice Questions in Collaborative Learning: A Mathematical Learning Model Analysis

Science.gov (United States)

Nakamura, Yasuyuki; Nishi, Shinnosuke; Muramatsu, Yuta; Yasutake, Koichi; Yamakawa, Osamu; Tagawa, Takahiro

2014-01-01

In this paper, we introduce a mathematical model for collaborative learning and the answering process for multiple-choice questions. The collaborative learning model is inspired by the Ising spin model and the model for answering multiple-choice questions is based on their difficulty level. An intensive simulation study predicts the possibility of…

High-speed tracking control of piezoelectric actuators using an ellipse-based hysteresis model.

Science.gov (United States)

Gu, Guoying; Zhu, Limin

2010-08-01

In this paper, an ellipse-based mathematic model is developed to characterize the rate-dependent hysteresis in piezoelectric actuators. Based on the proposed model, an expanded input space is constructed to describe the multivalued hysteresis function H[u](t) by a multiple input single output (MISO) mapping Gamma:R(2)-->R. Subsequently, the inverse MISO mapping Gamma(-1)(H[u](t),H[u](t);u(t)) is proposed for real-time hysteresis compensation. In controller design, a hybrid control strategy combining a model-based feedforward controller and a proportional integral differential (PID) feedback loop is used for high-accuracy and high-speed tracking control of piezoelectric actuators. The real-time feedforward controller is developed to cancel the rate-dependent hysteresis based on the inverse hysteresis model, while the PID controller is used to compensate for the creep, modeling errors, and parameter uncertainties. Finally, experiments with and without hysteresis compensation are conducted and the experimental results are compared. The experimental results show that the hysteresis compensation in the feedforward path can reduce the hysteresis-caused error by up to 88% and the tracking performance of the hybrid controller is greatly improved in high-speed tracking control applications, e.g., the root-mean-square tracking error is reduced to only 0.34% of the displacement range under the input frequency of 100 Hz.

Protein structure modeling for CASP10 by multiple layers of global optimization.

Science.gov (United States)

Joo, Keehyoung; Lee, Juyong; Sim, Sangjin; Lee, Sun Young; Lee, Kiho; Heo, Seungryong; Lee, In-Ho; Lee, Sung Jong; Lee, Jooyoung

2014-02-01

In the template-based modeling (TBM) category of CASP10 experiment, we introduced a new protocol called protein modeling system (PMS) to generate accurate protein structures in terms of side-chains as well as backbone trace. In the new protocol, a global optimization algorithm, called conformational space annealing (CSA), is applied to the three layers of TBM procedure: multiple sequence-structure alignment, 3D chain building, and side-chain re-modeling. For 3D chain building, we developed a new energy function which includes new distance restraint terms of Lorentzian type (derived from multiple templates), and new energy terms that combine (physical) energy terms such as dynamic fragment assembly (DFA) energy, DFIRE statistical potential energy, hydrogen bonding term, etc. These physical energy terms are expected to guide the structure modeling especially for loop regions where no template structures are available. In addition, we developed a new quality assessment method based on random forest machine learning algorithm to screen templates, multiple alignments, and final models. For TBM targets of CASP10, we find that, due to the combination of three stages of CSA global optimizations and quality assessment, the modeling accuracy of PMS improves at each additional stage of the protocol. It is especially noteworthy that the side-chains of the final PMS models are far more accurate than the models in the intermediate steps. Copyright © 2013 Wiley Periodicals, Inc.

Large Display Interaction via Multiple Acceleration Curves and Multifinger Pointer Control

Directory of Open Access Journals (Sweden)

Andrey Esakia

2014-01-01

Full Text Available Large high-resolution displays combine high pixel density with ample physical dimensions. The combination of these factors creates a multiscale workspace where interactive targeting of on-screen objects requires both high speed for distant targets and high accuracy for small targets. Modern operating systems support implicit dynamic control-display gain adjustment (i.e., a pointer acceleration curve that helps to maintain both speed and accuracy. However, large high-resolution displays require a broader range of control-display gains than a single acceleration curve can usably enable. Some interaction techniques attempt to solve the problem by utilizing multiple explicit modes of interaction, where different modes provide different levels of pointer precision. Here, we investigate the alternative hypothesis of using a single mode of interaction for continuous pointing that enables both (1 standard implicit granularity control via an acceleration curve and (2 explicit switching between multiple acceleration curves in an efficient and dynamic way. We evaluate a sample solution that augments standard touchpad accelerated pointer manipulation with multitouch capability, where the choice of acceleration curve dynamically changes depending on the number of fingers in contact with the touchpad. Specifically, users can dynamically switch among three different acceleration curves by using one, two, or three fingers on the touchpad.

Consensus seeking, formation keeping, and trajectory tracking in multiple vehicle cooperative control

Science.gov (United States)

Ren, Wei

Cooperative control problems for multiple vehicle systems can be categorized as either formation control problems with applications to mobile robots, unmanned air vehicles, autonomous underwater vehicles, satellites, aircraft, spacecraft, and automated highway systems, or non-formation control problems such as task assignment, cooperative transport, cooperative role assignment, air traffic control, cooperative timing, and cooperative search. The cooperative control of multiple vehicle systems poses significant theoretical and practical challenges. For cooperative control strategies to be successful, numerous issues must be addressed. We consider three important and correlated issues: consensus seeking, formation keeping, and trajectory tracking. For consensus seeking, we investigate algorithms and protocols so that a team of vehicles can reach consensus on the values of the coordination data in the presence of imperfect sensors, communication dropout, sparse communication topologies, and noisy and unreliable communication links. The main contribution of this dissertation in this area is that we show necessary and/or sufficient conditions for consensus seeking with limited, unidirectional, and unreliable information exchange under fixed and switching interaction topologies (through either communication or sensing). For formation keeping, we apply a so-called "virtual structure" approach to spacecraft formation flying and multi-vehicle formation maneuvers. As a result, single vehicle path planning and trajectory generation techniques can be employed for the virtual structure while trajectory tracking strategies can be employed for each vehicle. The main contribution of this dissertation in this area is that we propose a decentralized architecture for multiple spacecraft formation flying in deep space with formation feedback introduced. This architecture ensures the necessary precision in the presence of actuator saturation, internal and external disturbances, and

Interacting Multiple Model (IMM Fifth-Degree Spherical Simplex-Radial Cubature Kalman Filter for Maneuvering Target Tracking

Directory of Open Access Journals (Sweden)

Hua Liu

2017-06-01

Full Text Available For improving the tracking accuracy and model switching speed of maneuvering target tracking in nonlinear systems, a new algorithm named the interacting multiple model fifth-degree spherical simplex-radial cubature Kalman filter (IMM5thSSRCKF is proposed in this paper. The new algorithm is a combination of the interacting multiple model (IMM filter and the fifth-degree spherical simplex-radial cubature Kalman filter (5thSSRCKF. The proposed algorithm makes use of Markov process to describe the switching probability among the models, and uses 5thSSRCKF to deal with the state estimation of each model. The 5thSSRCKF is an improved filter algorithm, which utilizes the fifth-degree spherical simplex-radial rule to improve the filtering accuracy. Finally, the tracking performance of the IMM5thSSRCKF is evaluated by simulation in a typical maneuvering target tracking scenario. Simulation results show that the proposed algorithm has better tracking performance and quicker model switching speed when disposing maneuver models compared with the interacting multiple model unscented Kalman filter (IMMUKF, the interacting multiple model cubature Kalman filter (IMMCKF and the interacting multiple model fifth-degree cubature Kalman filter (IMM5thCKF.

Interacting Multiple Model (IMM) Fifth-Degree Spherical Simplex-Radial Cubature Kalman Filter for Maneuvering Target Tracking.

Science.gov (United States)

Liu, Hua; Wu, Wen

2017-06-13

For improving the tracking accuracy and model switching speed of maneuvering target tracking in nonlinear systems, a new algorithm named the interacting multiple model fifth-degree spherical simplex-radial cubature Kalman filter (IMM5thSSRCKF) is proposed in this paper. The new algorithm is a combination of the interacting multiple model (IMM) filter and the fifth-degree spherical simplex-radial cubature Kalman filter (5thSSRCKF). The proposed algorithm makes use of Markov process to describe the switching probability among the models, and uses 5thSSRCKF to deal with the state estimation of each model. The 5thSSRCKF is an improved filter algorithm, which utilizes the fifth-degree spherical simplex-radial rule to improve the filtering accuracy. Finally, the tracking performance of the IMM5thSSRCKF is evaluated by simulation in a typical maneuvering target tracking scenario. Simulation results show that the proposed algorithm has better tracking performance and quicker model switching speed when disposing maneuver models compared with the interacting multiple model unscented Kalman filter (IMMUKF), the interacting multiple model cubature Kalman filter (IMMCKF) and the interacting multiple model fifth-degree cubature Kalman filter (IMM5thCKF).

Comparing Multiple-Group Multinomial Log-Linear Models for Multidimensional Skill Distributions in the General Diagnostic Model. Research Report. ETS RR-08-35

Science.gov (United States)

Xu, Xueli; von Davier, Matthias

2008-01-01

The general diagnostic model (GDM) utilizes located latent classes for modeling a multidimensional proficiency variable. In this paper, the GDM is extended by employing a log-linear model for multiple populations that assumes constraints on parameters across multiple groups. This constrained model is compared to log-linear models that assume…

Controlled multiple neutral planes by low elastic modulus adhesive for flexible organic photovoltaics.

Science.gov (United States)

Kim, Wansun; Lee, Inhwa; Yoon Kim, Dong; Yu, Youn-Yeol; Jung, Hae-Yoon; Kwon, Seyeoul; Seo Park, Weon; Kim, Taek-Soo

2017-05-12

To protect brittle layers in organic photovoltaic devices, the mechanical neutral plane strategy can be adopted through placing the brittle functional materials close to the neutral plane where stress and strain are zero during bending. However, previous research has been significantly limited in the location and number of materials to protect through using a single neutral plane. In this study, multiple neutral planes are generated using low elastic modulus adhesives and are controlled through quantitative analyses in order to protect the multiple brittle materials at various locations. Moreover, the protection of multiple brittle layers at various locations under both concave and convex bending directions is demonstrated. Multilayer structures that have soft adhesives are further analyzed using the finite element method analysis in order to propose guidelines for structural design when employing multiple neutral planes.

Progression of regional grey matter atrophy in multiple sclerosis.

Science.gov (United States)

Eshaghi, Arman; Marinescu, Razvan V; Young, Alexandra L; Firth, Nicholas C; Prados, Ferran; Jorge Cardoso, M; Tur, Carmen; De Angelis, Floriana; Cawley, Niamh; Brownlee, Wallace J; De Stefano, Nicola; Laura Stromillo, M; Battaglini, Marco; Ruggieri, Serena; Gasperini, Claudio; Filippi, Massimo; Rocca, Maria A; Rovira, Alex; Sastre-Garriga, Jaume; Geurts, Jeroen J G; Vrenken, Hugo; Wottschel, Viktor; Leurs, Cyra E; Uitdehaag, Bernard; Pirpamer, Lukas; Enzinger, Christian; Ourselin, Sebastien; Gandini Wheeler-Kingshott, Claudia A; Chard, Declan; Thompson, Alan J; Barkhof, Frederik; Alexander, Daniel C; Ciccarelli, Olga

2018-06-01

See Stankoff and Louapre (doi:10.1093/brain/awy114) for a scientific commentary on this article.Grey matter atrophy is present from the earliest stages of multiple sclerosis, but its temporal ordering is poorly understood. We aimed to determine the sequence in which grey matter regions become atrophic in multiple sclerosis and its association with disability accumulation. In this longitudinal study, we included 1417 subjects: 253 with clinically isolated syndrome, 708 with relapsing-remitting multiple sclerosis, 128 with secondary-progressive multiple sclerosis, 125 with primary-progressive multiple sclerosis, and 203 healthy control subjects from seven European centres. Subjects underwent repeated MRI (total number of scans 3604); the mean follow-up for patients was 2.41 years (standard deviation = 1.97). Disability was scored using the Expanded Disability Status Scale. We calculated the volume of brain grey matter regions and brainstem using an unbiased within-subject template and used an established data-driven event-based model to determine the sequence of occurrence of atrophy and its uncertainty. We assigned each subject to a specific event-based model stage, based on the number of their atrophic regions. Linear mixed-effects models were used to explore associations between the rate of increase in event-based model stages, and T2 lesion load, disease-modifying treatments, comorbidity, disease duration and disability accumulation. The first regions to become atrophic in patients with clinically isolated syndrome and relapse-onset multiple sclerosis were the posterior cingulate cortex and precuneus, followed by the middle cingulate cortex, brainstem and thalamus. A similar sequence of atrophy was detected in primary-progressive multiple sclerosis with the involvement of the thalamus, cuneus, precuneus, and pallidum, followed by the brainstem and posterior cingulate cortex. The cerebellum, caudate and putamen showed early atrophy in relapse-onset multiple

Progression of regional grey matter atrophy in multiple sclerosis

Science.gov (United States)

Marinescu, Razvan V; Young, Alexandra L; Firth, Nicholas C; Jorge Cardoso, M; Tur, Carmen; De Angelis, Floriana; Cawley, Niamh; Brownlee, Wallace J; De Stefano, Nicola; Laura Stromillo, M; Battaglini, Marco; Ruggieri, Serena; Gasperini, Claudio; Filippi, Massimo; Rocca, Maria A; Rovira, Alex; Sastre-Garriga, Jaume; Geurts, Jeroen J G; Vrenken, Hugo; Wottschel, Viktor; Leurs, Cyra E; Uitdehaag, Bernard; Pirpamer, Lukas; Enzinger, Christian; Ourselin, Sebastien; Gandini Wheeler-Kingshott, Claudia A; Chard, Declan; Thompson, Alan J; Barkhof, Frederik; Alexander, Daniel C; Ciccarelli, Olga

2018-01-01

Abstract See Stankoff and Louapre (doi:10.1093/brain/awy114) for a scientific commentary on this article. Grey matter atrophy is present from the earliest stages of multiple sclerosis, but its temporal ordering is poorly understood. We aimed to determine the sequence in which grey matter regions become atrophic in multiple sclerosis and its association with disability accumulation. In this longitudinal study, we included 1417 subjects: 253 with clinically isolated syndrome, 708 with relapsing-remitting multiple sclerosis, 128 with secondary-progressive multiple sclerosis, 125 with primary-progressive multiple sclerosis, and 203 healthy control subjects from seven European centres. Subjects underwent repeated MRI (total number of scans 3604); the mean follow-up for patients was 2.41 years (standard deviation = 1.97). Disability was scored using the Expanded Disability Status Scale. We calculated the volume of brain grey matter regions and brainstem using an unbiased within-subject template and used an established data-driven event-based model to determine the sequence of occurrence of atrophy and its uncertainty. We assigned each subject to a specific event-based model stage, based on the number of their atrophic regions. Linear mixed-effects models were used to explore associations between the rate of increase in event-based model stages, and T2 lesion load, disease-modifying treatments, comorbidity, disease duration and disability accumulation. The first regions to become atrophic in patients with clinically isolated syndrome and relapse-onset multiple sclerosis were the posterior cingulate cortex and precuneus, followed by the middle cingulate cortex, brainstem and thalamus. A similar sequence of atrophy was detected in primary-progressive multiple sclerosis with the involvement of the thalamus, cuneus, precuneus, and pallidum, followed by the brainstem and posterior cingulate cortex. The cerebellum, caudate and putamen showed early atrophy in relapse

A latent class multiple constraint multiple discrete-continuous extreme value model of time use and goods consumption.

