Data-Based Predictive Control with Multirate Prediction Step

Science.gov (United States)

Barlow, Jonathan S.

2010-01-01

Data-based predictive control is an emerging control method that stems from Model Predictive Control (MPC). MPC computes current control action based on a prediction of the system output a number of time steps into the future and is generally derived from a known model of the system. Data-based predictive control has the advantage of deriving predictive models and controller gains from input-output data. Thus, a controller can be designed from the outputs of complex simulation code or a physical system where no explicit model exists. If the output data happens to be corrupted by periodic disturbances, the designed controller will also have the built-in ability to reject these disturbances without the need to know them. When data-based predictive control is implemented online, it becomes a version of adaptive control. One challenge of MPC is computational requirements increasing with prediction horizon length. This paper develops a closed-loop dynamic output feedback controller that minimizes a multi-step-ahead receding-horizon cost function with multirate prediction step. One result is a reduced influence of prediction horizon and the number of system outputs on the computational requirements of the controller. Another result is an emphasis on portions of the prediction window that are sampled more frequently. A third result is the ability to include more outputs in the feedback path than in the cost function.

Prediction of critical heat flux by a new local condition hypothesis

International Nuclear Information System (INIS)

Im, J. H.; Jun, K. D.; Sim, J. W.; Deng, Zhijian

1998-01-01

Critical Heat Flux(CHF) was predicted for uniformly heated vertical round tube by a new local condition hypothesis which incorporates a local true steam quality. This model successfully overcame the difficulties in predicted the subcooled and quality CHF by the thermodynamic equilibrium quality. The local true steam quality is a dependent variable of the thermodynamic equilibrium quality at the exit and the quality at the Onset of Significant Vaporization(OSV). The exit thermodynamic equilibrium quality was obtained from the heat balance, and the quality at OSV was obtained from the Saha-Zuber correlation. In the past CHF has been predicted by the experimental correlation based on local or non-local condition hypothesis. This preliminary study showed that all the available world data on uniform CHF could be predicted by the model based on the local condition hypothesis

An ensemble method for predicting subnuclear localizations from primary protein structures.

Directory of Open Access Journals (Sweden)

Guo Sheng Han

Full Text Available BACKGROUND: Predicting protein subnuclear localization is a challenging problem. Some previous works based on non-sequence information including Gene Ontology annotations and kernel fusion have respective limitations. The aim of this work is twofold: one is to propose a novel individual feature extraction method; another is to develop an ensemble method to improve prediction performance using comprehensive information represented in the form of high dimensional feature vector obtained by 11 feature extraction methods. METHODOLOGY/PRINCIPAL FINDINGS: A novel two-stage multiclass support vector machine is proposed to predict protein subnuclear localizations. It only considers those feature extraction methods based on amino acid classifications and physicochemical properties. In order to speed up our system, an automatic search method for the kernel parameter is used. The prediction performance of our method is evaluated on four datasets: Lei dataset, multi-localization dataset, SNL9 dataset and a new independent dataset. The overall accuracy of prediction for 6 localizations on Lei dataset is 75.2% and that for 9 localizations on SNL9 dataset is 72.1% in the leave-one-out cross validation, 71.7% for the multi-localization dataset and 69.8% for the new independent dataset, respectively. Comparisons with those existing methods show that our method performs better for both single-localization and multi-localization proteins and achieves more balanced sensitivities and specificities on large-size and small-size subcellular localizations. The overall accuracy improvements are 4.0% and 4.7% for single-localization proteins and 6.5% for multi-localization proteins. The reliability and stability of our classification model are further confirmed by permutation analysis. CONCLUSIONS: It can be concluded that our method is effective and valuable for predicting protein subnuclear localizations. A web server has been designed to implement the proposed method

Predicting local field potentials with recurrent neural networks.

Science.gov (United States)

Kim, Louis; Harer, Jacob; Rangamani, Akshay; Moran, James; Parks, Philip D; Widge, Alik; Eskandar, Emad; Dougherty, Darin; Chin, Sang Peter

2016-08-01

We present a Recurrent Neural Network using LSTM (Long Short Term Memory) that is capable of modeling and predicting Local Field Potentials. We train and test the network on real data recorded from epilepsy patients. We construct networks that predict multi-channel LFPs for 1, 10, and 100 milliseconds forward in time. Our results show that prediction using LSTM outperforms regression when predicting 10 and 100 millisecond forward in time.

Radiotherapy of tonsillar and base of the tongue carcinoma. Prediction of local control

NARCIS (Netherlands)

Mak-Kregar, S.; Baris, G.; Lebesque, J. V.; Balm, A. J.; Hart, A. A.; Hilgers, F. J.

1993-01-01

119 patients with squamous cell carcinoma of the tonsillar region (68) and the base of the tongue (51), who received external radiotherapy with curative intent between 1966 and 1984, are analysed with respect to overall treatment results, local tumour control and prognostic factors. Radiation doses

Support Vector Machine-Based Prediction of Local Tumor Control After Stereotactic Body Radiation Therapy for Early-Stage Non-Small Cell Lung Cancer

International Nuclear Information System (INIS)

Klement, Rainer J.; Allgäuer, Michael; Appold, Steffen; Dieckmann, Karin; Ernst, Iris; Ganswindt, Ute; Holy, Richard; Nestle, Ursula; Nevinny-Stickel, Meinhard; Semrau, Sabine; Sterzing, Florian; Wittig, Andrea; Andratschke, Nicolaus; Guckenberger, Matthias

2014-01-01

Background: Several prognostic factors for local tumor control probability (TCP) after stereotactic body radiation therapy (SBRT) for early stage non-small cell lung cancer (NSCLC) have been described, but no attempts have been undertaken to explore whether a nonlinear combination of potential factors might synergistically improve the prediction of local control. Methods and Materials: We investigated a support vector machine (SVM) for predicting TCP in a cohort of 399 patients treated at 13 German and Austrian institutions. Among 7 potential input features for the SVM we selected those most important on the basis of forward feature selection, thereby evaluating classifier performance by using 10-fold cross-validation and computing the area under the ROC curve (AUC). The final SVM classifier was built by repeating the feature selection 10 times with different splitting of the data for cross-validation and finally choosing only those features that were selected at least 5 out of 10 times. It was compared with a multivariate logistic model that was built by forward feature selection. Results: Local failure occurred in 12% of patients. Biologically effective dose (BED) at the isocenter (BED ISO ) was the strongest predictor of TCP in the logistic model and also the most frequently selected input feature for the SVM. A bivariate logistic function of BED ISO and the pulmonary function indicator forced expiratory volume in 1 second (FEV1) yielded the best description of the data but resulted in a significantly smaller AUC than the final SVM classifier with the input features BED ISO , age, baseline Karnofsky index, and FEV1 (0.696 ± 0.040 vs 0.789 ± 0.001, P<.03). The final SVM resulted in sensitivity and specificity of 67.0% ± 0.5% and 78.7% ± 0.3%, respectively. Conclusions: These results confirm that machine learning techniques like SVMs can be successfully applied to predict treatment outcome after SBRT. Improvements over traditional TCP modeling are

Comparative Analysis of Local Control Prediction Using Different Biophysical Models for Non-Small Cell Lung Cancer Patients Undergoing Stereotactic Body Radiotherapy

Directory of Open Access Journals (Sweden)

Bao-Tian Huang

2017-01-01

Full Text Available Purpose. The consistency for predicting local control (LC data using biophysical models for stereotactic body radiotherapy (SBRT treatment of lung cancer is unclear. This study aims to compare the results calculated from different models using the treatment planning data. Materials and Methods. Treatment plans were designed for 17 patients diagnosed with primary non-small cell lung cancer (NSCLC using 5 different fraction schemes. The Martel model, Ohri model, and the Tai model were used to predict the 2-year LC value. The Gucken model, Santiago model, and the Tai model were employed to estimate the 3-year LC data. Results. We found that the employed models resulted in completely different LC prediction except for the Gucken and the Santiago models which exhibited quite similar 3-year LC data. The predicted 2-year and 3-year LC values in different models were not only associated with the dose normalization but also associated with the employed fraction schemes. The greatest difference predicted by different models was up to 15.0%. Conclusions. Our results show that different biophysical models influence the LC prediction and the difference is not only correlated to the dose normalization but also correlated to the employed fraction schemes.

Real-time prediction of respiratory motion based on local regression methods

International Nuclear Information System (INIS)

Ruan, D; Fessler, J A; Balter, J M

2007-01-01

Recent developments in modulation techniques enable conformal delivery of radiation doses to small, localized target volumes. One of the challenges in using these techniques is real-time tracking and predicting target motion, which is necessary to accommodate system latencies. For image-guided-radiotherapy systems, it is also desirable to minimize sampling rates to reduce imaging dose. This study focuses on predicting respiratory motion, which can significantly affect lung tumours. Predicting respiratory motion in real-time is challenging, due to the complexity of breathing patterns and the many sources of variability. We propose a prediction method based on local regression. There are three major ingredients of this approach: (1) forming an augmented state space to capture system dynamics, (2) local regression in the augmented space to train the predictor from previous observation data using semi-periodicity of respiratory motion, (3) local weighting adjustment to incorporate fading temporal correlations. To evaluate prediction accuracy, we computed the root mean square error between predicted tumor motion and its observed location for ten patients. For comparison, we also investigated commonly used predictive methods, namely linear prediction, neural networks and Kalman filtering to the same data. The proposed method reduced the prediction error for all imaging rates and latency lengths, particularly for long prediction lengths

Experimental Validation of Energy Resources Integration in Microgrids via Distributed Predictive Control

DEFF Research Database (Denmark)

Mantovani, Giancarlo; Costanzo, Giuseppe Tommaso; Marinelli, Mattia

2014-01-01

This paper presents an innovative control scheme for the management of energy consumption in commercial build- ings with local energy production, such as photovoltaic panels or wind turbine and an energy storage unit. The presented scheme is based on distributed model predictive controllers, which...... sources, a vanadium redox battery system, resistive load, and a point of common coupling to the national grid. Several experiments are carried to assess the performance of the control scheme in managing local energy pro- duction and consumption....

Real-time prediction of respiratory motion based on a local dynamic model in an augmented space.

Science.gov (United States)

Hong, S-M; Jung, B-H; Ruan, D

2011-03-21

Motion-adaptive radiotherapy aims to deliver ablative radiation dose to the tumor target with minimal normal tissue exposure, by accounting for real-time target movement. In practice, prediction is usually necessary to compensate for system latency induced by measurement, communication and control. This work focuses on predicting respiratory motion, which is most dominant for thoracic and abdominal tumors. We develop and investigate the use of a local dynamic model in an augmented space, motivated by the observation that respiratory movement exhibits a locally circular pattern in a plane augmented with a delayed axis. By including the angular velocity as part of the system state, the proposed dynamic model effectively captures the natural evolution of respiratory motion. The first-order extended Kalman filter is used to propagate and update the state estimate. The target location is predicted by evaluating the local dynamic model equations at the required prediction length. This method is complementary to existing work in that (1) the local circular motion model characterizes 'turning', overcoming the limitation of linear motion models; (2) it uses a natural state representation including the local angular velocity and updates the state estimate systematically, offering explicit physical interpretations; (3) it relies on a parametric model and is much less data-satiate than the typical adaptive semiparametric or nonparametric method. We tested the performance of the proposed method with ten RPM traces, using the normalized root mean squared difference between the predicted value and the retrospective observation as the error metric. Its performance was compared with predictors based on the linear model, the interacting multiple linear models and the kernel density estimator for various combinations of prediction lengths and observation rates. The local dynamic model based approach provides the best performance for short to medium prediction lengths under relatively

Neural Network with Local Memory for Nuclear Reactor Power Level Control

International Nuclear Information System (INIS)

Uluyol, Oender; Ragheb, Magdi; Tsoukalas, Lefteri

2001-01-01

A methodology is introduced for a neural network with local memory called a multilayered local output gamma feedback (LOGF) neural network within the paradigm of locally-recurrent globally-feedforward neural networks. It appears to be well-suited for the identification, prediction, and control tasks in highly dynamic systems; it allows for the presentation of different timescales through incorporation of a gamma memory. A learning algorithm based on the backpropagation-through-time approach is derived. The spatial and temporal weights of the network are iteratively optimized for a given problem using the derived learning algorithm. As a demonstration of the methodology, it is applied to the task of power level control of a nuclear reactor at different fuel cycle conditions. The results demonstrate that the LOGF neural network controller outperforms the classical as well as the state feedback-assisted classical controllers for reactor power level control by showing a better tracking of the demand power, improving the fuel and exit temperature responses, and by performing robustly in different fuel cycle and power level conditions

Towards structural controllability of local-world networks

International Nuclear Information System (INIS)

Sun, Shiwen; Ma, Yilin; Wu, Yafang; Wang, Li; Xia, Chengyi

2016-01-01

Controlling complex networks is of vital importance in science and engineering. Meanwhile, local-world effect is an important ingredient which should be taken into consideration in the complete description of real-world complex systems. In this letter, structural controllability of a class of local-world networks is investigated. Through extensive numerical simulations, firstly, effects of local world size M and network size N on structural controllability are examined. For local-world networks with sparse topological configuration, compared to network size, local-world size can induce stronger influence on controllability, however, for dense networks, controllability is greatly affected by network size and local-world effect can be neglected. Secondly, relationships between controllability and topological properties are analyzed. Lastly, the robustness of local-world networks under targeted attacks regarding structural controllability is discussed. These results can help to deepen the understanding of structural complexity and connectivity patterns of complex systems. - Highlights: • Structural controllability of a class of local-world networks is investigated. • For sparse local-world networks, compared to network size, local-world size can bring stronger influence on controllability. • For dense networks, controllability is greatly affected by network size and the effect of local-world size can be neglected. • Structural controllability against targeted node attacks is discussed.

Towards structural controllability of local-world networks

Energy Technology Data Exchange (ETDEWEB)

Sun, Shiwen, E-mail: sunsw80@126.com [Tianjin Key Laboratory of Intelligence Computing and Novel Software Technology, Tianjin University of Technology, Tianjin 300384 (China); Key Laboratory of Computer Vision and System (Tianjin University of Technology), Ministry of Education, Tianjin 300384 (China); Ma, Yilin; Wu, Yafang; Wang, Li; Xia, Chengyi [Tianjin Key Laboratory of Intelligence Computing and Novel Software Technology, Tianjin University of Technology, Tianjin 300384 (China); Key Laboratory of Computer Vision and System (Tianjin University of Technology), Ministry of Education, Tianjin 300384 (China)

2016-05-20

Controlling complex networks is of vital importance in science and engineering. Meanwhile, local-world effect is an important ingredient which should be taken into consideration in the complete description of real-world complex systems. In this letter, structural controllability of a class of local-world networks is investigated. Through extensive numerical simulations, firstly, effects of local world size M and network size N on structural controllability are examined. For local-world networks with sparse topological configuration, compared to network size, local-world size can induce stronger influence on controllability, however, for dense networks, controllability is greatly affected by network size and local-world effect can be neglected. Secondly, relationships between controllability and topological properties are analyzed. Lastly, the robustness of local-world networks under targeted attacks regarding structural controllability is discussed. These results can help to deepen the understanding of structural complexity and connectivity patterns of complex systems. - Highlights: • Structural controllability of a class of local-world networks is investigated. • For sparse local-world networks, compared to network size, local-world size can bring stronger influence on controllability. • For dense networks, controllability is greatly affected by network size and the effect of local-world size can be neglected. • Structural controllability against targeted node attacks is discussed.

Positron Emission Tomography (PET) Evaluation After Initial Chemotherapy and Radiation Therapy Predicts Local Control in Rhabdomyosarcoma

Energy Technology Data Exchange (ETDEWEB)

Dharmarajan, Kavita V., E-mail: dharmark@mskcc.org [Departments of Radiation Oncology, Pediatric Oncology, and Nuclear Medicine, Memorial Sloan-Kettering, New York, New York (United States); Wexler, Leonard H.; Gavane, Somali; Fox, Josef J.; Schoder, Heiko; Tom, Ashlyn K.; Price, Alison N.; Meyers, Paul A.; Wolden, Suzanne L. [Departments of Radiation Oncology, Pediatric Oncology, and Nuclear Medicine, Memorial Sloan-Kettering, New York, New York (United States)

2012-11-15

Purpose: 18-fluorodeoxyglucose positron emission tomography (PET) is already an integral part of staging in rhabdomyosarcoma. We investigated whether primary-site treatment response characterized by serial PET imaging at specific time points can be correlated with local control. Patients and Methods: We retrospectively examined 94 patients with rhabdomyosarcoma who received initial chemotherapy 15 weeks (median) before radiotherapy and underwent baseline, preradiation, and postradiation PET. Baseline PET standardized uptake values (SUVmax) and the presence or absence of abnormal uptake (termed PET-positive or PET-negative) both before and after radiation were examined for the primary site. Local relapse-free survival (LRFS) was calculated according to baseline SUVmax, PET-positive status, and PET-negative status by the Kaplan-Meier method, and comparisons were tested with the log-rank test. Results: The median patient age was 11 years. With 3-year median follow-up, LRFS was improved among postradiation PET-negative vs PET-positive patients: 94% vs 75%, P=.02. By contrast, on baseline PET, LRFS was not significantly different for primary-site SUVmax {<=}7 vs >7 (median), although the findings suggested a trend toward improved LRFS: 96% for SUVmax {<=}7 vs 79% for SUVmax >7, P=.08. Preradiation PET also suggested a statistically insignificant trend toward improved LRFS for PET-negative (97%) vs PET-positive (81%) patients (P=.06). Conclusion: Negative postradiation PET predicted improved LRFS. Notably, 77% of patients with persistent postradiation uptake did not experience local failure, suggesting that these patients could be closely followed up rather than immediately referred for intervention. Negative baseline and preradiation PET findings suggested statistically insignificant trends toward improved LRFS. Additional study may further understanding of relationships between PET findings at these time points and outcome in rhabdomyosarcoma.

Control of dynamical localization

International Nuclear Information System (INIS)

Gong Jiangbin; Woerner, Hans Jakob; Brumer, Paul

2003-01-01

Control over the quantum dynamics of chaotic kicked rotor systems is demonstrated. Specifically, control over a number of quantum coherent phenomena is achieved by a simple modification of the kicking field. These include the enhancement of the dynamical localization length, the introduction of classical anomalous diffusion assisted control for systems far from the semiclassical regime, and the observation of a variety of strongly nonexponential line shapes for dynamical localization. The results provide excellent examples of controlled quantum dynamics in a system that is classically chaotic and offer opportunities to explore quantum fluctuations and correlations in quantum chaos

DeepLoc: prediction of protein subcellular localization using deep learning

DEFF Research Database (Denmark)

Almagro Armenteros, Jose Juan; Sønderby, Casper Kaae; Sønderby, Søren Kaae

2017-01-01

The prediction of eukaryotic protein subcellular localization is a well-studied topic in bioinformatics due to its relevance in proteomics research. Many machine learning methods have been successfully applied in this task, but in most of them, predictions rely on annotation of homologues from...... knowledge databases. For novel proteins where no annotated homologues exist, and for predicting the effects of sequence variants, it is desirable to have methods for predicting protein properties from sequence information only. Here, we present a prediction algorithm using deep neural networks to predict...... current state-of-the-art algorithms, including those relying on homology information. The method is available as a web server at http://www.cbs.dtu.dk/services/DeepLoc . Example code is available at https://github.com/JJAlmagro/subcellular_localization . The dataset is available at http...

Using fire-weather forecasts and local weather observations in predicting burning index for individual fire-danger stations.

Science.gov (United States)

Owen P. Cramer

1958-01-01

Any agency engaged in forest-fire control needs accurate weather forecasts and systematic procedures for making the best use of predicted and reported weather information. This study explores the practicability of using several tabular and graphical aids for converting area forecasts and local observations of relative humidity and wind speed into predicted values for...

Predicting the subcellular localization of viral proteins within a mammalian host cell

Directory of Open Access Journals (Sweden)

Thomas DY

2006-04-01

Full Text Available Abstract Background The bioinformatic prediction of protein subcellular localization has been extensively studied for prokaryotic and eukaryotic organisms. However, this is not the case for viruses whose proteins are often involved in extensive interactions at various subcellular localizations with host proteins. Results Here, we investigate the extent of utilization of human cellular localization mechanisms by viral proteins and we demonstrate that appropriate eukaryotic subcellular localization predictors can be used to predict viral protein localization within the host cell. Conclusion Such predictions provide a method to rapidly annotate viral proteomes with subcellular localization information. They are likely to have widespread applications both in the study of the functions of viral proteins in the host cell and in the design of antiviral drugs.

Support Vector Machine-Based Prediction of Local Tumor Control After Stereotactic Body Radiation Therapy for Early-Stage Non-Small Cell Lung Cancer

Energy Technology Data Exchange (ETDEWEB)

Klement, Rainer J., E-mail: rainer_klement@gmx.de [Department of Radiation Oncology, University of Würzburg (Germany); Department of Radiotherapy and Radiation Oncology, Leopoldina Hospital, Schweinfurt (Germany); Allgäuer, Michael [Department of Radiotherapy, Barmherzige Brüder Regensburg, Regensburg (Germany); Appold, Steffen [Department of Radiation Oncology, Technische Universität Dresden (Germany); Dieckmann, Karin [Department of Radiotherapy, Medical University of Vienna (Austria); Ernst, Iris [Department of Radiotherapy, University Hospital Münster (Germany); Ganswindt, Ute [Department of Radiation Oncology, Ludwigs-Maximilians-University Munich, München (Germany); Holy, Richard [Department of Radiation Oncology, RWTH Aachen University, Aachen (Germany); Nestle, Ursula [Department of Radiation Oncology, University Hospital Freiburg, Freiburg i Br (Germany); Nevinny-Stickel, Meinhard [Department of Therapeutic Radiology and Oncology, Innsbruck Medical University (Austria); Semrau, Sabine [Department of Radiation Oncology, Friedrich-Alexander University Erlangen-Nuremberg, Erlangen (Germany); Sterzing, Florian [Department of Radiation Oncology, University Hospital Heidelberg (Germany); Wittig, Andrea [Department of Radiotherapy and Radiation Oncology, Philipps-University Marburg (Germany); Andratschke, Nicolaus [Department of Radiation Oncology, Technische Universität München (Germany); Guckenberger, Matthias [Department of Radiation Oncology, University of Würzburg (Germany)

2014-03-01

Background: Several prognostic factors for local tumor control probability (TCP) after stereotactic body radiation therapy (SBRT) for early stage non-small cell lung cancer (NSCLC) have been described, but no attempts have been undertaken to explore whether a nonlinear combination of potential factors might synergistically improve the prediction of local control. Methods and Materials: We investigated a support vector machine (SVM) for predicting TCP in a cohort of 399 patients treated at 13 German and Austrian institutions. Among 7 potential input features for the SVM we selected those most important on the basis of forward feature selection, thereby evaluating classifier performance by using 10-fold cross-validation and computing the area under the ROC curve (AUC). The final SVM classifier was built by repeating the feature selection 10 times with different splitting of the data for cross-validation and finally choosing only those features that were selected at least 5 out of 10 times. It was compared with a multivariate logistic model that was built by forward feature selection. Results: Local failure occurred in 12% of patients. Biologically effective dose (BED) at the isocenter (BED{sub ISO}) was the strongest predictor of TCP in the logistic model and also the most frequently selected input feature for the SVM. A bivariate logistic function of BED{sub ISO} and the pulmonary function indicator forced expiratory volume in 1 second (FEV1) yielded the best description of the data but resulted in a significantly smaller AUC than the final SVM classifier with the input features BED{sub ISO}, age, baseline Karnofsky index, and FEV1 (0.696 ± 0.040 vs 0.789 ± 0.001, P<.03). The final SVM resulted in sensitivity and specificity of 67.0% ± 0.5% and 78.7% ± 0.3%, respectively. Conclusions: These results confirm that machine learning techniques like SVMs can be successfully applied to predict treatment outcome after SBRT. Improvements over traditional TCP

Model Predictive Control for Load Frequency Control with Wind Turbines

Directory of Open Access Journals (Sweden)

Yi Zhang

2015-01-01

Full Text Available Reliable load frequency (LFC control is crucial to the operation and design of modern electric power systems. Considering the LFC problem of a four-area interconnected power system with wind turbines, this paper presents a distributed model predictive control (DMPC based on coordination scheme. The proposed algorithm solves a series of local optimization problems to minimize a performance objective for each control area. The scheme incorporates the two critical nonlinear constraints, for example, the generation rate constraint (GRC and the valve limit, into convex optimization problems. Furthermore, the algorithm reduces the impact on the randomness and intermittence of wind turbine effectively. A performance comparison between the proposed controller with and that without the participation of the wind turbines is carried out. Good performance is obtained in the presence of power system nonlinearities due to the governors and turbines constraints and load change disturbances.

Local connectome phenotypes predict social, health, and cognitive factors

Directory of Open Access Journals (Sweden)

Michael A. Powell

2018-03-01

Full Text Available The unique architecture of the human connectome is defined initially by genetics and subsequently sculpted over time with experience. Thus, similarities in predisposition and experience that lead to similarities in social, biological, and cognitive attributes should also be reflected in the local architecture of white matter fascicles. Here we employ a method known as local connectome fingerprinting that uses diffusion MRI to measure the fiber-wise characteristics of macroscopic white matter pathways throughout the brain. This fingerprinting approach was applied to a large sample (N = 841 of subjects from the Human Connectome Project, revealing a reliable degree of between-subject correlation in the local connectome fingerprints, with a relatively complex, low-dimensional substructure. Using a cross-validated, high-dimensional regression analysis approach, we derived local connectome phenotype (LCP maps that could reliably predict a subset of subject attributes measured, including demographic, health, and cognitive measures. These LCP maps were highly specific to the attribute being predicted but also sensitive to correlations between attributes. Collectively, these results indicate that the local architecture of white matter fascicles reflects a meaningful portion of the variability shared between subjects along several dimensions. The local connectome is the pattern of fiber systems (i.e., number of fibers, orientation, and size within a voxel, and it reflects the proximal characteristics of white matter fascicles distributed throughout the brain. Here we show how variability in the local connectome is correlated in a principled way across individuals. This intersubject correlation is reliable enough that unique phenotype maps can be learned to predict between-subject variability in a range of social, health, and cognitive attributes. This work shows, for the first time, how the local connectome has both the sensitivity and the specificity to

Predictors of Individual Tumor Local Control After Stereotactic Radiosurgery for Non-Small Cell Lung Cancer Brain Metastases

International Nuclear Information System (INIS)

Garsa, Adam A.; Badiyan, Shahed N.; DeWees, Todd; Simpson, Joseph R.; Huang, Jiayi; Drzymala, Robert E.; Barani, Igor J.; Dowling, Joshua L.; Rich, Keith M.; Chicoine, Michael R.; Kim, Albert H.; Leuthardt, Eric C.; Robinson, Clifford G.

2014-01-01

Purpose: To evaluate local control rates and predictors of individual tumor local control for brain metastases from non-small cell lung cancer (NSCLC) treated with stereotactic radiosurgery (SRS). Methods and Materials: Between June 1998 and May 2011, 401 brain metastases in 228 patients were treated with Gamma Knife single-fraction SRS. Local failure was defined as an increase in lesion size after SRS. Local control was estimated using the Kaplan-Meier method. The Cox proportional hazards model was used for univariate and multivariate analysis. Receiver operating characteristic analysis was used to identify an optimal cutpoint for conformality index relative to local control. A P value <.05 was considered statistically significant. Results: Median age was 60 years (range, 27-84 years). There were 66 cerebellar metastases (16%) and 335 supratentorial metastases (84%). The median prescription dose was 20 Gy (range, 14-24 Gy). Median overall survival from time of SRS was 12.1 months. The estimated local control at 12 months was 74%. On multivariate analysis, cerebellar location (hazard ratio [HR] 1.94, P=.009), larger tumor volume (HR 1.09, P<.001), and lower conformality (HR 0.700, P=.044) were significant independent predictors of local failure. Conformality index cutpoints of 1.4-1.9 were predictive of local control, whereas a cutpoint of 1.75 was the most predictive (P=.001). The adjusted Kaplan-Meier 1-year local control for conformality index ≥1.75 was 84% versus 69% for conformality index <1.75, controlling for tumor volume and location. The 1-year adjusted local control for cerebellar lesions was 60%, compared with 77% for supratentorial lesions, controlling for tumor volume and conformality index. Conclusions: Cerebellar tumor location, lower conformality index, and larger tumor volume were significant independent predictors of local failure after SRS for brain metastases from NSCLC. These results warrant further investigation in a prospective

A range-based predictive localization algorithm for WSID networks

Science.gov (United States)

Liu, Yuan; Chen, Junjie; Li, Gang

2017-11-01

Most studies on localization algorithms are conducted on the sensor networks with densely distributed nodes. However, the non-localizable problems are prone to occur in the network with sparsely distributed sensor nodes. To solve this problem, a range-based predictive localization algorithm (RPLA) is proposed in this paper for the wireless sensor networks syncretizing the RFID (WSID) networks. The Gaussian mixture model is established to predict the trajectory of a mobile target. Then, the received signal strength indication is used to reduce the residence area of the target location based on the approximate point-in-triangulation test algorithm. In addition, collaborative localization schemes are introduced to locate the target in the non-localizable situations. Simulation results verify that the RPLA achieves accurate localization for the network with sparsely distributed sensor nodes. The localization accuracy of the RPLA is 48.7% higher than that of the APIT algorithm, 16.8% higher than that of the single Gaussian model-based algorithm and 10.5% higher than that of the Kalman filtering-based algorithm.

Estimation and prediction under local volatility jump-diffusion model

Science.gov (United States)

Kim, Namhyoung; Lee, Younhee

2018-02-01

Volatility is an important factor in operating a company and managing risk. In the portfolio optimization and risk hedging using the option, the value of the option is evaluated using the volatility model. Various attempts have been made to predict option value. Recent studies have shown that stochastic volatility models and jump-diffusion models reflect stock price movements accurately. However, these models have practical limitations. Combining them with the local volatility model, which is widely used among practitioners, may lead to better performance. In this study, we propose a more effective and efficient method of estimating option prices by combining the local volatility model with the jump-diffusion model and apply it using both artificial and actual market data to evaluate its performance. The calibration process for estimating the jump parameters and local volatility surfaces is divided into three stages. We apply the local volatility model, stochastic volatility model, and local volatility jump-diffusion model estimated by the proposed method to KOSPI 200 index option pricing. The proposed method displays good estimation and prediction performance.