Science.gov (United States)

2016-06-01

This paper develops a microeconomic theory-based multiple discrete continuous choice model that considers: (a) that both goods consumption and time allocations (to work and non-work activities) enter separately as decision variables in the utility fu...

Distributed Autonomous Control of Multiple Spacecraft During Close Proximity Operations

Science.gov (United States)

2007-12-01

Neubauer [54][55]. 87 VII. LQR/APF CONTROL ALGORITHM APPROACH The LQR approach can be recursively applied to the multiple spacecraft close... Neubauer and Swartwout’s research [55]. It is generally possible to select a closed map over which the algorithm is stable and robust. For these...can be easily edited and transferred into video format for presentations. Modifications of camera key frames ( camera position and angle) and

Hybrid approaches for multiple-species stochastic reaction-diffusion models

Science.gov (United States)

Spill, Fabian; Guerrero, Pilar; Alarcon, Tomas; Maini, Philip K.; Byrne, Helen

2015-10-01

Reaction-diffusion models are used to describe systems in fields as diverse as physics, chemistry, ecology and biology. The fundamental quantities in such models are individual entities such as atoms and molecules, bacteria, cells or animals, which move and/or react in a stochastic manner. If the number of entities is large, accounting for each individual is inefficient, and often partial differential equation (PDE) models are used in which the stochastic behaviour of individuals is replaced by a description of the averaged, or mean behaviour of the system. In some situations the number of individuals is large in certain regions and small in others. In such cases, a stochastic model may be inefficient in one region, and a PDE model inaccurate in another. To overcome this problem, we develop a scheme which couples a stochastic reaction-diffusion system in one part of the domain with its mean field analogue, i.e. a discretised PDE model, in the other part of the domain. The interface in between the two domains occupies exactly one lattice site and is chosen such that the mean field description is still accurate there. In this way errors due to the flux between the domains are small. Our scheme can account for multiple dynamic interfaces separating multiple stochastic and deterministic domains, and the coupling between the domains conserves the total number of particles. The method preserves stochastic features such as extinction not observable in the mean field description, and is significantly faster to simulate on a computer than the pure stochastic model.

Hybrid approaches for multiple-species stochastic reaction-diffusion models.

KAUST Repository

Spill, Fabian; Guerrero, Pilar; Alarcon, Tomas; Maini, Philip K; Byrne, Helen

2015-01-01

Reaction-diffusion models are used to describe systems in fields as diverse as physics, chemistry, ecology and biology. The fundamental quantities in such models are individual entities such as atoms and molecules, bacteria, cells or animals, which move and/or react in a stochastic manner. If the number of entities is large, accounting for each individual is inefficient, and often partial differential equation (PDE) models are used in which the stochastic behaviour of individuals is replaced by a description of the averaged, or mean behaviour of the system. In some situations the number of individuals is large in certain regions and small in others. In such cases, a stochastic model may be inefficient in one region, and a PDE model inaccurate in another. To overcome this problem, we develop a scheme which couples a stochastic reaction-diffusion system in one part of the domain with its mean field analogue, i.e. a discretised PDE model, in the other part of the domain. The interface in between the two domains occupies exactly one lattice site and is chosen such that the mean field description is still accurate there. In this way errors due to the flux between the domains are small. Our scheme can account for multiple dynamic interfaces separating multiple stochastic and deterministic domains, and the coupling between the domains conserves the total number of particles. The method preserves stochastic features such as extinction not observable in the mean field description, and is significantly faster to simulate on a computer than the pure stochastic model.

Hybrid approaches for multiple-species stochastic reaction-diffusion models.

KAUST Repository

Spill, Fabian

2015-10-01

Reaction-diffusion models are used to describe systems in fields as diverse as physics, chemistry, ecology and biology. The fundamental quantities in such models are individual entities such as atoms and molecules, bacteria, cells or animals, which move and/or react in a stochastic manner. If the number of entities is large, accounting for each individual is inefficient, and often partial differential equation (PDE) models are used in which the stochastic behaviour of individuals is replaced by a description of the averaged, or mean behaviour of the system. In some situations the number of individuals is large in certain regions and small in others. In such cases, a stochastic model may be inefficient in one region, and a PDE model inaccurate in another. To overcome this problem, we develop a scheme which couples a stochastic reaction-diffusion system in one part of the domain with its mean field analogue, i.e. a discretised PDE model, in the other part of the domain. The interface in between the two domains occupies exactly one lattice site and is chosen such that the mean field description is still accurate there. In this way errors due to the flux between the domains are small. Our scheme can account for multiple dynamic interfaces separating multiple stochastic and deterministic domains, and the coupling between the domains conserves the total number of particles. The method preserves stochastic features such as extinction not observable in the mean field description, and is significantly faster to simulate on a computer than the pure stochastic model.

Risk Prediction Models for Other Cancers or Multiple Sites

Science.gov (United States)

Developing statistical models that estimate the probability of developing other multiple cancers over a defined period of time will help clinicians identify individuals at higher risk of specific cancers, allowing for earlier or more frequent screening and counseling of behavioral changes to decrease risk.

MULTIPLE HUMAN TRACKING IN COMPLEX SITUATION BY DATA ASSIMILATION WITH PEDESTRIAN BEHAVIOR MODEL

Directory of Open Access Journals (Sweden)

W. Nakanishi

2012-07-01

Full Text Available A new method of multiple human tracking is proposed. The key concept is that to assume a tracking process as a data assimilation process. Despite the importance of understanding pedestrian behavior in public space with regard to achieving more sophisticated space design and flow control, automatic human tracking in complex situation is still challenging when people move close to each other or are occluded by others. For this difficulty, we stochastically combine existing tracking method by image processing with simulation models of walking behavior. We describe a system in a form of general state space model and define the components of the model according to the review on related works. Then we apply the proposed method to the data acquired at the ticket gate of the railway station. We show the high performance of the method, as well as compare the result with other model to present the advantage of integrating the behavior model to the tracking method. We also show the method's ability to acquire passenger flow information such as ticket gate choice and OD data automatically from the tracking result.

Changes of deep gray matter magnetic susceptibility over 2years in multiple sclerosis and healthy control brain

Directory of Open Access Journals (Sweden)

Jesper Hagemeier

Full Text Available In multiple sclerosis, pathological changes of both tissue iron and myelin occur, yet these factors have not been characterized in a longitudinal fashion using the novel iron- and myelin-sensitive quantitative susceptibility mapping (QSM MRI technique. We investigated disease-relevant tissue changes associated with myelin loss and iron accumulation in multiple sclerosis deep gray matter (DGM over two years. One-hundred twenty (120 multiple sclerosis patients and 40 age- and sex-matched healthy controls were included in this prospective study. Written informed consent and local IRB approval were obtained from all participants. Clinical testing and QSM were performed both at baseline and at follow-up. Brain magnetic susceptibility was measured in major DGM structures. Temporal (baseline vs. follow-up and cross-sectional (multiple sclerosis vs. controls differences were studied using mixed factorial ANOVA analysis and appropriate t-tests. At either time-point, multiple sclerosis patients had significantly higher susceptibility in the caudate and globus pallidus and lower susceptibility in the thalamus. Over two years, susceptibility increased significantly in the caudate of both controls and multiple sclerosis patients. Inverse thalamic findings among MS patients suggest a multi-phase pathology explained by simultaneous myelin loss and/or iron accumulation followed by iron depletion and/or calcium deposition at later stages. Keywords: Quantitative susceptibility mapping, QSM, Iron, Multiple sclerosis, Longitudinal study

Exclusive description of multiple production on nuclei in the additive quark model. Multiplicity distributions in interactions with heavy nuclei

International Nuclear Information System (INIS)

Levchenko, B.B.; Nikolaev, N.N.

1985-01-01

In the framework of the additive quark model of multiple production on nuclei we calculate the multiplicity distributions of secondary particles and the correlations between secondary particles in πA and pA interactions with heavy nuclei. We show that intranuclear cascades are responsible for up to 50% of the nuclear increase of the multiplicity of fast particles. We analyze the sensitivity of the multiplicities and their correlations to the choice of the quark-hadronization function. We show that with good accuracy the yield of relativistic secondary particles from heavy and intermediate nuclei depends only on the number N/sub p/ of protons knocked out of the nucleus, and not on the mass number of the nucleus (N/sub p/ scaling)

Multiple attribute decision making model and application to food safety risk evaluation.

Science.gov (United States)

Ma, Lihua; Chen, Hong; Yan, Huizhe; Yang, Lifeng; Wu, Lifeng

2017-01-01

Decision making for supermarket food purchase decisions are characterized by network relationships. This paper analyzed factors that influence supermarket food selection and proposes a supplier evaluation index system based on the whole process of food production. The author established the intuitive interval value fuzzy set evaluation model based on characteristics of the network relationship among decision makers, and validated for a multiple attribute decision making case study. Thus, the proposed model provides a reliable, accurate method for multiple attribute decision making.

$H^\\infty$ control of systems with multiple I/O delays via decomposition to adobe problems

NARCIS (Netherlands)

Meinsma, Gjerrit; Mirkin, Leonid

In this paper, the standard (four-block) $H^\\infty$ control problem for systems with multiple input-output delays in the feedback loop is studied. The central idea is to see the multiple delay operator as a special series connection of elementary delay operators, called the adobe delay operators.

Stock management in hospital pharmacy using chance-constrained model predictive control.

Science.gov (United States)

Jurado, I; Maestre, J M; Velarde, P; Ocampo-Martinez, C; Fernández, I; Tejera, B Isla; Prado, J R Del

2016-05-01

One of the most important problems in the pharmacy department of a hospital is stock management. The clinical need for drugs must be satisfied with limited work labor while minimizing the use of economic resources. The complexity of the problem resides in the random nature of the drug demand and the multiple constraints that must be taken into account in every decision. In this article, chance-constrained model predictive control is proposed to deal with this problem. The flexibility of model predictive control allows taking into account explicitly the different objectives and constraints involved in the problem while the use of chance constraints provides a trade-off between conservativeness and efficiency. The solution proposed is assessed to study its implementation in two Spanish hospitals. Copyright © 2015 Elsevier Ltd. All rights reserved.

Penerapan Model Pembelajaran Atraktif Berbasis Multiple Intelligences Tentang Pemantulan Cahaya pada Cermin

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Intan Kusumawati

2016-03-01

Full Text Available Penelitian ini bertujuan untuk mengetahui efektivitas penerapan model pembelajaran atraktif berbasis multiple intelligences dalam meremediasi miskonsepsi siswa tentang pemantulan cahaya pada cermin. Pada penelitian ini digunakan bentuk pre-eksperimental design dengan rancangan one group pretest-post test design. Alat pengumpulan data berupa tes pilihan ganda dengan reasoning. Hasil validitas sebesar 4,08 dan reliabilitas 0,537. Siswa dibagi menjadi lima kelompok kecerdasan, yaitu kelompok linguistic intelligence, mathematical-logical intelligence, visual-spatial intelligence, bodily-khinestetic intelligence, dan musical intelligence. Siswa membahas konsep fisika sesuai kelompok kecerdasannya dalam bentuk pembuatan pantun-puisi, teka-teki silang, menggambar kreatif, drama, dan mengarang lirik lagu. Efektivitas penerapan model pembelajaran multiple intelligences menggunakan persamaan effect size. Ditemukan bahwa skor effect size masing-masing kelompok berkategori tinggi sebesar 5,76; 3,76; 4,60; 1,70; dan 1,34. Penerapan model pembelajaran atraktif berbasis multiple intelligences efektif dalam meremediasi miskonsepsi siswa. Penelitian ini diharapkan dapat digunakan pada materi fisika dan sekolah lainnya.

Tumor Control Probability Modeling for Stereotactic Body Radiation Therapy of Early-Stage Lung Cancer Using Multiple Bio-physical Models

Science.gov (United States)

Liu, Feng; Tai, An; Lee, Percy; Biswas, Tithi; Ding, George X.; El Naqa, Isaam; Grimm, Jimm; Jackson, Andrew; Kong, Feng-Ming (Spring); LaCouture, Tamara; Loo, Billy; Miften, Moyed; Solberg, Timothy; Li, X Allen

2017-01-01

Purpose To analyze pooled clinical data using different radiobiological models and to understand the relationship between biologically effective dose (BED) and tumor control probability (TCP) for stereotactic body radiotherapy (SBRT) of early-stage non-small cell lung cancer (NSCLC). Method and Materials The clinical data of 1-, 2-, 3-, and 5-year actuarial or Kaplan-Meier TCP from 46 selected studies were collected for SBRT of NSCLC in the literature. The TCP data were separated for Stage T1 and T2 tumors if possible, otherwise collected for combined stages. BED was calculated at isocenters using six radiobiological models. For each model, the independent model parameters were determined from a fit to the TCP data using the least chi-square (χ2) method with either one set of parameters regardless of tumor stages or two sets for T1 and T2 tumors separately. Results The fits to the clinic data yield consistent results of large α/β ratios of about 20 Gy for all models investigated. The regrowth model that accounts for the tumor repopulation and heterogeneity leads to a better fit to the data, compared to other 5 models where the fits were indistinguishable between the models. The models based on the fitting parameters predict that the T2 tumors require about additional 1 Gy physical dose at isocenters per fraction (≤5 fractions) to achieve the optimal TCP when compared to the T1 tumors. Conclusion This systematic analysis of a large set of published clinical data using different radiobiological models shows that local TCP for SBRT of early-stage NSCLC has strong dependence on BED with large α/β ratios of about 20 Gy. The six models predict that a BED (calculated with α/β of 20) of 90 Gy is sufficient to achieve TCP ≥ 95%. Among the models considered, the regrowth model leads to a better fit to the clinical data. PMID:27871671

Real Time Hybrid Model Predictive Control for the Current Profile of the Tokamak à Configuration Variable (TCV

Directory of Open Access Journals (Sweden)

Izaskun Garrido

2016-08-01

Full Text Available Plasma stability is one of the obstacles in the path to the successful operation of fusion devices. Numerical control-oriented codes as it is the case of the widely accepted RZIp may be used within Tokamak simulations. The novelty of this article relies in the hierarchical development of a dynamic control loop. It is based on a current profile Model Predictive Control (MPC algorithm within a multiloop structure, where a MPC is developed at each step so as to improve the Proportional Integral Derivative (PID global scheme. The inner control loop is composed of a PID-based controller that acts over the Multiple Input Multiple Output (MIMO system resulting from the RZIp plasma model of the Tokamak à Configuration Variable (TCV. The coefficients of this PID controller are initially tuned using an eigenmode reduction over the passive structure model. The control action corresponding to the state of interest is then optimized in the outer MPC loop. For the sake of comparison, both the traditionally used PID global controller as well as the multiloop enhanced MPC are applied to the same TCV shot. The results show that the proposed control algorithm presents a superior performance over the conventional PID algorithm in terms of convergence. Furthermore, this enhanced MPC algorithm contributes to extend the discharge length and to overcome the limited power availability restrictions that hinder the performance of advanced tokamaks.

Experimental Study of Flexible Plate Vibration Control by Using Two-Loop Sliding Mode Control Strategy

Science.gov (United States)

Yang, Jingyu; Lin, Jiahui; Liu, Yuejun; Yang, Kang; Zhou, Lanwei; Chen, Guoping

2017-08-01

It is well known that intelligent control theory has been used in many research fields, novel modeling method (DROMM) is used for flexible rectangular active vibration control, and then the validity of new model is confirmed by comparing finite element model with new model. In this paper, taking advantage of the dynamics of flexible rectangular plate, a two-loop sliding mode (TSM) MIMO approach is introduced for designing multiple-input multiple-output continuous vibration control system, which can overcome uncertainties, disturbances or unstable dynamics. An illustrative example is given in order to show the feasibility of the method. Numerical simulations and experiment confirm the effectiveness of the proposed TSM MIMO controller.

A basket two-part model to analyze medical expenditure on interdependent multiple sectors.

Science.gov (United States)

Sugawara, Shinya; Wu, Tianyi; Yamanishi, Kenji

2018-05-01

This study proposes a novel statistical methodology to analyze expenditure on multiple medical sectors using consumer data. Conventionally, medical expenditure has been analyzed by two-part models, which separately consider purchase decision and amount of expenditure. We extend the traditional two-part models by adding the step of basket analysis for dimension reduction. This new step enables us to analyze complicated interdependence between multiple sectors without an identification problem. As an empirical application for the proposed method, we analyze data of 13 medical sectors from the Medical Expenditure Panel Survey. In comparison with the results of previous studies that analyzed the multiple sector independently, our method provides more detailed implications of the impacts of individual socioeconomic status on the composition of joint purchases from multiple medical sectors; our method has a better prediction performance.

A Telerehabilitation Program Improves Postural Control in Multiple Sclerosis Patients: A Spanish Preliminary Study

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Rosa Ortiz-Gutiérrez

2013-10-01

Full Text Available Postural control disorders are among the most frequent motor disorder symptoms associated with multiple sclerosis. This study aims to demonstrate the potential improvements in postural control among patients with multiple sclerosis who complete a telerehabilitation program that represents a feasible alternative to physical therapy for situations in which conventional treatment is not available. Fifty patients were recruited. Control group (n = 25 received physiotherapy treatment twice a week (40 min per session. Experimental group (n = 25 received monitored telerehabilitation treatment via videoconference using the Xbox 360® and Kinect console. Experimental group attended 40 sessions, four sessions per week (20 min per session.The treatment schedule lasted 10 weeks for both groups. A computerized dynamic posturography (Sensory Organization Test was used to evaluate all patients at baseline and at the end of the treatment protocol. Results showed an improvement over general balance in both groups. Visual preference and the contribution of vestibular information yielded significant differences in the experimental group. Our results demonstrated that a telerehabilitation program based on a virtual reality system allows one to optimize the sensory information processing and integration systems necessary to maintain the balance and postural control of people with multiple sclerosis. We suggest that our virtual reality program enables anticipatory PC and response mechanisms and might serve as a successful therapeutic alternative in situations in which conventional therapy is not readily available.

A Telerehabilitation Program Improves Postural Control in Multiple Sclerosis Patients: A Spanish Preliminary Study

Science.gov (United States)

Ortiz-Gutiérrez, Rosa; Cano-de-la-Cuerda, Roberto; Galán-del-Río, Fernando; Alguacil-Diego, Isabel María; Palacios-Ceña, Domingo; Miangolarra-Page, Juan Carlos

2013-01-01

Postural control disorders are among the most frequent motor disorder symptoms associated with multiple sclerosis. This study aims to demonstrate the potential improvements in postural control among patients with multiple sclerosis who complete a telerehabilitation program that represents a feasible alternative to physical therapy for situations in which conventional treatment is not available. Fifty patients were recruited. Control group (n = 25) received physiotherapy treatment twice a week (40 min per session). Experimental group (n = 25) received monitored telerehabilitation treatment via videoconference using the Xbox 360® and Kinect console. Experimental group attended 40 sessions, four sessions per week (20 min per session).The treatment schedule lasted 10 weeks for both groups. A computerized dynamic posturography (Sensory Organization Test) was used to evaluate all patients at baseline and at the end of the treatment protocol. Results showed an improvement over general balance in both groups. Visual preference and the contribution of vestibular information yielded significant differences in the experimental group. Our results demonstrated that a telerehabilitation program based on a virtual reality system allows one to optimize the sensory information processing and integration systems necessary to maintain the balance and postural control of people with multiple sclerosis. We suggest that our virtual reality program enables anticipatory PC and response mechanisms and might serve as a successful therapeutic alternative in situations in which conventional therapy is not readily available. PMID:24185843

MMOSS-I: a CANDU multiple-channel thermosyphoning flow stability model

Energy Technology Data Exchange (ETDEWEB)

Gulshani, P [Atomic Energy of Canada Ltd., Mississauga, ON (Canada); Huynh, H [Hydro-Quebec, Montreal, PQ (Canada)

1996-12-31

This paper presents a multiple-channel flow stability model, dubbed MMOSS, developed to predict the conditions for the onset of flow oscillations in a CANDU-type multiple-channel heat transport system under thermosyphoning conditions. The model generalizes that developed previously to account for the effects of any channel flow reversal. Two-phase thermosyphoning conditions are predicted by thermalhydraulic codes for some postulated accident scenarios in CANDU. Two-phase thermosyphoning experiments in the multiple-channel RD-14M facility have indicated that pass-to-pass out-of-phase oscillations in the loop conditions caused the flow in some of the heated channels to undergo sustained reversal in direction. This channel flow reversal had significant effects on the channel and loop conditions. It is, therefore, important to understand the nature of the oscillations and be able to predict the conditions for the onset of the oscillations or for stable flow in RD-14M and the reactor. For stable flow conditions, oscillation-induced channel flow reversal is not expected. MMOSS was developed for a figure-of-eight system with any number of channels. The system characteristic equation was derived from a linearization of the conservation equations. In this paper, the MMOSS characteristic equation is solved for a system of N identical channel assemblies. The resulting model is called MMOSS-I. This simplification provides valuable physical insight and reasonably accurate results. MMOSS-I and a previously-developed steady-state model THERMOSYPHON are used to predict thermosyphoning flow stability maps for RD-14M and the Gentilly 2 reactor. (author). 11 refs., 7 figs.

Model predictive control-based scheduler for repetitive discrete event systems with capacity constraints

Directory of Open Access Journals (Sweden)

Hiroyuki Goto

2013-07-01

Full Text Available A model predictive control-based scheduler for a class of discrete event systems is designed and developed. We focus on repetitive, multiple-input, multiple-output, and directed acyclic graph structured systems on which capacity constraints can be imposed. The target system’s behaviour is described by linear equations in max-plus algebra, referred to as state-space representation. Assuming that the system’s performance can be improved by paying additional cost, we adjust the system parameters and determine control inputs for which the reference output signals can be observed. The main contribution of this research is twofold, 1: For systems with capacity constraints, we derived an output prediction equation as functions of adjustable variables in a recursive form, 2: Regarding the construct for the system’s representation, we improved the structure to accomplish general operations which are essential for adjusting the system parameters. The result of numerical simulation in a later section demonstrates the effectiveness of the developed controller.

Multiple levels of epigenetic control for bone biology and pathology.

Science.gov (United States)

Montecino, Martin; Stein, Gary; Stein, Janet; Zaidi, Kaleem; Aguilar, Rodrigo

2015-12-01

Multiple dimensions of epigenetic control contribute to regulation of gene expression that governs bone biology and pathology. Once confined to DNA methylation and a limited number of post-translational modifications of histone proteins, the definition of epigenetic mechanisms is expanding to include contributions of non-coding RNAs and mitotic bookmarking, a mechanism for retaining phenotype identity during cell proliferation. Together these different levels of epigenetic control of physiological processes and their perturbations that are associated with compromised gene expression during the onset and progression of disease, have contributed to an unprecedented understanding of the activities (operation) of the genomic landscape. Here, we address general concepts that explain the contribution of epigenetic control to the dynamic regulation of gene expression during eukaryotic transcription. This article is part of a Special Issue entitled Epigenetics and Bone. Copyright © 2015 Elsevier Inc. All rights reserved.

Dynamics of underactuated multibody systems modeling, control and optimal design

CERN Document Server

Seifried, Robert

2014-01-01

Underactuated multibody systems are intriguing mechatronic systems, as they possess fewer control inputs than degrees of freedom. Some examples are modern light-weight flexible robots and articulated manipulators with passive joints. This book investigates such underactuated multibody systems from an integrated perspective. This includes all major steps from the modeling of rigid and flexible multibody systems, through nonlinear control theory, to optimal system design. The underlying theories and techniques from these different fields are presented using a self-contained and unified approach and notation system. Subsequently, the book focuses on applications to large multibody systems with multiple degrees of freedom, which require a combination of symbolical and numerical procedures. Finally, an integrated, optimization-based design procedure is proposed, whereby both structural and control design are considered concurrently. Each chapter is supplemented by illustrated examples.

Model for nucleus-nucleus, hadron-nucleus and hadron-proton multiplicity distributions

International Nuclear Information System (INIS)

Singh, C.P.; Shyam, M.; Tuli, S.K.

1986-07-01

A model relating hadron-proton, hadron-nucleus and nucleus-nucleus multiplicity distributions is proposed and some interesting consequences are derived. The values of the parameters are the same for all the processes and are given by the QCD hypothesis of ''universal'' hadronic multiplicities which are found to be asymptotically independent of target and beam in hadronic and current induced reactions in particle physics. (author)

Multiple attribute decision making model and application to food safety risk evaluation.

Directory of Open Access Journals (Sweden)

Lihua Ma

Full Text Available Decision making for supermarket food purchase decisions are characterized by network relationships. This paper analyzed factors that influence supermarket food selection and proposes a supplier evaluation index system based on the whole process of food production. The author established the intuitive interval value fuzzy set evaluation model based on characteristics of the network relationship among decision makers, and validated for a multiple attribute decision making case study. Thus, the proposed model provides a reliable, accurate method for multiple attribute decision making.

Hierarchical Multiple Markov Chain Model for Unsupervised Texture Segmentation

Czech Academy of Sciences Publication Activity Database

Scarpa, G.; Gaetano, R.; Haindl, Michal; Zerubia, J.