Incoherent control of locally controllable quantum systems

International Nuclear Information System (INIS)

Dong Daoyi; Zhang Chenbin; Rabitz, Herschel; Pechen, Alexander; Tarn, T.-J.

2008-01-01

An incoherent control scheme for state control of locally controllable quantum systems is proposed. This scheme includes three steps: (1) amplitude amplification of the initial state by a suitable unitary transformation, (2) projective measurement of the amplified state, and (3) final optimization by a unitary controlled transformation. The first step increases the amplitudes of some desired eigenstates and the corresponding probability of observing these eigenstates, the second step projects, with high probability, the amplified state into a desired eigenstate, and the last step steers this eigenstate into the target state. Within this scheme, two control algorithms are presented for two classes of quantum systems. As an example, the incoherent control scheme is applied to the control of a hydrogen atom by an external field. The results support the suggestion that projective measurements can serve as an effective control and local controllability information can be used to design control laws for quantum systems. Thus, this scheme establishes a subtle connection between control design and controllability analysis of quantum systems and provides an effective engineering approach in controlling quantum systems with partial controllability information.

Notions of local controllability and optimal feedforward control for quantum systems

International Nuclear Information System (INIS)

Chakrabarti, Raj

2011-01-01

Local controllability is an essential concept for regulation and control of time-varying nonlinear dynamical systems; in the classical control logic it is at the foundation of neighboring optimal feedback and feedforward control. We introduce notions of local controllability suited to feedforward control of classical input disturbances in bilinear quantum systems evolving on projective spaces and Lie groups. Tests for local controllability based on a Gramian matrix analogous to the nonlinear local controllability Gramian, which allow assessment of which trajectories can be regulated by perturbative feedforward in the presence of classical input noise, are presented. These notions explicitly incorporate system bilinearity and the geometry of quantum states into the definition of local controllability of quantum systems. Associated feedforward strategies are described.

Notions of local controllability and optimal feedforward control for quantum systems

Energy Technology Data Exchange (ETDEWEB)

Chakrabarti, Raj, E-mail: rchakra@purdue.edu [School of Chemical Engineering, Purdue University, West Lafayette, IN 47907 (United States)

2011-05-06

Local controllability is an essential concept for regulation and control of time-varying nonlinear dynamical systems; in the classical control logic it is at the foundation of neighboring optimal feedback and feedforward control. We introduce notions of local controllability suited to feedforward control of classical input disturbances in bilinear quantum systems evolving on projective spaces and Lie groups. Tests for local controllability based on a Gramian matrix analogous to the nonlinear local controllability Gramian, which allow assessment of which trajectories can be regulated by perturbative feedforward in the presence of classical input noise, are presented. These notions explicitly incorporate system bilinearity and the geometry of quantum states into the definition of local controllability of quantum systems. Associated feedforward strategies are described.

Pretreatment tables predicting pathologic stage of locally advanced prostate cancer.

Science.gov (United States)

Joniau, Steven; Spahn, Martin; Briganti, Alberto; Gandaglia, Giorgio; Tombal, Bertrand; Tosco, Lorenzo; Marchioro, Giansilvio; Hsu, Chao-Yu; Walz, Jochen; Kneitz, Burkhard; Bader, Pia; Frohneberg, Detlef; Tizzani, Alessandro; Graefen, Markus; van Cangh, Paul; Karnes, R Jeffrey; Montorsi, Francesco; van Poppel, Hein; Gontero, Paolo

2015-02-01

Pretreatment tables for the prediction of pathologic stage have been published and validated for localized prostate cancer (PCa). No such tables are available for locally advanced (cT3a) PCa. To construct tables predicting pathologic outcome after radical prostatectomy (RP) for patients with cT3a PCa with the aim to help guide treatment decisions in clinical practice. This was a multicenter retrospective cohort study including 759 consecutive patients with cT3a PCa treated with RP between 1987 and 2010. Retropubic RP and pelvic lymphadenectomy. Patients were divided into pretreatment prostate-specific antigen (PSA) and biopsy Gleason score (GS) subgroups. These parameters were used to construct tables predicting pathologic outcome and the presence of positive lymph nodes (LNs) after RP for cT3a PCa using ordinal logistic regression. In the model predicting pathologic outcome, the main effects of biopsy GS and pretreatment PSA were significant. A higher GS and/or higher PSA level was associated with a more unfavorable pathologic outcome. The validation procedure, using a repeated split-sample method, showed good predictive ability. Regression analysis also showed an increasing probability of positive LNs with increasing PSA levels and/or higher GS. Limitations of the study are the retrospective design and the long study period. These novel tables predict pathologic stage after RP for patients with cT3a PCa based on pretreatment PSA level and biopsy GS. They can be used to guide decision making in men with locally advanced PCa. Our study might provide physicians with a useful tool to predict pathologic stage in locally advanced prostate cancer that might help select patients who may need multimodal treatment. Copyright © 2014 European Association of Urology. Published by Elsevier B.V. All rights reserved.

Singlet oxygen explicit dosimetry to predict long-term local tumor control for BPD-mediated photodynamic therapy

Science.gov (United States)

Kim, Michele M.; Penjweini, Rozhin; Ong, Yi Hong; Zhu, Timothy C.

2017-02-01

Photodynamic therapy (PDT) is a well-established treatment modality for cancer and other malignant diseases; however, quantities such as light fluence, photosensitizer photobleaching rate, and PDT dose do not fully account for all of the dynamic interactions between the key components involved. In particular, fluence rate (Φ) effects are not accounted for, which has a large effect on the oxygen consumption rate. In this preclinical study, reacted singlet oxygen [1O2]rx was investigated as a dosimetric quantity for PDT outcome. The ability of [1O2]rx to predict the long-term local tumor control rate (LCR) for BPD-mediated PDT was examined. Mice bearing radioactivelyinduced fibrosarcoma (RIF) tumors were treated with different in-air fluences (250, 300, and 350 J/cm2) and in-air ϕ (75, 100, and150 mW/cm2) with a BPD dose of 1 mg/kg and a drug-light interval of 3 hours. Treatment was delivered with a collimated laser beam of 1 cm diameter at 690 nm. Explicit dosimetry of initial tissue oxygen concentration, tissue optical properties, and BPD concentration was used to calculate [1O2]rx. Φ was calculated for the treatment volume based on Monte-Carlo simulations and measured tissue optical properties. Kaplan-Meier analyses for LCR were done for an endpoint of tumor volume defined as the product of the timeintegral of photosensitizer concentration and Φ at a 3 mm tumor depth. Preliminary studies show that [1O2]rx better correlates with LCR and is an effective dosimetric quantity that can predict treatment outcome.

Delta-Domain Predictive Control and Identification for Control

DEFF Research Database (Denmark)

Lauritsen, Morten Bach

1997-01-01

The present thesis is concerned with different aspects of modelling, control and identification of linear systems. Traditionally, discrete-time sampled-data systems are represented using shift-operator parametrizations. Such parametrizations are not suitable at fast sampling rates. An alternative...... minimum-variance predictor as a special case and to have a well-defined continuous-time limit. By means of this new prediction method a unified framework for discrete-time and continuous-time predictive control algorithms is developed. This contains a continuous-time like discrete-time predictive...... controller which is insensitive to the choice of sampling period and has a well-defined limit in the continuous-time case. Also more conventional discrete-time predictive control methods may be described within the unified approach. The predictive control algorithms are extended to frequency weighted...

Control of territorial communities in local government

Directory of Open Access Journals (Sweden)

О. А. Смоляр

2015-11-01

Full Text Available According to Art. 5 of the Constitution of Ukraine all power in Ukraine belong to people, which is primary, unified, inalienable and carried people through free will through elections, referendum and other forms of direct democracy, including those intended to control the activity of bodies and officials of the government and local government. Paper objective. At the local level the main supervisory entity in local government is local community. Consolidation of the Constitution of Ukraine the primary subject of local self-government territorial community not only meets current international practice, but also the historical traditions of Ukrainian people. Control territorial community in all phases of local government is one of the most important functions of managing the development of appropriate settlements, and therefore needs an effective mechanism of legal regulation, clearly define mutual rights and responsibilities of controlling and controlled entities. Recent research and publications analysis. Problems Assessment of local communities and the activities of local government officials in their works viewed Y.G. Barabash, P.M. Liubchenko, O.D. Skopych, Y.P. Strilets. However, given the variety of aspects of this area of research remain many questions that need resolving, on which depends largely on the further process of local governance. The paper main body. The existing regulation territorial communities can exercise control in local government actually only through local governments. The control of the executive bodies of village, town council municipalities can only be made through the appropriate council. The existing regulation of territorial communities can exercise control in local government actually only through local governments. The control of the executive bodies of village, town council municipalities can only be made through the appropriate council. The author emphasizes that only by implementing self-control powers local

Local and Integral Control of Workload

NARCIS (Netherlands)

M.B.M. de Koster (René); J. Wijngaard (Jacob)

1989-01-01

textabstractIn most of the literature on performance analysis of production systems, buffer are assumed to be controlled locally. In automated production systems buffers are not always the result of local physical space restrictions, but may also be software- controlled. Software-controlled buffers

Singlet oxygen explicit dosimetry to predict long-term local tumor control for Photofrin-mediated photodynamic therapy

Science.gov (United States)

Penjweini, Rozhin; Kim, Michele M.; Ong, Yi Hong; Zhu, Timothy C.

2017-02-01

Although photodynamic therapy (PDT) is an established modality for the treatment of cancer, current dosimetric quantities do not account for the variations in PDT oxygen consumption for different fluence rates (φ). In this study we examine the efficacy of reacted singlet oxygen concentration ([1O2]rx) to predict long-term local control rate (LCR) for Photofrin-mediated PDT. Radiation-induced fibrosarcoma (RIF) tumors in the right shoulders of female C3H mice are treated with different in-air fluences of 225-540 J/cm2 and in-air fluence rate (φair) of 50 and 75 mW/cm2 at 5 mg/kg Photofrin and a drug-light interval of 24 hours using a 1 cm diameter collimated laser beam at 630 nm wavelength. [1O2]rx is calculated by using a macroscopic model based on explicit dosimetry of Photofrin concentration, tissue optical properties, tissue oxygenation and blood flow changes during PDT. The tumor volume of each mouse is tracked for 90 days after PDT and Kaplan-Meier analyses for LCR are performed based on a tumor volume defined as a temporal integral of photosensitizer concentration and Φ at a 3 mm tumor depth. φ is calculated throughout the treatment volume based on Monte-Carlo simulation and measured tissue optical properties. Our preliminary studies show that [1O2]rx is the best dosimetric quantity that can predict tumor response and correlate with LCR. Moreover, [1O2]rx calculated using the blood flow changes was in agreement with [1O2]rx calculated based on the actual tissue oxygenation.

Neural-Fuzzy Digital Strategy of Continuous-Time Nonlinear Systems Using Adaptive Prediction and Random-Local-Optimization Design

Directory of Open Access Journals (Sweden)

Zhi-Ren Tsai

2013-01-01

Full Text Available A tracking problem, time-delay, uncertainty and stability analysis of a predictive control system are considered. The predictive control design is based on the input and output of neural plant model (NPM, and a recursive fuzzy predictive tracker has scaling factors which limit the value zone of measured data and cause the tuned parameters to converge to obtain a robust control performance. To improve the further control performance, the proposed random-local-optimization design (RLO for a model/controller uses offline initialization to obtain a near global optimal model/controller. Other issues are the considerations of modeling error, input-delay, sampling distortion, cost, greater flexibility, and highly reliable digital products of the model-based controller for the continuous-time (CT nonlinear system. They are solved by a recommended two-stage control design with the first-stage (offline RLO and second-stage (online adaptive steps. A theorizing method is then put forward to replace the sensitivity calculation, which reduces the calculation of Jacobin matrices of the back-propagation (BP method. Finally, the feedforward input of reference signals helps the digital fuzzy controller improve the control performance, and the technique works to control the CT systems precisely.

Evaluation and comparison of mammalian subcellular localization prediction methods

Directory of Open Access Journals (Sweden)

Fink J Lynn

2006-12-01

Full Text Available Abstract Background Determination of the subcellular location of a protein is essential to understanding its biochemical function. This information can provide insight into the function of hypothetical or novel proteins. These data are difficult to obtain experimentally but have become especially important since many whole genome sequencing projects have been finished and many resulting protein sequences are still lacking detailed functional information. In order to address this paucity of data, many computational prediction methods have been developed. However, these methods have varying levels of accuracy and perform differently based on the sequences that are presented to the underlying algorithm. It is therefore useful to compare these methods and monitor their performance. Results In order to perform a comprehensive survey of prediction methods, we selected only methods that accepted large batches of protein sequences, were publicly available, and were able to predict localization to at least nine of the major subcellular locations (nucleus, cytosol, mitochondrion, extracellular region, plasma membrane, Golgi apparatus, endoplasmic reticulum (ER, peroxisome, and lysosome. The selected methods were CELLO, MultiLoc, Proteome Analyst, pTarget and WoLF PSORT. These methods were evaluated using 3763 mouse proteins from SwissProt that represent the source of the training sets used in development of the individual methods. In addition, an independent evaluation set of 2145 mouse proteins from LOCATE with a bias towards the subcellular localization underrepresented in SwissProt was used. The sensitivity and specificity were calculated for each method and compared to a theoretical value based on what might be observed by random chance. Conclusion No individual method had a sufficient level of sensitivity across both evaluation sets that would enable reliable application to hypothetical proteins. All methods showed lower performance on the LOCATE

SPE dose prediction using locally weighted regression

International Nuclear Information System (INIS)

Hines, J. W.; Townsend, L. W.; Nichols, T. F.

2005-01-01

When astronauts are outside earth's protective magnetosphere, they are subject to large radiation doses resulting from solar particle events (SPEs). The total dose received from a major SPE in deep space could cause severe radiation poisoning. The dose is usually received over a 20-40 h time interval but the event's effects may be mitigated with an early warning system. This paper presents a method to predict the total dose early in the event. It uses a locally weighted regression model, which is easier to train and provides predictions as accurate as neural network models previously used. (authors)

SPE dose prediction using locally weighted regression

International Nuclear Information System (INIS)

Hines, J. W.; Townsend, L. W.; Nichols, T. F.

2005-01-01

When astronauts are outside Earth's protective magnetosphere, they are subject to large radiation doses resulting from solar particle events. The total dose received from a major solar particle event in deep space could cause severe radiation poisoning. The dose is usually received over a 20-40 h time interval but the event's effects may be reduced with an early warning system. This paper presents a method to predict the total dose early in the event. It uses a locally weighted regression model, which is easier to train, and provides predictions as accurate as the neural network models that were used previously. (authors)

ClubSub-P: Cluster-based subcellular localization prediction for Gram-negative bacteria and Archaea.

Directory of Open Access Journals (Sweden)

Nagarajan eParamasivam

2011-11-01

Full Text Available The subcellular localization of proteins provides important clues to their function in a cell. In our efforts to predict useful vaccine targets against Gram-negative bacteria, we noticed that misannotated start codons frequently lead to wrongly assigned subcellular localizations. This and other problems in subcellular localization prediction, such as the relatively high false positive and false negative rates of some tools, can be avoided by applying multiple prediction tools to groups of homologous proteins. Here we present ClubSub-P, an online database that combines existing subcellular localization prediction tools into a consensus pipeline from more than 600 proteomes of fully sequenced microorganisms. On top of the consensus prediction at the level of single sequences, the tool uses clusters of homologous proteins from Gram-negative bacteria and from Archaea to eliminate false positive and false negative predictions. ClubSub-P can assign the subcellular localization of proteins from Gram-negative bacteria and Archaea with high precision. The database is searchable, and can easily be expanded using either new bacterial genomes or new prediction tools as they become available. This will further improve the performance of the subcellular localization prediction, as well as the detection of misannotated start codons and other annotation errors. ClubSub-P is available online at http://toolkit.tuebingen.mpg.de/clubsubp/

Neural Network Classifiers for Local Wind Prediction.

Science.gov (United States)

Kretzschmar, Ralf; Eckert, Pierre; Cattani, Daniel; Eggimann, Fritz

2004-05-01

This paper evaluates the quality of neural network classifiers for wind speed and wind gust prediction with prediction lead times between +1 and +24 h. The predictions were realized based on local time series and model data. The selection of appropriate input features was initiated by time series analysis and completed by empirical comparison of neural network classifiers trained on several choices of input features. The selected input features involved day time, yearday, features from a single wind observation device at the site of interest, and features derived from model data. The quality of the resulting classifiers was benchmarked against persistence for two different sites in Switzerland. The neural network classifiers exhibited superior quality when compared with persistence judged on a specific performance measure, hit and false-alarm rates.

Should Aggressive Surgical Local Control Be Attempted in All Patients with Metastatic or Pelvic Ewing's Sarcoma?

Science.gov (United States)

Thorpe, Steven W.; Weiss, Kurt R.; Goodman, Mark A.; Heyl, Alma E.; McGough, Richard L.

2012-01-01

In previous reports, patients with Ewing's sarcoma received radiation therapy (XRT) for definitive local control because metastatic disease and pelvic location were thought to preclude aggressive local treatment. We sought to determine if single-site metastatic disease should be treated differently from multicentric-metastatic disease. We also wanted to reinvestigate the impact of XRT, pelvic location, and local recurrence on outcomes. Our results demonstrated a significant difference in overall survival (OS) between patients with either localized disease or a single-metastatic site and patients with multicentric-metastatic disease (P = 0.004). Local control was also found to be an independent predictor of outcomes as demonstrated by a significant difference in OS between those with and without local recurrence (P = 0.001). Axial and pelvic location did not predict a decreased OS. Based on these results, we concluded that pelvic location and the diagnosis of metastatic disease at diagnosis should not preclude aggressive local control, except in cases of multicentric-metastatic disease. PMID:22550427

MU-LOC: A Machine-Learning Method for Predicting Mitochondrially Localized Proteins in Plants

DEFF Research Database (Denmark)

Zhang, Ning; Rao, R Shyama Prasad; Salvato, Fernanda

2018-01-01

-sequence or a multitude of internal signals. Compared with experimental approaches, computational predictions provide an efficient way to infer subcellular localization of a protein. However, it is still challenging to predict plant mitochondrially localized proteins accurately due to various limitations. Consequently......, the performance of current tools can be improved with new data and new machine-learning methods. We present MU-LOC, a novel computational approach for large-scale prediction of plant mitochondrial proteins. We collected a comprehensive dataset of plant subcellular localization, extracted features including amino...

Globalization and localization of Management Control Systems

DEFF Research Database (Denmark)

Toldbod, Thomas; Israelsen, Poul

2014-01-01

Through an empirical case study this article examines the operation of multiple management control systems as a package in a Danish manufacturing company. The analysis focuses on four different management control systems; cybernetic controls, planning controls, reward controls, and administrative...... have more particular characteristics. Specifically, this study finds that cybernetic controls and administrative controls are designed as global management control systems. Planning controls are glocal systems and reward & compensation controls assume local characteristics. The finding leads...... controls, through the theoretical lens of globalization, localization, and glocalization. The analysis documents that these different management control systems are affected differently by the processes of globalization and localization, whereby some are universal throughout the organization and others...

Adaptive filtering prediction and control

CERN Document Server

Goodwin, Graham C

2009-01-01

Preface1. Introduction to Adaptive TechniquesPart 1. Deterministic Systems2. Models for Deterministic Dynamical Systems3. Parameter Estimation for Deterministic Systems4. Deterministic Adaptive Prediction5. Control of Linear Deterministic Systems6. Adaptive Control of Linear Deterministic SystemsPart 2. Stochastic Systems7. Optimal Filtering and Prediction8. Parameter Estimation for Stochastic Dynamic Systems9. Adaptive Filtering and Prediction10. Control of Stochastic Systems11. Adaptive Control of Stochastic SystemsAppendicesA. A Brief Review of Some Results from Systems TheoryB. A Summary o

Determinates of tumor response to radiation: Tumor cells, tumor stroma and permanent local control

International Nuclear Information System (INIS)

Li, Wende; Huang, Peigen; Chen, David J.; Gerweck, Leo E.

2014-01-01

Background and purpose: The causes of tumor response variation to radiation remain obscure, thus hampering the development of predictive assays and strategies to decrease resistance. The present study evaluates the impact of host tumor stromal elements and the in vivo environment on tumor cell kill, and relationship between tumor cell radiosensitivity and the tumor control dose. Material and methods: Five endpoints were evaluated and compared in a radiosensitive DNA double-strand break repair-defective (DNA-PKcs −/− ) tumor line, and its DNA-PKcs repair competent transfected counterpart. In vitro colony formation assays were performed on in vitro cultured cells, on cells obtained directly from tumors, and on cells irradiated in situ. Permanent local control was assessed by the TCD 50 assay. Vascular effects were evaluated by functional vascular density assays. Results: The fraction of repair competent and repair deficient tumor cells surviving radiation did not substantially differ whether irradiated in vitro, i.e., in the absence of host stromal elements and factors, from the fraction of cells killed following in vivo irradiation. Additionally, the altered tumor cell sensitivity resulted in a proportional change in the dose required to achieve permanent local control. The estimated number of tumor cells per tumor, their cloning efficiency and radiosensitivity, all assessed by in vitro assays, were used to predict successfully, the measured tumor control doses. Conclusion: The number of clonogens per tumor and their radiosensitivity govern the permanent local control dose

New prediction of chaotic time series based on local Lyapunov exponent

International Nuclear Information System (INIS)

Zhang Yong

2013-01-01

A new method of predicting chaotic time series is presented based on a local Lyapunov exponent, by quantitatively measuring the exponential rate of separation or attraction of two infinitely close trajectories in state space. After reconstructing state space from one-dimensional chaotic time series, neighboring multiple-state vectors of the predicting point are selected to deduce the prediction formula by using the definition of the local Lyapunov exponent. Numerical simulations are carried out to test its effectiveness and verify its higher precision over two older methods. The effects of the number of referential state vectors and added noise on forecasting accuracy are also studied numerically. (general)

MultiLoc2: integrating phylogeny and Gene Ontology terms improves subcellular protein localization prediction

Directory of Open Access Journals (Sweden)

Kohlbacher Oliver

2009-09-01

Full Text Available Abstract Background Knowledge of subcellular localization of proteins is crucial to proteomics, drug target discovery and systems biology since localization and biological function are highly correlated. In recent years, numerous computational prediction methods have been developed. Nevertheless, there is still a need for prediction methods that show more robustness and higher accuracy. Results We extended our previous MultiLoc predictor by incorporating phylogenetic profiles and Gene Ontology terms. Two different datasets were used for training the system, resulting in two versions of this high-accuracy prediction method. One version is specialized for globular proteins and predicts up to five localizations, whereas a second version covers all eleven main eukaryotic subcellular localizations. In a benchmark study with five localizations, MultiLoc2 performs considerably better than other methods for animal and plant proteins and comparably for fungal proteins. Furthermore, MultiLoc2 performs clearly better when using a second dataset that extends the benchmark study to all eleven main eukaryotic subcellular localizations. Conclusion MultiLoc2 is an extensive high-performance subcellular protein localization prediction system. By incorporating phylogenetic profiles and Gene Ontology terms MultiLoc2 yields higher accuracies compared to its previous version. Moreover, it outperforms other prediction systems in two benchmarks studies. MultiLoc2 is available as user-friendly and free web-service, available at: http://www-bs.informatik.uni-tuebingen.de/Services/MultiLoc2.

Protein Sub-Nuclear Localization Prediction Using SVM and Pfam Domain Information

Science.gov (United States)

Kumar, Ravindra; Jain, Sohni; Kumari, Bandana; Kumar, Manish

2014-01-01

The nucleus is the largest and the highly organized organelle of eukaryotic cells. Within nucleus exist a number of pseudo-compartments, which are not separated by any membrane, yet each of them contains only a specific set of proteins. Understanding protein sub-nuclear localization can hence be an important step towards understanding biological functions of the nucleus. Here we have described a method, SubNucPred developed by us for predicting the sub-nuclear localization of proteins. This method predicts protein localization for 10 different sub-nuclear locations sequentially by combining presence or absence of unique Pfam domain and amino acid composition based SVM model. The prediction accuracy during leave-one-out cross-validation for centromeric proteins was 85.05%, for chromosomal proteins 76.85%, for nuclear speckle proteins 81.27%, for nucleolar proteins 81.79%, for nuclear envelope proteins 79.37%, for nuclear matrix proteins 77.78%, for nucleoplasm proteins 76.98%, for nuclear pore complex proteins 88.89%, for PML body proteins 75.40% and for telomeric proteins it was 83.33%. Comparison with other reported methods showed that SubNucPred performs better than existing methods. A web-server for predicting protein sub-nuclear localization named SubNucPred has been established at http://14.139.227.92/mkumar/subnucpred/. Standalone version of SubNucPred can also be downloaded from the web-server. PMID:24897370

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...

Local control room

CERN Multimedia

CERN PhotoLab

1972-01-01

Local control room in the ejection building : all electronics pertaining to proton distribution and concomitants such as beam gymnastics and diagnostics at high energies will eventually be gathered here. Shown is the first of two rows of fast ejection electronic racks. It includes only what is necessary for operation.

Event-triggered decentralized robust model predictive control for constrained large-scale interconnected systems

Directory of Open Access Journals (Sweden)

Ling Lu

2016-12-01

Full Text Available This paper considers the problem of event-triggered decentralized model predictive control (MPC for constrained large-scale linear systems subject to additive bounded disturbances. The constraint tightening method is utilized to formulate the MPC optimization problem. The local predictive control law for each subsystem is determined aperiodically by relevant triggering rule which allows a considerable reduction of the computational load. And then, the robust feasibility and closed-loop stability are proved and it is shown that every subsystem state will be driven into a robust invariant set. Finally, the effectiveness of the proposed approach is illustrated via numerical simulations.

Analytical model for local scour prediction around hydrokinetic turbine foundations

Science.gov (United States)

Musa, M.; Heisel, M.; Hill, C.; Guala, M.

2017-12-01

Marine and Hydrokinetic renewable energy is an emerging sustainable and secure technology which produces clean energy harnessing water currents from mostly tidal and fluvial waterways. Hydrokinetic turbines are typically anchored at the bottom of the channel, which can be erodible or non-erodible. Recent experiments demonstrated the interactions between operating turbines and an erodible surface with sediment transport, resulting in a remarkable localized erosion-deposition pattern significantly larger than those observed by static in-river construction such as bridge piers, etc. Predicting local scour geometry at the base of hydrokinetic devices is extremely important during foundation design, installation, operation, and maintenance (IO&M), and long-term structural integrity. An analytical modeling framework is proposed applying the phenomenological theory of turbulence to the flow structures that promote the scouring process at the base of a turbine. The evolution of scour is directly linked to device operating conditions through the turbine drag force, which is inferred to locally dictate the energy dissipation rate in the scour region. The predictive model is validated using experimental data obtained at the University of Minnesota's St. Anthony Falls Laboratory (SAFL), covering two sediment mobility regimes (clear water and live bed), different turbine designs, hydraulic parameters, grain size distribution and bedform types. The model is applied to a potential prototype scale deployment in the lower Mississippi River, demonstrating its practical relevance and endorsing the feasibility of hydrokinetic energy power plants in large sandy rivers. Multi-turbine deployments are further studied experimentally by monitoring both local and non-local geomorphic effects introduced by a twelve turbine staggered array model installed in a wide channel at SAFL. Local scour behind each turbine is well captured by the theoretical predictive model. However, multi

Model predictive Controller for Mobile Robot

OpenAIRE

Alireza Rezaee

2017-01-01

This paper proposes a Model Predictive Controller (MPC) for control of a P2AT mobile robot. MPC refers to a group of controllers that employ a distinctly identical model of process to predict its future behavior over an extended prediction horizon. The design of a MPC is formulated as an optimal control problem. Then this problem is considered as linear quadratic equation (LQR) and is solved by making use of Ricatti equation. To show the effectiveness of the proposed method this controller is...

Binding Ligand Prediction for Proteins Using Partial Matching of Local Surface Patches

Directory of Open Access Journals (Sweden)

Lee Sael

2010-12-01

Full Text Available Functional elucidation of uncharacterized protein structures is an important task in bioinformatics. We report our new approach for structure-based function prediction which captures local surface features of ligand binding pockets. Function of proteins, specifically, binding ligands of proteins, can be predicted by finding similar local surface regions of known proteins. To enable partial comparison of binding sites in proteins, a weighted bipartite matching algorithm is used to match pairs of surface patches. The surface patches are encoded with the 3D Zernike descriptors. Unlike the existing methods which compare global characteristics of the protein fold or the global pocket shape, the local surface patch method can find functional similarity between non-homologous proteins and binding pockets for flexible ligand molecules. The proposed method improves prediction results over global pocket shape-based method which was previously developed by our group.

Binding ligand prediction for proteins using partial matching of local surface patches.

Science.gov (United States)

Sael, Lee; Kihara, Daisuke

2010-01-01

Functional elucidation of uncharacterized protein structures is an important task in bioinformatics. We report our new approach for structure-based function prediction which captures local surface features of ligand binding pockets. Function of proteins, specifically, binding ligands of proteins, can be predicted by finding similar local surface regions of known proteins. To enable partial comparison of binding sites in proteins, a weighted bipartite matching algorithm is used to match pairs of surface patches. The surface patches are encoded with the 3D Zernike descriptors. Unlike the existing methods which compare global characteristics of the protein fold or the global pocket shape, the local surface patch method can find functional similarity between non-homologous proteins and binding pockets for flexible ligand molecules. The proposed method improves prediction results over global pocket shape-based method which was previously developed by our group.

Prediction of resource volumes at untested locations using simple local prediction models

Science.gov (United States)

Attanasi, E.D.; Coburn, T.C.; Freeman, P.A.

2006-01-01

This paper shows how local spatial nonparametric prediction models can be applied to estimate volumes of recoverable gas resources at individual undrilled sites, at multiple sites on a regional scale, and to compute confidence bounds for regional volumes based on the distribution of those estimates. An approach that combines cross-validation, the jackknife, and bootstrap procedures is used to accomplish this task. Simulation experiments show that cross-validation can be applied beneficially to select an appropriate prediction model. The cross-validation procedure worked well for a wide range of different states of nature and levels of information. Jackknife procedures are used to compute individual prediction estimation errors at undrilled locations. The jackknife replicates also are used with a bootstrap resampling procedure to compute confidence bounds for the total volume. The method was applied to data (partitioned into a training set and target set) from the Devonian Antrim Shale continuous-type gas play in the Michigan Basin in Otsego County, Michigan. The analysis showed that the model estimate of total recoverable volumes at prediction sites is within 4 percent of the total observed volume. The model predictions also provide frequency distributions of the cell volumes at the production unit scale. Such distributions are the basis for subsequent economic analyses. ?? Springer Science+Business Media, LLC 2007.