2009-01-01

Roč. 18, č. 8 (2009), s. 1830-1843 ISSN 1057-7149 R&D Projects: GA ČR GA102/08/0593 EU Projects: European Commission(XE) 507752 - MUSCLE Institutional research plan: CEZ:AV0Z10750506 Keywords : Classification * texture analysis * segmentation * hierarchical image models * Markov process Subject RIV: BD - Theory of Information Impact factor: 2.848, year: 2009 http://library.utia.cas.cz/separaty/2009/RO/haindl-hierarchical multiple markov chain model for unsupervised texture segmentation.pdf

The establishment of a multiple sclerosis model for clinical MRI study

International Nuclear Information System (INIS)

Zhang Haiqin; Li Kuncheng; Yu Chunshui; Ma Jia; Qin Wen; Ji Zhijuan; Piao Yueshan

2009-01-01

Objective: To establish a rat model of multiple sclerosis (MS) for clinical MRI study. Methods: The Lewis (LEW) rats were immunized by myelin oligodendrocyte glycoprotein peptide 35-55 (MOG 35-55 ) emulsified with complete Freunds adjuvant/incomplete Freunds adjuvant. Twenty LEW rats were selected. Group A rats were 5, group B rats were 10 and control group rats were 5. MRI and histopathology analysis were observed on group A and control group, and clinical course were observed on group B. The clinical course was observed and the brain and spinal cord of EAE rats were scanned on 3.0 T MR system with quadrature wrist joint coil on the third day of the acute stage of disease. The T 2 /T 1 weighted images and Gadolinium enhanced T 1 weighted images in 3D volume were obtained respectively. The magnetization transfer ratio (MTR) images were calculated with special software in workstation. Rats were sacrificed within 24 h after MRI, and the histopathological changes of central nervous system were observed. Results: Twice immunization of MOG 35-55 was used and a rat model of MS was successfully induced with all the rats. The model had varied clinical symptoms. The lesions of central nervous system at acute stage on group A (5 rats) were depicted on MRI. The lesions located in the brain and the spinal cord with main manifestation of hyperintensity on T 2 weighed images and hypointensity on T 1 weighted images. Some lesions had Gd-DTPA enhancement, and the value of MTR decreased. The infiltration of mononuclear cells around blood vessels and the extensive distribution of lesions of demyelination in brain and spinal cord were verified by histological examination. Conclusions: Twice immunization of MOG 35-55 could produce a rat model which mimics MS. The model is stable with higher incidence, and the antigen is cheap and obtained easily. The intravital monitoring of brain and spinal cord lesions in MOG 35-55 induced rat model is possible on 3.0 T clinical whole- body MR

A Convex Variational Model for Restoring Blurred Images with Multiplicative Noise

DEFF Research Database (Denmark)

Dong, Yiqiu; Tieyong Zeng

2013-01-01

In this paper, a new variational model for restoring blurred images with multiplicative noise is proposed. Based on the statistical property of the noise, a quadratic penalty function technique is utilized in order to obtain a strictly convex model under a mild condition, which guarantees...

The empirical content of models with multiple equilibria in economies with social interactions

OpenAIRE

Alberto Bisin; Andrea Moro; Giorgio Topa

2011-01-01

We study a general class of models with social interactions that might display multiple equilibria. We propose an estimation procedure for these models and evaluate its efficiency and computational feasibility relative to different approaches taken to the curse of dimensionality implied by the multiplicity. Using data on smoking among teenagers, we implement the proposed estimation procedure to understand how group interactions affect health-related choices. We find that interaction effects a...

Modeling and Control for Microgrids

Science.gov (United States)

Steenis, Joel

Traditional approaches to modeling microgrids include the behavior of each inverter operating in a particular network configuration and at a particular operating point. Such models quickly become computationally intensive for large systems. Similarly, traditional approaches to control do not use advanced methodologies and suffer from poor performance and limited operating range. In this document a linear model is derived for an inverter connected to the Thevenin equivalent of a microgrid. This model is then compared to a nonlinear simulation model and analyzed using the open and closed loop systems in both the time and frequency domains. The modeling error is quantified with emphasis on its use for controller design purposes. Control design examples are given using a Glover McFarlane controller, gain scheduled Glover McFarlane controller, and bumpless transfer controller which are compared to the standard droop control approach. These examples serve as a guide to illustrate the use of multi-variable modeling techniques in the context of robust controller design and show that gain scheduled MIMO control techniques can extend the operating range of a microgrid. A hardware implementation is used to compare constant gain droop controllers with Glover McFarlane controllers and shows a clear advantage of the Glover McFarlane approach.

A Spanish pillbox app for elderly patients taking multiple medications: randomized controlled trial.

Science.gov (United States)

Mira, José Joaquín; Navarro, Isabel; Botella, Federico; Borrás, Fernando; Nuño-Solinís, Roberto; Orozco, Domingo; Iglesias-Alonso, Fuencisla; Pérez-Pérez, Pastora; Lorenzo, Susana; Toro, Nuria

2014-04-04

Nonadherence and medication errors are common among patients with complex drug regimens. Apps for smartphones and tablets are effective for improving adherence, but they have not been tested in elderly patients with complex chronic conditions and who typically have less experience with this type of technology. The objective of this study was to design, implement, and evaluate a medication self-management app (called ALICE) for elderly patients taking multiple medications with the intention of improving adherence and safe medication use. A single-blind randomized controlled trial was conducted with a control and an experimental group (N=99) in Spain in 2013. The characteristics of ALICE were specified based on the suggestions of 3 nominal groups with a total of 23 patients and a focus group with 7 professionals. ALICE was designed for Android and iOS to allow for the personalization of prescriptions and medical advice, showing images of each of the medications (the packaging and the medication itself) together with alerts and multiple reminders for each alert. The randomly assigned patients in the control group received oral and written information on the safe use of their medications and the patients in the experimental group used ALICE for 3 months. Pre and post measures included rate of missed doses and medication errors reported by patients, scores from the 4-item Morisky Medication Adherence Scale (MMAS-4), level of independence, self-perceived health status, and biochemical test results. In the experimental group, data were collected on their previous experience with information and communication technologies, their rating of ALICE, and their perception of the level of independence they had achieved. The intergroup intervention effects were calculated by univariate linear models and ANOVA, with the pre to post intervention differences as the dependent variables. Data were obtained from 99 patients (48 and 51 in the control and experimental groups, respectively

A systems modelling framework for the design of integrated process control systems

International Nuclear Information System (INIS)

Lind, M.

1983-12-01

The paper describes a systems modelling methodology, called multilevel flow modelling, or MFM, which aims at describing complex production plants as designs, i.e. as systems having goals, functions and equipment realizing these functions. The modelling concepts are based on thermodynamics and lead to a system description in terms of multiple levels of interrelated mass or energy flow structures. The paper discusses as a basis for the modelling framework the general properties of artifacts or designs, characterizes the complexity of production systems and defines the MFM concepts which allow a consistent specification of goals and functions of these systems as generated in the process design. A modelling example is given and the application of the models for the design of plant control strategies is outlined. (author)

Prediction of pediatric unipolar depression using multiple neuromorphometric measurements: a pattern classification approach.

Science.gov (United States)

Wu, Mon-Ju; Wu, Hanjing Emily; Mwangi, Benson; Sanches, Marsal; Selvaraj, Sudhakar; Zunta-Soares, Giovana B; Soares, Jair C

2015-03-01

Diagnosis of pediatric neuropsychiatric disorders such as unipolar depression is largely based on clinical judgment - without objective biomarkers to guide diagnostic process and subsequent therapeutic interventions. Neuroimaging studies have previously reported average group-level neuroanatomical differences between patients with pediatric unipolar depression and healthy controls. In the present study, we investigated the utility of multiple neuromorphometric indices in distinguishing pediatric unipolar depression patients from healthy controls at an individual subject level. We acquired structural T1-weighted scans from 25 pediatric unipolar depression patients and 26 demographically matched healthy controls. Multiple neuromorphometric indices such as cortical thickness, volume, and cortical folding patterns were obtained. A support vector machine pattern classification model was 'trained' to distinguish individual subjects with pediatric unipolar depression from healthy controls based on multiple neuromorphometric indices and model predictive validity (sensitivity and specificity) calculated. The model correctly identified 40 out of 51 subjects translating to 78.4% accuracy, 76.0% sensitivity and 80.8% specificity, chi-square p-value = 0.000049. Volumetric and cortical folding abnormalities in the right thalamus and right temporal pole respectively were most central in distinguishing individual patients with pediatric unipolar depression from healthy controls. These findings provide evidence that a support vector machine pattern classification model using multiple neuromorphometric indices may qualify as diagnostic marker for pediatric unipolar depression. In addition, our results identified the most relevant neuromorphometric features in distinguishing PUD patients from healthy controls. Copyright © 2015 Elsevier Ltd. All rights reserved.

Flexible Modeling of Survival Data with Covariates Subject to Detection Limits via Multiple Imputation.

Science.gov (United States)

Bernhardt, Paul W; Wang, Huixia Judy; Zhang, Daowen

2014-01-01

Models for survival data generally assume that covariates are fully observed. However, in medical studies it is not uncommon for biomarkers to be censored at known detection limits. A computationally-efficient multiple imputation procedure for modeling survival data with covariates subject to detection limits is proposed. This procedure is developed in the context of an accelerated failure time model with a flexible seminonparametric error distribution. The consistency and asymptotic normality of the multiple imputation estimator are established and a consistent variance estimator is provided. An iterative version of the proposed multiple imputation algorithm that approximates the EM algorithm for maximum likelihood is also suggested. Simulation studies demonstrate that the proposed multiple imputation methods work well while alternative methods lead to estimates that are either biased or more variable. The proposed methods are applied to analyze the dataset from a recently-conducted GenIMS study.

Ozone flux of an urban orange grove: multiple scaled measurements and model comparisons

Science.gov (United States)

Alstad, K. P.; Grulke, N. E.; Jenerette, D. G.; Schilling, S.; Marrett, K.

2009-12-01

There is significant uncertainty about the ozone sink properties of the phytosphere due to a complexity of interactions and feedbacks with biotic and abiotic factors. Improved understanding of the controls on ozone fluxes is critical to estimating and regulating the total ozone budget. Ozone exchanges of an orange orchard within the city of Riverside, CA were examined using a multiple-scaled approach. We access the carbon, water, and energy budgets at the stand- to leaf- level to elucidate the mechanisms controlling the variability in ozone fluxes of this agro-ecosystem. The two initial goals of the study were 1. To consider variations and controls on the ozone fluxes within the canopy; and, 2. To examine different modeling and scaling approaches for totaling the ozone fluxes of this orchard. Current understanding of the total ozone flux between the atmosphere near ground and the phytosphere (F-total) include consideration of a fraction which is absorbed by vegetation through stomatal uptake (F-absorb), and fractional components of deposition on external, non-stomatal, surfaces of the vegetation (F-external) and soil (F-soil). Multiplicative stomatal-conductance models have been commonly used to estimate F-absorb, since this flux cannot be measured directly. We approach F-absorb estimates for this orange orchard using chamber measurement of leaf stomatal-conductance, as well as non-chamber sap-conductance collected on branches of varied aspect and sun/shade conditions within the canopy. We use two approaches to measure the F-total of this stand. Gradient flux profiles were measured using slow-response ozone sensors collecting within and above the canopy (4.6 m), and at the top of the tower (8.5 m). In addition, an eddy-covariance system fitted with a high-frequency chemiluminescence ozone system will be deployed (8.5 m). Preliminary ozone gradient flux profiles demonstrate a substantial ozone sink strength of this orchard, with diurnal concentration differentials

Economic Optimization of Spray Dryer Operation using Nonlinear Model Predictive Control with State Estimation

DEFF Research Database (Denmark)

Petersen, Lars Norbert; Jørgensen, John Bagterp; Rawlings, James B.

2015-01-01

In this paper, we develop an economically optimizing Nonlinear Model Predictive Controller (E-NMPC) for a complete spray drying plant with multiple stages. In the E-NMPC the initial state is estimated by an extended Kalman Filter (EKF) with noise covariances estimated by an autocovariance least...... squares method (ALS). We present a model for the spray drying plant and use this model for simulation as well as for prediction in the E-NMPC. The open-loop optimal control problem in the E-NMPC is solved using the single-shooting method combined with a quasi-Newton Sequential Quadratic programming (SQP......) algorithm and the adjoint method for computation of gradients. We evaluate the economic performance when unmeasured disturbances are present. By simulation, we demonstrate that the E-NMPC improves the profit of spray drying by 17% compared to conventional PI control....

Improving the Pattern Reproducibility of Multiple-Point-Based Prior Models Using Frequency Matching

DEFF Research Database (Denmark)

Cordua, Knud Skou; Hansen, Thomas Mejer; Mosegaard, Klaus

2014-01-01

Some multiple-point-based sampling algorithms, such as the snesim algorithm, rely on sequential simulation. The conditional probability distributions that are used for the simulation are based on statistics of multiple-point data events obtained from a training image. During the simulation, data...... events with zero probability in the training image statistics may occur. This is handled by pruning the set of conditioning data until an event with non-zero probability is found. The resulting probability distribution sampled by such algorithms is a pruned mixture model. The pruning strategy leads...... to a probability distribution that lacks some of the information provided by the multiple-point statistics from the training image, which reduces the reproducibility of the training image patterns in the outcome realizations. When pruned mixture models are used as prior models for inverse problems, local re...

Theoretical Models of Protostellar Binary and Multiple Systems with AMR Simulations

Science.gov (United States)

Matsumoto, Tomoaki; Tokuda, Kazuki; Onishi, Toshikazu; Inutsuka, Shu-ichiro; Saigo, Kazuya; Takakuwa, Shigehisa

2017-05-01

We present theoretical models for protostellar binary and multiple systems based on the high-resolution numerical simulation with an adaptive mesh refinement (AMR) code, SFUMATO. The recent ALMA observations have revealed early phases of the binary and multiple star formation with high spatial resolutions. These observations should be compared with theoretical models with high spatial resolutions. We present two theoretical models for (1) a high density molecular cloud core, MC27/L1521F, and (2) a protobinary system, L1551 NE. For the model for MC27, we performed numerical simulations for gravitational collapse of a turbulent cloud core. The cloud core exhibits fragmentation during the collapse, and dynamical interaction between the fragments produces an arc-like structure, which is one of the prominent structures observed by ALMA. For the model for L1551 NE, we performed numerical simulations of gas accretion onto protobinary. The simulations exhibit asymmetry of a circumbinary disk. Such asymmetry has been also observed by ALMA in the circumbinary disk of L1551 NE.

The BDNF Val66Met polymorphism has opposite effects on memory circuits of multiple sclerosis patients and controls.

Directory of Open Access Journals (Sweden)

Francesco Fera

Full Text Available Episodic memory deficits are frequent symptoms in Multiple Sclerosis and have been associated with dysfunctions of the hippocampus, a key region for learning. However, it is unclear whether genetic factors that influence neural plasticity modulate episodic memory in MS. We thus studied how the Brain Derived Neurotrophic Factor Val(66Met genotype, a common polymorphism influencing the hippocampal function in healthy controls, impacted on brain networks underlying episodic memory in patients with Multiple Sclerosis. Functional magnetic resonance imaging was used to assess how the Brain Derived Neurotrophic Factor Val(66Met polymorphism modulated brain regional activity and functional connectivity in 26 cognitively unimpaired Multiple Sclerosis patients and 25 age- and education-matched healthy controls while performing an episodic memory task that included encoding and retrieving visual scenes. We found a highly significant group by genotype interaction in the left posterior hippocampus, bilateral parahippocampus, and left posterior cingulate cortex. In particular, Multiple Sclerosis patients homozygous for the Val(66 allele, relative to Met(66 carriers, showed greater brain responses during both encoding and retrieval while the opposite was true for healthy controls. Furthermore, a robust group by genotype by task interaction was detected for the functional connectivity between the left posterior hippocampus and the ipsilateral posterior cingulate cortex. Here, greater hippocampus-posterior cingulate cortex connectivity was observed in Multiple Sclerosis Met(66 carriers relative to Val(66 homozygous during retrieval (but not encoding while, again, the reverse was true for healthy controls. The Val(66Met polymorphism has opposite effects on hippocampal circuitry underlying episodic memory in Multiple Sclerosis patients and healthy controls. Enhancing the knowledge of how genetic factors influence cognitive functions may improve the clinical

Availability analysis of safety grade multiple redundant controller used in advanced nuclear safety systems

International Nuclear Information System (INIS)

Son, Kwang Seop; Kim, Dong Hoon; Park, Gee Yong; Kang, Hyun Gook

2018-01-01

Highlights: •The multiple redundant controller, SPLC is configured as the combination of DMR and TMR architecture. •We construct the Markov model of SPLC using the concept of the system unavailability rate. •To satisfy the availability requirement of safety grade controller, the fault coverage factor (FCF) should be ≥0.8 and the MTTR of each module should be ≤100 h when FCF is 0.9. •The availability of SPLC is better than that of PLC having iTMR architecture however it is poorer than iTMR considering the off-line test and inspection on the assumption that MTTR of each module is ≤200 h. -- Abstract: We analyze the availability of the Safety Programmable Logic Controller (SPLC) having multiple redundant architectures. In the SPLC, input/output and processor module are configured as triple modular redundancy (TMR), and backplane bus, power and communication modules are configured as dual modular redundancy (DMR). The voting logics for redundant architectures are based on the forwarding error detection. It means that the receivers perform the voting logics based on the status information of transmitters. To analyze the availability of SPLC, we construct the Markov model and simplify the model adopting the system unavailability rate. The results show that the fault coverage factor should be ≥0.8 and Mean Time To Repair (MTTR) should be ≤100 h in order to satisfy the requirement that the availability of the safety grade PLC should be ≥0.995. Also we evaluate the availability of SPLC comparing to other PLCs such as simplex, processor DMR (pDMR) and independent TMR (iTMR) PLCs used in the existing nuclear safety systems. The availability of SPLC is higher than those of the simplex, pDMR but is lower than that of iTMR for one month which is the periodic off-line test and inspection. That’s why the number of redundant modules used in PLC is more dominant to increasing the availability than the number of fault masking methods such as voting logics used

Vehicle coordinated transportation dispatching model base on multiple crisis locations

Science.gov (United States)

Tian, Ran; Li, Shanwei; Yang, Guoying

2018-05-01

Many disastrous events are often caused after unconventional emergencies occur, and the requirements of disasters are often different. It is difficult for a single emergency resource center to satisfy such requirements at the same time. Therefore, how to coordinate the emergency resources stored by multiple emergency resource centers to various disaster sites requires the coordinated transportation of emergency vehicles. In this paper, according to the problem of emergency logistics coordination scheduling, based on the related constraints of emergency logistics transportation, an emergency resource scheduling model based on multiple disasters is established.

A P-value model for theoretical power analysis and its applications in multiple testing procedures

Directory of Open Access Journals (Sweden)

Fengqing Zhang

2016-10-01

Full Text Available Abstract Background Power analysis is a critical aspect of the design of experiments to detect an effect of a given size. When multiple hypotheses are tested simultaneously, multiplicity adjustments to p-values should be taken into account in power analysis. There are a limited number of studies on power analysis in multiple testing procedures. For some methods, the theoretical analysis is difficult and extensive numerical simulations are often needed, while other methods oversimplify the information under the alternative hypothesis. To this end, this paper aims to develop a new statistical model for power analysis in multiple testing procedures. Methods We propose a step-function-based p-value model under the alternative hypothesis, which is simple enough to perform power analysis without simulations, but not too simple to lose the information from the alternative hypothesis. The first step is to transform distributions of different test statistics (e.g., t, chi-square or F to distributions of corresponding p-values. We then use a step function to approximate each of the p-value’s distributions by matching the mean and variance. Lastly, the step-function-based p-value model can be used for theoretical power analysis. Results The proposed model is applied to problems in multiple testing procedures. We first show how the most powerful critical constants can be chosen using the step-function-based p-value model. Our model is then applied to the field of multiple testing procedures to explain the assumption of monotonicity of the critical constants. Lastly, we apply our model to a behavioral weight loss and maintenance study to select the optimal critical constants. Conclusions The proposed model is easy to implement and preserves the information from the alternative hypothesis.

Synthesis of Carbon Dots with Multiple Color Emission by Controlled Graphitization and Surface Functionalization.

Science.gov (United States)

Miao, Xiang; Qu, Dan; Yang, Dongxue; Nie, Bing; Zhao, Yikang; Fan, Hongyou; Sun, Zaicheng

2018-01-01

Multiple-color-emissive carbon dots (CDots) have potential applications in various fields such as bioimaging, light-emitting devices, and photocatalysis. The majority of the current CDots to date exhibit excitation-wavelength-dependent emissions with their maximum emission limited at the blue-light region. Here, a synthesis of multiple-color-emission CDots by controlled graphitization and surface function is reported. The CDots are synthesized through controlled thermal pyrolysis of citric acid and urea. By regulating the thermal-pyrolysis temperature and ratio of reactants, the maximum emission of the resulting CDots gradually shifts from blue to red light, covering the entire light spectrum. Specifically, the emission position of the CDots can be tuned from 430 to 630 nm through controlling the extent of graphitization and the amount of surface functional groups, COOH. The relative photoluminescence quantum yields of the CDots with blue, green, and red emission reach up to 52.6%, 35.1%, and 12.9%, respectively. Furthermore, it is demonstrated that the CDots can be uniformly dispersed into epoxy resins and be fabricated as transparent CDots/epoxy composites for multiple-color- and white-light-emitting devices. This research opens a door for developing low-cost CDots as alternative phosphors for light-emitting devices. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Evaluation of genetically inactivated alpha toxin for protection in multiple mouse models of Staphylococcus aureus infection.

Directory of Open Access Journals (Sweden)

Rebecca A Brady

Full Text Available Staphylococcus aureus is a major human pathogen and a leading cause of nosocomial and community-acquired infections. Development of a vaccine against this pathogen is an important goal. While S. aureus protective antigens have been identified in the literature, the majority have only been tested in a single animal model of disease. We wished to evaluate the ability of one S. aureus vaccine antigen to protect in multiple mouse models, thus assessing whether protection in one model translates to protection in other models encompassing the full breadth of infections the pathogen can cause. We chose to focus on genetically inactivated alpha toxin mutant HlaH35L. We evaluated the protection afforded by this antigen in three models of infection using the same vaccine dose, regimen, route of immunization, adjuvant, and challenge strain. When mice were immunized with HlaH35L and challenged via a skin and soft tissue infection model, HlaH35L immunization led to a less severe infection and decreased S. aureus levels at the challenge site when compared to controls. Challenge of HlaH35L-immunized mice using a systemic infection model resulted in a limited, but statistically significant decrease in bacterial colonization as compared to that observed with control mice. In contrast, in a prosthetic implant model of chronic biofilm infection, there was no significant difference in bacterial levels when compared to controls. These results demonstrate that vaccines may confer protection against one form of S. aureus disease without conferring protection against other disease presentations and thus underscore a significant challenge in S. aureus vaccine development.

Evaluation of Hemodynamic Properties of Cerebral Venous Drainage in Patients with Multiple Sclerosis: A Case-Control Study

International Nuclear Information System (INIS)

Jandaghi, Ali Babaei; Amanian, Dayan; Roudbari, Seyed Ali; Kanafi, Alireza Rajabzadeh; Pourghorban, Ramin

2014-01-01

The purpose of this study was to compare patients with multiple sclerosis and healthy control subjects as regards hemodynamics of cerebral venous drainage. Between December 2012 and May 2013, 44 consecutive patients with multiple sclerosis and 44 age- and sex-matched healthy subjects underwent the B-mode, color Doppler, and duplex Doppler evaluations of the internal jugular vein (IJV) and vertebral vein. The following four parameters were investigated: IJV stenosis, reversal of postural control of the cerebral venous outflow pathways, absence of detectable blood flow in the IJVs and/or vertebral veins, and reflux in the IJVs and/or vertebral veins in the sitting or supine position. In the study group, IJV stenosis, postural control reversal of the cerebral venous outflow pathways, and absence of flow in the IJVs and/or vertebral veins were found in 3 (6.8%), 2 (4.5%), and 3 (6.8%) patients, respectively. In the control group, IJV stenosis (P=0.12), postural control reversal of the cerebral venous outflow pathways (P=0.50), and absence of flow (P=0.12) were not detected. Abnormal reflux was found neither in multiple sclerosis patients nor in healthy subjects. No significant difference in the cerebral venous drainage through the IJV or vertebral vein was found between patients with multiple sclerosis and healthy subjects within any of the investigated ultrasonographic parameters

Challenges in LCA modelling of multiple loops for aluminium cans

DEFF Research Database (Denmark)

Niero, Monia; Olsen, Stig Irving

considered the case of closed-loop recycling for aluminium cans, where body and lid are different alloys, and discussed the abovementioned challenge. The Life Cycle Inventory (LCI) modelling of aluminium processes is traditionally based on a pure aluminium flow, therefore neglecting the presence of alloying...... elements. We included the effect of alloying elements on the LCA modelling of aluminium can recycling. First, we performed a mass balance of the main alloying elements (Mn, Fe, Si, Cu) in aluminium can recycling at increasing levels of recycling rate. The analysis distinguished between different aluminium...... packaging scrap sources (i.e. used beverage can and mixed aluminium packaging) to understand the limiting factors for multiple loop aluminium can recycling. Secondly, we performed a comparative LCA of aluminium can production and recycling in multiple loops considering the two aluminium packaging scrap...

A Memory/Immunology-Based Control Approach with Applications to Multiple Spacecraft Formation Flying

Directory of Open Access Journals (Sweden)

Liguo Weng

2013-01-01

Full Text Available This paper addresses the problem of formation control for multiple spacecrafts in Planetary Orbital Environment (POE. Due to the presence of diverse interferences and uncertainties in the outer space, such as the changing spacecraft mass, unavailable space parameters, and varying gravity forces, traditional control methods encounter great difficulties in this area. A new control approach inspired by human memory and immune system is proposed, and this approach is shown to be capable of learning from past control experience and current behavior to improve its performance. It demands much less system dynamic information as compared with traditional controls. Both theoretic analysis and computer simulation verify its effectiveness.

Modeling Social Influence via Combined Centralized and Distributed Planning Control

Science.gov (United States)

Vaccaro, James; Guest, Clark

2010-01-01

Real world events are driven by a mixture of both centralized and distributed control of individual agents based on their situational context and internal make up. For example, some people have partial allegiances to multiple, contradictory authorities, as well as to their own goals and principles. This can create a cognitive dissonance that can be exploited by an appropriately directed psychological influence operation (PSYOP). An Autonomous Dynamic Planning and Execution (ADP&E) approach is proposed for modeling both the unperturbed context as well as its reaction to various PSYOP interventions. As an illustrative example, the unrest surrounding the Iranian elections in the summer of 2009 is described in terms applicable to an ADP&E modeling approach. Aspects of the ADP&E modeling process are discussed to illustrate its application and advantages for this example.

A minimal unified model of disease trajectories captures hallmarks of multiple sclerosis

KAUST Repository

Kannan, Venkateshan

2017-03-29

Multiple Sclerosis (MS) is an autoimmune disease targeting the central nervous system (CNS) causing demyelination and neurodegeneration leading to accumulation of neurological disability. Here we present a minimal, computational model involving the immune system and CNS that generates the principal subtypes of the disease observed in patients. The model captures several key features of MS, especially those that distinguish the chronic progressive phase from that of the relapse-remitting. In addition, a rare subtype of the disease, progressive relapsing MS naturally emerges from the model. The model posits the existence of two key thresholds, one in the immune system and the other in the CNS, that separate dynamically distinct behavior of the model. Exploring the two-dimensional space of these thresholds, we obtain multiple phases of disease evolution and these shows greater variation than the clinical classification of MS, thus capturing the heterogeneity that is manifested in patients.

Modelling multiple cycles of static and dynamic recrystallisation using a fully implicit isotropic material model based on dislocation density

Science.gov (United States)

Jansen van Rensburg, Gerhardus J.; Kok, Schalk; Wilke, Daniel N.