A Gaussian mixture copula model based localized Gaussian process regression approach for long-term wind speed prediction

International Nuclear Information System (INIS)

Yu, Jie; Chen, Kuilin; Mori, Junichi; Rashid, Mudassir M.

2013-01-01

Optimizing wind power generation and controlling the operation of wind turbines to efficiently harness the renewable wind energy is a challenging task due to the intermittency and unpredictable nature of wind speed, which has significant influence on wind power production. A new approach for long-term wind speed forecasting is developed in this study by integrating GMCM (Gaussian mixture copula model) and localized GPR (Gaussian process regression). The time series of wind speed is first classified into multiple non-Gaussian components through the Gaussian mixture copula model and then Bayesian inference strategy is employed to incorporate the various non-Gaussian components using the posterior probabilities. Further, the localized Gaussian process regression models corresponding to different non-Gaussian components are built to characterize the stochastic uncertainty and non-stationary seasonality of the wind speed data. The various localized GPR models are integrated through the posterior probabilities as the weightings so that a global predictive model is developed for the prediction of wind speed. The proposed GMCM–GPR approach is demonstrated using wind speed data from various wind farm locations and compared against the GMCM-based ARIMA (auto-regressive integrated moving average) and SVR (support vector regression) methods. In contrast to GMCM–ARIMA and GMCM–SVR methods, the proposed GMCM–GPR model is able to well characterize the multi-seasonality and uncertainty of wind speed series for accurate long-term prediction. - Highlights: • A novel predictive modeling method is proposed for long-term wind speed forecasting. • Gaussian mixture copula model is estimated to characterize the multi-seasonality. • Localized Gaussian process regression models can deal with the random uncertainty. • Multiple GPR models are integrated through Bayesian inference strategy. • The proposed approach shows higher prediction accuracy and reliability

Model predictive control using fuzzy decision functions

NARCIS (Netherlands)

Kaymak, U.; Costa Sousa, da J.M.

2001-01-01

Fuzzy predictive control integrates conventional model predictive control with techniques from fuzzy multicriteria decision making, translating the goals and the constraints to predictive control in a transparent way. The information regarding the (fuzzy) goals and the (fuzzy) constraints of the

Model Prediction Control For Water Management Using Adaptive Prediction Accuracy

NARCIS (Netherlands)

Tian, X.; Negenborn, R.R.; Van Overloop, P.J.A.T.M.; Mostert, E.

2014-01-01

In the field of operational water management, Model Predictive Control (MPC) has gained popularity owing to its versatility and flexibility. The MPC controller, which takes predictions, time delay and uncertainties into account, can be designed for multi-objective management problems and for

Unreachable Setpoints in Model Predictive Control

DEFF Research Database (Denmark)

Rawlings, James B.; Bonné, Dennis; Jørgensen, John Bagterp

2008-01-01

In this work, a new model predictive controller is developed that handles unreachable setpoints better than traditional model predictive control methods. The new controller induces an interesting fast/slow asymmetry in the tracking response of the system. Nominal asymptotic stability of the optimal...... steady state is established for terminal constraint model predictive control (MPC). The region of attraction is the steerable set. Existing analysis methods for closed-loop properties of MPC are not applicable to this new formulation, and a new analysis method is developed. It is shown how to extend...

Dynamic Algorithm for LQGPC Predictive Control

DEFF Research Database (Denmark)

Hangstrup, M.; Ordys, A.W.; Grimble, M.J.

1998-01-01

In this paper the optimal control law is derived for a multi-variable state space Linear Quadratic Gaussian Predictive Controller (LQGPC). A dynamic performance index is utilized resulting in an optimal steady state controller. Knowledge of future reference values is incorporated into the control......In this paper the optimal control law is derived for a multi-variable state space Linear Quadratic Gaussian Predictive Controller (LQGPC). A dynamic performance index is utilized resulting in an optimal steady state controller. Knowledge of future reference values is incorporated...... into the controller design and the solution is derived using the method of Lagrange multipliers. It is shown how well-known GPC controller can be obtained as a special case of the LQGPC controller design. The important advantage of using the LQGPC framework for designing predictive, e.g. GPS is that LQGPC enables...

Online prediction and control in nonlinear stochastic systems

DEFF Research Database (Denmark)

Nielsen, Torben Skov

2002-01-01

speed and the relationship between (primarily) wind speed and wind power (the power curve). In paper G the model parameters are estimated using a RLS algorithm and any systematic time-variation of the model parameters is disregarded. Two di erent parameterizations of the power curve is considered...... are estimated using the algorithm proposed in paper C. The power curve and the diurnal variation of wind speed is estimated separately using the local polynomial regression procedure described in paper A . In paper J the parameters of the prediction model is assumed to be smooth functions of wind direction (and......The present thesis consists of a summary report and ten research papers. The subject of the thesis is on-line prediction and control of non-linear and non-stationary systems based on stochastic modelling. The thesis consists of three parts where the rst part deals with on-line estimation in linear...

Embedded controllers for local board-control

CERN Document Server

Neufeld, Niko; Mini, Giuseppe; Sannino, Mario; Guzik, Zbigniew; Jacobsson, Richard; Jost, Beat

2005-01-01

The LHCb experiment at CERN has a large number of custom electronic boards performing high-speed data-processing. Like in any large experiment the control and monitoring of these crate-mounted boards must be integrated into the overall control-system. Traditionally this has been done by using buses like VME on the back-plane of the crates. LHCb has chosen to equip every board with an embedded micro-controller and connecting them in a large Local Area Network. The intelligence of these devices allows complex (soft) real-time control and monitoring, required for modern powerful FPGA driven electronics. Moreover each board has its own, isolated control access path, which increases the robustness of the entire system. The system is now in pre-production at several sites and will go into full production during next year. The hardware and software will be discussed and experiences from the R&D and pre-production will be reviewed, with an emphasis on advantages and difficulties of this approach to board-control.

Wind turbine control and model predictive control for uncertain systems

DEFF Research Database (Denmark)

Thomsen, Sven Creutz

as disturbance models for controller design. The theoretical study deals with Model Predictive Control (MPC). MPC is an optimal control method which is characterized by the use of a receding prediction horizon. MPC has risen in popularity due to its inherent ability to systematically account for time...

Improved fuzzy PID controller design using predictive functional control structure.

Science.gov (United States)

Wang, Yuzhong; Jin, Qibing; Zhang, Ridong

2017-11-01

In conventional PID scheme, the ensemble control performance may be unsatisfactory due to limited degrees of freedom under various kinds of uncertainty. To overcome this disadvantage, a novel PID control method that inherits the advantages of fuzzy PID control and the predictive functional control (PFC) is presented and further verified on the temperature model of a coke furnace. Based on the framework of PFC, the prediction of the future process behavior is first obtained using the current process input signal. Then, the fuzzy PID control based on the multi-step prediction is introduced to acquire the optimal control law. Finally, the case study on a temperature model of a coke furnace shows the effectiveness of the fuzzy PID control scheme when compared with conventional PID control and fuzzy self-adaptive PID control. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.

Enabling Controlling Complex Networks with Local Topological Information.

Science.gov (United States)

Li, Guoqi; Deng, Lei; Xiao, Gaoxi; Tang, Pei; Wen, Changyun; Hu, Wuhua; Pei, Jing; Shi, Luping; Stanley, H Eugene

2018-03-15

Complex networks characterize the nature of internal/external interactions in real-world systems including social, economic, biological, ecological, and technological networks. Two issues keep as obstacles to fulfilling control of large-scale networks: structural controllability which describes the ability to guide a dynamical system from any initial state to any desired final state in finite time, with a suitable choice of inputs; and optimal control, which is a typical control approach to minimize the cost for driving the network to a predefined state with a given number of control inputs. For large complex networks without global information of network topology, both problems remain essentially open. Here we combine graph theory and control theory for tackling the two problems in one go, using only local network topology information. For the structural controllability problem, a distributed local-game matching method is proposed, where every node plays a simple Bayesian game with local information and local interactions with adjacent nodes, ensuring a suboptimal solution at a linear complexity. Starring from any structural controllability solution, a minimizing longest control path method can efficiently reach a good solution for the optimal control in large networks. Our results provide solutions for distributed complex network control and demonstrate a way to link the structural controllability and optimal control together.

State Aid, Voter Power and Local Control in Education.

Science.gov (United States)

Zak, Itai; Glasman, Naftaly S.

1979-01-01

Not only did voter power contribute meaningfully to local control behavior regardless of the exact shape of the relations between state aid and local control, but the hypothesized inverse relationship between state aid and local control did not receive support. Journal availability: see EA 511 898. (Author/IRT)

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

Science.gov (United States)

Nandola, Naresh N.; Rivera, Daniel E.

2011-01-01

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

Predicting Posttraumatic Stress Symptom Prevalence and Local Distribution after an Earthquake with Scarce Data.

Science.gov (United States)

Dussaillant, Francisca; Apablaza, Mauricio

2017-08-01

After a major earthquake, the assignment of scarce mental health emergency personnel to different geographic areas is crucial to the effective management of the crisis. The scarce information that is available in the aftermath of a disaster may be valuable in helping predict where are the populations that are in most need. The objectives of this study were to derive algorithms to predict posttraumatic stress (PTS) symptom prevalence and local distribution after an earthquake and to test whether there are algorithms that require few input data and are still reasonably predictive. A rich database of PTS symptoms, informed after Chile's 2010 earthquake and tsunami, was used. Several model specifications for the mean and centiles of the distribution of PTS symptoms, together with posttraumatic stress disorder (PTSD) prevalence, were estimated via linear and quantile regressions. The models varied in the set of covariates included. Adjusted R2 for the most liberal specifications (in terms of numbers of covariates included) ranged from 0.62 to 0.74, depending on the outcome. When only including peak ground acceleration (PGA), poverty rate, and household damage in linear and quadratic form, predictive capacity was still good (adjusted R2 from 0.59 to 0.67 were obtained). Information about local poverty, household damage, and PGA can be used as an aid to predict PTS symptom prevalence and local distribution after an earthquake. This can be of help to improve the assignment of mental health personnel to the affected localities. Dussaillant F , Apablaza M . Predicting posttraumatic stress symptom prevalence and local distribution after an earthquake with scarce data. Prehosp Disaster Med. 2017;32(4):357-367.

MU-LOC: A Machine-Learning Method for Predicting Mitochondrially Localized Proteins in Plants

Directory of Open Access Journals (Sweden)

Ning Zhang

2018-05-01

Full Text Available Targeting and translocation of proteins to the appropriate subcellular compartments are crucial for cell organization and function. Newly synthesized proteins are transported to mitochondria with the assistance of complex targeting sequences containing either an N-terminal pre-sequence or a multitude of internal signals. Compared with experimental approaches, computational predictions provide an efficient way to infer subcellular localization of a protein. However, it is still challenging to predict plant mitochondrially localized proteins accurately due to various limitations. Consequently, the performance of current tools can be improved with new data and new machine-learning methods. We present MU-LOC, a novel computational approach for large-scale prediction of plant mitochondrial proteins. We collected a comprehensive dataset of plant subcellular localization, extracted features including amino acid composition, protein position weight matrix, and gene co-expression information, and trained predictors using deep neural network and support vector machine. Benchmarked on two independent datasets, MU-LOC achieved substantial improvements over six state-of-the-art tools for plant mitochondrial targeting prediction. In addition, MU-LOC has the advantage of predicting plant mitochondrial proteins either possessing or lacking N-terminal pre-sequences. We applied MU-LOC to predict candidate mitochondrial proteins for the whole proteome of Arabidopsis and potato. MU-LOC is publicly available at http://mu-loc.org.

Model Predictive Controller for Active Demand Side Management with PV Self-consumption in an Intelligent Building

DEFF Research Database (Denmark)

Zong, Yi; Mihet-Popa, Lucian; Kullmann, Daniel

2012-01-01

This paper presents a Model Predictive Controller (MPC) for electrical heaters’ predictive power consumption including maximizing the use of local generation (e.g. solar power) in an intelligent building. The MPC is based on dynamic power price and weather forecast, considering users’ comfort...... settings to meet an optimization objective such as minimum cost and minimum reference temperature error. It demonstrates that this MPC strategy can realize load shifting, and maximize the PV self-consumption in the residential sector. With this demand side control study, it is expected that MPC strategy...

A Particle Swarm Optimization-Based Approach with Local Search for Predicting Protein Folding.

Science.gov (United States)

Yang, Cheng-Hong; Lin, Yu-Shiun; Chuang, Li-Yeh; Chang, Hsueh-Wei

2017-10-01

The hydrophobic-polar (HP) model is commonly used for predicting protein folding structures and hydrophobic interactions. This study developed a particle swarm optimization (PSO)-based algorithm combined with local search algorithms; specifically, the high exploration PSO (HEPSO) algorithm (which can execute global search processes) was combined with three local search algorithms (hill-climbing algorithm, greedy algorithm, and Tabu table), yielding the proposed HE-L-PSO algorithm. By using 20 known protein structures, we evaluated the performance of the HE-L-PSO algorithm in predicting protein folding in the HP model. The proposed HE-L-PSO algorithm exhibited favorable performance in predicting both short and long amino acid sequences with high reproducibility and stability, compared with seven reported algorithms. The HE-L-PSO algorithm yielded optimal solutions for all predicted protein folding structures. All HE-L-PSO-predicted protein folding structures possessed a hydrophobic core that is similar to normal protein folding.

Error Control in Distributed Node Self-Localization

Directory of Open Access Journals (Sweden)

Ying Zhang

2008-03-01

Full Text Available Location information of nodes in an ad hoc sensor network is essential to many tasks such as routing, cooperative sensing, and service delivery. Distributed node self-localization is lightweight and requires little communication overhead, but often suffers from the adverse effects of error propagation. Unlike other localization papers which focus on designing elaborate localization algorithms, this paper takes a different perspective, focusing on the error propagation problem, addressing questions such as where localization error comes from and how it propagates from node to node. To prevent error from propagating and accumulating, we develop an error-control mechanism based on characterization of node uncertainties and discrimination between neighboring nodes. The error-control mechanism uses only local knowledge and is fully decentralized. Simulation results have shown that the active selection strategy significantly mitigates the effect of error propagation for both range and directional sensors. It greatly improves localization accuracy and robustness.

Hybrid Predictive Control for Dynamic Transport Problems

CERN Document Server

Núñez, Alfredo A; Cortés, Cristián E

2013-01-01

Hybrid Predictive Control for Dynamic Transport Problems develops methods for the design of predictive control strategies for nonlinear-dynamic hybrid discrete-/continuous-variable systems. The methodology is designed for real-time applications, particularly the study of dynamic transport systems. Operational and service policies are considered, as well as cost reduction. The control structure is based on a sound definition of the key variables and their evolution. A flexible objective function able to capture the predictive behaviour of the system variables is described. Coupled with efficient algorithms, mainly drawn from the area of computational intelligence, this is shown to optimize performance indices for real-time applications. The framework of the proposed predictive control methodology is generic and, being able to solve nonlinear mixed-integer optimization problems dynamically, is readily extendable to other industrial processes. The main topics of this book are: ●hybrid predictive control (HPC) ...

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...

Rupture prediction for induction bends under opening mode bending with emphasis on strain localization

International Nuclear Information System (INIS)

Mitsuya, Masaki; Sakanoue, Takashi

2015-01-01

This study focuses on the opening mode of induction bends; this mode represents the deformation outside a bend. Bending experiments on induction bends are shown and the manner of failure of these bends was investigated. Ruptures occur at the intrados of the bends, which undergo tensile stress, and accompany the local reduction of wall thickness, i.e., necking that indicates strain localization. By implementing finite element analysis (FEA), it was shown that the rupture is dominated not by the fracture criterion of material but by the initiation of strain localization that is a deformation characteristic of the material. These ruptures are due to the rapid increase of local strain after the initiation of strain localization and suddenly reach the fracture criterion. For the evaluation of the deformability of the bends, a method based on FEA that can predict the displacement at the rupture is proposed. We show that the yield surface shape and the true stress–strain relationship after uniform elongation have to be defined on the basis of the actual properties of the bend material. The von Mises yield criterion, which is commonly used in cases of elastic–plastic FEA, could not predict the rupture and overestimated the deformability. In contrast, a yield surface obtained by performing tensile tests on a biaxial specimen could predict the rupture. The prediction of the rupture was accomplished by an inverse calibration method that determined the true stress-strain relationship after uniform elongation. As an alternative to the inverse calibration, a simple extrapolation method of the true stress-strain relationship after uniform elongation which can predict the rupture is proposed. - Highlights: • A method based on FEA that can predict the displacement at the rupture is proposed. • The yield surface shape and the true stress–strain have to be defined precisely. • The von Mises yield criterion overestimated the deformability. • The ruptures are due to the

Common neighbours and the local-community-paradigm for topological link prediction in bipartite networks

International Nuclear Information System (INIS)

Daminelli, Simone; Thomas, Josephine Maria; Durán, Claudio; Vittorio Cannistraci, Carlo

2015-01-01

Bipartite networks are powerful descriptions of complex systems characterized by two different classes of nodes and connections allowed only across but not within the two classes. Unveiling physical principles, building theories and suggesting physical models to predict bipartite links such as product-consumer connections in recommendation systems or drug–target interactions in molecular networks can provide priceless information to improve e-commerce or to accelerate pharmaceutical research. The prediction of nonobserved connections starting from those already present in the topology of a network is known as the link-prediction problem. It represents an important subject both in many-body interaction theory in physics and in new algorithms for applied tools in computer science. The rationale is that the existing connectivity structure of a network can suggest where new connections can appear with higher likelihood in an evolving network, or where nonobserved connections are missing in a partially known network. Surprisingly, current complex network theory presents a theoretical bottle-neck: a general framework for local-based link prediction directly in the bipartite domain is missing. Here, we overcome this theoretical obstacle and present a formal definition of common neighbour index and local-community-paradigm (LCP) for bipartite networks. As a consequence, we are able to introduce the first node-neighbourhood-based and LCP-based models for topological link prediction that utilize the bipartite domain. We performed link prediction evaluations in several networks of different size and of disparate origin, including technological, social and biological systems. Our models significantly improve topological prediction in many bipartite networks because they exploit local physical driving-forces that participate in the formation and organization of many real-world bipartite networks. Furthermore, we present a local-based formalism that allows to intuitively

Common neighbours and the local-community-paradigm for topological link prediction in bipartite networks

Science.gov (United States)

Daminelli, Simone; Thomas, Josephine Maria; Durán, Claudio; Vittorio Cannistraci, Carlo

2015-11-01

Bipartite networks are powerful descriptions of complex systems characterized by two different classes of nodes and connections allowed only across but not within the two classes. Unveiling physical principles, building theories and suggesting physical models to predict bipartite links such as product-consumer connections in recommendation systems or drug-target interactions in molecular networks can provide priceless information to improve e-commerce or to accelerate pharmaceutical research. The prediction of nonobserved connections starting from those already present in the topology of a network is known as the link-prediction problem. It represents an important subject both in many-body interaction theory in physics and in new algorithms for applied tools in computer science. The rationale is that the existing connectivity structure of a network can suggest where new connections can appear with higher likelihood in an evolving network, or where nonobserved connections are missing in a partially known network. Surprisingly, current complex network theory presents a theoretical bottle-neck: a general framework for local-based link prediction directly in the bipartite domain is missing. Here, we overcome this theoretical obstacle and present a formal definition of common neighbour index and local-community-paradigm (LCP) for bipartite networks. As a consequence, we are able to introduce the first node-neighbourhood-based and LCP-based models for topological link prediction that utilize the bipartite domain. We performed link prediction evaluations in several networks of different size and of disparate origin, including technological, social and biological systems. Our models significantly improve topological prediction in many bipartite networks because they exploit local physical driving-forces that participate in the formation and organization of many real-world bipartite networks. Furthermore, we present a local-based formalism that allows to intuitively

Prediction of protein subcellular localization using support vector machine with the choice of proper kernel

Directory of Open Access Journals (Sweden)

Al Mehedi Hasan

2017-07-01

Full Text Available The prediction of subcellular locations of proteins can provide useful hints for revealing their functions as well as for understanding the mechanisms of some diseases and, finally, for developing novel drugs. As the number of newly discovered proteins has been growing exponentially, laboratory-based experiments to determine the location of an uncharacterized protein in a living cell have become both expensive and time-consuming. Consequently, to tackle these challenges, computational methods are being developed as an alternative to help biologists in selecting target proteins and designing related experiments. However, the success of protein subcellular localization prediction is still a complicated and challenging problem, particularly when query proteins may have multi-label characteristics, i.e. their simultaneous existence in more than one subcellular location, or if they move between two or more different subcellular locations as well. At this point, to get rid of this problem, several types of subcellular localization prediction methods with different levels of accuracy have been proposed. The support vector machine (SVM has been employed to provide potential solutions for problems connected with the prediction of protein subcellular localization. However, the practicability of SVM is affected by difficulties in selecting its appropriate kernel as well as in selecting the parameters of that selected kernel. The literature survey has shown that most researchers apply the radial basis function (RBF kernel to build a SVM based subcellular localization prediction system. Surprisingly, there are still many other kernel functions which have not yet been applied in the prediction of protein subcellular localization. However, the nature of this classification problem requires the application of different kernels for SVM to ensure an optimal result. From this viewpoint, this paper presents the work to apply different kernels for SVM in protein

Malignant melanoma and radiotherapy: past myths, excellent local control in 146 studied lesions at Georgetown University, and improving future management

International Nuclear Information System (INIS)

Jahanshahi, Pooya; Nasr, Nadim; Unger, Keith; Batouli, Ali; Gagnon, Gregory J.

2012-01-01

Introduction: Once thought to be radioresistant, emerging cellular and clinical evidence now suggests melanoma can respond to large radiation doses per fraction. Materials and Methods: We conducted a retrospective study of all patients treated with stereotactic radiosurgery and stereotactic body radiotherapy at Georgetown University Hospital from May 2002 through November 2008 and studied the classic extrapolated total dose corrected for volume (ETD vol ) model for predicting melanoma tumor response. Region-specific tumor outcomes were categorized by RECIST criteria and local control curves were estimated and analyzed when stratified by ETD vol thresholds by use of the Kaplan–Meier method. Results: Follow-up information was available for 78 lesions (49 intracranial, 8 spinal, and 21 body) with mean follow-up period of 9.2 (range, 2–36) months. 1-year local control rates for intracranial, spinal, and body tumors were 84, 100, and 72%, respectively. Treatments in general were well-tolerated. Increased ETD vol (p < 0.001) among intracranial sites resulted from larger (p < 0.001) doses per fraction combined with smaller (p < 0.001) tumor diameters. Intracranial 6-, 12-, and 24-month local control rates when treated above ETD vol threshold of 230 Gy were all 90 vs. 89, 80, and 53% below this threshold. Body 6- and 12-month local control rates when treated above ETD vol threshold of 100 Gy were 100 and 80% vs. 74 and 59% below this threshold. Discussion: By tailoring to melanoma’s unique radiobiology with large radiation doses per fraction, favorable local control was safely achieved. The ETD vol model combines the important factor of dose per fraction in melanoma treatment with a volume correction factor to predict tumor response. Although limited sample size may have prevented reaching statistical significance for local control improvements using ETD vol thresholds, optimal thresholds may exist to improve future tumor responses and further research is required.

Integrated analysis of CFD data with K-means clustering algorithm and extreme learning machine for localized HVAC control

International Nuclear Information System (INIS)

Zhou, Hongming; Soh, Yeng Chai; Wu, Xiaoying

2015-01-01

Maintaining a desired comfort level while minimizing the total energy consumed is an interesting optimization problem in Heating, ventilating and air conditioning (HVAC) system control. This paper proposes a localized control strategy that uses Computational Fluid Dynamics (CFD) simulation results and K-means clustering algorithm to optimally partition an air-conditioned room into different zones. The temperature and air velocity results from CFD simulation are combined in two ways: 1) based on the relationship indicated in predicted mean vote (PMV) formula; 2) based on the relationship extracted from ASHRAE RP-884 database using extreme learning machine (ELM). Localized control can then be effected in which each of the zones can be treated individually and an optimal control strategy can be developed based on the partitioning result. - Highlights: • The paper provides a visual guideline for thermal comfort analysis. • CFD, K-means, PMV and ELM are used to analyze thermal conditions within a room. • Localized control strategy could be developed based on our clustering results

Prediction and control of rock burst of coal seam contacting gas in deep mining

Energy Technology Data Exchange (ETDEWEB)

En-yuan Wang; Xiao-fei Liu; En-lai Zhao; Zhen-tang Liu [China University of Mining and Technology, Xuzhou (China). School of Safety Engineering

2009-06-15

By analyzing the characteristics and the production mechanism of rock burst that goes with abnormal gas emission in deep coal seams, the essential method of eliminating abnormal gas emission by eliminating the occurrence of rock burst or depressing the magnitude of rock burst was considered. The No.237 working face in Nanshan coal mine was selected as the typical working face contacting gas in deep mining; aimed at this working face, a system of rock burst prediction and control for coal seam contacting gas in deep mining was established using the three-dimensional distinct element code software 3DEC. This system includes three parts: (1) regional prediction of rock burst hazard before mining; (2) local prediction of rock burst hazard during mining; and (3) rock burts control by an electromagnetic radiation method and specific drilling method. 8 refs., 4 figs., 1 tab.

Model Predictive Control for Smart Energy Systems

DEFF Research Database (Denmark)

Halvgaard, Rasmus

pumps, heat tanks, electrical vehicle battery charging/discharging, wind farms, power plants). 2.Embed forecasting methodologies for the weather (e.g. temperature, solar radiation), the electricity consumption, and the electricity price in a predictive control system. 3.Develop optimization algorithms....... Chapter 3 introduces Model Predictive Control (MPC) including state estimation, filtering and prediction for linear models. Chapter 4 simulates the models from Chapter 2 with the certainty equivalent MPC from Chapter 3. An economic MPC minimizes the costs of consumption based on real electricity prices...... that determined the flexibility of the units. A predictive control system easily handles constraints, e.g. limitations in power consumption, and predicts the future behavior of a unit by integrating predictions of electricity prices, consumption, and weather variables. The simulations demonstrate the expected...

Local knowledge of fishermen in weather prediction in Moa and ...

African Journals Online (AJOL)

This study investigated local knowledge of fishermen in weather prediction in Moa and Kwale coastal villages, Tanzania. Focus Group Discussions, Seasonal Calendars, Time line analysis, key informant interviews, questionnaire surveys and documentary reviews were used to gather data. The SPSS programme was used ...

Predicting the nutritional health status of locally produced palm oil ...

African Journals Online (AJOL)

Three physical properties of locally produced palm oil – viscosity, thermal conductivity and density for varying temperatures were determined. The values obtained were compared with corresponding internationally stipulated standard values using statistics of mean and graphs. The purpose of the comparison was to predict ...

Predicting Traffic Flow in Local Area Networks by the Largest Lyapunov Exponent

Directory of Open Access Journals (Sweden)

Yan Liu

2016-01-01

Full Text Available The dynamics of network traffic are complex and nonlinear, and chaotic behaviors and their prediction, which play an important role in local area networks (LANs, are studied in detail, using the largest Lyapunov exponent. With the introduction of phase space reconstruction based on the time sequence, the high-dimensional traffic is projected onto the low dimension reconstructed phase space, and a reduced dynamic system is obtained from the dynamic system viewpoint. Then, a numerical method for computing the largest Lyapunov exponent of the low-dimensional dynamic system is presented. Further, the longest predictable time, which is related to chaotic behaviors in the system, is studied using the largest Lyapunov exponent, and the Wolf method is used to predict the evolution of the traffic in a local area network by both Dot and Interval predictions, and a reliable result is obtained by the presented method. As the conclusion, the results show that the largest Lyapunov exponent can be used to describe the sensitivity of the trajectory in the reconstructed phase space to the initial values. Moreover, Dot Prediction can effectively predict the flow burst. The numerical simulation also shows that the presented method is feasible and efficient for predicting the complex dynamic behaviors in LAN traffic, especially for congestion and attack in networks, which are the main two complex phenomena behaving as chaos in networks.

{sup 18}F-Fluorodeoxyglucose/Positron Emission Tomography Predicts Patterns of Failure After Definitive Chemoradiation Therapy for Locally Advanced Non-Small Cell Lung Cancer

Energy Technology Data Exchange (ETDEWEB)

Ohri, Nitin, E-mail: ohri.nitin@gmail.com [Department of Radiation Oncology, Montefiore Medical Center, Albert Einstein College of Medicine, Bronx, New York (United States); Bodner, William R. [Department of Radiation Oncology, Montefiore Medical Center, Albert Einstein College of Medicine, Bronx, New York (United States); Halmos, Balazs; Cheng, Haiying; Perez-Soler, Roman [Department of Oncology, Montefiore Medical Center, Albert Einstein College of Medicine, Bronx, New York (United States); Keller, Steven M. [Department of Cardiothoracic Surgery, Montefiore Medical Center, Albert Einstein College of Medicine, Bronx, New York (United States); Kalnicki, Shalom; Garg, Madhur [Department of Radiation Oncology, Montefiore Medical Center, Albert Einstein College of Medicine, Bronx, New York (United States)

2017-02-01

Background: We previously reported that pretreatment positron emission tomography (PET) identifies lesions at high risk for progression after concurrent chemoradiation therapy (CRT) for locally advanced non-small cell lung cancer (NSCLC). Here we validate those findings and generate tumor control probability (TCP) models. Methods: We identified patients treated with definitive, concurrent CRT for locally advanced NSCLC who underwent staging {sup 18}F-fluorodeoxyglucose/PET/computed tomography. Visible hypermetabolic lesions (primary tumors and lymph nodes) were delineated on each patient's pretreatment PET scan. Posttreatment imaging was reviewed to identify locations of disease progression. Competing risks analyses were performed to examine metabolic tumor volume (MTV) and radiation therapy dose as predictors of local disease progression. TCP modeling was performed to describe the likelihood of local disease control as a function of lesion size. Results: Eighty-nine patients with 259 hypermetabolic lesions (83 primary tumors and 176 regional lymph nodes) met the inclusion criteria. Twenty-eight patients were included in our previous report, and the remaining 61 constituted our validation cohort. The median follow-up time was 22.7 months for living patients. In 20 patients, the first site of progression was a primary tumor or lymph node treated with radiation therapy. The median time to progression for those patients was 11.5 months. Data from our validation cohort confirmed that lesion MTV predicts local progression, with a 30-month cumulative incidence rate of 23% for lesions above 25 cc compared with 4% for lesions below 25 cc (P=.008). We found no evidence that radiation therapy dose was associated with local progression risk. TCP modeling yielded predicted 30-month local control rates of 98% for a 1-cc lesion, 94% for a 10-cc lesion, and 74% for a 50-cc lesion. Conclusion: Pretreatment FDG-PET identifies lesions at risk for progression after CRT for

ngLOC: software and web server for predicting protein subcellular localization in prokaryotes and eukaryotes

Directory of Open Access Journals (Sweden)

King Brian R

2012-07-01

Full Text Available Abstract Background Understanding protein subcellular localization is a necessary component toward understanding the overall function of a protein. Numerous computational methods have been published over the past decade, with varying degrees of success. Despite the large number of published methods in this area, only a small fraction of them are available for researchers to use in their own studies. Of those that are available, many are limited by predicting only a small number of organelles in the cell. Additionally, the majority of methods predict only a single location for a sequence, even though it is known that a large fraction of the proteins in eukaryotic species shuttle between locations to carry out their function. Findings We present a software package and a web server for predicting the subcellular localization of protein sequences based on the ngLOC method. ngLOC is an n-gram-based Bayesian classifier that predicts subcellular localization of proteins both in prokaryotes and eukaryotes. The overall prediction accuracy varies from 89.8% to 91.4% across species. This program can predict 11 distinct locations each in plant and animal species. ngLOC also predicts 4 and 5 distinct locations on gram-positive and gram-negative bacterial datasets, respectively. Conclusions ngLOC is a generic method that can be trained by data from a variety of species or classes for predicting protein subcellular localization. The standalone software is freely available for academic use under GNU GPL, and the ngLOC web server is also accessible at http://ngloc.unmc.edu.

Composite control for raymond mill based on model predictive control and disturbance observer

Directory of Open Access Journals (Sweden)

Dan Niu

2016-03-01

Full Text Available In the raymond mill grinding process, precise control of operating load is vital for the high product quality. However, strong external disturbances, such as variations of ore size and ore hardness, usually cause great performance degradation. It is not easy to control the current of raymond mill constant. Several control strategies have been proposed. However, most of them (such as proportional–integral–derivative and model predictive control reject disturbances just through feedback regulation, which may lead to poor control performance in the presence of strong disturbances. For improving disturbance rejection, a control method based on model predictive control and disturbance observer is put forward in this article. The scheme employs disturbance observer as feedforward compensation and model predictive control controller as feedback regulation. The test results illustrate that compared with model predictive control method, the proposed disturbance observer–model predictive control method can obtain significant superiority in disturbance rejection, such as shorter settling time and smaller peak overshoot under strong disturbances.

Model Predictive Vibration Control Efficient Constrained MPC Vibration Control for Lightly Damped Mechanical Structures

CERN Document Server

Takács, Gergely

2012-01-01

Real-time model predictive controller (MPC) implementation in active vibration control (AVC) is often rendered difficult by fast sampling speeds and extensive actuator-deformation asymmetry. If the control of lightly damped mechanical structures is assumed, the region of attraction containing the set of allowable initial conditions requires a large prediction horizon, making the already computationally demanding on-line process even more complex. Model Predictive Vibration Control provides insight into the predictive control of lightly damped vibrating structures by exploring computationally efficient algorithms which are capable of low frequency vibration control with guaranteed stability and constraint feasibility. In addition to a theoretical primer on active vibration damping and model predictive control, Model Predictive Vibration Control provides a guide through the necessary steps in understanding the founding ideas of predictive control applied in AVC such as: ·         the implementation of ...

Model Predictive Control for Integrating Traffic Control Measures

NARCIS (Netherlands)

Hegyi, A.

2004-01-01

Dynamic traffic control measures, such as ramp metering and dynamic speed limits, can be used to better utilize the available road capacity. Due to the increasing traffic volumes and the increasing number of traffic jams the interaction between the control measures has increased such that local

Predicting Loss-of-Control Boundaries Toward a Piloting Aid

Science.gov (United States)

Barlow, Jonathan; Stepanyan, Vahram; Krishnakumar, Kalmanje

2012-01-01

This work presents an approach to predicting loss-of-control with the goal of providing the pilot a decision aid focused on maintaining the pilot's control action within predicted loss-of-control boundaries. The predictive architecture combines quantitative loss-of-control boundaries, a data-based predictive control boundary estimation algorithm and an adaptive prediction method to estimate Markov model parameters in real-time. The data-based loss-of-control boundary estimation algorithm estimates the boundary of a safe set of control inputs that will keep the aircraft within the loss-of-control boundaries for a specified time horizon. The adaptive prediction model generates estimates of the system Markov Parameters, which are used by the data-based loss-of-control boundary estimation algorithm. The combined algorithm is applied to a nonlinear generic transport aircraft to illustrate the features of the architecture.

Local dimension and finite time prediction in coupled map lattices

Indian Academy of Sciences (India)

Forecasting, for obvious reasons, often become the most important goal to be achieved. For spatially extended systems (e.g. atmospheric system) where the local nonlinearities lead to the most unpredictable chaotic evolution, it is highly desirable to have a simple diagnostic tool to identify regions of predictable behaviour.

Intelligent Predictive Control of Nonlienar Processes Using

DEFF Research Database (Denmark)

Nørgård, Peter Magnus; Sørensen, Paul Haase; Poulsen, Niels Kjølstad

1996-01-01

This paper presents a novel approach to design of generalized predictive controllers (GPC) for nonlinear processes. A neural network is used for modelling the process and a gain-scheduling type of GPC is subsequently designed. The combination of neural network models and predictive control has...... frequently been discussed in the neural network community. This paper proposes an approximate scheme, the approximate predictive control (APC), which facilitates the implementation and gives a substantial reduction in the required amount of computations. The method is based on a technique for extracting...... linear models from a nonlinear neural network and using them in designing the control system. The performance of the controller is demonstrated in a simulation study of a pneumatic servo system...

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

Science.gov (United States)

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

2017-10-01

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

Local Fitness Landscapes Predict Yeast Evolutionary Dynamics in Directionally Changing Environments.

Science.gov (United States)

Gorter, Florien A; Aarts, Mark G M; Zwaan, Bas J; de Visser, J Arjan G M

2018-01-01

The fitness landscape is a concept that is widely used for understanding and predicting evolutionary adaptation. The topography of the fitness landscape depends critically on the environment, with potentially far-reaching consequences for evolution under changing conditions. However, few studies have assessed directly how empirical fitness landscapes change across conditions, or validated the predicted consequences of such change. We previously evolved replicate yeast populations in the presence of either gradually increasing, or constant high, concentrations of the heavy metals cadmium (Cd), nickel (Ni), and zinc (Zn), and analyzed their phenotypic and genomic changes. Here, we reconstructed the local fitness landscapes underlying adaptation to each metal by deleting all repeatedly mutated genes both by themselves and in combination. Fitness assays revealed that the height, and/or shape, of each local fitness landscape changed considerably across metal concentrations, with distinct qualitative differences between unconditionally (Cd) and conditionally toxic metals (Ni and Zn). This change in topography had particularly crucial consequences in the case of Ni, where a substantial part of the individual mutational fitness effects changed in sign across concentrations. Based on the Ni landscape analyses, we made several predictions about which mutations had been selected when during the evolution experiment. Deep sequencing of population samples from different time points generally confirmed these predictions, demonstrating the power of landscape reconstruction analyses for understanding and ultimately predicting evolutionary dynamics, even under complex scenarios of environmental change. Copyright © 2018 by the Genetics Society of America.

Effect of local automatic control rods on three-dimensional calculations of the power distribution in an RBMK

International Nuclear Information System (INIS)

Pogosbekyan, L.R.; Lysov, D.A.; Bronitskii, L.L.

1993-01-01

Numerical simulators and information systems that support nuclear reactor operators must have fast models to estimate how fuel reloads and control rod displacement affect neutron and power distributions in the core. The consequences of reloads and control rod displacement cannot be evaluated correctly without considering local automatic control-rod operations in maintaining the radial power distribution. Fast three-dimensional models to estimate the effects of reloads and displacement of the control and safety rods have already been examined. I.V. Zonov et al. used the following assumptions in their calculational model: (1) the full-scale problem could be reduced a three-dimensional fragment of a locally perturbed core, and (2) the boundary conditions of the fragment and its total power were constant. The last assumption considers approximately how local automatic control rods stabilize the radial power distribution, but three dimensional calculations with these rods are not considered. These assumptions were introduced to obtain high computational speed. I.L. Bronitskii et al. considered in more detail how moving the local automatic control rods affect the power dimensional in the three-dimensional fragment, because, with on-line monitoring of the reload process, information on control rod positions is periodically renewed, and the calculations are done in real time. This model to predict the three-dimensional power distribution to (1) do a preliminary reload analysis, and (2) prepare the core for reloading did not consider the effect of perturbations from the local automatic control rods. Here we examine a model of a stationary neutron distribution. On one hand it gives results in an acceptable computation time; on the other it is a full-scale three-dimensional model and considers how local automatic control rods affect both the radial and axial power distribution

B220 analysis with the local lymph node assay: proposal for a more flexible prediction model.

Science.gov (United States)

Betts, Catherine J; Dearman, Rebecca J; Kimber, Ian; Ryan, Cindy A; Gerberick, G Frank; Lalko, Jon; Api, Anne Marie

2007-01-01

The mouse local lymph node assay (LLNA) has been developed and validated for the identification of chemicals that have the potential to induce skin sensitisation. In common with other predictive test methods the accuracy of the LLNA is not absolute and experience has revealed that a few chemicals, including for instance a minority of skin irritants, may elicit false-positive reactions in the assay. To improve further the performance of the LLNA, and to eliminate or reduce false-positives, there has been interest in an adjunct method in which the ability of chemicals to cause increases in the frequency of B220(+) lymphocytes in skin-draining lymph nodes is measured. Previous studies suggest that the use of B220 analyses aligned with the standard LLNA may serve to distinguish further between contact allergens and skin irritants. In the original predictive model, chemicals were regarded as being skin sensitisers if they were able to induce a 1.25-fold or greater increase in the percentage of B220(+) cells within lymph nodes compared with concurrent vehicle controls. Although this first prediction model has proven useful, in the light of more recent experience, and specifically as a consequence of some variability observed in the frequency of B220(+) lymphocytes in nodes taken from vehicle control-treated animals, it is timely now to reconsider and refine the model. As a result a new prediction model is proposed in which reliance on the use of absolute thresholds is reduced, and in which small changes in control values can be better accommodated. (c) 2007 John Wiley & Sons, Ltd.

Local control stations

International Nuclear Information System (INIS)

Brown, W.S.; Higgins, J.C.; Wachtel, J.A.

1993-01-01

This paper describes research concerning the effects of human engineering design at local control stations (i.e., operator interfaces located outside the control room) on human performance and plant safety. The research considered both multifunction panels (e.g. remote shutdown panels) as well as single-function interfaces (e.g., valves, breakers, gauges, etc.). Changes in performance shaping factors associated with variations in human engineering at LCSs were estimated based on expert opinion. By means of a scaling procedure, these estimates were used to modify the human error probabilities in a PRA model, which was then employed to generate estimates of plant risk and scoping-level value/impact ratios for various human engineering upgrades. Recent documentation of human engineering deficiencies at single-function LCSs was also reviewed, and an assessment of the current status of LCSs with respect to human engineering was conducted

ESLpred2: improved method for predicting subcellular localization of eukaryotic proteins

Directory of Open Access Journals (Sweden)

Raghava Gajendra PS

2008-11-01

Full Text Available Abstract Background The expansion of raw protein sequence databases in the post genomic era and availability of fresh annotated sequences for major localizations particularly motivated us to introduce a new improved version of our previously forged eukaryotic subcellular localizations prediction method namely "ESLpred". Since, subcellular localization of a protein offers essential clues about its functioning, hence, availability of localization predictor would definitely aid and expedite the protein deciphering studies. However, robustness of a predictor is highly dependent on the superiority of dataset and extracted protein attributes; hence, it becomes imperative to improve the performance of presently available method using latest dataset and crucial input features. Results Here, we describe augmentation in the prediction performance obtained for our most popular ESLpred method using new crucial features as an input to Support Vector Machine (SVM. In addition, recently available, highly non-redundant dataset encompassing three kingdoms specific protein sequence sets; 1198 fungi sequences, 2597 from animal and 491 plant sequences were also included in the present study. First, using the evolutionary information in the form of profile composition along with whole and N-terminal sequence composition as an input feature vector of 440 dimensions, overall accuracies of 72.7, 75.8 and 74.5% were achieved respectively after five-fold cross-validation. Further, enhancement in performance was observed when similarity search based results were coupled with whole and N-terminal sequence composition along with profile composition by yielding overall accuracies of 75.9, 80.8, 76.6% respectively; best accuracies reported till date on the same datasets. Conclusion These results provide confidence about the reliability and accurate prediction of SVM modules generated in the present study using sequence and profile compositions along with similarity search

Fatigue Life Prediction of High Modulus Asphalt Concrete Based on the Local Stress-Strain Method

Directory of Open Access Journals (Sweden)

Mulian Zheng

2017-03-01

Full Text Available Previously published studies have proposed fatigue life prediction models for dense graded asphalt pavement based on flexural fatigue test. This study focused on the fatigue life prediction of High Modulus Asphalt Concrete (HMAC pavement using the local strain-stress method and direct tension fatigue test. First, the direct tension fatigue test at various strain levels was conducted on HMAC prism samples cut from plate specimens. Afterwards, their true stress-strain loop curves were obtained and modified to develop the strain-fatigue life equation. Then the nominal strain of HMAC course determined using finite element method was converted into local strain using the Neuber method. Finally, based on the established fatigue equation and converted local strain, a method to predict the pavement fatigue crack initiation life was proposed and the fatigue life of a typical HMAC overlay pavement which runs a risk of bottom-up cracking was predicted and validated. Results show that the proposed method was able to produce satisfactory crack initiation life.

Local control station for development, testing and maintenance of mirror fusion facility subsystem controls

International Nuclear Information System (INIS)

Ables, E.; Kelly, M.F.

1985-01-01

A Local Control Station (LCS) was designed and built to provide a simplified ad easily configurable means of controlling any Mirror Fusion Test Facility (MFTF-B) subsystem for the purpose of development, testing and maintenance of the subsystem. All MFTF-B Subsystems incorporate at least one Local Control Computer (LCC) that is connected to and accepts high level commands from one of the Supervisory Control and Diagnostic System (SCDS) computers. The LCS connects directly to the LCC in place of SCDS. The LCS communicates with the subsystem hardware using the same SCDS commands that the local control computer recognizes and as such requires no special configuration of the LCC

Tracking local control of a parabolic trough collector. Control local de Seguimiento cilindro parabolico ACE 20

Energy Technology Data Exchange (ETDEWEB)

Ajona Maeztu, J.I.; Alberdi Primicia, J.; Gamero Aranda, E.; Blanco, J.

1991-01-01

In the local control, the sun position related to the trough collector is measured by two photo-resistors. the provided electronic signal is then compared with reference levels in order to get a set of 8 logical signals which form a byte. This byte and the commands issued by a programmable controller are connected to the inputs of a P.R.O.M. memory which is programmed with the logical ecuations of the control system. the memory output lines give the control commands of the parabolic trough collector motor. (author)

Tracking local control of a parabolic trough collector; Control local de Seguimiento cilindro parabolico ACE 20

Energy Technology Data Exchange (ETDEWEB)

Ajona Maeztu, J.I.; Alberdi Primicia, J.; Gamero Aranda, E.; Blanco, J.

1991-12-31

In the local control, the sun position related to the trough collector is measured by two photo-resistors. the provided electronic signal is then compared with reference levels in order to get a set of 8 logical signals which form a byte. This byte and the commands issued by a programmable controller are connected to the inputs of a P.R.O.M. memory which is programmed with the logical ecuations of the control system. the memory output lines give the control commands of the parabolic trough collector motor. (author)

Tracking local control of a parabolic trough collector; Control local de seguimiento cilindro parabolico ACE20

Energy Technology Data Exchange (ETDEWEB)

Ajona, J I; Alberdi, J; Gamero, E; Blanco, J

1992-07-01

In the local control, the sun position related to the trough collector is measured by two photo-resistors. The provided electronic signal is then compared with reference levels in order to get a set of B logical signals which form a byte. This byte and the commands issued by a programmable controller are connected to the inputs of o P.R.O.M. memory which is programmed with the logical equations of the control system. The memory output lines give the control command of the parabolic trough collector motor. (Author)

Performance of local information-based link prediction: a sampling perspective

Science.gov (United States)

Zhao, Jichang; Feng, Xu; Dong, Li; Liang, Xiao; Xu, Ke

2012-08-01

Link prediction is pervasively employed to uncover the missing links in the snapshots of real-world networks, which are usually obtained through different kinds of sampling methods. In the previous literature, in order to evaluate the performance of the prediction, known edges in the sampled snapshot are divided into the training set and the probe set randomly, without considering the underlying sampling approaches. However, different sampling methods might lead to different missing links, especially for the biased ways. For this reason, random partition-based evaluation of performance is no longer convincing if we take the sampling method into account. In this paper, we try to re-evaluate the performance of local information-based link predictions through sampling method governed division of the training set and the probe set. It is interesting that we find that for different sampling methods, each prediction approach performs unevenly. Moreover, most of these predictions perform weakly when the sampling method is biased, which indicates that the performance of these methods might have been overestimated in the prior works.

Modeling and Control of CSTR using Model based Neural Network Predictive Control

OpenAIRE

Shrivastava, Piyush

2012-01-01

This paper presents a predictive control strategy based on neural network model of the plant is applied to Continuous Stirred Tank Reactor (CSTR). This system is a highly nonlinear process; therefore, a nonlinear predictive method, e.g., neural network predictive control, can be a better match to govern the system dynamics. In the paper, the NN model and the way in which it can be used to predict the behavior of the CSTR process over a certain prediction horizon are described, and some commen...

[Predictive ocular motor control in Parkinson's disease].

Science.gov (United States)

Ying, Li; Liu, Zhen-Guo; Chen, Wei; Gan, Jing; Wang, Wen-An

2008-02-19

To investigate the changes of predictive ocular motor function in the patients with Parkinson's disease (PD), and to discuss its clinical value. Videonystagmography (VNG) was used to examine 24 patients with idiopathic Parkinson's disease, 15 males and 9 females, aged 61 +/- 6 (50-69), and 24 sex and age-matched healthy control subjects on random ocular saccade (with the target moving at random intervals to random positions) and predictive ocular saccade (with the 1.25-second light target moving 10 degrees right or left from the center). In the random ocular saccade program, the latency of saccade of the PD patients was 284 ms +/- 58 ms, significantly longer than that of the healthy controls (236 ms +/- 37 ms, P = 0.003). In the predictive ocular saccade pattern, the latency of saccades the PD patients was 150 ms +/- 138 ms, significantly longer than that of the healthy controls (59 ms +/- 102 ms, P = 0.002). The appearance rate of predictive saccades (with the latency of saccade <80 ms) in the PD group was 21%, significantly lower than that in the control group (31%, P = 0.003). There is dysfunction of predictive ocular motor control in the PD patients, and the cognitive function may be impaired at the early stage of PD.

Improving spatial prediction of Schistosoma haematobium prevalence in southern Ghana through new remote sensors and local water access profiles.

Science.gov (United States)

Kulinkina, Alexandra V; Walz, Yvonne; Koch, Magaly; Biritwum, Nana-Kwadwo; Utzinger, Jürg; Naumova, Elena N

2018-06-04

Schistosomiasis is a water-related neglected tropical disease. In many endemic low- and middle-income countries, insufficient surveillance and reporting lead to poor characterization of the demographic and geographic distribution of schistosomiasis cases. Hence, modeling is relied upon to predict areas of high transmission and to inform control strategies. We hypothesized that utilizing remotely sensed (RS) environmental data in combination with water, sanitation, and hygiene (WASH) variables could improve on the current predictive modeling approaches. Schistosoma haematobium prevalence data, collected from 73 rural Ghanaian schools, were used in a random forest model to investigate the predictive capacity of 15 environmental variables derived from RS data (Landsat 8, Sentinel-2, and Global Digital Elevation Model) with fine spatial resolution (10-30 m). Five methods of variable extraction were tested to determine the spatial linkage between school-based prevalence and the environmental conditions of potential transmission sites, including applying the models to known human water contact locations. Lastly, measures of local water access and groundwater quality were incorporated into RS-based models to assess the relative importance of environmental and WASH variables. Predictive models based on environmental characterization of specific locations where people contact surface water bodies offered some improvement as compared to the traditional approach based on environmental characterization of locations where prevalence is measured. A water index (MNDWI) and topographic variables (elevation and slope) were important environmental risk factors, while overall, groundwater iron concentration predominated in the combined model that included WASH variables. The study helps to understand localized drivers of schistosomiasis transmission. Specifically, unsatisfactory water quality in boreholes perpetuates reliance of surface water bodies, indirectly increasing

Multi-Objective Predictive Balancing Control of Battery Packs Based on Predictive Current

Directory of Open Access Journals (Sweden)

Wenbiao Li

2016-04-01

Full Text Available Various balancing topology and control methods have been proposed for the inconsistency problem of battery packs. However, these strategies only focus on a single objective, ignore the mutual interaction among various factors and are only based on the external performance of the battery pack inconsistency, such as voltage balancing and state of charge (SOC balancing. To solve these problems, multi-objective predictive balancing control (MOPBC based on predictive current is proposed in this paper, namely, in the driving process of an electric vehicle, using predictive control to predict the battery pack output current the next time. Based on this information, the impact of the battery pack temperature caused by the output current can be obtained. Then, the influence is added to the battery pack balancing control, which makes the present degradation, temperature, and SOC imbalance achieve balance automatically due to the change of the output current the next moment. According to MOPBC, the simulation model of the balancing circuit is built with four cells in Matlab/Simulink. The simulation results show that MOPBC is not only better than the other traditional balancing control strategies but also reduces the energy loss in the balancing process.

Intensity-Modulated Radiotherapy for Oral Cavity Squamous Cell Carcinoma: Patterns of Failure and Predictors of Local Control

International Nuclear Information System (INIS)

Daly, Megan E.; Le, Quynh-Thu; Kozak, Margaret M.; Maxim, Peter G.; Murphy, James D.; Hsu, Annie; Loo, Billy W.; Kaplan, Michael J.; Fischbein, Nancy J.; Chang, Daniel T.

2011-01-01

Purpose: Few studies have evaluated the use of intensity-modulated radiotherapy (IMRT) for squamous cell carcinoma (SCC) of the oral cavity (OC). We report clinical outcomes and failure patterns for these patients. Methods and Materials: Between October 2002 and June 2009, 37 patients with newly diagnosed SCC of the OC underwent postoperative (30) or definitive (7) IMRT. Twenty-five patients (66%) received systemic therapy. The median follow-up was 38 months (range, 10-87 months). The median interval from surgery to RT was 5.9 weeks (range, 2.1-10.7 weeks). Results: Thirteen patients experienced local-regional failure at a median of 8.1 months (range, 2.4-31.9 months), and 2 additional patients experienced local recurrence between surgery and RT. Seven local failures occurred in-field (one with simultaneous nodal and distant disease) and two at the margin. Four regional failures occurred, two in-field and two out-of-field, one with synchronous metastases. Six patients experienced distant failure. The 3-year actuarial estimates of local control, local-regional control, freedom from distant metastasis, and overall survival were 67%, 53%, 81%, and 60% among postoperative patients, respectively, and 60%, 60%, 71%, and 57% among definitive patients. Four patients developed Grade ≥2 chronic toxicity. Increased surgery to RT interval predicted for decreased LRC (p = 0.04). Conclusions: Local-regional control for SCC of the OC treated with IMRT with or without surgery remains unsatisfactory. Definitive and postoperative IMRT have favorable toxicity profiles. A surgery-to-RT interval of <6 weeks improves local-regional control. The predominant failure pattern was local, suggesting that both improvements in target delineation and radiosensitization and/or dose escalation are needed.

Prediction of N2O emission from local information with Random Forest

International Nuclear Information System (INIS)

Philibert, Aurore; Loyce, Chantal; Makowski, David

2013-01-01

Nitrous oxide is a potent greenhouse gas, with a global warming potential 298 times greater than that of CO 2 . In agricultural soils, N 2 O emissions are influenced by a large number of environmental characteristics and crop management techniques that are not systematically reported in experiments. Random Forest (RF) is a machine learning method that can handle missing data and ranks input variables on the basis of their importance. We aimed to predict N 2 O emission on the basis of local information, to rank environmental and crop management variables according to their influence on N 2 O emission, and to compare the performances of RF with several regression models. RF outperformed the regression models for predictive purposes, and this approach led to the identification of three important input variables: N fertilization, type of crop, and experiment duration. This method could be used in the future for prediction of N 2 O emissions from local information. -- Highlights: ► Random Forest gave more accurate N 2 O predictions than regression. ► Missing data were well handled by Random Forest. ► The most important factors were nitrogen rate, type of crop and experiment duration. -- Random Forest, a machine learning method, outperformed the regression models for predicting N 2 O emissions and led to the identification of three important input variables

Robot trajectory tracking with self-tuning predicted control

Science.gov (United States)

Cui, Xianzhong; Shin, Kang G.

1988-01-01

A controller that combines self-tuning prediction and control is proposed for robot trajectory tracking. The controller has two feedback loops: one is used to minimize the prediction error, and the other is designed to make the system output track the set point input. Because the velocity and position along the desired trajectory are given and the future output of the system is predictable, a feedforward loop can be designed for robot trajectory tracking with self-tuning predicted control (STPC). Parameters are estimated online to account for the model uncertainty and the time-varying property of the system. The authors describe the principle of STPC, analyze the system performance, and discuss the simplification of the robot dynamic equations. To demonstrate its utility and power, the controller is simulated for a Stanford arm.

Pre- and post-radiotherapy computed tomography in laryngeal cancer: imaging-based prediction of local failure

International Nuclear Information System (INIS)

Pameijer, Frank A.; Hermans, Robert; Mancuso, Anthony A.; Mendenhall, William M.; Parsons, James T.; Stringer, Scott P.; Kubilis, Paul S.; Tinteren, Harm van

1999-01-01

Purpose: To determine if pre-radiotherapy (RT) and/or post-radiotherapy computed tomography (CT) can predict local failure in patients with laryngeal carcinoma treated with definitive RT. Methods and Materials: The pre- and post-RT CT examinations of 59 patients (T3 glottic carcinoma [n = 30] and T1-T4 supraglottic carcinoma [n = 29]) were reviewed. For each patient, the first post-RT CT study between 1 and 6 months after irradiation was used. All patients were treated with definitive hyperfractionated twice-daily continuous-course irradiation to a total dose of 6,720-7,920 cGy, and followed-up clinically for at least 2 years after completion of RT. Local control was defined as absence of primary tumor recurrence and a functioning larynx. On the pre-treatment CT study, each tumor was assigned a high-or low-risk profile for local failure after RT. The post-RT CT examinations were evaluated for post-treatment changes using a three-point post-RT CT-score: 1 = expected post-RT changes; 2 = focal mass with a maximal diameter of 1 cm, or < 50% estimated tumor volume reduction. Results: The local control rates at 2 years post-RT based on pre-treatment CT evaluation were 88% for low pre-treatment risk profile patients (95% CI: 66-96%) and 34% (95% CI: 19-50%) for high pre-treatment risk profile patients (risk ratio 6.583; 95% CI: 2.265-9.129; p = 0.0001). Based on post-treatment CT, the local control rates at 2 years post-RT were 94% for score 1, 67% for score 2, and 10% for score 3 (risk ratio 4.760; 95% CI: 2.278-9.950 p 0.0001). Post-RT CT scores added significant information to the pre-treatment risk profiles on prognosis. Conclusions: Pre-treatment CT risk profiles, as well as post-RT CT evaluation can identify patients, irradiated for laryngeal carcinomas, at high risk for developing local failure. When the post-RT CT score is available, it proves to be an even better prognosticator than the pre-treatment CT-risk profile

Control and monitoring of the localized corrosion of zirconium in acidic chloride solutions

International Nuclear Information System (INIS)

Fahey, J.; Holmes, D.; Yau, T.L.

1995-01-01

Zirconium in acidic chloride solutions which are contaminated with ferric or cupric cations is prone to localized corrosion. This tendency can be reduced by ensuring that the zirconium surface is clean and smooth. In this paper, the effect of surface condition on the localized corrosion of zirconium in acidic chloride solutions is predicted with potentiodynamic scans. These predictions are confirmed by weight loss tests on various combinations of surface finish and acid concentrations. A real time indication of localized corrosion is seen by monitoring the electrochemical noise produced between two similar electrodes immersed in an acidic chloride solutions. Electrochemical noise monitoring correlates well with the predictions from potentiodynamic and weight loss experiments. The electrochemical noise results show that while an elevated (more anodic) potential caused by ferric ion contamination may be a necessary condition for localized corrosion, it is not a sufficient condition: A smooth, clean zirconium surface reduces the localized corrosion of zirconium

Predictive Variable Gain Iterative Learning Control for PMSM

Directory of Open Access Journals (Sweden)

Huimin Xu

2015-01-01

Full Text Available A predictive variable gain strategy in iterative learning control (ILC is introduced. Predictive variable gain iterative learning control is constructed to improve the performance of trajectory tracking. A scheme based on predictive variable gain iterative learning control for eliminating undesirable vibrations of PMSM system is proposed. The basic idea is that undesirable vibrations of PMSM system are eliminated from two aspects of iterative domain and time domain. The predictive method is utilized to determine the learning gain in the ILC algorithm. Compression mapping principle is used to prove the convergence of the algorithm. Simulation results demonstrate that the predictive variable gain is superior to constant gain and other variable gains.