2018-03-01

This paper presents the development and numerical implementation of a state variable based thermomechanical material model, intended for use within a fully implicit finite element formulation. Plastic hardening, thermal recovery and multiple cycles of recrystallisation can be tracked for single peak as well as multiple peak recrystallisation response. The numerical implementation of the state variable model extends on a J2 isotropic hypo-elastoplastic modelling framework. The complete numerical implementation is presented as an Abaqus UMAT and linked subroutines. Implementation is discussed with detailed explanation of the derivation and use of various sensitivities, internal state variable management and multiple recrystallisation cycle contributions. A flow chart explaining the proposed numerical implementation is provided as well as verification on the convergence of the material subroutine. The material model is characterised using two high temperature data sets for cobalt and copper. The results of finite element analyses using the material parameter values characterised on the copper data set are also presented.

PWR hybrid computer model for assessing the safety implications of control systems

International Nuclear Information System (INIS)

Smith, O.L.; Booth, R.S.; Clapp, N.E.; DiFilippo, F.C.; Renier, J.P.; Sozer, A.

1985-01-01

The ORNL study of safety-related aspects of control systems consists of two interrelated tasks, (1) a failure mode and effects analysis that, in part, identifies single and multiple component failures that may lead to significant plant upsets, and (2) a hybrid computer model that uses these failures as initial conditions and traces the dynamic impact on the control system and remainder of the plant. The second task is reported here. The initial step in model development was to define a suitable interface between the FMEA and computer simulation tasks. This involved identifying primary plant components that must be simulated in dynamic detail and secondary components that can be treated adequately by the FMEA alone. The FMEA in general explores broader spectra of initiating events that may collapse into a reduced number of computer runs. A portion of the FMEA includes consideration of power supply failures. Consequences of the transients may feedback on the initiating causes, and there may be an interactive relationship between the FMEA and the computer simulation. Since the thrust of this program is to investigate control system behavior, the controls are modeled in detail to accurately reproduce characteristic response under normal and off-normal transients. The balance of the model, including neutronics, thermohydraulics and component submodels, is developed in sufficient detail to provide a suitable support for the control system

Coordinated Formation Control of Multiple Autonomous Underwater Vehicles for Pipeline Inspection

Directory of Open Access Journals (Sweden)

Xianbo Xiang

2010-02-01

Full Text Available This paper addresses the control problem of inspecting underwater pipeline on the seabed, with coordinated multiple autonomous underwater vehicles in a formation. Based on the leader-follower strategy, the dedicated nonlinear path following controller is rigorously built on Lyapunov-based design, driving a fleet of vehicles onto assigned parallel paths elevated and offset from the underwater pipeline, while keeping a triangle formation to capture complete 3D images for inspection. Due to the spatial-temporal decoupling characteristics of individual path following controller, the velocities of the followers can be adapted in the coordinated control level, only relying on the information of generalized along-path length from the leader, in order to build the desired formation. Thus, the communication variable broadcast from the leader is kept to a minimum, which is feasible under the severely constraints of acoustic communication bandwidth. Simulation results illustrate the efficiency of coordinated formation controller proposed for underwater pipeline inspection.

A Model of Distraction using new Architectural Mechanisms to Manage Multiple Goals

NARCIS (Netherlands)

Taatgen, Niels; Katidioti, Ioanna; Borst, Jelmer; van Vugt, Marieke; Taatgen, Niels; van Vugt, Marieke; Borst, Jelmer; Mehlhorn, Katja

2015-01-01

Cognitive models assume a one-to-one correspondence between task and goals. We argue that modeling a task by combining multiple goals has several advantages: a task can be constructed from components that are reused from other tasks, and it enables modeling thought processes that compete with or

A distributed Synchronous reservation multiple access control protocol for mobile Ad hoc networks

Institute of Scientific and Technical Information of China (English)

ZHANG Yanling; SUN Xianpu; LI Jiandong

2007-01-01

This study proposes a new multiple access control protocol named distributed synchronous reservation multiple access control protocol.in which the hidden and exposed terminal problems are solved,and the quality of service(QoS)requirements for real-time traffic are guaranteed.The protocol is founded on time division multiplex address and a different type of traffic is assigned to difierent priority,according to which a node should compete for and reserve the free slots in a different method.Moreover,there is a reservation acknowledgement process before data transmit in each reserved slot,so that the intruded terminal problem is solved.The throughput and average packets drop probability of this protocol are analyzed and simulated in a fully connected network.the results of which indicate that this protocol is efficient enough to support the real-time traffic.and it is more suitable to MANETs.

The Impact of Five VDR Polymorphisms on Multiple Sclerosis Risk and Progression: a Case-Control and Genotype-Phenotype Study.

Science.gov (United States)

Křenek, Pavel; Benešová, Yvonne; Bienertová-Vašků, Julie; Vašků, Anna

2018-04-01

Vitamin D receptor polymorphisms have been the target of many studies focusing on multiple sclerosis. However, previously reported results have been inconclusive. The objective of this study was to investigate the association between five vitamin D receptor polymorphisms (EcoRV, FokI, ApaI, TaqI, and BsmI) and multiple sclerosis susceptibility and its course. The study was carried out as a case-control and genotype-phenotype study, consisted of 296 Czech multiple sclerosis patients and 135 healthy controls. Genotyping was carried out using polymerase chain reaction and restriction analysis. In multiple sclerosis men, allele and/or genotype distributions differed in EcoRV, TaqI, BsmI, and ApaI polymorphisms as compared to controls (EcoRV, p a = 0.02; Taq, p g = 0.02, p a = 0.02; BsmI, p g = 0.02, p a = 0.04; ApaI, p g = 0.008, p a = 0.005). In multiple sclerosis women, differences in the frequency of alleles and genotypes were found to be significant in ApaI (controls vs multiple sclerosis women: p g = 0.01, p a = 0.05). Conclusive results were observed between multiple sclerosis women in the case of EcoRV [differences in Expanded Disability Status Scale (p = 0.05); CT genotype was found to increase the risk of primary progressive multiple sclerosis 5.5 times (CT vs CC+TT p corr = 0.01, sensitivity 0.833, specificity 0.525, power test 0.823)] and FokI [borderline difference in Multiple Sclerosis Severity Score (p = 0.05)]. Our results indicate that the distribution of investigated vitamin D receptor polymorphisms is a risk factor for multiple sclerosis susceptibility and progression in the Czech population. The association between disease risk and polymorphisms was found to be stronger in men. The association of disease progression with polymorphisms was observed only in women.

Fuzzy Control Teaching Models

Directory of Open Access Journals (Sweden)

Klaus-Dietrich Kramer

2016-05-01

Full Text Available Many degree courses at technical universities include the subject of control systems engineering. As an addition to conventional approaches Fuzzy Control can be used to easily find control solutions for systems, even if they include nonlinearities. To support further educational training, models which represent a technical system to be controlled are required. These models have to represent the system in a transparent and easy cognizable manner. Furthermore, a programming tool is required that supports an easy Fuzzy Control development process, including the option to verify the results and tune the system behavior. In order to support the development process a graphical user interface is needed to display the fuzzy terms under real time conditions, especially with a debug system and trace functionality. The experiences with such a programming tool, the Fuzzy Control Design Tool (FHFCE Tool, and four fuzzy teaching models will be presented in this paper. The methodical and didactical objective in the utilization of these teaching models is to develop solution strategies using Computational Intelligence (CI applications for Fuzzy Controllers in order to analyze different algorithms of inference or defuzzyfication and to verify and tune those systems efficiently.

A Limb Action Detector Enabling People with Multiple Disabilities to Control Environmental Stimulation through Limb Action with a Nintendo Wii Remote Controller

Science.gov (United States)

Shih, Ching-Hsiang; Chang, Man-Ling; Shih, Ching-Tien

2010-01-01

This study assessed whether two persons with multiple disabilities would be able to control environmental stimulation using limb action with a Nintendo Wii Remote Controller and a newly developed limb action detection program (LADP, i.e., a new software program that turns a Wii Remote Controller into a precise limb action detector). This study was…

Experiences in simulating and testing coordinated voltage control provided by multiple wind power plants

Energy Technology Data Exchange (ETDEWEB)

Arlaban, T.; Alonso, O.; Ortiz, D. [Acciona Windpower S.A. (Spain); Peiro, J.; Rivas, R. [Red Electrica de Espana SAU (Spain); Quinonez-Varela, G.; Lorenzo, P. [Acciona Energia S.A. (Spain)

2011-07-01

This document presents some field tests performed in a transmission system node in order to check the adequacy of voltage control performance by multiple wind power plants, with an overall capacity of 395 MW. It briefly explains the Spanish TSO motivation towards new voltage control requirements and the necessity of performing such tests in order to set the most convenient voltage control parameters and to verify the stable operation. It presents how different the voltage control capability between modern wind turbines (DFIG) and older ones (SCIG) specifically retrofitted for voltage control is. (orig.)

Distributed Containment Control for Multiple Unknown Second-Order Nonlinear Systems With Application to Networked Lagrangian Systems.

Science.gov (United States)

Mei, Jie; Ren, Wei; Li, Bing; Ma, Guangfu

2015-09-01

In this paper, we consider the distributed containment control problem for multiagent systems with unknown nonlinear dynamics. More specifically, we focus on multiple second-order nonlinear systems and networked Lagrangian systems. We first study the distributed containment control problem for multiple second-order nonlinear systems with multiple dynamic leaders in the presence of unknown nonlinearities and external disturbances under a general directed graph that characterizes the interaction among the leaders and the followers. A distributed adaptive control algorithm with an adaptive gain design based on the approximation capability of neural networks is proposed. We present a necessary and sufficient condition on the directed graph such that the containment error can be reduced as small as desired. As a byproduct, the leaderless consensus problem is solved with asymptotical convergence. Because relative velocity measurements between neighbors are generally more difficult to obtain than relative position measurements, we then propose a distributed containment control algorithm without using neighbors' velocity information. A two-step Lyapunov-based method is used to study the convergence of the closed-loop system. Next, we apply the ideas to deal with the containment control problem for networked unknown Lagrangian systems under a general directed graph. All the proposed algorithms are distributed and can be implemented using only local measurements in the absence of communication. Finally, simulation examples are provided to show the effectiveness of the proposed control algorithms.

Model predictive control for a thermostatic controlled system

DEFF Research Database (Denmark)

Shafiei, Seyed Ehsan; Rasmussen, Henrik; Stoustrup, Jakob

2013-01-01

This paper proposes a model predictive control scheme to provide temperature set-points to thermostatic controlled cooling units in refrigeration systems. The control problem is formulated as a convex programming problem to minimize the overall operating cost of the system. The foodstuff temperat......This paper proposes a model predictive control scheme to provide temperature set-points to thermostatic controlled cooling units in refrigeration systems. The control problem is formulated as a convex programming problem to minimize the overall operating cost of the system. The foodstuff...

Ultra-precise tracking control of piezoelectric actuators via a fuzzy hysteresis model.

Science.gov (United States)

Li, Pengzhi; Yan, Feng; Ge, Chuan; Zhang, Mingchao

2012-08-01

In this paper, a novel Takagi-Sugeno (T-S) fuzzy system based model is proposed for hysteresis in piezoelectric actuators. The antecedent and consequent structures of the fuzzy hysteresis model (FHM) can be, respectively, identified on-line through uniform partition approach and recursive least squares (RLS) algorithm. With respect to controller design, the inverse of FHM is used to develop a feedforward controller to cancel out the hysteresis effect. Then a hybrid controller is designed for high-performance tracking. It combines the feedforward controller with a proportional integral differential (PID) controller favourable for stabilization and disturbance compensation. To achieve nanometer-scale tracking precision, the enhanced adaptive hybrid controller is further developed. It uses real-time input and output data to update FHM, thus changing the feedforward controller to suit the on-site hysteresis character of the piezoelectric actuator. Finally, as to 3 cases of 50 Hz sinusoidal, multiple frequency sinusoidal and 50 Hz triangular trajectories tracking, experimental results demonstrate the efficiency of the proposed controllers. Especially, being only 0.35% of the maximum desired displacement, the maximum error of 50 Hz sinusoidal tracking is greatly reduced to 5.8 nm, which clearly shows the ultra-precise nanometer-scale tracking performance of the developed adaptive hybrid controller.

Relationships between trunk performance, gait and postural control in persons with multiple sclerosis.

Science.gov (United States)

Freund, Jane E; Stetts, Deborah M; Vallabhajosula, Srikant

2016-06-30

Multiple sclerosis (MS) is a chronic progressive disease of the central nervous system. Compared to healthy individuals, persons with multiple sclerosis (PwMS) have increased postural sway in quiet stance, decreased gait speed and increased fall incidence. Trunk performance has been implicated in postural control, gait dysfunction, and fall prevention in older adults. However, the relationship of trunk performance to postural control and gait has not been adequately studied in PwMS. To compare trunk muscle structure and performance in PwMS to healthy age and gendered-matched controls (HC); to determine the effects of isometric trunk endurance testing on postural control in both populations; and to determine the relationship of trunk performance with postural control, gait and step activity in PwMS. Fifteen PwMS and HC completed ultrasound imaging of trunk muscles, 10 m walk test, isometric trunk endurance tests, and postural sway test. Participants wore a step activity monitor for 7 days. PwMS had worse isometric trunk endurance compared to HC. PwMS trunk flexion endurance negatively correlated to several postural control measures and positively correlated to gait speed and step activity. Clinicians should consider evaluation and interventions directed at impaired trunk endurance in PwMS.

Mining gene expression data of multiple sclerosis.

Directory of Open Access Journals (Sweden)

Pi Guo

Full Text Available Microarray produces a large amount of gene expression data, containing various biological implications. The challenge is to detect a panel of discriminative genes associated with disease. This study proposed a robust classification model for gene selection using gene expression data, and performed an analysis to identify disease-related genes using multiple sclerosis as an example.Gene expression profiles based on the transcriptome of peripheral blood mononuclear cells from a total of 44 samples from 26 multiple sclerosis patients and 18 individuals with other neurological diseases (control were analyzed. Feature selection algorithms including Support Vector Machine based on Recursive Feature Elimination, Receiver Operating Characteristic Curve, and Boruta algorithms were jointly performed to select candidate genes associating with multiple sclerosis. Multiple classification models categorized samples into two different groups based on the identified genes. Models' performance was evaluated using cross-validation methods, and an optimal classifier for gene selection was determined.An overlapping feature set was identified consisting of 8 genes that were differentially expressed between the two phenotype groups. The genes were significantly associated with the pathways of apoptosis and cytokine-cytokine receptor interaction. TNFSF10 was significantly associated with multiple sclerosis. A Support Vector Machine model was established based on the featured genes and gave a practical accuracy of ∼86%. This binary classification model also outperformed the other models in terms of Sensitivity, Specificity and F1 score.The combined analytical framework integrating feature ranking algorithms and Support Vector Machine model could be used for selecting genes for other diseases.