Multi-model predictive control method for nuclear steam generator water level

International Nuclear Information System (INIS)

Hu Ke; Yuan Jingqi

2008-01-01

The dynamics of a nuclear steam generator (SG) is very different according to the power levels and changes as time goes on. Therefore, it is an intractable as well as challenging task to improve the water level control system of the SG. In this paper, a robust model predictive control (RMPC) method is developed for the level control problem. Based on a multi-model framework, a combination of a local nominal model with a polytopic uncertain linear parameter varying (LPV) model is built to approximate the system's non-linear behavior. The optimization problem solved here is based on a receding horizon scheme involving the linear matrix inequality (LMI) technique. Closed loop stability and constraints satisfaction in the entire operating range are guaranteed by the feasibility of the optimization problem. Finally, simulation results show the effectiveness and the good performance of the proposed method

Predictive Control of Networked Multiagent Systems via Cloud Computing.

Science.gov (United States)

Liu, Guo-Ping

2017-01-18

This paper studies the design and analysis of networked multiagent predictive control systems via cloud computing. A cloud predictive control scheme for networked multiagent systems (NMASs) is proposed to achieve consensus and stability simultaneously and to compensate for network delays actively. The design of the cloud predictive controller for NMASs is detailed. The analysis of the cloud predictive control scheme gives the necessary and sufficient conditions of stability and consensus of closed-loop networked multiagent control systems. The proposed scheme is verified to characterize the dynamical behavior and control performance of NMASs through simulations. The outcome provides a foundation for the development of cooperative and coordinative control of NMASs and its applications.

Detrended cross-correlation coefficient: Application to predict apoptosis protein subcellular localization.

Science.gov (United States)

Liang, Yunyun; Liu, Sanyang; Zhang, Shengli

2016-12-01

Apoptosis, or programed cell death, plays a central role in the development and homeostasis of an organism. Obtaining information on subcellular location of apoptosis proteins is very helpful for understanding the apoptosis mechanism. The prediction of subcellular localization of an apoptosis protein is still a challenging task, and existing methods mainly based on protein primary sequences. In this paper, we introduce a new position-specific scoring matrix (PSSM)-based method by using detrended cross-correlation (DCCA) coefficient of non-overlapping windows. Then a 190-dimensional (190D) feature vector is constructed on two widely used datasets: CL317 and ZD98, and support vector machine is adopted as classifier. To evaluate the proposed method, objective and rigorous jackknife cross-validation tests are performed on the two datasets. The results show that our approach offers a novel and reliable PSSM-based tool for prediction of apoptosis protein subcellular localization. Copyright © 2016 Elsevier Inc. All rights reserved.

Globalization and Localization of the Management Control System package

DEFF Research Database (Denmark)

Toldbod, Thomas; Israelsen, Poul

2015-01-01

Through an empirical case study, this article examines the operation of multiple management control systems as a package in a Danish manufacturing company. The analysis focuses on four different management control systems – cybernetic controls, planning controls, reward controls, and administrative...... the organization and others have more particular characteristics. Specifically, this study finds that cybernetic controls and administrative controls are designed as global management control systems. Planning controls and reward and compensation controls are glocal systems. The finding leads to the conclusion...... controls – through the theoretical lens of globalization, localization, and glocalization. Based on a single-case study, the analysis documents that these different management control systems are affected differently by the processes of globalization and localization, some of which are universal throughout...

Prediction of CT Substitutes from MR Images Based on Local Diffeomorphic Mapping for Brain PET Attenuation Correction.

Science.gov (United States)

Wu, Yao; Yang, Wei; Lu, Lijun; Lu, Zhentai; Zhong, Liming; Huang, Meiyan; Feng, Yanqiu; Feng, Qianjin; Chen, Wufan

2016-10-01

Attenuation correction is important for PET reconstruction. In PET/MR, MR intensities are not directly related to attenuation coefficients that are needed in PET imaging. The attenuation coefficient map can be derived from CT images. Therefore, prediction of CT substitutes from MR images is desired for attenuation correction in PET/MR. This study presents a patch-based method for CT prediction from MR images, generating attenuation maps for PET reconstruction. Because no global relation exists between MR and CT intensities, we propose local diffeomorphic mapping (LDM) for CT prediction. In LDM, we assume that MR and CT patches are located on 2 nonlinear manifolds, and the mapping from the MR manifold to the CT manifold approximates a diffeomorphism under a local constraint. Locality is important in LDM and is constrained by the following techniques. The first is local dictionary construction, wherein, for each patch in the testing MR image, a local search window is used to extract patches from training MR/CT pairs to construct MR and CT dictionaries. The k-nearest neighbors and an outlier detection strategy are then used to constrain the locality in MR and CT dictionaries. Second is local linear representation, wherein, local anchor embedding is used to solve MR dictionary coefficients when representing the MR testing sample. Under these local constraints, dictionary coefficients are linearly transferred from the MR manifold to the CT manifold and used to combine CT training samples to generate CT predictions. Our dataset contains 13 healthy subjects, each with T1- and T2-weighted MR and CT brain images. This method provides CT predictions with a mean absolute error of 110.1 Hounsfield units, Pearson linear correlation of 0.82, peak signal-to-noise ratio of 24.81 dB, and Dice in bone regions of 0.84 as compared with real CTs. CT substitute-based PET reconstruction has a regression slope of 1.0084 and R 2 of 0.9903 compared with real CT-based PET. In this method, no

Novel Approach for Prediction of Localized Necking in Case of Nonlinear Strain Paths

Science.gov (United States)

Drotleff, K.; Liewald, M.

2017-09-01

Rising customer expectations regarding design complexity and weight reduction of sheet metal components alongside with further reduced time to market implicate increased demand for process validation using numerical forming simulation. Formability prediction though often is still based on the forming limit diagram first presented in the 1960s. Despite many drawbacks in case of nonlinear strain paths and major advances in research in the recent years, the forming limit curve (FLC) is still one of the most commonly used criteria for assessing formability of sheet metal materials. Especially when forming complex part geometries nonlinear strain paths may occur, which cannot be predicted using the conventional FLC-Concept. In this paper a novel approach for calculation of FLCs for nonlinear strain paths is presented. Combining an interesting approach for prediction of FLC using tensile test data and IFU-FLC-Criterion a model for prediction of localized necking for nonlinear strain paths can be derived. Presented model is purely based on experimental tensile test data making it easy to calibrate for any given material. Resulting prediction of localized necking is validated using an experimental deep drawing specimen made of AA6014 material having a sheet thickness of 1.04 mm. The results are compared to IFU-FLC-Criterion based on data of pre-stretched Nakajima specimen.

A study of fatigue life prediction for automotive spot weldment using local strain approach

International Nuclear Information System (INIS)

Lee, Song In; Yu, Hyo Sun; Na, Sung Hun; Na, Eui Gyun

2000-01-01

The fatigue crack initiation life is studied on automotive spot weldment made from cold rolled carbon steel(SPC) sheet by using DCPDM and local strain approach. It can be found that the fatigue crack initiation behavior in spot weldment can be definitely detected by DCPDM system. The local stresses and strains are estimated by elastic-plastic FEM analysis and the alternative approximate method based on Neuber's rule were applied to predict the fatigue life of spot weldment. A satisfactory correlation between the predicted life and experimental life can be found in spot weldment within a factor of 4

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...

Wind turbine control with constraint handling: a model predictive control approach

DEFF Research Database (Denmark)

Henriksen, Lars Christian; Hansen, Morten Hartvig; Poulsen, Niels Kjølstad

2012-01-01

on model predictive control, a control method well suited for constraint handling. The performance of the presented controller during an extreme operating gust is compared to that of a proportional-integral controller with integrator anti-windup. Furthermore, the presented controller-s capability...

Prediction of macroscopic and local stress-strain behaviors of perforated plates under primary and secondary creep conditions

International Nuclear Information System (INIS)

Igari, Toshihide; Tokiyoshi, Takumi; Mizokami, Yorikata

2000-01-01

Prediction methods of macroscopic and local creep behaviors of perforated plates are examined in order to apply these methods to the structural design of perforated structures such as heat exchangers used in elevated temperatures. Both primary and secondary creeps are considered for predicting macroscopic and local creep behaviors of perorated plates which are made of actual structural materials. Both uniaxial and multiaxial loading of perforated plates are taken into consideration. The concept of effective stress is applied to the prediction of macroscopic creep behaviors of perforated plates, and the predicted results are compared with the numerical results by FEM for the unit section of perorated plated under creep, in order to confirm the propriety of the proposed method. Based on the idea that stress exponents in creep equations govern the stress distribution of perforated plates, a modified Neuber's rule is used for predicting local stress and strain concentrations. The propriety of this prediction method is shown through a comparison of the prediction with the numerical results by FEM for the unit section of perforated plates under creep, and experimental results by the Moire method. (author)

QUESTION OF IMPROVEMENT OF BUDGET CONTROL AT THE LOCAL LEVEL

Directory of Open Access Journals (Sweden)

Oleg Vatslavskyi

2016-11-01

Full Text Available The aim is to analyse the current practice of budgetary control to develop its areas of improvement at the local level. The subject of the research is theoretical and methodological principles of functioning of budgetary control at the local level. The methodological basis of the study comprises research approaches, general theoretical principles of scientific knowledge, system of methods and techniques. The paper clarifies the nature of budgetary control at the local level. The main bodies that implement budget control, namely the State Audit Office, the Accounting Chamber, the State Treasury, the State Fiscal Service, financial and management departments are singled out. It is found that the leading part among all of the special budgetary control bodies in the rational and efficient use of local financial resources is performed by the State Audit Office. Analysis of the State Audit Office in three regions of Ukraine for the period 2013-2015 has been carried out. We distinguish two main types of violations that the State Audit Service reveals during its work at the local level: 1 shortfall in the financial resources of public enterprises, institutions and organizations; 2 violations that lead to illegal, non-target costs and shortages. It is proved that the efficiency of budgetary control is low. The paper states basic problems of budget control at the local level, namely, low income funds and reimbursements from violations revealed by regulatory agencies; insufficient work with the public to explain the problems of budget control and eliminate violations in the public sector; lack of a consolidated legal act, which would have regulated all the major components of budgetary control; insufficient use of controlling and auditing methods aimed at determining the effectiveness of budget funds; low preventive function on the part of budget control bodies. We offer ways to improve budget control at the local level through: standardization system of

Investigation for GOTHIC-3D prediction capability for the local hydrogen behavior analysis in the NPP containment

International Nuclear Information System (INIS)

Lee, Un-jang; Park, Goon-cherl

2002-01-01

Under a severe accident condition, hydrogen can be generated mainly from the reaction of zirconium cladding with hot steam and flammable hydrogen/air/steam mixtures can be formed. Thus hydrogen analysis is needed for a variety of reasons in the containment building; to predict the global containment response against the threat potential by hydrogen; to address certain safety issues such as the safety feature survivability due to global burning or explosion of hydrogen; or for designing and positioning of the hydrogen controller. In this study an analytical tool was used to predict the local hydrogen behavior in a small compartment and its analytical capability was examined through verification tests, which have been performed in SNU hydrogen mixing facilities. The analytical tool that was employed is the code GOTHIC which is a 3D three-fields (vapor, liquid and droplets) code specially developed for the containment analysis, and has the additional capability of modeling a number of different gases as well as air. The comparison between experimental and analytical tests results showed that the GOTHIC code is not applicable for the analysis of local hydrogen behavior in the highly transient condition and/or in small size compartment. (authors)

Distributed Model Predictive Load Frequency Control of Multi-area Power System with DFIGs

Institute of Scientific and Technical Information of China (English)

Yi Zhang; Xiangjie Liu; Bin Qu

2017-01-01

Reliable load frequency control(LFC) is crucial to the operation and design of modern electric power systems. Considering the LFC problem of a four-area interconnected power system with wind turbines, this paper presents a distributed model predictive control(DMPC) based on coordination scheme.The proposed algorithm solves a series of local optimization problems to minimize a performance objective for each control area. The generation rate constraints(GRCs), load disturbance changes, and the wind speed constraints are considered. Furthermore, the DMPC algorithm may reduce the impact of the randomness and intermittence of wind turbine effectively. A performance comparison between the proposed controller with and without the participation of the wind turbines is carried out. Analysis and simulation results show possible improvements on closed–loop performance, and computational burden with the physical constraints.

Enhancing the Situational Awareness of Airfield Local Controllers

National Research Council Canada - National Science Library

Mowery, Samuel

2002-01-01

.... In air traffic control operations, situational awareness of a local controller at an airfield such as Marine Corps Air Station Camp Pendleton, California, is critical to prevention of catastrophic...

Prediction of localization and interactions of apoptotic proteins

Directory of Open Access Journals (Sweden)

Matula Pavel

2009-07-01

Full Text Available Abstract During apoptosis several mitochondrial proteins are released. Some of them participate in caspase-independent nuclear DNA degradation, especially apoptosis-inducing factor (AIF and endonuclease G (endoG. Another interesting protein, which was expected to act similarly as AIF due to the high sequence homology with AIF is AIF-homologous mitochondrion-associated inducer of death (AMID. We studied the structure, cellular localization, and interactions of several proteins in silico and also in cells using fluorescent microscopy. We found the AMID protein to be cytoplasmic, most probably incorporated into the cytoplasmic side of the lipid membranes. Bioinformatic predictions were conducted to analyze the interactions of the studied proteins with each other and with other possible partners. We conducted molecular modeling of proteins with unknown 3D structures. These models were then refined by MolProbity server and employed in molecular docking simulations of interactions. Our results show data acquired using a combination of modern in silico methods and image analysis to understand the localization, interactions and functions of proteins AMID, AIF, endonuclease G, and other apoptosis-related proteins.

Seasonal prediction of lightning activity in North Western Venezuela: Large-scale versus local drivers

Science.gov (United States)

Muñoz, Á. G.; Díaz-Lobatón, J.; Chourio, X.; Stock, M. J.

2016-05-01

The Lake Maracaibo Basin in North Western Venezuela has the highest annual lightning rate of any place in the world (~ 200 fl km- 2 yr- 1), whose electrical discharges occasionally impact human and animal lives (e.g., cattle) and frequently affect economic activities like oil and natural gas exploitation. Lightning activity is so common in this region that it has a proper name: Catatumbo Lightning (plural). Although short-term lightning forecasts are now common in different parts of the world, to the best of the authors' knowledge, seasonal prediction of lightning activity is still non-existent. This research discusses the relative role of both large-scale and local climate drivers as modulators of lightning activity in the region, and presents a formal predictability study at seasonal scale. Analysis of the Catatumbo Lightning Regional Mode, defined in terms of the second Empirical Orthogonal Function of monthly Lightning Imaging Sensor (LIS-TRMM) and Optical Transient Detector (OTD) satellite data for North Western South America, permits the identification of potential predictors at seasonal scale via a Canonical Correlation Analysis. Lightning activity in North Western Venezuela responds to well defined sea-surface temperature patterns (e.g., El Niño-Southern Oscillation, Atlantic Meridional Mode) and changes in the low-level meridional wind field that are associated with the Inter-Tropical Convergence Zone migrations, the Caribbean Low Level Jet and tropical cyclone activity, but it is also linked to local drivers like convection triggered by the topographic configuration and the effect of the Maracaibo Basin Nocturnal Low Level Jet. The analysis indicates that at seasonal scale the relative contribution of the large-scale drivers is more important than the local (basin-wide) ones, due to the synoptic control imposed by the former. Furthermore, meridional CAPE transport at 925 mb is identified as the best potential predictor for lightning activity in the Lake

Predictive torque and flux control of an induction machine drive ...

Indian Academy of Sciences (India)

Finite-state model predictive control; fuzzy decision making; multi-objective optimization; predictive torque control. Abstract. Among the numerous direct torque control techniques, the finite-state predictive torque control (FS-PTC) has emerged as a powerful alternative as it offers the fast dynamic response and the flexibility to ...

Rate-Based Model Predictive Control of Turbofan Engine Clearance

Science.gov (United States)

DeCastro, Jonathan A.

2006-01-01

An innovative model predictive control strategy is developed for control of nonlinear aircraft propulsion systems and sub-systems. At the heart of the controller is a rate-based linear parameter-varying model that propagates the state derivatives across the prediction horizon, extending prediction fidelity to transient regimes where conventional models begin to lose validity. The new control law is applied to a demanding active clearance control application, where the objectives are to tightly regulate blade tip clearances and also anticipate and avoid detrimental blade-shroud rub occurrences by optimally maintaining a predefined minimum clearance. Simulation results verify that the rate-based controller is capable of satisfying the objectives during realistic flight scenarios where both a conventional Jacobian-based model predictive control law and an unconstrained linear-quadratic optimal controller are incapable of doing so. The controller is evaluated using a variety of different actuators, illustrating the efficacy and versatility of the control approach. It is concluded that the new strategy has promise for this and other nonlinear aerospace applications that place high importance on the attainment of control objectives during transient regimes.

The efficacy of control environment as fraud deterrence in local government

Directory of Open Access Journals (Sweden)

Nuswantara Dian Anita

2017-12-01

Full Text Available In a globalised scenario, the topic of an enormous increase of malfeasance in the local governments, posing catastrophic threats which come from vicious bureaucratic apparatus, becomes a global phenomenon. This current study uses case study material on the risk management control system specially the control environment in Indonesia local governments to extend existing theory by developing a contingency theory for the public sector. Within local government, contingency theory has emerged as a lens for exploring the links between public sector initiatives to improve risk mitigation and the structure of the control system. The case illustrates that the discretion of control environment - the encouragement of a local government’s control environment - is considered as a springboard for fraud deterrence and might be the loopholes in the government control systems.

Domestic appliances energy optimization with model predictive control

International Nuclear Information System (INIS)

Rodrigues, E.M.G.; Godina, R.; Pouresmaeil, E.; Ferreira, J.R.; Catalão, J.P.S.

2017-01-01

Highlights: • An alternative power management control for home appliances that require thermal regulation is presented. • A Model Predictive Control scheme is assessed and its performance studied and compared to the thermostat. • Problem formulation is explored through tuning weights with the aim of reducing energetic consumption and cost. • A modulation scheme of a two-level Model Predictive Control signal as an interface block is presented. • The implementation costs in home appliances with thermal regulation requirements are reduced. - Abstract: A vital element in making a sustainable world is correctly managing the energy in the domestic sector. Thus, this sector evidently stands as a key one for to be addressed in terms of climate change goals. Increasingly, people are aware of electricity savings by turning off the equipment that is not been used, or connect electrical loads just outside the on-peak hours. However, these few efforts are not enough to reduce the global energy consumption, which is increasing. Much of the reduction was due to technological improvements, however with the advancing of the years new types of control arise. Domestic appliances with the purpose of heating and cooling rely on thermostatic regulation technique. The study in this paper is focused on the subject of an alternative power management control for home appliances that require thermal regulation. In this paper a Model Predictive Control scheme is assessed and its performance studied and compared to the thermostat with the aim of minimizing the cooling energy consumption through the minimization of the energy cost while satisfying the adequate temperature range for the human comfort. In addition, the Model Predictive Control problem formulation is explored through tuning weights with the aim of reducing energetic consumption and cost. For this purpose, the typical consumption of a 24 h period of a summer day was simulated a three-level tariff scheme was used. The new

Developing a local least-squares support vector machines-based neuro-fuzzy model for nonlinear and chaotic time series prediction.

Science.gov (United States)

Miranian, A; Abdollahzade, M

2013-02-01

Local modeling approaches, owing to their ability to model different operating regimes of nonlinear systems and processes by independent local models, seem appealing for modeling, identification, and prediction applications. In this paper, we propose a local neuro-fuzzy (LNF) approach based on the least-squares support vector machines (LSSVMs). The proposed LNF approach employs LSSVMs, which are powerful in modeling and predicting time series, as local models and uses hierarchical binary tree (HBT) learning algorithm for fast and efficient estimation of its parameters. The HBT algorithm heuristically partitions the input space into smaller subdomains by axis-orthogonal splits. In each partitioning, the validity functions automatically form a unity partition and therefore normalization side effects, e.g., reactivation, are prevented. Integration of LSSVMs into the LNF network as local models, along with the HBT learning algorithm, yield a high-performance approach for modeling and prediction of complex nonlinear time series. The proposed approach is applied to modeling and predictions of different nonlinear and chaotic real-world and hand-designed systems and time series. Analysis of the prediction results and comparisons with recent and old studies demonstrate the promising performance of the proposed LNF approach with the HBT learning algorithm for modeling and prediction of nonlinear and chaotic systems and time series.

Model predictive control for spacecraft rendezvous in elliptical orbit

Science.gov (United States)

Li, Peng; Zhu, Zheng H.

2018-05-01

This paper studies the control of spacecraft rendezvous with attitude stable or spinning targets in an elliptical orbit. The linearized Tschauner-Hempel equation is used to describe the motion of spacecraft and the problem is formulated by model predictive control. The control objective is to maximize control accuracy and smoothness simultaneously to avoid unexpected change or overshoot of trajectory for safe rendezvous. It is achieved by minimizing the weighted summations of control errors and increments. The effects of two sets of horizons (control and predictive horizons) in the model predictive control are examined in terms of fuel consumption, rendezvous time and computational effort. The numerical results show the proposed control strategy is effective.

Neural Generalized Predictive Control of a non-linear Process

DEFF Research Database (Denmark)

Sørensen, Paul Haase; Nørgård, Peter Magnus; Ravn, Ole

1998-01-01

The use of neural network in non-linear control is made difficult by the fact the stability and robustness is not guaranteed and that the implementation in real time is non-trivial. In this paper we introduce a predictive controller based on a neural network model which has promising stability qu...... detail and discuss the implementation difficulties. The neural generalized predictive controller is tested on a pneumatic servo sys-tem.......The use of neural network in non-linear control is made difficult by the fact the stability and robustness is not guaranteed and that the implementation in real time is non-trivial. In this paper we introduce a predictive controller based on a neural network model which has promising stability...... qualities. The controller is a non-linear version of the well-known generalized predictive controller developed in linear control theory. It involves minimization of a cost function which in the present case has to be done numerically. Therefore, we develop the numerical algorithms necessary in substantial...

Data-driven modeling and predictive control for boiler-turbine unit using fuzzy clustering and subspace methods.

Science.gov (United States)

Wu, Xiao; Shen, Jiong; Li, Yiguo; Lee, Kwang Y

2014-05-01

This paper develops a novel data-driven fuzzy modeling strategy and predictive controller for boiler-turbine unit using fuzzy clustering and subspace identification (SID) methods. To deal with the nonlinear behavior of boiler-turbine unit, fuzzy clustering is used to provide an appropriate division of the operation region and develop the structure of the fuzzy model. Then by combining the input data with the corresponding fuzzy membership functions, the SID method is extended to extract the local state-space model parameters. Owing to the advantages of the both methods, the resulting fuzzy model can represent the boiler-turbine unit very closely, and a fuzzy model predictive controller is designed based on this model. As an alternative approach, a direct data-driven fuzzy predictive control is also developed following the same clustering and subspace methods, where intermediate subspace matrices developed during the identification procedure are utilized directly as the predictor. Simulation results show the advantages and effectiveness of the proposed approach. Copyright © 2014 ISA. Published by Elsevier Ltd. All rights reserved.

Applying model predictive control to power system frequency control

OpenAIRE

Ersdal, AM; Imsland, L; Cecilio, IM; Fabozzi, D; Thornhill, NF

2013-01-01

16.07.14 KB Ok to add accepted version to Spiral Model predictive control (MPC) is investigated as a control method which may offer advantages in frequency control of power systems than the control methods applied today, especially in presence of increased renewable energy penetration. The MPC includes constraints on both generation amount and generation rate of change, and it is tested on a one-area system. The proposed MPC is tested against a conventional proportional-integral (PI) cont...

The improvement of PWR(OPR-1000) Local Control Pannel

Energy Technology Data Exchange (ETDEWEB)

Lee, Joo-Youl; Kim, Min-Soo; Kim, Kyung-Min; Lee, Jun-Kou [KHNP CRI, Daejeon (Korea, Republic of)

2016-10-15

The malfunction of feature in NPP could be occurred by physical aging, electrical false signal and natural disaster. The first recognition of malfunction is almost done by alarm system. Due to the importance of alarm system, design basis of alarm system is described in FSAR 18.1.4.20(alarm system design review). Operators can recognize malfunction of feature and importance of alarm in short distance. The sound of alarm is also changed depending on frequency so it contributes recognition of alarm. This system is not helpful in recognition of alarm for filed operators. In this study, the way that FSAR(priority of alarm and color indication) is also applied on local control is suggested. The alarm sound considering field situation, alarm name, status indication in circuit breaker are suggested to improve overall local control panel. These can contribute to safety operation. This paper is made from improvement items of local control panel in the sight of field operator. The research of local panel is necessary to apply these improvements and the collaboration of related department is also needed. In this study, The alarm sound considering field situation, alarm name, status indication in circuit breaker are suggested to improve overall local control panel based on Hanul Unit 6. If the improvement is applied, the qualitative effect of safe operation will be increased, and fatigue of work stress will be lower.

Outdoor flocking of quadcopter drones with decentralized model predictive control.

Science.gov (United States)

Yuan, Quan; Zhan, Jingyuan; Li, Xiang

2017-11-01

In this paper, we present a multi-drone system featured with a decentralized model predictive control (DMPC) flocking algorithm. The drones gather localized information from neighbors and update their velocities using the DMPC flocking algorithm. In the multi-drone system, data packages are transmitted through XBee ® wireless modules in broadcast mode, yielding such an anonymous and decentralized system where all the calculations and controls are completed on an onboard minicomputer of each drone. Each drone is a double-layered agent system with the coordination layer running multi-drone flocking algorithms and the flight control layer navigating the drone, and the final formation of the flock relies on both the communication range and the desired inter-drone distance. We give both numerical simulations and field tests with a flock of five drones, showing that the DMPC flocking algorithm performs well on the presented multi-drone system in both the convergence rate and the ability of tracking a desired path. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.

Splice site prediction in Arabidopsis thaliana pre-mRNA by combining local and global sequence information

DEFF Research Database (Denmark)

Hebsgaard, Stefan M.; Korning, Peter G.; Tolstrup, Niels

1996-01-01

Artificial neural networks have been combined with a rule based system to predict intron splice sites in the dicot plant Arabidopsis thaliana. A two step prediction scheme, where a global prediction of the coding potential regulates a cutoff level for a local predicition of splice sites, is refin...

Predicting Eye Fixations on Complex Visual Stimuli Using Local Symmetry.

Science.gov (United States)

Kootstra, Gert; de Boer, Bart; Schomaker, Lambert R B

2011-03-01

Most bottom-up models that predict human eye fixations are based on contrast features. The saliency model of Itti, Koch and Niebur is an example of such contrast-saliency models. Although the model has been successfully compared to human eye fixations, we show that it lacks preciseness in the prediction of fixations on mirror-symmetrical forms. The contrast model gives high response at the borders, whereas human observers consistently look at the symmetrical center of these forms. We propose a saliency model that predicts eye fixations using local mirror symmetry. To test the model, we performed an eye-tracking experiment with participants viewing complex photographic images and compared the data with our symmetry model and the contrast model. The results show that our symmetry model predicts human eye fixations significantly better on a wide variety of images including many that are not selected for their symmetrical content. Moreover, our results show that especially early fixations are on highly symmetrical areas of the images. We conclude that symmetry is a strong predictor of human eye fixations and that it can be used as a predictor of the order of fixation.

Improved local control with neoadjuvant chemotherapy for locally advanced rectal carcinoma: Long-term analysis

International Nuclear Information System (INIS)

Nakfoor, Bruce M.; Willett, Christopher G.; Kaufman, S. Donald; Shellito, Paul C.; Daly, William J.

1996-01-01

Objective: Since 1979, our institution has treated locally advanced rectal cancer with preoperative irradiation followed by resection with or without intraoperative radiation therapy (IORT). In 1986, our preoperative treatment policy was changed to include bolus 5-FU chemotherapy concurrent with irradiation in hopes of improving resectability, downstaging and/or local control rates. We report the long-term results with the addition of 5-FU chemotherapy to preoperative irradiation. Materials and Methods: From 1979 - 1994, 200 patients with locally advanced rectal carcinoma (primary or recurrent) received preoperative irradiation, resection and IORT if indicated. Bolus 5-FU (500mg/m 2 /day) chemotherapy was administered for three days during weeks one and five of irradiation. The change in treatment policy was limited to the addition of 5-FU chemotherapy: the radiation techniques (four-field), doses (50.4 Gy), and indications for intraoperative radiation (microscopic residual, gross residual, tumor adherence) remained constant. The median follow-up for the entire group of patients was 33 months (.95 months - 199 months), and the minimum follow-up was 1.5 years. Tabular results are 5-year actuarial calculations. Results: One hundred and five patients received preoperative 5-FU chemotherapy and irradiation whereas 95 patients underwent preoperative irradiation alone. Sixty-five percent of the patients were able to undergo complete resections, and 53% had transmural disease upon pathologic examination. The addition of chemotherapy did not affect the rates of resectability or tumor downstaging. However, the 10-year local control rate was significantly improved for those patients who received preoperative chemotherapy: 77% vs. 44% (p<0.01) (see figure). When stratified by extent of resection and stage, those patients who underwent complete resections or had transmural disease had significantly improved local control rates when compared to the non-chemotherapy group: No

Predicting macropores in space and time by earthworms and abiotic controls

Science.gov (United States)

Hohenbrink, Tobias Ludwig; Schneider, Anne-Kathrin; Zangerlé, Anne; Reck, Arne; Schröder, Boris; van Schaik, Loes

2017-04-01

Macropore flow increases infiltration and solute leaching. The macropore density and connectivity, and thereby the hydrological effectiveness, vary in space and time due to earthworms' burrowing activity and their ability to refill their burrows in order to survive drought periods. The aim of our study was to predict the spatiotemporal variability of macropore distributions by a set of potentially controlling abiotic variables and abundances of different earthworm species. We measured earthworm abundances and effective macropore distributions using tracer rainfall infiltration experiments in six measurement campaigns during one year at six field sites in Luxembourg. Hydrologically effective macropores were counted in three soil depths (3, 10, 30 cm) and distinguished into three diameter classes (6 mm). Earthworms were sampled and determined to species-level. In a generalized linear modelling framework, we related macropores to potential spatial and temporal controlling factors. Earthworm species such as Lumbricus terrestris and Aporrectodea longa, local abiotic site conditions (land use, TWI, slope), temporally varying weather conditions (temperature, humidity, precipitation) and soil moisture affected the number of effective macropores. Main controlling factors and explanatory power of the models (uncertainty and model performance) varied depending on the depth and diameter class of macropores. We present spatiotemporal predictions of macropore density by daily-resolved, one year time series of macropore numbers and maps of macropore distributions at specific dates in a small-scale catchment with 5 m resolution.

Electrochemotherapy increases local control after incomplete ...