Active control: Wind turbine model

DEFF Research Database (Denmark)

Bindner, H.

1999-01-01

This report is a part of the reporting of the work done in the project 'Active Control of Wind Turbines'. This project aim is to develop a simulation model for design of control systems for turbines with pitch control and to use that model to designcontrollers. This report describes the model...... validation as well as parameter estimation. The model includes a simple model of the structure of the turbine including tower and flapwise blade bending,a detailed model of the gear box and induction generator, a linearized aerodynamic model including modelling of induction lag and actuator and sensor models...

A dynamical model of car-following with the consideration of the multiple information of preceding cars

International Nuclear Information System (INIS)

Peng, G.H.; Sun, D.H.

2010-01-01

An improved multiple car-following (MCF) model is proposed, based on the full velocity difference (FVD) model, but taking into consideration multiple information inputs from preceding vehicles. The linear stability condition of the model is obtained by using the linear stability theory. Through nonlinear analysis, the modified Korteweg-de Vries (mKdV) equation is derived to describe the traffic behavior near the critical point. Numerical simulation shows that the proposed model is theoretically an improvement over others, while retaining many strong points in the previous ones by adjusting the information of the multiple leading vehicles.

Optimal planning approaches with multiple impulses for rendezvous based on hybrid genetic algorithm and control method

Directory of Open Access Journals (Sweden)

JingRui Zhang

2015-03-01

Full Text Available In this article, we focus on safe and effective completion of a rendezvous and docking task by looking at planning approaches and control with fuel-optimal rendezvous for a target spacecraft running on a near-circular reference orbit. A variety of existent practical path constraints are considered, including the constraints of field of view, impulses, and passive safety. A rendezvous approach is calculated by using a hybrid genetic algorithm with those constraints. Furthermore, a control method of trajectory tracking is adopted to overcome the external disturbances. Based on Clohessy–Wiltshire equations, we first construct the mathematical model of optimal planning approaches of multiple impulses with path constraints. Second, we introduce the principle of hybrid genetic algorithm with both stronger global searching ability and local searching ability. We additionally explain the application of this algorithm in the problem of trajectory planning. Then, we give three-impulse simulation examples to acquire an optimal rendezvous trajectory with the path constraints presented in this article. The effectiveness and applicability of the tracking control method are verified with the optimal trajectory above as control objective through the numerical simulation.

Stabilization of multiple rib fractures in a canine model.

Science.gov (United States)

Huang, Ke-Nan; Xu, Zhi-Fei; Sun, Ju-Xian; Ding, Xin-Yu; Wu, Bin; Li, Wei; Qin, Xiong; Tang, Hua

2014-12-01

Operative stabilization is frequently used in the clinical treatment of multiple rib fractures (MRF); however, no ideal material exists for use in this fixation. This study investigates a newly developed biodegradable plate system for the stabilization of MRF. Silk fiber-reinforced polycaprolactone (SF/PCL) plates were developed for rib fracture stabilization and studied using a canine flail chest model. Adult mongrel dogs were divided into three groups: one group received the SF/PCL plates, one group received standard clinical steel plates, and the final group did not undergo operative fracture stabilization (n = 6 for each group). Radiographic, mechanical, and histologic examination was performed to evaluate the effectiveness of the biodegradable material for the stabilization of the rib fractures. No nonunion and no infections were found when using SF-PCL plates. The fracture sites collapsed in the untreated control group, leading to obvious chest wall deformity not encountered in the two groups that underwent operative stabilization. Our experimental study shows that the SF/PCL plate has the biocompatibility and mechanical strength suitable for fixation of MRF and is potentially ideal for the treatment of these injuries. Copyright © 2014 Elsevier Inc. All rights reserved.

Multiple sequential failure model: A probabilistic approach to quantifying human error dependency

International Nuclear Information System (INIS)

Samanta

1985-01-01

This paper rpesents a probabilistic approach to quantifying human error dependency when multiple tasks are performed. Dependent human failures are dominant contributors to risks from nuclear power plants. An overview of the Multiple Sequential Failure (MSF) model developed and its use in probabilistic risk assessments (PRAs) depending on the available data are discussed. A small-scale psychological experiment was conducted on the nature of human dependency and the interpretation of the experimental data by the MSF model show remarkable accommodation of the dependent failure data. The model, which provides an unique method for quantification of dependent failures in human reliability analysis, can be used in conjunction with any of the general methods currently used for performing the human reliability aspect in PRAs

Hierarchical Robot Control System and Method for Controlling Select Degrees of Freedom of an Object Using Multiple Manipulators

Science.gov (United States)

Abdallah, Muhammad E. (Inventor); Platt, Robert (Inventor); Wampler, II, Charles W. (Inventor)

2013-01-01

A robotic system includes a robot having manipulators for grasping an object using one of a plurality of grasp types during a primary task, and a controller. The controller controls the manipulators during the primary task using a multiple-task control hierarchy, and automatically parameterizes the internal forces of the system for each grasp type in response to an input signal. The primary task is defined at an object-level of control, e.g., using a closed-chain transformation, such that only select degrees of freedom are commanded for the object. A control system for the robotic system has a host machine and algorithm for controlling the manipulators using the above hierarchy. A method for controlling the system includes receiving and processing the input signal using the host machine, including defining the primary task at the object-level of control, e.g., using a closed-chain definition, and parameterizing the internal forces for each of grasp type.

Multi-sources model and control algorithm of an energy management system for light electric vehicles

International Nuclear Information System (INIS)

Hannan, M.A.; Azidin, F.A.; Mohamed, A.

2012-01-01

Highlights: ► An energy management system (EMS) is developed for a scooter under normal and heavy power load conditions. ► The battery, FC, SC, EMS, DC machine and vehicle dynamics are modeled and designed for the system. ► State-based logic control algorithms provide an efficient and feasible multi-source EMS for light electric vehicles. ► Vehicle’s speed and power are closely matched with the ECE-47 driving cycle under normal and heavy load conditions. ► Sources of energy changeover occurred at 50% of the battery state of charge level in heavy load conditions. - Abstract: This paper presents the multi-sources energy models and ruled based feedback control algorithm of an energy management system (EMS) for light electric vehicle (LEV), i.e., scooters. The multiple sources of energy, such as a battery, fuel cell (FC) and super-capacitor (SC), EMS and power controller, DC machine and vehicle dynamics are designed and modeled using MATLAB/SIMULINK. The developed control strategies continuously support the EMS of the multiple sources of energy for a scooter under normal and heavy power load conditions. The performance of the proposed system is analyzed and compared with that of the ECE-47 test drive cycle in terms of vehicle speed and load power. The results show that the designed vehicle’s speed and load power closely match those of the ECE-47 test driving cycle under normal and heavy load conditions. This study’s results suggest that the proposed control algorithm provides an efficient and feasible EMS for LEV.

Double-multiple streamtube model for studying vertical-axis wind turbines

Science.gov (United States)

Paraschivoiu, Ion

1988-08-01

This work describes the present state-of-the-art in double-multiple streamtube method for modeling the Darrieus-type vertical-axis wind turbine (VAWT). Comparisons of the analytical results with the other predictions and available experimental data show a good agreement. This method, which incorporates dynamic-stall and secondary effects, can be used for generating a suitable aerodynamic-load model for structural design analysis of the Darrieus rotor.

Comparison of Masking Level Difference in Patients with Multiple Sclerosis and Healthy Control Group

Directory of Open Access Journals (Sweden)

Soghrat Faghihzadeh

2012-03-01

Full Text Available Background and Aim: Multiple sclerosis (MS is a neurological disorder that involves central nervous system. Studies have showed that multiple sclerosis affects behavioral central auditory tests, such as masking release or masking level difference (MLD. The purpose of this study is to compare the masking level difference between multiple sclerosis patients and normal subjects.Methods: This cross sectional and non-interventional study was conducted on 32 multiple sclerosis patients aged between 20-50 years and 32 controls matched for age and gender in Faculty of Rehabilitation, Tehran University of Medical Sciences. masking level difference test was performed on each subject.Results: The mean masking level difference in the two groups was significantly different (p<0.01 however, gender did not prove to play a role in this difference.Conclusion: As part of the multiple sclerosis diagnosis panel, masking level difference test is an efficient modality for evaluation of hearing impairment and monitoring of rehabilitation progress.

Multiple Surrogate Modeling for Wire-Wrapped Fuel Assembly Optimization

International Nuclear Information System (INIS)

Raza, Wasim; Kim, Kwang-Yong

2007-01-01

In this work, shape optimization of seven pin wire wrapped fuel assembly has been carried out in conjunction with RANS analysis in order to evaluate the performances of surrogate models. Previously, Ahmad and Kim performed the flow and heat transfer analysis based on the three-dimensional RANS analysis. But numerical optimization has not been applied to the design of wire-wrapped fuel assembly, yet. Surrogate models are being widely used in multidisciplinary optimization. Queipo et al. reviewed various surrogates based models used in aerospace applications. Goel et al. developed weighted average surrogate model based on response surface approximation (RSA), radial basis neural network (RBNN) and Krigging (KRG) models. In addition to the three basic models, RSA, RBNN and KRG, the multiple surrogate model, PBA also has been employed. Two geometric design variables and a multi-objective function with a weighting factor have been considered for this problem

Glucose uptake heterogeneity of the leg muscles is similar between patients with multiple sclerosis and healthy controls during walking.

Science.gov (United States)

Kindred, John H; Ketelhut, Nathaniel B; Rudroff, Thorsten

2015-02-01

Difficulties in ambulation are one of the main problems reported by patients with multiple sclerosis. A previous study by our research group showed increased recruitment of muscle groups during walking, but the influence of skeletal muscle properties, such as muscle fiber activity, has not been fully elucidated. The purpose of this investigation was to use the novel method of calculating glucose uptake heterogeneity in the leg muscles of patients with multiple sclerosis and compare these results to healthy controls. Eight patients with multiple sclerosis (4 men) and 8 healthy controls (4 men) performed 15 min of treadmill walking at a comfortable self-selected speed following muscle strength tests. Participants were injected with ≈ 8 mCi of [(18)F]-fluorodeoxyglucose during walking after which positron emission tomography/computed tomography imaging was performed. No differences in muscle strength were detected between multiple sclerosis and control groups (P>0.27). Within the multiple sclerosis, group differences in muscle volume existed between the stronger and weaker legs in the vastus lateralis, semitendinosus, and semimembranosus (Pmuscle group or individual muscle of the legs (P>0.16, P≥0.05). Patients with multiple sclerosis and healthy controls showed similar muscle fiber activity during walking. Interpretations of these results, with respect to our previous study, suggest that walking difficulties in patients with multiple sclerosis may be more associated with altered central nervous system motor patterns rather than alterations in skeletal muscle properties. Published by Elsevier Ltd.

Improved Hypoxia Modeling for Nutrient Control Decisions in the Gulf of Mexico

Science.gov (United States)

Habib, Shahid; Pickering, Ken; Tzortziou, Maria; Maninio, Antonio; Policelli, Fritz; Stehr, Jeff

2011-01-01

The Gulf of Mexico Modeling Framework is a suite of coupled models linking the deposition and transport of sediment and nutrients to subsequent bio-geo chemical processes and the resulting effect on concentrations of dissolved oxygen in the coastal waters of Louisiana and Texas. Here, we examine the potential benefits of using multiple NASA remote sensing data products within this Modeling Framework for increasing the accuracy of the models and their utility for nutrient control decisions in the Gulf of Mexico. Our approach is divided into three components: evaluation and improvement of (a) the precipitation input data (b) atmospheric constituent concentrations in EPA's air quality/deposition model and (c) the calculation of algal biomass, organic carbon and suspended solids within the water quality/eutrophication models of the framework.

Modelling the Dynamics of Intracellular Processes as an Organisation of Multiple Agents

NARCIS (Netherlands)

Bosse, T.; Jonker, C.M.; Treur, J.; Armano, G.; Merelli, E.; Denzinger, J.; Martin, A.; Miles, S.; Tianfield, H.; Unland, R.

2005-01-01

This paper explores how the dynamics of complex biological processes can be modeled as an organisation of multiple agents. This modelling perspective identifies organisational structure occurring in complex decentralised processes and handles complexity of the analysis of the dynamics by structuring

A modeling and numerical algorithm for thermoporomechanics in multiple porosity media for naturally fractured reservoirs

Science.gov (United States)

Kim, J.; Sonnenthal, E. L.; Rutqvist, J.

2011-12-01

Rigorous modeling of coupling between fluid, heat, and geomechanics (thermo-poro-mechanics), in fractured porous media is one of the important and difficult topics in geothermal reservoir simulation, because the physics are highly nonlinear and strongly coupled. Coupled fluid/heat flow and geomechanics are investigated using the multiple interacting continua (MINC) method as applied to naturally fractured media. In this study, we generalize constitutive relations for the isothermal elastic dual porosity model proposed by Berryman (2002) to those for the non-isothermal elastic/elastoplastic multiple porosity model, and derive the coupling coefficients of coupled fluid/heat flow and geomechanics and constraints of the coefficients. When the off-diagonal terms of the total compressibility matrix for the flow problem are zero, the upscaled drained bulk modulus for geomechanics becomes the harmonic average of drained bulk moduli of the multiple continua. In this case, the drained elastic/elastoplastic moduli for mechanics are determined by a combination of the drained moduli and volume fractions in multiple porosity materials. We also determine a relation between local strains of all multiple porosity materials in a gridblock and the global strain of the gridblock, from which we can track local and global elastic/plastic variables. For elastoplasticity, the return mapping is performed for all multiple porosity materials in the gridblock. For numerical implementation, we employ and extend the fixed-stress sequential method of the single porosity model to coupled fluid/heat flow and geomechanics in multiple porosity systems, because it provides numerical stability and high accuracy. This sequential scheme can be easily implemented by using a porosity function and its corresponding porosity correction, making use of the existing robust flow and geomechanics simulators. We implemented the proposed modeling and numerical algorithm to the reaction transport simulator

A multiple objective test assembly approach for exposure control problems in Computerized Adaptive Testing

Directory of Open Access Journals (Sweden)

Theo J.H.M. Eggen

2010-01-01

Full Text Available Overexposure and underexposure of items in the bank are serious problems in operational computerized adaptive testing (CAT systems. These exposure problems might result in item compromise, or point at a waste of investments. The exposure control problem can be viewed as a test assembly problem with multiple objectives. Information in the test has to be maximized, item compromise has to be minimized, and pool usage has to be optimized. In this paper, a multiple objectives method is developed to deal with both types of exposure problems. In this method, exposure control parameters based on observed exposure rates are implemented as weights for the information in the item selection procedure. The method does not need time consuming simulation studies, and it can be implemented conditional on ability level. The method is compared with Sympson Hetter method for exposure control, with the Progressive method and with alphastratified testing. The results show that the method is successful in dealing with both kinds of exposure problems.

Large-scale building energy efficiency retrofit: Concept, model and control

International Nuclear Information System (INIS)

Wu, Zhou; Wang, Bo; Xia, Xiaohua

2016-01-01

BEER (Building energy efficiency retrofit) projects are initiated in many nations and regions over the world. Existing studies of BEER focus on modeling and planning based on one building and one year period of retrofitting, which cannot be applied to certain large BEER projects with multiple buildings and multi-year retrofit. In this paper, the large-scale BEER problem is defined in a general TBT (time-building-technology) framework, which fits essential requirements of real-world projects. The large-scale BEER is newly studied in the control approach rather than the optimization approach commonly used before. Optimal control is proposed to design optimal retrofitting strategy in terms of maximal energy savings and maximal NPV (net present value). The designed strategy is dynamically changing on dimensions of time, building and technology. The TBT framework and the optimal control approach are verified in a large BEER project, and results indicate that promising performance of energy and cost savings can be achieved in the general TBT framework. - Highlights: • Energy efficiency retrofit of many buildings is studied. • A TBT (time-building-technology) framework is proposed. • The control system of the large-scale BEER is modeled. • The optimal retrofitting strategy is obtained.

Modeling and Control of a Tailsitter with a Ducted Fan

Science.gov (United States)

Argyle, Matthew Elliott

dissertation, we develop two different approaches that can achieve near constant altitude transitions for some types of aircraft. The first method, based on multiple LQR controllers, requires a high fidelity model of the aircraft. However, the second method, based on the energy along the body axes, requires almost no aerodynamic information.

Nonconvex model predictive control for commercial refrigeration

Science.gov (United States)

Gybel Hovgaard, Tobias; Boyd, Stephen; Larsen, Lars F. S.; Bagterp Jørgensen, John

2013-08-01

We consider the control of a commercial multi-zone refrigeration system, consisting of several cooling units that share a common compressor, and is used to cool multiple areas or rooms. In each time period we choose cooling capacity to each unit and a common evaporation temperature. The goal is to minimise the total energy cost, using real-time electricity prices, while obeying temperature constraints on the zones. We propose a variation on model predictive control to achieve this goal. When the right variables are used, the dynamics of the system are linear, and the constraints are convex. The cost function, however, is nonconvex due to the temperature dependence of thermodynamic efficiency. To handle this nonconvexity we propose a sequential convex optimisation method, which typically converges in fewer than 5 or so iterations. We employ a fast convex quadratic programming solver to carry out the iterations, which is more than fast enough to run in real time. We demonstrate our method on a realistic model, with a full year simulation and 15-minute time periods, using historical electricity prices and weather data, as well as random variations in thermal load. These simulations show substantial cost savings, on the order of 30%, compared to a standard thermostat-based control system. Perhaps more important, we see that the method exhibits sophisticated response to real-time variations in electricity prices. This demand response is critical to help balance real-time uncertainties in generation capacity associated with large penetration of intermittent renewable energy sources in a future smart grid.

Hybrid Control System for Greater Resilience Using Multiple Isolation and Building Connection

Directory of Open Access Journals (Sweden)

Masaki Taniguchi

2016-10-01

Full Text Available An innovative hybrid control building system of multiple isolation and connection is proposed and investigated using both time-history and input energy responses for various types of ground motions together with transfer functions. It is concerned that the seismic displacement response at the base-isolation layer of the existing base-isolated buildings may extremely increase under long-period and long-duration ground motions which are getting great attention recently. In order to enhance the seismic performance of those base-isolated buildings, a novel hybrid system of multiple isolation and building-connection is proposed and compared with other structural systems such as an independent multiple isolation system, a hybrid system of base-isolation and building-connection. Furthermore, the robustness of seismic responses of the proposed hybrid system for various types of ground motion is discussed through the comparison of various structural systems including non-hybrid systems. Finally the optimal connection damper location is investigated using a sensitivity-type optimization approach.

The Relationship Between Poor Quality of Life and Desire to Hasten Death: A Multiple Mediation Model Examining the Contributions of Depression, Demoralization, Loss of Control, and Low Self-worth.

Science.gov (United States)

Robinson, Sophie; Kissane, David W; Brooker, Joanne; Hempton, Courtney; Burney, Susan

2017-02-01

The risk of suicide is elevated in palliative care patients compared with the general population. Various psychological factors, including depression, demoralization, loss of control, and low self-worth, have been associated with a desire to hasten death. The aim of this study was to investigate whether depression, demoralization, loss of control, and low self-worth mediated the relationship between global quality of life and desire to hasten death. A sample of 162 palliative care patients completed measures of global quality of life, depression, demoralization, perceived control, self-worth, and desire to hasten death. A multiple mediation model with bootstrapping sampling tested the total (combined) indirect effect and individual indirect effects of depression, the two subscales of demoralization (Meaning and Purpose, and Distress and Coping Ability), perceived control, and self-worth. Depressive symptoms, loss of meaning and purpose, loss of control, and low self-worth mediated the direct effect of global quality of life on desire to hasten death. The Distress and Coping Ability component of demoralization was not a significant mediator. Depression, loss of meaning and purpose, loss of control, and low self-worth are strong clinical markers for desire to hasten death. Targeting these symptoms through existentially oriented therapies, such as meaning-centered therapy, may ameliorate suicidal thinking. Copyright © 2016 American Academy of Hospice and Palliative Medicine. Published by Elsevier Inc. All rights reserved.

Automatic Flight Controller With Model Inversion

Science.gov (United States)

Meyer, George; Smith, G. Allan

1992-01-01

Automatic digital electronic control system based on inverse-model-follower concept being developed for proposed vertical-attitude-takeoff-and-landing airplane. Inverse-model-follower control places inverse mathematical model of dynamics of controlled plant in series with control actuators of controlled plant so response of combination of model and plant to command is unity. System includes feedback to compensate for uncertainties in mathematical model and disturbances imposed from without.

Dynamics of nonlinear feedback control

NARCIS (Netherlands)

Snippe, H.P.; Hateren, J.H. van

Feedback control in neural systems is ubiquitous. Here we study the mathematics of nonlinear feedback control. We compare models in which the input is multiplied by a dynamic gain (multiplicative control) with models in which the input is divided by a dynamic attenuation (divisive control). The gain

A Two-Level Optimal Scheduling Strategy for Central Air-Conditioners Based on Metal Model with Comprehensive State-Queueing Control Models

Directory of Open Access Journals (Sweden)

Yebai Qi

2017-12-01

Full Text Available Unlike some thermostatically controlled appliances (TCAs with small capacities, Central Air-conditioner (CAC has huge potential for demand response because of its large capacity. This paper presents a new CAC control strategy under multiple constraints. The CAC is modeled by three main modules: CAC central unit, water pumps, and temperature simulation of terminal users. The CAC’s power consumption is mainly determined by users’ load ratio. As the information and communication system have become the central nervous system of the smart grid, big data analysis is of great significance. Assuming that reliable two-way communication systems are preset, an integrated parameter priority list (IPPL control strategy is used to control and monitor CAC. A new intelligent algorithm, Space Exploration and Unimodal Region Elimination (SEUMRE algorithm, is introduced for solving the optimization problem of demand response targets generation under multiple constraints with the help of big data analysis. In this paper, influences and constrain factors, such as price and users’ comfortable levels are taken into account to satisfy the need of actual situation. Simulation results show that the proposed approach, when comparing with other typical optimization algorithms, yields better performances and efficiency.

Model selection with multiple regression on distance matrices leads to incorrect inferences.

Directory of Open Access Journals (Sweden)

Ryan P Franckowiak

Full Text Available In landscape genetics, model selection procedures based on Information Theoretic and Bayesian principles have been used with multiple regression on distance matrices (MRM to test the relationship between multiple vectors of pairwise genetic, geographic, and environmental distance. Using Monte Carlo simulations, we examined the ability of model selection criteria based on Akaike's information criterion (AIC, its small-sample correction (AICc, and the Bayesian information criterion (BIC to reliably rank candidate models when applied with MRM while varying the sample size. The results showed a serious problem: all three criteria exhibit a systematic bias toward selecting unnecessarily complex models containing spurious random variables and erroneously suggest a high level of support for the incorrectly ranked best model. These problems effectively increased with increasing sample size. The failure of AIC, AICc, and BIC was likely driven by the inflated sample size and different sum-of-squares partitioned by MRM, and the resulting effect on delta values. Based on these findings, we strongly discourage the continued application of AIC, AICc, and BIC for model selection with MRM.

Multiple Temperature Model for Near Continuum Flows

International Nuclear Information System (INIS)

XU, Kun; Liu, Hongwei; Jiang, Jianzheng

2007-01-01

In the near continuum flow regime, the flow may have different translational temperatures in different directions. It is well known that for increasingly rarefied flow fields, the predictions from continuum formulation, such as the Navier-Stokes equations, lose accuracy. These inaccuracies may be partially due to the single temperature assumption in the Navier-Stokes equations. Here, based on the gas-kinetic Bhatnagar-Gross-Krook (BGK) equation, a multitranslational temperature model is proposed and used in the flow calculations. In order to fix all three translational temperatures, two constraints are additionally proposed to model the energy exchange in different directions. Based on the multiple temperature assumption, the Navier-Stokes relation between the stress and strain is replaced by the temperature relaxation term, and the Navier-Stokes assumption is recovered only in the limiting case when the flow is close to the equilibrium with the same temperature in different directions. In order to validate the current model, both the Couette and Poiseuille flows are studied in the transition flow regime

ECONOMIC MODELING STOCKS CONTROL SYSTEM: SIMULATION MODEL

OpenAIRE

Климак, М.С.; Войтко, С.В.

2016-01-01

Considered theoretical and applied aspects of the development of simulation models to predictthe optimal development and production systems that create tangible products andservices. It isproved that theprocessof inventory control needs of economicandmathematical modeling in viewof thecomplexity of theoretical studies. A simulation model of stocks control that allows make managementdecisions with production logistics

A toy MCT model for multiple glass transitions: Double swallow tail singularity

Energy Technology Data Exchange (ETDEWEB)

Ryzhov, V.N. [Institute for High Pressure Physics, Russian Academy of Sciences, Troitsk 142190, Moscow region (Russian Federation); Moscow Institute of Physics and Technology, 141700 Moscow (Russian Federation); Tareyeva, E.E. [Institute for High Pressure Physics, Russian Academy of Sciences, Troitsk 142190, Moscow region (Russian Federation)

2014-11-07

We propose a toy model to describe in the frame of Mode Coupling Theory multiple glass transitions. The model is based on the postulated simple form for static structure factor as a sum of two delta-functions. This form makes it possible to solve the MCT equations in almost analytical way. The phase diagram is governed by two swallow tails resulting from two A{sub 4} singularities and includes liquid–glass transition and multiple glasses. The diagram has much in common with those of binary and quasibinary systems. - Highlights: • A simple toy model is proposed for description of glass–glass transitions. • The static structure factor of the model has the form of a sum of delta-functions. • The phase diagram contains A{sub 4} bifurcation singularities and A{sub 3} end points. • The results can be applied for the qualitative description of quasibinary systems.

Validation and calibration of structural models that combine information from multiple sources.

Science.gov (United States)

Dahabreh, Issa J; Wong, John B; Trikalinos, Thomas A

2017-02-01

Mathematical models that attempt to capture structural relationships between their components and combine information from multiple sources are increasingly used in medicine. Areas covered: We provide an overview of methods for model validation and calibration and survey studies comparing alternative approaches. Expert commentary: Model validation entails a confrontation of models with data, background knowledge, and other models, and can inform judgments about model credibility. Calibration involves selecting parameter values to improve the agreement of model outputs with data. When the goal of modeling is quantitative inference on the effects of interventions or forecasting, calibration can be viewed as estimation. This view clarifies issues related to parameter identifiability and facilitates formal model validation and the examination of consistency among different sources of information. In contrast, when the goal of modeling is the generation of qualitative insights about the modeled phenomenon, calibration is a rather informal process for selecting inputs that result in model behavior that roughly reproduces select aspects of the modeled phenomenon and cannot be equated to an estimation procedure. Current empirical research on validation and calibration methods consists primarily of methodological appraisals or case-studies of alternative techniques and cannot address the numerous complex and multifaceted methodological decisions that modelers must make. Further research is needed on different approaches for developing and validating complex models that combine evidence from multiple sources.