African Journals Online (AJOL)

Ibrahim Eldaghayes

2016-11-24

Nov 24, 2016 ... The treatment was well tolerated, and the patient is still disease free after 12 months. ECT resulted in improved local control and should be considered among the available adjuvant treatments in equines carrying soft tissue tumors. Keywords: Cisplatin, Electrochemotherapy, Equine, Fibrosarcoma.

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

Highly tunable local gate controlled complementary graphene device performing as inverter and voltage controlled resistor.

Science.gov (United States)

Kim, Wonjae; Riikonen, Juha; Li, Changfeng; Chen, Ya; Lipsanen, Harri

2013-10-04

Using single-layer CVD graphene, a complementary field effect transistor (FET) device is fabricated on the top of separated back-gates. The local back-gate control of the transistors, which operate with low bias at room temperature, enables highly tunable device characteristics due to separate control over electrostatic doping of the channels. Local back-gating allows control of the doping level independently of the supply voltage, which enables device operation with very low VDD. Controllable characteristics also allow the compensation of variation in the unintentional doping typically observed in CVD graphene. Moreover, both p-n and n-p configurations of FETs can be achieved by electrostatic doping using the local back-gate. Therefore, the device operation can also be switched from inverter to voltage controlled resistor, opening new possibilities in using graphene in logic circuitry.

Tube Model Predictive Control with an Auxiliary Sliding Mode Controller

Directory of Open Access Journals (Sweden)

Miodrag Spasic

2016-07-01

Full Text Available This paper studies Tube Model Predictive Control (MPC with a Sliding Mode Controller (SMC as an auxiliary controller. It is shown how to calculate the tube widths under SMC control, and thus how much the constraints of the nominal MPC have to be tightened in order to achieve robust stability and constraint fulfillment. The analysis avoids the assumption of infinitely fast switching in the SMC controller.

Barriers to adopting and implementing local-level tobacco control policies.

Science.gov (United States)

Satterlund, Travis D; Cassady, Diana; Treiber, Jeanette; Lemp, Cathy

2011-08-01

Although California communities have been relatively successful in adopting and implementing a wide range of local tobacco control policies, the process has not been without its setbacks and barriers. Little is known about local policy adoption, and this paper examines these processes related to adopting and implementing outdoor smoke-free policies, focusing on the major barriers faced by local-level tobacco control organizations in this process. Ninety-six projects funded by the California Tobacco Control Program submitted final evaluation reports pertaining to an outdoor smoking objective, and the reports from these projects were analyzed. The barriers were grouped in three primary areas: politically polarizing barriers, organizational barriers, and local political orientation. The barriers identified in this study underscore the need for an organized action plan in adopting local tobacco policy. The authors also suggest potential strategies to offset the barriers, including: (1) having a "champion" who helps to carry an objective forward; (2) tapping into a pool of youth volunteers; (3) collecting and using local data as a persuasive tool; (4) educating the community in smoke-free policy efforts; (5) working strategically within the local political climate; and (6) demonstrating to policymakers the constituent support for proposed policy.

Predictive local receptive fields based respiratory motion tracking for motion-adaptive radiotherapy.

Science.gov (United States)

Yubo Wang; Tatinati, Sivanagaraja; Liyu Huang; Kim Jeong Hong; Shafiq, Ghufran; Veluvolu, Kalyana C; Khong, Andy W H

2017-07-01

Extracranial robotic radiotherapy employs external markers and a correlation model to trace the tumor motion caused by the respiration. The real-time tracking of tumor motion however requires a prediction model to compensate the latencies induced by the software (image data acquisition and processing) and hardware (mechanical and kinematic) limitations of the treatment system. A new prediction algorithm based on local receptive fields extreme learning machines (pLRF-ELM) is proposed for respiratory motion prediction. All the existing respiratory motion prediction methods model the non-stationary respiratory motion traces directly to predict the future values. Unlike these existing methods, the pLRF-ELM performs prediction by modeling the higher-level features obtained by mapping the raw respiratory motion into the random feature space of ELM instead of directly modeling the raw respiratory motion. The developed method is evaluated using the dataset acquired from 31 patients for two horizons in-line with the latencies of treatment systems like CyberKnife. Results showed that pLRF-ELM is superior to that of existing prediction methods. Results further highlight that the abstracted higher-level features are suitable to approximate the nonlinear and non-stationary characteristics of respiratory motion for accurate prediction.

Adjuvant radiation for vulvar carcinoma: improved local control

International Nuclear Information System (INIS)

Faul, Clare M.; Mirmow, Dwight; Huang Qingshon; Gerszten, Kristina; Day, Roger; Jones, Mirka W.

1997-01-01

Purpose: Local recurrence is a significant problem following primary surgery for advanced vulva carcinoma. The objectives of this study were to evaluate the impact of adjuvant vulvar radiation on local control in high risk patients and the impact of local recurrence on overall survival. Methods and Materials: From 1980-1994, 62 patients with invasive vulva carcinoma and either positive or close (less 8 mm) margins of excision were retrospectively studied. Thirty-one patients were treated with adjuvant radiation therapy to the vulva and 31 patients were observed after surgery. Kaplan-Meier estimates and the Cox proportional hazard regression model were used to evaluate the effect of adjuvant radiation therapy on local recurrence and overall survival. Independent prognostic factors for local recurrence and survival were also assessed. Results: Local recurrence occurred in 58% of observed patients and 16% in patients treated with adjuvant radiation therapy. Adjuvant radiation therapy significantly reduced local recurrence rates in both the close margin and positive margin groups (p = 0.036, p = 0.0048). On both univariate and multivariate analysis adjuvant radiation and margins of excision were significant prognostic predictors for local control. Significant determinants of actuarial survival included International Federation of Gynecologists and Obstetricians (FIGO) stage, percentage of pathologically positive inguinal nodes and margins of excision. The positive margin observed group had a significantly poorer actuarial 5 year survival than the other groups (p = 0.0016) and adjuvant radiation significantly improved survival for this group. The 2 year actuarial survival after developing local recurrence was 25%. Local recurrence was a significant predictor for death from vulva carcinoma (risk ratio 3.54). Conclusion: Local recurrence is a common occurrence in high risk patients. In this study adjuvant radiation therapy significantly reduced local recurrence rates and

Supervisor localization a top-down approach to distributed control of discrete-event systems

CERN Document Server

Cai, Kai

2016-01-01

This monograph presents a systematic top-down approach to distributed control synthesis of discrete-event systems (DES). The approach is called supervisor localization; its essence is the allocation of external supervisory control action to individual component agents as their internal control strategies. The procedure is: first synthesize a monolithic supervisor, to achieve globally optimal and nonblocking controlled behavior, then decompose the monolithic supervisor into local controllers, one for each agent. The collective behavior of the resulting local controllers is identical to that achieved by the monolithic supervisor. The basic localization theory is first presented in the Ramadge–Wonham language-based supervisory control framework, then demonstrated with distributed control examples of multi-robot formations, manufacturing systems, and distributed algorithms. An architectural approach is adopted to apply localization to large-scale DES; this yields a heterarchical localization procedure, which is...

Dynamics and control of quadcopter using linear model predictive control approach

Science.gov (United States)

Islam, M.; Okasha, M.; Idres, M. M.

2017-12-01

This paper investigates the dynamics and control of a quadcopter using the Model Predictive Control (MPC) approach. The dynamic model is of high fidelity and nonlinear, with six degrees of freedom that include disturbances and model uncertainties. The control approach is developed based on MPC to track different reference trajectories ranging from simple ones such as circular to complex helical trajectories. In this control technique, a linearized model is derived and the receding horizon method is applied to generate the optimal control sequence. Although MPC is computer expensive, it is highly effective to deal with the different types of nonlinearities and constraints such as actuators’ saturation and model uncertainties. The MPC parameters (control and prediction horizons) are selected by trial-and-error approach. Several simulation scenarios are performed to examine and evaluate the performance of the proposed control approach using MATLAB and Simulink environment. Simulation results show that this control approach is highly effective to track a given reference trajectory.

Quality Controlled Local Climatological Data (QCLCD) Publication

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — Quality Controlled Local Climatological Data (QCLCD) contains summaries from major airport weather stations that include a daily account of temperature extremes,...

Adjuvant Radiation Therapy Improves Local Control After Surgical Resection in Patients With Localized Adrenocortical Carcinoma

International Nuclear Information System (INIS)

Sabolch, Aaron; Else, Tobias; Griffith, Kent A.; Ben-Josef, Edgar; Williams, Andrew; Miller, Barbra S.; Worden, Francis; Hammer, Gary D.; Jolly, Shruti

2015-01-01

Purpose: Adrenocortical carcinoma (ACC) is a rare malignancy known for high rates of local recurrence, though the benefit of postoperative radiation therapy (RT) has not been established. In this study of grossly resected ACC, we compare local control of patients treated with surgery followed by adjuvant RT to a matched cohort treated with surgery alone. Methods and Materials: We retrospectively identified patients with localized disease who underwent R0 or R1 resection followed by adjuvant RT. Only patients treated with RT at our institution were included. Matching to surgical controls was on the basis of stage, surgical margin status, tumor grade, and adjuvant mitotane. Results: From 1991 to 2011, 360 ACC patients were evaluated for ACC at the University of Michigan (Ann Arbor, MI). Twenty patients with localized disease received postoperative adjuvant RT. These were matched to 20 controls. There were no statistically significant differences between the groups with regard to stage, margins, grade, or mitotane. Median RT dose was 55 Gy (range, 45-60 Gy). Median follow-up was 34 months. Local recurrence occurred in 1 patient treated with RT, compared with 12 patients not treated with RT (P=.0005; hazard ratio [HR] 12.59; 95% confidence interval [CI] 1.62-97.88). However, recurrence-free survival was no different between the groups (P=.17; HR 1.52; 95% CI 0.67-3.45). Overall survival was also not significantly different (P=.13; HR 1.97; 95% CI 0.57-6.77), with 4 deaths in the RT group compared with 9 in the control group. Conclusions: Postoperative RT significantly improved local control compared with the use of surgery alone in this case-matched cohort analysis of grossly resected ACC patients. Although this retrospective series represents the largest study to date on adjuvant RT for ACC, its findings need to be prospectively confirmed

Adjuvant Radiation Therapy Improves Local Control After Surgical Resection in Patients With Localized Adrenocortical Carcinoma

Energy Technology Data Exchange (ETDEWEB)

Sabolch, Aaron [Department of Radiation Oncology, University of Michigan Hospital and Health Systems, Ann Arbor, Mchigan (United States); Else, Tobias [Division of Metabolism, Endocrinology, and Diabetes, Department of Internal Medicine, University of Michigan Hospital and Health Systems, Ann Arbor, Mchigan (United States); Griffith, Kent A. [Center for Cancer Biostatistics, School of Public Health, University of Michigan, Ann Arbor, Mchigan (United States); Ben-Josef, Edgar [Department of Radiation Oncology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania (United States); Williams, Andrew [University of Michigan Medical School, Ann Arbor, Mchigan (United States); Miller, Barbra S. [Division of Endocrine Surgery, Department of General Surgery, University of Michigan Hospital and Health Systems, Ann Arbor, Mchigan (United States); Worden, Francis [Division of Hematology/Oncology, Department of Internal Medicine, University of Michigan Hospital and Health Systems, Ann Arbor, Mchigan (United States); Hammer, Gary D. [Division of Metabolism, Endocrinology, and Diabetes, Department of Internal Medicine, University of Michigan Hospital and Health Systems, Ann Arbor, Mchigan (United States); Jolly, Shruti, E-mail: shrutij@med.umich.edu [Department of Radiation Oncology, University of Michigan Hospital and Health Systems, Ann Arbor, Mchigan (United States)

2015-06-01

Purpose: Adrenocortical carcinoma (ACC) is a rare malignancy known for high rates of local recurrence, though the benefit of postoperative radiation therapy (RT) has not been established. In this study of grossly resected ACC, we compare local control of patients treated with surgery followed by adjuvant RT to a matched cohort treated with surgery alone. Methods and Materials: We retrospectively identified patients with localized disease who underwent R0 or R1 resection followed by adjuvant RT. Only patients treated with RT at our institution were included. Matching to surgical controls was on the basis of stage, surgical margin status, tumor grade, and adjuvant mitotane. Results: From 1991 to 2011, 360 ACC patients were evaluated for ACC at the University of Michigan (Ann Arbor, MI). Twenty patients with localized disease received postoperative adjuvant RT. These were matched to 20 controls. There were no statistically significant differences between the groups with regard to stage, margins, grade, or mitotane. Median RT dose was 55 Gy (range, 45-60 Gy). Median follow-up was 34 months. Local recurrence occurred in 1 patient treated with RT, compared with 12 patients not treated with RT (P=.0005; hazard ratio [HR] 12.59; 95% confidence interval [CI] 1.62-97.88). However, recurrence-free survival was no different between the groups (P=.17; HR 1.52; 95% CI 0.67-3.45). Overall survival was also not significantly different (P=.13; HR 1.97; 95% CI 0.57-6.77), with 4 deaths in the RT group compared with 9 in the control group. Conclusions: Postoperative RT significantly improved local control compared with the use of surgery alone in this case-matched cohort analysis of grossly resected ACC patients. Although this retrospective series represents the largest study to date on adjuvant RT for ACC, its findings need to be prospectively confirmed.

Scanning laser Doppler imaging may predict disease progression of localized scleroderma in children and young adults.

Science.gov (United States)

Shaw, L J; Shipley, J; Newell, E L; Harris, N; Clinch, J G; Lovell, C R

2013-07-01

Localized scleroderma is a rare but potentially disfiguring and disabling condition. Systemic treatment should be started early in those with active disease in key functional and cosmetic sites, but disease activity is difficult to determine clinically. Superficial blood flow has been shown to correlate with disease activity in localized scleroderma. To examine whether superficial blood flow measured by laser Doppler imaging (LDI) has the potential to predict disease progression and therefore select patients for early systemic treatment. A group of 20 individuals had clinical assessment and scanning LDI blood-flow measurements of 32 affected body sites. After a mean follow-up of 8.7 months their clinical outcome was compared with the results of the initial LDI assessment. Eleven out of 15 patients with an assessment of active LDI had progressed clinically, and 16 out of the 17 scans with inactive LDI assessment had not progressed, giving a positive predictive value of 73% and a negative predictive value of 94%. We believe that LDI can be a useful tool in predicting disease progression in localized scleroderma, and it may help clinicians to decide which patients to treat early. © 2013 The Authors BJD © 2013 British Association of Dermatologists.

SU-E-T-630: Predictive Modeling of Mortality, Tumor Control, and Normal Tissue Complications After Stereotactic Body Radiotherapy for Stage I Non-Small Cell Lung Cancer

International Nuclear Information System (INIS)

Lindsay, WD; Berlind, CG; Gee, JC; Simone, CB

2015-01-01

Purpose: While rates of local control have been well characterized after stereotactic body radiotherapy (SBRT) for stage I non-small cell lung cancer (NSCLC), less data are available characterizing survival and normal tissue toxicities, and no validated models exist assessing these parameters after SBRT. We evaluate the reliability of various machine learning techniques when applied to radiation oncology datasets to create predictive models of mortality, tumor control, and normal tissue complications. Methods: A dataset of 204 consecutive patients with stage I non-small cell lung cancer (NSCLC) treated with stereotactic body radiotherapy (SBRT) at the University of Pennsylvania between 2009 and 2013 was used to create predictive models of tumor control, normal tissue complications, and mortality in this IRB-approved study. Nearly 200 data fields of detailed patient- and tumor-specific information, radiotherapy dosimetric measurements, and clinical outcomes data were collected. Predictive models were created for local tumor control, 1- and 3-year overall survival, and nodal failure using 60% of the data (leaving the remainder as a test set). After applying feature selection and dimensionality reduction, nonlinear support vector classification was applied to the resulting features. Models were evaluated for accuracy and area under ROC curve on the 81-patient test set. Results: Models for common events in the dataset (such as mortality at one year) had the highest predictive power (AUC = .67, p < 0.05). For rare occurrences such as radiation pneumonitis and local failure (each occurring in less than 10% of patients), too few events were present to create reliable models. Conclusion: Although this study demonstrates the validity of predictive analytics using information extracted from patient medical records and can most reliably predict for survival after SBRT, larger sample sizes are needed to develop predictive models for normal tissue toxicities and more advanced

SU-E-T-630: Predictive Modeling of Mortality, Tumor Control, and Normal Tissue Complications After Stereotactic Body Radiotherapy for Stage I Non-Small Cell Lung Cancer

Energy Technology Data Exchange (ETDEWEB)

Lindsay, WD [University of Pennsylvania, Philadelphia, PA (United States); Oncora Medical, LLC, Philadelphia, PA (United States); Berlind, CG [Georgia Institute of Technology, Atlanta, GA (Georgia); Oncora Medical, LLC, Philadelphia, PA (United States); Gee, JC; Simone, CB [University of Pennsylvania, Philadelphia, PA (United States)

2015-06-15

Purpose: While rates of local control have been well characterized after stereotactic body radiotherapy (SBRT) for stage I non-small cell lung cancer (NSCLC), less data are available characterizing survival and normal tissue toxicities, and no validated models exist assessing these parameters after SBRT. We evaluate the reliability of various machine learning techniques when applied to radiation oncology datasets to create predictive models of mortality, tumor control, and normal tissue complications. Methods: A dataset of 204 consecutive patients with stage I non-small cell lung cancer (NSCLC) treated with stereotactic body radiotherapy (SBRT) at the University of Pennsylvania between 2009 and 2013 was used to create predictive models of tumor control, normal tissue complications, and mortality in this IRB-approved study. Nearly 200 data fields of detailed patient- and tumor-specific information, radiotherapy dosimetric measurements, and clinical outcomes data were collected. Predictive models were created for local tumor control, 1- and 3-year overall survival, and nodal failure using 60% of the data (leaving the remainder as a test set). After applying feature selection and dimensionality reduction, nonlinear support vector classification was applied to the resulting features. Models were evaluated for accuracy and area under ROC curve on the 81-patient test set. Results: Models for common events in the dataset (such as mortality at one year) had the highest predictive power (AUC = .67, p < 0.05). For rare occurrences such as radiation pneumonitis and local failure (each occurring in less than 10% of patients), too few events were present to create reliable models. Conclusion: Although this study demonstrates the validity of predictive analytics using information extracted from patient medical records and can most reliably predict for survival after SBRT, larger sample sizes are needed to develop predictive models for normal tissue toxicities and more advanced

Local control of Ewing's sarcoma: an analysis of 67 patients

International Nuclear Information System (INIS)

Brown, A.P.; Fixsen, J.A.; Plowman, P.N.

1987-01-01

Local control of Ewing's sarcoma was analysed in a series of 67 patients treated by surgery and/or radiotherapy as well as combination chemotherapy. Radiotherapy was employed with or without surgery in 60 patients and produced an overall local control rate of 55%; complete excision of the primary lesion seemed to be beneficial. There was a marked variation in control rates depending on the site of the primary lesion: limb 85%, rib 53%, pelvis 31% and other sites 33%.Primary tumours greater than 10 cm in diameter were significantly less likely to be controlled. Using daily fractions of approximately 180 cGy, total doses in excess of 6000 cGy seem more likely to produce serious late morbidity amd may not increase the local control rate. No cases of second malignancy arising in irradiated tissue have been observed to date, but one patient developed acute lymphoblastic leukaemia. (author)

Decentralized model predictive based load frequency control in an interconnected power system

Energy Technology Data Exchange (ETDEWEB)

Mohamed, T.H., E-mail: tarekhie@yahoo.co [High Institute of Energy, South Valley University (Egypt); Bevrani, H., E-mail: bevrani@ieee.or [Dept. of Electrical Engineering and Computer Science, University of Kurdistan (Iran, Islamic Republic of); Hassan, A.A., E-mail: aahsn@yahoo.co [Faculty of Engineering, Dept. of Electrical Engineering, Minia University, Minia (Egypt); Hiyama, T., E-mail: hiyama@cs.kumamoto-u.ac.j [Dept. of Electrical Engineering and Computer Science, Kumamoto University, Kumamoto (Japan)

2011-02-15

This paper presents a new load frequency control (LFC) design using the model predictive control (MPC) technique in a multi-area power system. The MPC technique has been designed such that the effect of the uncertainty due to governor and turbine parameters variation and load disturbance is reduced. Each local area controller is designed independently such that stability of the overall closed-loop system is guaranteed. A frequency response model of multi-area power system is introduced, and physical constraints of the governors and turbines are considered. The model was employed in the MPC structures. Digital simulations for both two and three-area power systems are provided to validate the effectiveness of the proposed scheme. The results show that, with the proposed MPC technique, the overall closed-loop system performance demonstrated robustness in the face of uncertainties due to governors and turbines parameters variation and loads disturbances. A performance comparison between the proposed controller and a classical integral control scheme is carried out confirming the superiority of the proposed MPC technique.

Decentralized model predictive based load frequency control in an interconnected power system

International Nuclear Information System (INIS)

Mohamed, T.H.; Bevrani, H.; Hassan, A.A.; Hiyama, T.

2011-01-01

This paper presents a new load frequency control (LFC) design using the model predictive control (MPC) technique in a multi-area power system. The MPC technique has been designed such that the effect of the uncertainty due to governor and turbine parameters variation and load disturbance is reduced. Each local area controller is designed independently such that stability of the overall closed-loop system is guaranteed. A frequency response model of multi-area power system is introduced, and physical constraints of the governors and turbines are considered. The model was employed in the MPC structures. Digital simulations for both two and three-area power systems are provided to validate the effectiveness of the proposed scheme. The results show that, with the proposed MPC technique, the overall closed-loop system performance demonstrated robustness in the face of uncertainties due to governors and turbines parameters variation and loads disturbances. A performance comparison between the proposed controller and a classical integral control scheme is carried out confirming the superiority of the proposed MPC technique.

Assessing the variability of outcome for patients treated with localized prostate irradiation using different definitions of biochemical control

International Nuclear Information System (INIS)

Horwitz, Eric; Ziaja, Ellen; Vicini, Frank; Dmuchowski, Carl; Gonzalez, Jose; Stromberg, Jannifer; Brabbins, Donald; Hollander, Jay; Chen, Peter; Martinez, Alvaro

1995-01-01

control. All local recurrences were biopsy proven. Depending upon the definition used, substantial differences in the rates of biochemical control were observed. The differences in rates of biochemical control between all 4 groups ranged from 5 to 53% (P < .001). The Mantel Haenszel log rank test was used to evaluate the significance of pretx PSA for predicting biochemical control. Conclusion: When different definitions of biochemical control are used in assessing treatment outcome, significantly different rates of biochemical control are noted. Until a standardized definition of biochemical control is adopted, differences in treatment outcome cannot be accurately compared

Frequency weighted model predictive control of wind turbine

DEFF Research Database (Denmark)

Klauco, Martin; Poulsen, Niels Kjølstad; Mirzaei, Mahmood

2013-01-01

This work is focused on applying frequency weighted model predictive control (FMPC) on three blade horizontal axis wind turbine (HAWT). A wind turbine is a very complex, non-linear system influenced by a stochastic wind speed variation. The reduced dynamics considered in this work are the rotatio...... predictive controller are presented. Statistical comparison between frequency weighted MPC, standard MPC and baseline PI controller is shown as well.......This work is focused on applying frequency weighted model predictive control (FMPC) on three blade horizontal axis wind turbine (HAWT). A wind turbine is a very complex, non-linear system influenced by a stochastic wind speed variation. The reduced dynamics considered in this work...... are the rotational degree of freedom of the rotor and the tower for-aft movement. The MPC design is based on a receding horizon policy and a linearised model of the wind turbine. Due to the change of dynamics according to wind speed, several linearisation points must be considered and the control design adjusted...

Predictive Distribution of the Dirichlet Mixture Model by the Local Variational Inference Method

DEFF Research Database (Denmark)

Ma, Zhanyu; Leijon, Arne; Tan, Zheng-Hua

2014-01-01

the predictive likelihood of the new upcoming data, especially when the amount of training data is small. The Bayesian estimation of a Dirichlet mixture model (DMM) is, in general, not analytically tractable. In our previous work, we have proposed a global variational inference-based method for approximately...... calculating the posterior distributions of the parameters in the DMM analytically. In this paper, we extend our previous study for the DMM and propose an algorithm to calculate the predictive distribution of the DMM with the local variational inference (LVI) method. The true predictive distribution of the DMM...... is analytically intractable. By considering the concave property of the multivariate inverse beta function, we introduce an upper-bound to the true predictive distribution. As the global minimum of this upper-bound exists, the problem is reduced to seek an approximation to the true predictive distribution...

Prognostic nomograms for predicting survival and distant metastases in locally advanced rectal cancers.

Directory of Open Access Journals (Sweden)

Junjie Peng

Full Text Available To develop prognostic nomograms for predicting outcomes in patients with locally advanced rectal cancers who do not receive preoperative treatment.A total of 883 patients with stage II-III rectal cancers were retrospectively collected from a single institution. Survival analyses were performed to assess each variable for overall survival (OS, local recurrence (LR and distant metastases (DM. Cox models were performed to develop a predictive model for each endpoint. The performance of model prediction was validated by cross validation and on an independent group of patients.The 5-year LR, DM and OS rates were 22.3%, 32.7% and 63.8%, respectively. Two prognostic nomograms were successfully developed to predict 5-year OS and DM-free survival rates, with c-index of 0.70 (95% CI = [0.66, 0.73] and 0.68 (95% CI = [0.64, 0.72] on the original dataset, and 0.76 (95% CI = [0.67, 0.86] and 0.73 (95% CI = [0.63, 0.83] on the validation dataset, respectively. Factors in our models included age, gender, carcinoembryonic antigen value, tumor location, T stage, N stage, metastatic lymph nodes ratio, adjuvant chemotherapy and chemoradiotherapy. Predicted by our nomogram, substantial variability in terms of 5-year OS and DM-free survival was observed within each TNM stage category.The prognostic nomograms integrated demographic and clinicopathological factors to account for tumor and patient heterogeneity, and thereby provided a more individualized outcome prognostication. Our individualized prediction nomograms could help patients with preoperatively under-staged rectal cancer about their postoperative treatment strategies and follow-up protocols.

Clinical implication of negative conversion of predicted circumferential resection margin status after preoperative chemoradiotherapy for locally advanced rectal cancer

Energy Technology Data Exchange (ETDEWEB)

Lee, Nam Kwon [Department of Radiation Oncology, Korea University Medical Center, Korea University College of Medicine, Seoul (Korea, Republic of); Kim, Chul Yong, E-mail: kcyro@korea.ac.kr [Department of Radiation Oncology, Korea University Medical Center, Korea University College of Medicine, Seoul (Korea, Republic of); Park, Young Je; Yang, Dae Sik; Yoon, Won Sup [Department of Radiation Oncology, Korea University Medical Center, Korea University College of Medicine, Seoul (Korea, Republic of); Kim, Seon Hahn; Kim, Jin [Division of Colorectal Surgery, Department of Surgery, Korea University Medical Center, Korea University College of Medicine, Seoul (Korea, Republic of)

2014-02-15

Objective: To evaluate the prognostic implication of the negative conversion of predicted circumferential resection margin status before surgery in patients with locally advanced rectal cancer with predicted circumferential resection margin involvement. Methods: Thirty-eight patients (28 men, 10 women; median age, 61 years; age range, 39–80 years) with locally advanced rectal cancer with predicted circumferential resection margin involvement who underwent preoperative chemoradiotherapy followed by radical surgery were analyzed. Involvement of the circumferential resection margin was predicted on the basis of pre- and post-chemoradiotherapy magnetic resonance imaging. The primary endpoints were 3-year local recurrence-free survival and overall survival. Results: The median follow-up time was 41.1 months (range, 13.9–85.2 months). The negative conversion rate of predicted circumferential resection margin status after preoperative chemoradiotherapy was 65.8%. Patients who experienced negative conversion of predicted circumferential resection margin status had a significantly higher 3-year local recurrence-free survival rate (100.0% vs. 76.9%; P = 0.013), disease-free survival rate (91.7% vs. 59.3%; P = 0.023), and overall survival rate (96.0% vs. 73.8%; P = 0.016) than those who had persistent circumferential resection margin involvement. Conclusions: The negative conversion of the predicted circumferential resection margin status as predicted by magnetic resonance imaging will assist in individual risk stratification as a predictive factor for treatment response and survival before surgery. These findings may help physicians determine whether to administer more intense adjuvant chemotherapy or change the surgical plan for patients displaying resistance to preoperative chemoradiotherapy.

STAR-TYPE LOCAL AREA NETWORK ACCESS CONTROL

Institute of Scientific and Technical Information of China (English)

逯昭义; 齐藤忠夫

1990-01-01

The multiple access fashion is a new resolution for the star-type local area network (LAN) access control and star-type optical fibre LAN. Arguments about this network are discussed, and the results are introduced.

Performance and robustness of hybrid model predictive control for controllable dampers in building models

Science.gov (United States)

Johnson, Erik A.; Elhaddad, Wael M.; Wojtkiewicz, Steven F.

2016-04-01

A variety of strategies have been developed over the past few decades to determine controllable damping device forces to mitigate the response of structures and mechanical systems to natural hazards and other excitations. These "smart" damping devices produce forces through passive means but have properties that can be controlled in real time, based on sensor measurements of response across the structure, to dramatically reduce structural motion by exploiting more than the local "information" that is available to purely passive devices. A common strategy is to design optimal damping forces using active control approaches and then try to reproduce those forces with the smart damper. However, these design forces, for some structures and performance objectives, may achieve high performance by selectively adding energy, which cannot be replicated by a controllable damping device, causing the smart damper performance to fall far short of what an active system would provide. The authors have recently demonstrated that a model predictive control strategy using hybrid system models, which utilize both continuous and binary states (the latter to capture the switching behavior between dissipative and non-dissipative forces), can provide reductions in structural response on the order of 50% relative to the conventional clipped-optimal design strategy. This paper explores the robustness of this newly proposed control strategy through evaluating controllable damper performance when the structure model differs from the nominal one used to design the damping strategy. Results from the application to a two-degree-of-freedom structure model confirms the robustness of the proposed strategy.

Validation of the mortality prediction equation for damage control ...

African Journals Online (AJOL)

, preoperative lowest pH and lowest core body temperature to derive an equation for the purpose of predicting mortality in damage control surgery. It was shown to reliably predict death despite damage control surgery. The equation derivation ...

Local control of globally competing patterns in coupled Swift-Hohenberg equations

Science.gov (United States)

Becker, Maximilian; Frenzel, Thomas; Niedermayer, Thomas; Reichelt, Sina; Mielke, Alexander; Bär, Markus

2018-04-01

We present analytical and numerical investigations of two anti-symmetrically coupled 1D Swift-Hohenberg equations (SHEs) with cubic nonlinearities. The SHE provides a generic formulation for pattern formation at a characteristic length scale. A linear stability analysis of the homogeneous state reveals a wave instability in addition to the usual Turing instability of uncoupled SHEs. We performed weakly nonlinear analysis in the vicinity of the codimension-two point of the Turing-wave instability, resulting in a set of coupled amplitude equations for the Turing pattern as well as left- and right-traveling waves. In particular, these complex Ginzburg-Landau-type equations predict two major things: there exists a parameter regime where multiple different patterns are stable with respect to each other and that the amplitudes of different patterns interact by local mutual suppression. In consequence, different patterns can coexist in distinct spatial regions, separated by localized interfaces. We identified specific mechanisms for controlling the position of these interfaces, which distinguish what kinds of patterns the interface connects and thus allow for global pattern selection. Extensive simulations of the original SHEs confirm our results.

Electronically controllable spoof localized surface plasmons

Science.gov (United States)

Zhou, Yong Jin; Zhang, Chao; Yang, Liu; Xun Xiao, Qian

2017-10-01

Electronically controllable multipolar spoof localized surface plasmons (LSPs) are experimentally demonstrated in the microwave frequencies. It has been shown that half integer order LSPs modes exist on the corrugated ring loaded with a slit, which actually arise from the Fabry-Perot-like resonances. By mounting active components across the slit in the corrugated rings, electronic switchability and tunability of spoof LSPs modes have been accomplished. Both simulated and measured results demonstrate efficient dynamic control of the spoof LSPs. These elements may form the basis of highly integrated programmable plasmonic circuits in microwave and terahertz regimes.

Fault Tolerant Flight Control Using Sliding Modes and Subspace Identification-Based Predictive Control

KAUST Repository

Siddiqui, Bilal A.; El-Ferik, Sami; Abdelkader, Mohamed

2016-01-01

In this work, a cascade structure of a time-scale separated integral sliding mode and model predictive control is proposed as a viable alternative for fault-tolerant control. A multi-variable sliding mode control law is designed as the inner loop of the flight control system. Subspace identification is carried out on the aircraft in closed loop. The identified plant is then used for model predictive controllers in the outer loop. The overall control law demonstrates improved robustness to measurement noise, modeling uncertainties, multiple faults and severe wind turbulence and gusts. In addition, the flight control system employs filters and dead-zone nonlinear elements to reduce chattering and improve handling quality. Simulation results demonstrate the efficiency of the proposed controller using conventional fighter aircraft without control redundancy.

Fault Tolerant Flight Control Using Sliding Modes and Subspace Identification-Based Predictive Control

KAUST Repository

Siddiqui, Bilal A.

2016-07-26

In this work, a cascade structure of a time-scale separated integral sliding mode and model predictive control is proposed as a viable alternative for fault-tolerant control. A multi-variable sliding mode control law is designed as the inner loop of the flight control system. Subspace identification is carried out on the aircraft in closed loop. The identified plant is then used for model predictive controllers in the outer loop. The overall control law demonstrates improved robustness to measurement noise, modeling uncertainties, multiple faults and severe wind turbulence and gusts. In addition, the flight control system employs filters and dead-zone nonlinear elements to reduce chattering and improve handling quality. Simulation results demonstrate the efficiency of the proposed controller using conventional fighter aircraft without control redundancy.

Prediction of forces and moments for flight vehicle control effectors. Part 1: Validation of methods for predicting hypersonic vehicle controls forces and moments

Science.gov (United States)

Maughmer, Mark D.; Ozoroski, L.; Ozoroski, T.; Straussfogel, D.

1990-01-01

Many types of hypersonic aircraft configurations are currently being studied for feasibility of future development. Since the control of the hypersonic configurations throughout the speed range has a major impact on acceptable designs, it must be considered in the conceptual design stage. The ability of the aerodynamic analysis methods contained in an industry standard conceptual design system, APAS II, to estimate the forces and moments generated through control surface deflections from low subsonic to high hypersonic speeds is considered. Predicted control forces and moments generated by various control effectors are compared with previously published wind tunnel and flight test data for three configurations: the North American X-15, the Space Shuttle Orbiter, and a hypersonic research airplane concept. Qualitative summaries of the results are given for each longitudinal force and moment and each control derivative in the various speed ranges. Results show that all predictions of longitudinal stability and control derivatives are acceptable for use at the conceptual design stage. Results for most lateral/directional control derivatives are acceptable for conceptual design purposes; however, predictions at supersonic Mach numbers for the change in yawing moment due to aileron deflection and the change in rolling moment due to rudder deflection are found to be unacceptable. Including shielding effects in the analysis is shown to have little effect on lift and pitching moment predictions while improving drag predictions.

Blockage-induced condensation controlled by a local reaction

Science.gov (United States)

Cirillo, Emilio N. M.; Colangeli, Matteo; Muntean, Adrian

2016-10-01

We consider the setup of stationary zero range models and discuss the onset of condensation induced by a local blockage on the lattice. We show that the introduction of a local feedback on the hopping rates allows us to control the particle fraction in the condensed phase. This phenomenon results in a current versus blockage parameter curve characterized by two nonanalyticity points.

Model Predictive Control of a Wave Energy Converter

DEFF Research Database (Denmark)

Andersen, Palle; Pedersen, Tom Søndergård; Nielsen, Kirsten Mølgaard

2015-01-01

In this paper reactive control and Model Predictive Control (MPC) for a Wave Energy Converter (WEC) are compared. The analysis is based on a WEC from Wave Star A/S designed as a point absorber. The model predictive controller uses wave models based on the dominating sea states combined with a model...... connecting undisturbed wave sequences to sequences of torque. Losses in the conversion from mechanical to electrical power are taken into account in two ways. Conventional reactive controllers are tuned for each sea state with the assumption that the converter has the same efficiency back and forth. MPC...

Rate of PSA rise predicts metastatic versus local recurrence after definitive radiotherapy

International Nuclear Information System (INIS)

Sartor, C.I.; Strawderman, M.H.; Lin, X.; Kish, K.E.; McLaughlin, P.W.; Lichter, A.S.; Sandler, H.S.

1995-01-01

Objective: A rising PSA following treatment for adenocarcinoma of the prostate indicates eventual clinical failure, but the rate of rise can be quite different from patient to patient, as can the pattern of clinical failure. We sought to determine whether the rate of PSA rise could differentiate future local vs. metastatic failure. Materials and Methods: PSA values from our series of 671 patients treated between 1987 and 1994 with 3-D conformal radiotherapy for localized adenocarcinoma were analyzed. Patients who had a pre-treatment PSA and >4 post-treatment PSA values available, had received no hormonal therapy, and had information detailing clinical outcome were used in this analysis. First site of failure was determined by abnormal DRE or biopsy, abnormal bone scan or radiographic evidence of metastasis as directed by clinical symptoms or follow-up clinical exam. Each patient's PSA pattern was defined by the function PSA(t)=C 1 e - a 1 (t) + C 2 e a 2 (t) where -a 1 relates to the rate of decline and a 2 to the rate of rise, if any. Univariate analysis was used to determine the correlation between initial PSA or rising PSA and clinical failure. Adjacent category logistic regression analysis was used to analyze the rate of rise and pattern of clinical failure. Results: 671 patients were reviewed; 401 patients met the requirements and 2667 PSA values were analyzed. We confirmed the finding of others that pre-treatment PSA is a prognostic indicator: patients presenting with PSA 3-20ng/ml had a relative risk of 9 (p=0.03) and PSA>20ng/ml had a RR of 26 (p=0.002) for clinical failure when compared to presenting PSA 2 >1.5/year predicted metastatic as opposed to local failure when compared to PSA rise with a 2 between 0.5-1.5/yr or 1.5 log(ng/ml)/year vs. 0.5-1.5 log(ng/ml)/yr or <0.5 log(ng/ml)/yr. Conclusions: The rate of rise of PSA following definitive radiotherapy can predict clinical failure patterns, with a rapidly rising PSA indicating metastatic as opposed to

Fuzzy model predictive control algorithm applied in nuclear power plant

International Nuclear Information System (INIS)

Zuheir, Ahmad

2006-01-01

The aim of this paper is to design a predictive controller based on a fuzzy model. The Takagi-Sugeno fuzzy model with an Adaptive B-splines neuro-fuzzy implementation is used and incorporated as a predictor in a predictive controller. An optimization approach with a simplified gradient technique is used to calculate predictions of the future control actions. In this approach, adaptation of the fuzzy model using dynamic process information is carried out to build the predictive controller. The easy description of the fuzzy model and the easy computation of the gradient sector during the optimization procedure are the main advantages of the computation algorithm. The algorithm is applied to the control of a U-tube steam generation unit (UTSG) used for electricity generation. (author)

Cervical Gross Tumor Volume Dose Predicts Local Control Using Magnetic Resonance Imaging/Diffusion-Weighted Imaging—Guided High-Dose-Rate and Positron Emission Tomography/Computed Tomography—Guided Intensity Modulated Radiation Therapy

Energy Technology Data Exchange (ETDEWEB)

Dyk, Pawel; Jiang, Naomi; Sun, Baozhou; DeWees, Todd A. [Department of Radiation Oncology, Washington University School of Medicine, St Louis, Missouri (United States); Fowler, Kathryn J.; Narra, Vamsi [Department of Diagnostic Radiology, Mallinckrodt Institute of Radiology, Washington University School of Medicine, St Louis, Missouri (United States); Garcia-Ramirez, Jose L.; Schwarz, Julie K. [Department of Radiation Oncology, Washington University School of Medicine, St Louis, Missouri (United States); Grigsby, Perry W., E-mail: pgrigsby@wustl.edu [Department of Radiation Oncology, Washington University School of Medicine, St Louis, Missouri (United States); Division of Nuclear Medicine, Mallinckrodt Institute of Radiology, Washington University School of Medicine, St Louis, Missouri (United States); Division of Gynecologic Oncology, Mallinckrodt Institute of Radiology, Washington University School of Medicine, St Louis, Missouri (United States); Alvin J. Siteman Cancer Center, Washington University School of Medicine, St Louis, Missouri (United States)

2014-11-15

Purpose: Magnetic resonance imaging/diffusion weighted-imaging (MRI/DWI)-guided high-dose-rate (HDR) brachytherapy and {sup 18}F-fluorodeoxyglucose (FDG) — positron emission tomography/computed tomography (PET/CT)-guided intensity modulated radiation therapy (IMRT) for the definitive treatment of cervical cancer is a novel treatment technique. The purpose of this study was to report our analysis of dose-volume parameters predicting gross tumor volume (GTV) control. Methods and Materials: We analyzed the records of 134 patients with International Federation of Gynecology and Obstetrics stages IB1-IVB cervical cancer treated with combined MRI-guided HDR and IMRT from July 2009 to July 2011. IMRT was targeted to the metabolic tumor volume and lymph nodes by use of FDG-PET/CT simulation. The GTV for each HDR fraction was delineated by use of T2-weighted or apparent diffusion coefficient maps from diffusion-weighted sequences. The D100, D90, and Dmean delivered to the GTV from HDR and IMRT were summed to EQD2. Results: One hundred twenty-five patients received all irradiation treatment as planned, and 9 did not complete treatment. All 134 patients are included in this analysis. Treatment failure in the cervix occurred in 24 patients (18.0%). Patients with cervix failures had a lower D100, D90, and Dmean than those who did not experience failure in the cervix. The respective doses to the GTV were 41, 58, and 136 Gy for failures compared with 67, 99, and 236 Gy for those who did not experience failure (P<.001). Probit analysis estimated the minimum D100, D90, and Dmean doses required for ≥90% local control to be 69, 98, and 260 Gy (P<.001). Conclusions: Total dose delivered to the GTV from combined MRI-guided HDR and PET/CT-guided IMRT is highly correlated with local tumor control. The findings can be directly applied in the clinic for dose adaptation to maximize local control.

Fault Tolerant Control Using Gaussian Processes and Model Predictive Control

Directory of Open Access Journals (Sweden)

Yang Xiaoke

2015-03-01

Full Text Available Essential ingredients for fault-tolerant control are the ability to represent system behaviour following the occurrence of a fault, and the ability to exploit this representation for deciding control actions. Gaussian processes seem to be very promising candidates for the first of these, and model predictive control has a proven capability for the second. We therefore propose to use the two together to obtain fault-tolerant control functionality. Our proposal is illustrated by several reasonably realistic examples drawn from flight control.

Model Predictive Control with Constraints of a Wind Turbine

DEFF Research Database (Denmark)

Henriksen, Lars Christian; Poulsen, Niels Kjølstad

2007-01-01

Model predictive control of wind turbines offer a more systematic approach of constructing controllers that handle constraints while focusing on the main control objective. In this article several controllers are designed for different wind conditions and appropriate switching conditions ensure a...... an efficient control of the wind turbine over the entire range of wind speeds. Both onshore and floating offshore wind turbines are tested with the controllers.......Model predictive control of wind turbines offer a more systematic approach of constructing controllers that handle constraints while focusing on the main control objective. In this article several controllers are designed for different wind conditions and appropriate switching conditions ensure...

Perceived control among migrant live-in and local live-out home care workers in Israel.

Science.gov (United States)

Shinan-Altman, Shiri; Ayalon, Liat

2017-11-20

To examine perceived control among live-in and live-out home care workers and to identify factors that contribute to perceived control among both types of caregiving. 338 migrant live-in home care workers and 185 local live-out home care workers were asked to report their perceived control. Burnout, satisfaction with the relationship with the care recipient and the care recipient's family, and satisfaction with social relationship were also gathered. Both types of caregivers reported high levels of perceived control, although live-in home care workers expressed more perceived control. Higher age, higher levels of satisfaction with the relationship with the care recipient and the care recipient's family and lower levels of burnout, predicted perceived control. Satisfaction with social relationship was a stronger predictor of one's perceived control among live-in home care workers. Promoting social relationships outside the home care context by allowing migrant live-in home care workers to take part in social gatherings is recommended as this can strengthen their sense of perceived control.

Nonlinear predictive control in the LHC accelerator

CERN Document Server

Blanco, E; Cristea, S; Casas, J

2009-01-01

This paper describes the application of a nonlinear model-based control strategy in a real challenging process. A predictive controller based on a nonlinear model derived from physical relationships, mainly heat and mass balances, has been developed and commissioned in the inner triplet heat exchanger unit (IT-HXTU) of the large hadron collider (LHC) particle accelerator at European Center for Nuclear Research (CERN). The advanced regulation\\ maintains the magnets temperature at about 1.9 K. The development includes a constrained nonlinear state estimator with a receding horizon estimation procedure to improve the regulator predictions.

Generalized predictive control in the delta-domain

DEFF Research Database (Denmark)

Lauritsen, Morten Bach; Jensen, Morten Rostgaard; Poulsen, Niels Kjølstad

1995-01-01

This paper describes new approaches to generalized predictive control formulated in the delta (δ) domain. A new δ-domain version of the continuous-time emulator-based predictor is presented. It produces the optimal estimate in the deterministic case whenever the predictor order is chosen greater...... than or equal to the number of future predicted samples, however a “good” estimate is usually obtained in a much longer range of samples. This is particularly advantageous at fast sampling rates where a “conventional” predictor is bound to become very computationally demanding. Two controllers...

Climate Controls AM Fungal Distributions from Global to Local Scales

Science.gov (United States)

Kivlin, S. N.; Hawkes, C.; Muscarella, R.; Treseder, K. K.; Kazenel, M.; Lynn, J.; Rudgers, J.

2016-12-01

Arbuscular mycorrhizal (AM) fungi have key functions in terrestrial biogeochemical processes; thus, determining the relative importance of climate, edaphic factors, and plant community composition on their geographic distributions can improve predictions of their sensitivity to global change. Local adaptation by AM fungi to plant hosts, soil nutrients, and climate suggests that all of these factors may control fungal geographic distributions, but their relative importance is unknown. We created species distribution models for 142 AM fungal taxa at the global scale with data from GenBank. We compared climate variables (BioClim and soil moisture), edaphic variables (phosphorus, carbon, pH, and clay content), and plant variables using model selection on models with (1) all variables, (2) climatic variables only (including soil moisture) and (3) resource-related variables only (all other soil parameters and NPP) using the MaxEnt algorithm evaluated with ENMEval. We also evaluated whether drivers of AM fungal distributions were phylogenetically conserved. To test whether global correlates of AM fungal distributions were reflected at local scales, we then surveyed AM fungi in nine plant hosts along three elevation gradients in the Upper Gunnison Basin, Colorado, USA. At the global scale, the distributions of 55% of AM fungal taxa were affected by both climate and soil resources, whereas 16% were only affected by climate and 29% were only affected by soil resources. Even for AM fungi that were affected by both climate and resources, the effects of climatic variables nearly always outweighed those of resources. Soil moisture and isothermality were the main climatic and NPP and soil carbon the main resource related factors influencing AM fungal distributions. Distributions of closely related AM fungal taxa were similarly affected by climate, but not by resources. Local scale surveys of AM fungi across elevations confirmed that climate was a key driver of AM fungal

Local, distributed topology control for large-scale wireless ad-hoc networks

NARCIS (Netherlands)

Nieberg, T.; Hurink, Johann L.

In this document, topology control of a large-scale, wireless network by a distributed algorithm that uses only locally available information is presented. Topology control algorithms adjust the transmission power of wireless nodes to create a desired topology. The algorithm, named local power

Local Control With 21-Gy Radiation Therapy for High-Risk Neuroblastoma

International Nuclear Information System (INIS)

Casey, Dana L.; Kushner, Brian H.; Cheung, Nai-Kong V.; Modak, Shakeel; LaQuaglia, Michael P.; Wolden, Suzanne L.

2016-01-01

Purpose: To evaluate local control after 21-Gy radiation therapy (RT) to the primary site in patients with high-risk neuroblastoma. Methods and Materials: After receiving dose-intensive chemotherapy and gross total resection (GTR), 246 patients (aged 1.2-17.9 years, median 4.0 years) with high-risk neuroblastoma underwent RT to the primary site at Memorial Sloan Kettering from 2000 to 2014. Radiation therapy consisted of 21 Gy in twice-daily fractions of 1.5 Gy each. Local failure (LF) was correlated with biologic prognostic factors and clinical findings at the time of diagnosis and start of RT. Results: Median follow-up of surviving patients was 6.4 years. Cumulative incidence of LF was 7.1% at 2 years after RT and 9.8% at 5 years after RT. The isolated LF rate was 3.0%. Eighty-six percent of all local failures were within the RT field. Local control was worse in patients who required more than 1 surgical resection to achieve GTR (22.4% vs 8.3%, P=.01). There was also a trend toward inferior local control with MYCN-amplified tumors or serum lactate dehydrogenase ≥1500 U/L (P=.09 and P=.06, respectively). Conclusion: After intensive chemotherapy and maximal surgical debulking, hyperfractionated RT with 21 Gy in high-risk neuroblastoma results in excellent local control. Given the young patient age, concern for late effects, and local control >90%, dose reduction may be appropriate for patients without MYCN amplification who achieve GTR.

Local Control With 21-Gy Radiation Therapy for High-Risk Neuroblastoma

Energy Technology Data Exchange (ETDEWEB)

Casey, Dana L. [Department of Radiation Oncology, Memorial Sloan Kettering Cancer Center, New York, New York (United States); Kushner, Brian H.; Cheung, Nai-Kong V.; Modak, Shakeel [Department of Pediatrics, Memorial Sloan Kettering Cancer Center, New York, New York (United States); LaQuaglia, Michael P. [Department of Surgery, Memorial Sloan Kettering Cancer Center, New York, New York (United States); Wolden, Suzanne L., E-mail: woldens@mskcc.org [Department of Radiation Oncology, Memorial Sloan Kettering Cancer Center, New York, New York (United States)

2016-10-01

Purpose: To evaluate local control after 21-Gy radiation therapy (RT) to the primary site in patients with high-risk neuroblastoma. Methods and Materials: After receiving dose-intensive chemotherapy and gross total resection (GTR), 246 patients (aged 1.2-17.9 years, median 4.0 years) with high-risk neuroblastoma underwent RT to the primary site at Memorial Sloan Kettering from 2000 to 2014. Radiation therapy consisted of 21 Gy in twice-daily fractions of 1.5 Gy each. Local failure (LF) was correlated with biologic prognostic factors and clinical findings at the time of diagnosis and start of RT. Results: Median follow-up of surviving patients was 6.4 years. Cumulative incidence of LF was 7.1% at 2 years after RT and 9.8% at 5 years after RT. The isolated LF rate was 3.0%. Eighty-six percent of all local failures were within the RT field. Local control was worse in patients who required more than 1 surgical resection to achieve GTR (22.4% vs 8.3%, P=.01). There was also a trend toward inferior local control with MYCN-amplified tumors or serum lactate dehydrogenase ≥1500 U/L (P=.09 and P=.06, respectively). Conclusion: After intensive chemotherapy and maximal surgical debulking, hyperfractionated RT with 21 Gy in high-risk neuroblastoma results in excellent local control. Given the young patient age, concern for late effects, and local control >90%, dose reduction may be appropriate for patients without MYCN amplification who achieve GTR.

Supervisor Localization: A Top-Down Approach to Distributed Control of Discrete-Event Systems

International Nuclear Information System (INIS)

Cai, K.; Wonham, W. M.

2009-01-01

A purely distributed control paradigm is proposed for discrete-event systems (DES). In contrast to control by one or more external supervisors, distributed control aims to design built-in strategies for individual agents. First a distributed optimal nonblocking control problem is formulated. To solve it, a top-down localization procedure is developed which systematically decomposes an external supervisor into local controllers while preserving optimality and nonblockingness. An efficient localization algorithm is provided to carry out the computation, and an automated guided vehicles (AGV) example presented for illustration. Finally, the 'easiest' and 'hardest' boundary cases of localization are discussed.

Predictive models of glucose control: roles for glucose-sensing neurones

Science.gov (United States)

Kosse, C.; Gonzalez, A.; Burdakov, D.

2018-01-01

The brain can be viewed as a sophisticated control module for stabilizing blood glucose. A review of classical behavioural evidence indicates that central circuits add predictive (feedforward/anticipatory) control to the reactive (feedback/compensatory) control by peripheral organs. The brain/cephalic control is constructed and engaged, via associative learning, by sensory cues predicting energy intake or expenditure (e.g. sight, smell, taste, sound). This allows rapidly measurable sensory information (rather than slowly generated internal feedback signals, e.g. digested nutrients) to control food selection, glucose supply for fight-or-flight responses or preparedness for digestion/absorption. Predictive control is therefore useful for preventing large glucose fluctuations. We review emerging roles in predictive control of two classes of widely projecting hypothalamic neurones, orexin/hypocretin (ORX) and melanin-concentrating hormone (MCH) cells. Evidence is cited that ORX neurones (i) are activated by sensory cues (e.g. taste, sound), (ii) drive hepatic production, and muscle uptake, of glucose, via sympathetic nerves, (iii) stimulate wakefulness and exploration via global brain projections and (iv) are glucose-inhibited. MCH neurones are (i) glucose-excited, (ii) innervate learning and reward centres to promote synaptic plasticity, learning and memory and (iii) are critical for learning associations useful for predictive control (e.g. using taste to predict nutrient value of food). This evidence is unified into a model for predictive glucose control. During associative learning, inputs from some glucose-excited neurones may promote connections between the ‘fast’ senses and reward circuits, constructing neural shortcuts for efficient action selection. In turn, glucose-inhibited neurones may engage locomotion/exploration and coordinate the required fuel supply. Feedback inhibition of the latter neurones by glucose would ensure that glucose fluxes they

Predictive models of glucose control: roles for glucose-sensing neurones.

Science.gov (United States)

Kosse, C; Gonzalez, A; Burdakov, D

2015-01-01

The brain can be viewed as a sophisticated control module for stabilizing blood glucose. A review of classical behavioural evidence indicates that central circuits add predictive (feedforward/anticipatory) control to the reactive (feedback/compensatory) control by peripheral organs. The brain/cephalic control is constructed and engaged, via associative learning, by sensory cues predicting energy intake or expenditure (e.g. sight, smell, taste, sound). This allows rapidly measurable sensory information (rather than slowly generated internal feedback signals, e.g. digested nutrients) to control food selection, glucose supply for fight-or-flight responses or preparedness for digestion/absorption. Predictive control is therefore useful for preventing large glucose fluctuations. We review emerging roles in predictive control of two classes of widely projecting hypothalamic neurones, orexin/hypocretin (ORX) and melanin-concentrating hormone (MCH) cells. Evidence is cited that ORX neurones (i) are activated by sensory cues (e.g. taste, sound), (ii) drive hepatic production, and muscle uptake, of glucose, via sympathetic nerves, (iii) stimulate wakefulness and exploration via global brain projections and (iv) are glucose-inhibited. MCH neurones are (i) glucose-excited, (ii) innervate learning and reward centres to promote synaptic plasticity, learning and memory and (iii) are critical for learning associations useful for predictive control (e.g. using taste to predict nutrient value of food). This evidence is unified into a model for predictive glucose control. During associative learning, inputs from some glucose-excited neurones may promote connections between the 'fast' senses and reward circuits, constructing neural shortcuts for efficient action selection. In turn, glucose-inhibited neurones may engage locomotion/exploration and coordinate the required fuel supply. Feedback inhibition of the latter neurones by glucose would ensure that glucose fluxes they stimulate

Local gate control in carbon nanotube quantum devices

Science.gov (United States)

Biercuk, Michael Jordan

This thesis presents transport measurements of carbon nanotube electronic devices operated in the quantum regime. Nanotubes are contacted by source and drain electrodes, and multiple lithographically-patterned electrostatic gates are aligned to each device. Transport measurements of device conductance or current as a function of local gate voltages reveal that local gates couple primarily to the proximal section of the nanotube, hence providing spatially localized control over carrier density along the nanotube length. Further, using several different techniques we are able to produce local depletion regions along the length of a tube. This phenomenon is explored in detail for different contact metals to the nanotube. We utilize local gating techniques to study multiple quantum dots in carbon nanotubes produced both by naturally occurring defects, and by the controlled application of voltages to depletion gates. We study double quantum dots in detail, where transport measurements reveal honeycomb charge stability diagrams. We extract values of energy-level spacings, capacitances, and interaction energies for this system, and demonstrate independent control over all relevant tunneling rates. We report rf-reflectometry measurements of gate-defined carbon nanotube quantum dots with integrated charge sensors. Aluminum rf-SETs are electrostatically coupled to carbon nanotube devices and detect single electron charging phenomena in the Coulomb blockade regime. Simultaneous correlated measurements of single electron charging are made using reflected rf power from the nanotube itself and from the rf-SET on microsecond time scales. We map charge stability diagrams for the nanotube quantum dot via charge sensing, observing Coulomb charging diamonds beyond the first order. Conductance measurements of carbon nanotubes containing gated local depletion regions exhibit plateaus as a function of gate voltage, spaced by approximately 1e2/h, the quantum of conductance for a single

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

Science.gov (United States)

Salehifar, Mehdi; Moreno-Equilaz, Manuel

2016-01-01

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

Robust predictive control strategy applied for propofol dosing using BIS as a controlled variable during anesthesia

NARCIS (Netherlands)

Ionescu, Clara A.; De Keyser, Robin; Torrico, Bismark Claure; De Smet, Tom; Struys, Michel M. R. F.; Normey-Rico, Julio E.

This paper presents the application of predictive control to drug dosing during anesthesia in patients undergoing surgery. The performance of a generic predictive control strategy in drug dosing control, with a previously reported anesthesia-specific control algorithm, has been evaluated. The

Thailand Momentum on Policy and Practice in Local Legislation on Dengue Vector Control

Directory of Open Access Journals (Sweden)

Adisak Bhumiratana

2014-01-01

Full Text Available Over a past decade, an administrative decentralization model, adopted for local administration development in Thailand, is replacing the prior centralized (top-down command system. The change offers challenges to local governmental agencies and other public health agencies at all the ministerial, regional, and provincial levels. A public health regulatory and legislative framework for dengue vector control by local governmental agencies is a national topic of interest because dengue control program has been integrated into healthcare services at the provincial level and also has been given priority in health plans of local governmental agencies. The enabling environments of local administrations are unique, so this critical review focuses on the authority of local governmental agencies responsible for disease prevention and control and on the functioning of local legislation with respect to dengue vector control and practices.

Iterated non-linear model predictive control based on tubes and contractive constraints.

Science.gov (United States)

Murillo, M; Sánchez, G; Giovanini, L

2016-05-01

This paper presents a predictive control algorithm for non-linear systems based on successive linearizations of the non-linear dynamic around a given trajectory. A linear time varying model is obtained and the non-convex constrained optimization problem is transformed into a sequence of locally convex ones. The robustness of the proposed algorithm is addressed adding a convex contractive constraint. To account for linearization errors and to obtain more accurate results an inner iteration loop is added to the algorithm. A simple methodology to obtain an outer bounding-tube for state trajectories is also presented. The convergence of the iterative process and the stability of the closed-loop system are analyzed. The simulation results show the effectiveness of the proposed algorithm in controlling a quadcopter type unmanned aerial vehicle. Copyright © 2016 ISA. Published by Elsevier Ltd. All rights reserved.

Power Admission Control with Predictive Thermal Management in Smart Buildings

DEFF Research Database (Denmark)

Yao, Jianguo; Costanzo, Giuseppe Tommaso; Zhu, Guchuan

2015-01-01

This paper presents a control scheme for thermal management in smart buildings based on predictive power admission control. This approach combines model predictive control with budget-schedulability analysis in order to reduce peak power consumption as well as ensure thermal comfort. First...

Optimization control of LNG regasification plant using Model Predictive Control

Science.gov (United States)

Wahid, A.; Adicandra, F. F.

2018-03-01

Optimization of liquified natural gas (LNG) regasification plant is important to minimize costs, especially operational costs. Therefore, it is important to choose optimum LNG regasification plant design and maintaining the optimum operating conditions through the implementation of model predictive control (MPC). Optimal tuning parameter for MPC such as P (prediction horizon), M (control of the horizon) and T (sampling time) are achieved by using fine-tuning method. The optimal criterion for design is the minimum amount of energy used and for control is integral of square error (ISE). As a result, the optimum design is scheme 2 which is developed by Devold with an energy savings of 40%. To maintain the optimum conditions, required MPC with P, M and T as follows: tank storage pressure: 90, 2, 1; product pressure: 95, 2, 1; temperature vaporizer: 65, 2, 2; and temperature heater: 35, 6, 5, with ISE value at set point tracking respectively 0.99, 1792.78, 34.89 and 7.54, or improvement of control performance respectively 4.6%, 63.5%, 3.1% and 58.2% compared to PI controller performance. The energy savings that MPC controllers can make when there is a disturbance in temperature rise 1°C of sea water is 0.02 MW.

From link-prediction in brain connectomes and protein interactomes to the local-community-paradigm in complex networks.

KAUST Repository

Cannistraci, C.V.

2013-04-08

Growth and remodelling impact the network topology of complex systems, yet a general theory explaining how new links arise between existing nodes has been lacking, and little is known about the topological properties that facilitate link-prediction. Here we investigate the extent to which the connectivity evolution of a network might be predicted by mere topological features. We show how a link/community-based strategy triggers substantial prediction improvements because it accounts for the singular topology of several real networks organised in multiple local communities - a tendency here named local-community-paradigm (LCP). We observe that LCP networks are mainly formed by weak interactions and characterise heterogeneous and dynamic systems that use self-organisation as a major adaptation strategy. These systems seem designed for global delivery of information and processing via multiple local modules. Conversely, non-LCP networks have steady architectures formed by strong interactions, and seem designed for systems in which information/energy storage is crucial.

Hemoglobin levels do not predict biochemical outcome for localized prostate cancer treated with neoadjuvant androgen-suppression therapy and external-beam radiotherapy

International Nuclear Information System (INIS)

Pai, Howard Huaihan; Ludgate, Charles; Pickles, Tom; Paltiel, Chuck M.Sc.; Agranovich, Alex; Berthelet, Eric; Duncan, Graeme; Kim-Sing, Charmaine; Kwan, Winkle; Lim, Jan; Liu, Mitchell; Tyldesley, Scott

2006-01-01

Purpose: To investigate whether hemoglobin (Hb) levels affect outcome in men with localized prostate adenocarcinoma (LPA) treated with neoadjuvant androgen-suppression therapy (NAST) and external-beam radiotherapy (EBRT). Methods and Materials: A total of 563 men with LPA treated with NAST (median: 5.3 months) and EBRT who had Hb levels during treatment were retrospectively reviewed. Patient, tumor, and treatment variables, including the following Hb variables, were subjected to univariate and multivariable analyses to identify factors that predict biochemical control (bNED) and overall survival (OS): pre-EBRT Hb, Hb nadir during EBRT, and change in Hb from pre-EBRT to nadir during EBRT. Results: Median PSA follow-up was 4.25 years. Forty-nine percent of men were anemic during EBRT, with a median Hb of 13.4 g/dL, and 68% experienced a decline in Hb from pre-EBRT to during EBRT of median 0.6 g/dL. Five-year Nadir + 2 bNED and OS rates were similar for anemic and nonanemic patients during EBRT. High percent-positive biopsies, PSA and Gleason score, and use of AA monotherapy predicted worse bNED. High stage and age predicted worse OS. Hb variables were not predictive of bNED or OS. Conclusions: Anemia is a common side effect of NAST and is usually mild. Hb levels, however, do not predict biochemical control or survival

High level model predictive control for plug-and-play process control with stability guaranty

DEFF Research Database (Denmark)

Michelsen, Axel Gottlieb; Stoustrup, Jakob

2010-01-01

In this paper a method for designing a stabilizing high level model predictive controller for a hierarchical plug- and-play process is presented. This is achieved by abstracting the lower layers of the controller structure as low order models with uncertainty and by using a robust model predictive...... controller for generating the references for these. A simulation example, in which the actuators in a process control system are changed, is reported to show the potential of this approach for plug and play process control....

Fuzzy predictive filtering in nonlinear economic model predictive control for demand response

DEFF Research Database (Denmark)

Santos, Rui Mirra; Zong, Yi; Sousa, Joao M. C.

2016-01-01

problem. Moreover, to reduce the computation time and improve the controller's performance, a fuzzy predictive filter is introduced. With the purpose of testing the developed EMPC, a simulation controlling the temperature levels of an intelligent office building (PowerFlexHouse), with and without fuzzy...

Precise Localization and Control of Catalytic Janus Micromotors using Weak Magnetic Fields

NARCIS (Netherlands)

Khalil, Islam S. M.; Magdanz, Veronika; Sanchez, Samuel; Schmidt, Oliver G.; Misra, Sarthak

2015-01-01

We experimentally demonstrate the precise localization of spherical Pt-Silica Janus micromotors (diameter 5 mu m) under the influence of controlled magnetic fields. First, we control the motion of the Janus micromotors in two-dimensional (2D) space. The control system achieves precise localization

Controlling the delocalization-localization transition of light via electromagnetically induced transparency

International Nuclear Information System (INIS)

Cheng Jing; Huang Guoxiang

2011-01-01

We propose a scheme to realize a transition from delocalization to localization of light waves via electromagnetically induced transparency. The system we suggested is a resonant cold atomic ensemble having N configuration, with a control field consisting of two pairs of laser beams with different cross angles, which produce an electromagnetically induced quasiperiodic waveguide (EIQPW) for the propagation of a signal field. By appropriately tuning the incommensurate rate or relative modulation strength between the two pairs of control-field components, the signal field can exhibit the delocalization-localization transition as it transports inside the atomic ensemble. The delocalization-localization transition point is determined and the propagation property of the signal field is studied in detail. Our work provides a way of realizing wave localization via atomic coherence, which is quite different from the conventional, off-resonant mechanism-based Aubry-Andre model, and the great controllability of the EIQPW also allows an easy manipulation of the delocalization-localization transition.

Implementation of neural network based non-linear predictive control

DEFF Research Database (Denmark)

Sørensen, Paul Haase; Nørgård, Peter Magnus; Ravn, Ole

1999-01-01

This paper describes a control method for non-linear systems based on generalized predictive control. Generalized predictive control (GPC) was developed to control linear systems, including open-loop unstable and non-minimum phase systems, but has also been proposed to be extended for the control...... of non-linear systems. GPC is model based and in this paper we propose the use of a neural network for the modeling of the system. Based on the neural network model, a controller with extended control horizon is developed and the implementation issues are discussed, with particular emphasis...... on an efficient quasi-Newton algorithm. The performance is demonstrated on a pneumatic servo system....

A human genome-wide library of local phylogeny predictions for whole-genome inference problems

Directory of Open Access Journals (Sweden)

Schwartz Russell

2008-08-01

Full Text Available Abstract Background Many common inference problems in computational genetics depend on inferring aspects of the evolutionary history of a data set given a set of observed modern sequences. Detailed predictions of the full phylogenies are therefore of value in improving our ability to make further inferences about population history and sources of genetic variation. Making phylogenetic predictions on the scale needed for whole-genome analysis is, however, extremely computationally demanding. Results In order to facilitate phylogeny-based predictions on a genomic scale, we develop a library of maximum parsimony phylogenies within local regions spanning all autosomal human chromosomes based on Haplotype Map variation data. We demonstrate the utility of this library for population genetic inferences by examining a tree statistic we call 'imperfection,' which measures the reuse of variant sites within a phylogeny. This statistic is significantly predictive of recombination rate, shows additional regional and population-specific conservation, and allows us to identify outlier genes likely to have experienced unusual amounts of variation in recent human history. Conclusion Recent theoretical advances in algorithms for phylogenetic tree reconstruction have made it possible to perform large-scale inferences of local maximum parsimony phylogenies from single nucleotide polymorphism (SNP data. As results from the imperfection statistic demonstrate, phylogeny predictions encode substantial information useful for detecting genomic features and population history. This data set should serve as a platform for many kinds of inferences one may wish to make about human population history and genetic variation.

Stock return predictability and market integration: The role of global and local information

Directory of Open Access Journals (Sweden)

David G. McMillan

2016-12-01

Full Text Available This paper examines the predictability of a range of international stock markets where we allow the presence of both local and global predictive factors. Recent research has argued that US returns have predictive power for international stock returns. We expand this line of research, following work on market integration, to include a more general definition of the global factor, based on principal components analysis. Results identify three global expected returns factors, one related to the major stock markets of the US, UK and Asia and one related to the other markets analysed. The third component is related to dividend growth. A single dominant realised returns factor is also noted. A forecasting exercise comparing the principal components based factors to a US return factor and local market only factors, as well as the historical mean benchmark finds supportive evidence for the former approach. It is hoped that the results from this paper will be informative on three counts. First, to academics interested in understanding the dynamics asset price movement. Second, to market participants who aim to time the market and engage in portfolio and risk management. Third, to those (policy makers and others who are interested in linkages across international markets and the nature and degree of integration.

Nonparametric predictive inference in statistical process control

NARCIS (Netherlands)

Arts, G.R.J.; Coolen, F.P.A.; Laan, van der P.

2000-01-01

New methods for statistical process control are presented, where the inferences have a nonparametric predictive nature. We consider several problems in process control in terms of uncertainties about future observable random quantities, and we develop inferences for these random quantities hased on

Supply Chain Control Principles in Local Food Production: A Norwegian Case Study

Directory of Open Access Journals (Sweden)

Heidi C. Dreyer

2014-08-01

Full Text Available Based on an analysis of the supply chain of four producers of local specialty foods, we explore how planning and control principles can be applied to align supply chain capabilities and market requirements. It has been shown that local food struggles with market access, and that the supply chain is one of the obstacles preventing local food producers from gaining a solid market position. We identify a number of features of the local food chain, analyse the obstacles and develop generic designs and control principles for local food producers.

Study of Model Predictive Control for Path-Following Autonomous Ground Vehicle Control under Crosswind Effect

Directory of Open Access Journals (Sweden)

Fitri Yakub

2016-01-01

Full Text Available We present a comparative study of model predictive control approaches of two-wheel steering, four-wheel steering, and a combination of two-wheel steering with direct yaw moment control manoeuvres for path-following control in autonomous car vehicle dynamics systems. Single-track mode, based on a linearized vehicle and tire model, is used. Based on a given trajectory, we drove the vehicle at low and high forward speeds and on low and high road friction surfaces for a double-lane change scenario in order to follow the desired trajectory as close as possible while rejecting the effects of wind gusts. We compared the controller based on both simple and complex bicycle models without and with the roll vehicle dynamics for different types of model predictive control manoeuvres. The simulation result showed that the model predictive control gave a better performance in terms of robustness for both forward speeds and road surface variation in autonomous path-following control. It also demonstrated that model predictive control is useful to maintain vehicle stability along the desired path and has an ability to eliminate the crosswind effect.

Clinical and pathologic factors predictive of biochemical control following post-prostatectomy irradiation

International Nuclear Information System (INIS)

Stromberg, Jannifer S.; Ziaja, Ellen L.; Horwitz, Eric M.; Vicini, Frank A.; Brabbins, Donald S.; Dmuchowski, Carl F.; Gonzalez, Jose; Martinez, Alvaro A.

1996-01-01

Purpose/Objective: Indications for post-prostatectomy radiation therapy are not well defined. We reviewed our experience treating post-prostatectomy patients with external beam irradiation to assess clinical and pathologic factors predictive of biochemical control. Materials and Methods: Between 1/87 and 3/93, 61 patients received post-operative tumor bed irradiation with a median dose of 59.4 Gy (50.4 - 68 Gy). Median follow-up was 4.1 years (7.6 months - 8.3 years) from irradiation. Patients were treated for the following reasons: 1) adjuvantly, within 6 months of surgery for extracapsular extension, seminal vesicle involvement, or positive surgical margins (n=38); 2) persistently elevated PSA post-operatively (n=2); 3) rising PSA >6 months after surgery (n=9); and 4) biopsy proven local recurrence (n=12). No patients had known nodal or metastatic disease. All patients had post-radiation PSA data available. Biochemical control was the endpoint studied using Kaplan-Meier life table analysis. Biochemical control was defined as the ability to maintain an undetectable PSA ( 4 and ≤1 0, >10 and ≤20, and > 20 ng/ml. The 3 year actuarial rates of biochemical control were 100% for group 1, 66.7% for group 2, 61.5% for group 3, and 28.6% for group 4. Pre-RT PSA values were also evaluated. Univariate Cox models indicated lower presurgical and pre-RT PSA values were predictive of biochemical control (p=0.017, p 6 months after surgery (group 3), the 3 year actuarial rate of biochemical control was 55.6%. The 3 year actuarial rate of biochemical control for patients treated for a biopsy proven recurrence (group 4) was 8.3%. By pair-wise log rank test, the rates of biochemical control were significantly different between groups 1 and 3 (p=0.036), groups 1 and 4 (p<0.001), and groups 3 and 4 (p=0.009). Conclusion: Biochemical control was achieved in approximately half of the patients treated with post-operative prostatic fossa irradiation. Elevated presurgical and pre

When predictions take control: The effect of task predictions on task switching performance

Directory of Open Access Journals (Sweden)

Wout eDuthoo

2012-08-01

Full Text Available In this paper, we aimed to investigate the role of self-generated predictions in the flexible control of behaviour. Therefore, we ran a task switching experiment in which participants were asked to try to predict the upcoming task in three conditions varying in switch rate (30%, 50% and 70%. Irrespective of their predictions, the colour of the target indicated which task participants had to perform. In line with previous studies (Mayr, 2006; Monsell & Mizon, 2006, the switch cost was attenuated as the switch rate increased. Importantly, a clear task repetition bias was found in all conditions, yet the task repetition prediction rate dropped from 78% over 66% to 49% with increasing switch probability in the three conditions. Irrespective of condition, the switch cost was strongly reduced in expectation of a task alternation compared to the cost of an unexpected task alternation following repetition predictions. Hence, our data suggest that the reduction in the switch cost with increasing switch probability is caused by a diminished expectancy for the task to repeat. Taken together, this paper highlights the importance of predictions in the flexible control of behaviour, and suggests a crucial role for task repetition expectancy in the context-sensitive adjusting of task switching performance.

Post Laparoscopic Pain Control Using Local Anesthesia through Laparoscopic Port Sites

Directory of Open Access Journals (Sweden)

Seyyed Amir Vejdan

2014-08-01

Full Text Available Background: Severe abdominal pain is not common after laparoscopic surgeries, but acute or chronic pain after operation is considerable in some patients. Post-operative Pain control after laparoscopic surgeries, is conventionally achieved using analgesics such as non-steroidal anti-inflammatory drugs (NSAIDs and narcotics, but their administration has a lot of side effects. This study compares the efficacy and side effects of local anesthetic drugs versus conventional analgesics in post-operative pain control.Materials and Methods: This prospective investigation was conducted into two groups of patients (n=93. Group 1, as control group, was given conventional analgesics such as narcotics and NSAIDs. In investigational group, at the end of laparoscopic surgery, prior to port withdrawal, a local anesthetic mixture, a short acting (Lidocaine 2% plus a long acting (Bupivacaine 0.5% is instilled through the port lumen between the abdominal wall layers. The efficacy of both types of medications was compared to their efficacy and side effects.Results: 85% of the control group, received 5 to 20 ml Morphine for pain control while the others were controlled with trans-rectal NSAIDs. In the treatment group, the pain of 65% of the patients was controlled only by local anesthetic drugs, 30% required NSAIDs and the other 5% required narcotics administration for pain control.Conclusion: The administration of local anesthetic drugs after laparoscopic surgery is an effective method for pain control with a low complications rate and side effects of narcotics.

Local-regional control in breast cancer patients with a possible genetic predisposition

International Nuclear Information System (INIS)

Freedman, Laura M.; Buchholz, Thomas A.; Thames, Howard D.; Strom, Eric A.; McNeese, Marsha D.; Hortobagyi, Gabriel N.; Singletary, S. Eva; Heaton, Keith M.; Hunt, Kelly K.

2000-01-01

Purpose: Local control rates for breast cancer in genetically predisposed women are poorly defined. Because such a small percentage of breast cancer patients have proven germline mutations, surrogates, such as a family history for breast cancer, have been used to examine this issue. The purpose of this study was to evaluate local-regional control following breast conservation therapy (BCT) in patients with bilateral breast cancer and a breast cancer family history. Methods and Materials: We retrospectively reviewed records of all 58 patients with bilateral breast cancer and a breast cancer family history treated in our institution between 1959 and 1998. The primary surgical treatment was a breast-conserving procedure in 55 of the 116 breast cancer cases and a mastectomy in 61. The median follow-up was 68 months for the BCT patients and 57 months for the mastectomy-treated patients. Results: Eight local-regional recurrences occurred in the 55 cases treated with BCT, resulting in 5- and 10-year actuarial local-regional control rates of 86% and 76%, respectively. In the nine cases that did not receive radiation as a component of their BCT, four developed local-regional recurrences (5- and 10-year local-regional control rates of BCT without radiation: 49% and 49%). The 5- and 10-year actuarial local-regional control rates for the 46 cases treated with BCT and radiation were 94% and 83%, respectively. In these cases, there were two late local recurrences, developing at 8 years and 9 years, respectively. A log rank comparison of radiation versus no radiation actuarial data was significant at p = 0.009. In the cases treated with BCT, a multivariate analysis of radiation use, patient age, degree of family history, margin status, and stage revealed that only the use of radiation was associated with improved local control (Cox regression analysis p = 0.021). The 10-year actuarial rates of local-regional control following mastectomy with and without radiation were 91% and 89

Just-In-Time predictive control for a two-wheeled robot

OpenAIRE

Nakpong, Nuttapun; Yamamoto, Shigeru

2012-01-01

In this paper, we introduce the use of Just-In-Time predictive control to enhance the stability of a two-wheeled robot. Just-In-Time predictive control uses a database which includes a huge amounts of input-output data of the two-wheeled robot and predicts its future movements based on a Just-In-Time algorithm. © 2012 IEEE.

A Robust Practical Generalized Predictive Control for BoilerSuper Heater Temperature Control

OpenAIRE

Zaki Maki Mohialdeen

2015-01-01

A practical method of robust generalized predictive controller (GPC) application is developed using a combination of Ziegler-Nichols type functions relating the GPC controller parameters to a first order with time delay process parameters and a model matching controller. The GPC controller and the model matching controller are used in a master/slave configuration, with the GPC as the master controller and the model matching controller as the slave controlle...

Local control of muscle-invasive bladder cancer: preoperative radiotherapy and cystectomy versus cystectomy alone

Energy Technology Data Exchange (ETDEWEB)

Cole, Christopher J; Pollack, Alan; Zagars, Gunar K; Dinney, Colin P; Swanson, David A; Eschenbach, Andrew C. von

1995-05-15

account for the differences in local control in Stage T3b patients. For patients with Stage T3b disease, the only significant difference was by grouped age (p < 0.05, chisquare), which was not a significant factor in the univariate analyses of local control. A multivariate analysis using Cox proportional hazards models revealed pretreatment hemoglobin, blood urea nitrogen (BUN) concentration, and treatment type (PREOP vs. CYST) to be independently predictive of local control. Conclusion: We document here in a large number of patients treated at a single institution that preoperative radiotherapy had a significant impact on local control for patients with clinical Stage T3b disease. Because the CYST patients were treated using modern-day surgical techniques and 80% of those with Stage T3b disease received multiagent chemotherapy, it is probable that any biases, if present, would favor the CYST group. Thus, the differences between PREOP and CYST described may be underestimated. Preoperative radiotherapy should be considered as an adjunct to chemotherapy and surgery for clinical Stage T3b patients.

Model Predictive Controller Combined with LQG Controller and Velocity Feedback to Control the Stewart Platform

DEFF Research Database (Denmark)

Nadimi, Esmaeil Sharak; Bak, Thomas; Izadi-Zamanabadi, Roozbeh

2006-01-01

The main objective of this paper is to investigate the erformance and applicability of two GPC (generalized predictive control) based control methods on a complete benchmark model of the Stewart platform made in MATLAB V6.5. The first method involves an LQG controller (Linear Quadratic Gaussian...

Transforming local government by project portfolio management: Identifying and overcoming control problems

DEFF Research Database (Denmark)

Hansen, Lars Kristian

2013-01-01

Purpose – As public organizations strive for higher e-government maturity, information technology (IT) Project Portfolio Management (IT PPM) has become a high priority issue. Assuming control is central in IT PPM, the purpose of this paper is to investigate how a Danish local government conducts...... to understand how local governments can improve IT PPM. Keywords IT project portfolio management, E-government, Control theory, Control problems, Formal mechanisms, Informal mechanisms, Local government, Denmark...... control in IT PPM. The authors identify control problems and formulate recommendations to address these. Design/methodology/approach – Adopting principles from Engaged Scholarship, the authors have conducted a case study using a wide variety of data collection methods, including 29 interviews, one...

Precise Localization and Formation Control of Swarm Robots via Wireless Sensor Networks

Directory of Open Access Journals (Sweden)

Han Wu

2014-01-01

Full Text Available Precise localization and formation control are one of the key technologies to achieve coordination and control of swarm robots, which is also currently a bottleneck for practical applications of swarm robotic systems. Aiming at overcoming the limited individual perception and the difficulty of achieving precise localization and formation, a localization approach combining dead reckoning (DR with wireless sensor network- (WSN- based methods is proposed in this paper. Two kinds of WSN localization technologies are adopted in this paper, that is, ZigBee-based RSSI (received signal strength indication global localization and electronic tag floors for calibration of local positioning. First, the DR localization information is combined with the ZigBee-based RSSI position information using the Kalman filter method to achieve precise global localization and maintain the robot formation. Then the electronic tag floors provide the robots with their precise coordinates in some local areas and enable the robot swarm to calibrate its formation by reducing the accumulated position errors. Hence, the overall performance of localization and formation control of the swarm robotic system is improved. Both of the simulation results and the experimental results on a real schematic system are given to demonstrate the success of the proposed approach.

Profile control simulations and experiments on TCV: a controller test environment and results using a model-based predictive controller

Science.gov (United States)

Maljaars, E.; Felici, F.; Blanken, T. C.; Galperti, C.; Sauter, O.; de Baar, M. R.; Carpanese, F.; Goodman, T. P.; Kim, D.; Kim, S. H.; Kong, M.; Mavkov, B.; Merle, A.; Moret, J. M.; Nouailletas, R.; Scheffer, M.; Teplukhina, A. A.; Vu, N. M. T.; The EUROfusion MST1-team; The TCV-team

2017-12-01

The successful performance of a model predictive profile controller is demonstrated in simulations and experiments on the TCV tokamak, employing a profile controller test environment. Stable high-performance tokamak operation in hybrid and advanced plasma scenarios requires control over the safety factor profile (q-profile) and kinetic plasma parameters such as the plasma beta. This demands to establish reliable profile control routines in presently operational tokamaks. We present a model predictive profile controller that controls the q-profile and plasma beta using power requests to two clusters of gyrotrons and the plasma current request. The performance of the controller is analyzed in both simulation and TCV L-mode discharges where successful tracking of the estimated inverse q-profile as well as plasma beta is demonstrated under uncertain plasma conditions and the presence of disturbances. The controller exploits the knowledge of the time-varying actuator limits in the actuator input calculation itself such that fast transitions between targets are achieved without overshoot. A software environment is employed to prepare and test this and three other profile controllers in parallel in simulations and experiments on TCV. This set of tools includes the rapid plasma transport simulator RAPTOR and various algorithms to reconstruct the plasma equilibrium and plasma profiles by merging the available measurements with model-based predictions. In this work the estimated q-profile is merely based on RAPTOR model predictions due to the absence of internal current density measurements in TCV. These results encourage to further exploit model predictive profile control in experiments on TCV and other (future) tokamaks.

Force Control for a Pneumatic Cylinder Using Generalized Predictive Controller Approach

OpenAIRE

Mohd Faudzi, Ahmad ’Athif; Mustafa, Nu’man Din; Osman, Khairuddin

2014-01-01

Pneumatic cylinder is a well-known device because of its high power to weight ratio, easy use, and environmental safety. Pneumatic cylinder uses air as its power source and converts it to a possible movement such as linear and rotary movement. In order to control the pneumatic cylinder, controller algorithm is needed to control the on-off solenoid valve with encoder and pressure sensor as the feedback inputs. In this paper, generalized predictive controller (GPC) is proposed as the control st...

Government Internal Control System Maturity: The Role of Internal Guidance and External Control of Local Government in Indonesia

Directory of Open Access Journals (Sweden)

Sutaryo Sutaryo

2017-12-01

Full Text Available This study discusses the Government Internal Control System (SPIP. The purpose of this study is to obtain empirical evidence of influence of guidance, external control, and the characteristics of Local Governments on Internal Control (SPIP maturity of local governments in Indonesia. The samples used in this study are 188 local governments in 2014. The variables used include the dependent variable, i.e. the SPIP maturity of local government; Independent variables, i.e. guidance frequency, the number of internal control findings, total assets, total expenditure and the number of local government units. This study uses secondary data obtained from the Financial and Development Supervisory Agency (BPKP and the Supreme Audit Agency (BPK. This study uses multiple regression analysis and the results show that the guidace frequency and total expenditure have a positive influence on maturity of SPIP, SPI finding has a negative influence, and the total assets and the number of units do not have significant influence on the maturity of SPIP.

Local predation pressure predicts the strength of mobbing responses in tropical birds

Directory of Open Access Journals (Sweden)

Luis SANDOVAL, David R. WILSON

2012-10-01

Full Text Available Many birds join cooperative mobbing aggregations and collectively harass predators. Individuals participating in these ephemeral associations benefit by deterring the predator, but also incur energetic costs and increased risk of predation. Explaining the evolution of mobbing is challenging because individuals could prevail by selfishly seeking safety while allowing others to mob. An important step in understanding the evolution of mobbing is to identify factors affecting its expression. The ecological constraints model suggests that animals are more likely to cooperate under adverse environmental conditions, such as when local predation pressure is high. We tested this prediction by comparing the mobbing responses of several species of birds to the local abundance of their primary predator, the ferruginous pygmy-owl Glaucidium brasilianum. We used acoustic playback to elicit mobbing responses in environments where owls were common, uncommon, or rare. Stimuli were either the song of a ferruginous pygmy-owl or the mobbing calls of three of the owl’s common prey species. During each playback, we characterized mobbing responses by noting the number of species and individuals that approached the loudspeaker, as well as the closest approach by any bird. Mobbing responses to both stimuli were strong in locations where Ferruginous Pygmy-owls were common, intermediate where owls were uncommon, and weak where they were rare. This pattern persisted even after controlling for differences in species richness and composition among the three environments. Results support the ecological constraints model and provide strong evidence that intense predation pressure increases the expression of cooperative mobbing in tropical birds [Current Zoology 58 (5: 781-790, 2012].

General predictive control using the delta operator

DEFF Research Database (Denmark)

Jensen, Morten Rostgaard; Poulsen, Niels Kjølstad; Ravn, Ole

1993-01-01

This paper deals with two-discrete-time operators, the conventional forward shift-operator and the δ-operator. Both operators are treated in view of construction of suitable solutions to the Diophantine equation for the purpose of prediction. A general step-recursive scheme is presented. Finally...... a general predictive control (GPC) is formulated and applied adaptively to a continuous-time plant...

Model predictive control for Z-source power converter

DEFF Research Database (Denmark)

Mo, W.; Loh, P.C.; Blaabjerg, Frede

2011-01-01

This paper presents Model Predictive Control (MPC) of impedance-source (commonly known as Z-source) power converter. Output voltage control and current control for Z-source inverter are analyzed and simulated. With MPC's ability of multi- system variables regulation, load current and voltage...

Precise Localization and Control of Catalytic Janus Micromotors Using Weak Magnetic Fields

Directory of Open Access Journals (Sweden)

Islam S. M. Khalil

2015-01-01

Full Text Available We experimentally demonstrate the precise localization of spherical Pt-Silica Janus micromotors (diameter 5 μm under the influence of controlled magnetic fields. First, we control the motion of the Janus micromotors in two-dimensional (2D space. The control system achieves precise localization within an average region-of-convergence of 7 μm. Second, we show that these micromotors provide sufficient propulsion force, allowing them to overcome drag and gravitational forces and move both downwards and upwards. This propulsion is studied by moving the micromotors in three-dimensional (3D space. The micromotors move downwards and upwards at average speeds of 19.1 μm/s and 9.8 μm/s, respectively. Moreover, our closed-loop control system achieves localization in 3D space within an average region-of-convergence of 6.3 μm in diameter. The precise motion control and localization of the Janus micromotors in 2D and 3D spaces provides broad possibilities for nanotechnology applications.

Predictive Local Composition Models for Solid/Liquid Equilibrium in n-Alkane Systems: Wilson Equation for Multicomponent Systems

DEFF Research Database (Denmark)

Coutinho, João A.P.; Stenby, Erling Halfdan

1996-01-01

The predictive local composition model is applied to multicomponent hydrocarbon systems with long-chain n-alkanes as solutes. The results show that it can successfully be extended to highorder systems and accurately predict the solid appearance temperature, also known as cloud point, in solutions...

Tracking local control of a parabolic trough collector

International Nuclear Information System (INIS)

Ajona, J.I.; Alberdi, J.; Gamero, E.; Blanco, J.

1992-01-01

In the local control, the sun position related to the trough collector is measured by two photo-resistors. The provided electronic signal is then compared with reference levels in order to get a set of B logical signals which form a byte. This byte and the commands issued by a programmable controller are connected to the inputs of o P.R.O.M. memory which is programmed with the logical equations of the control system. The memory output lines give the control command of the parabolic trough collector motor. (Author)

Predictive control and identification: Applications to steering dynamics

DEFF Research Database (Denmark)

Hansen, Anca Daniela

1996-01-01

and of the loss function, which defines the optimality of the control. Some guidelines on how to choose the design parameters, depending on the type of process to be controlled and on the required control performance, are presented. A predictive track keeping system for a Mariner Class Vessel is formulated based...... the under- standing of the connection between identification and control, analysed in Chapter 7. Chapter 7 focuses on how to make the on-line identification for predictive control more robust towards unmodelled dynamics. The theory is verified via simulation studies on a Mariner Class Vessel. The effects...... and the need of a prefilter in the estimation are analysed and illustrated. Based on the idea that the control criterion must be dual to the estimation criterion, an iterative optimal prefilter is designed. This seems to be an appealing way to tune the model towards the objective for which the model...

Catalytic cracking models developed for predictive control purposes

Directory of Open Access Journals (Sweden)

Dag Ljungqvist

1993-04-01

Full Text Available The paper deals with state-space modeling issues in the context of model-predictive control, with application to catalytic cracking. Emphasis is placed on model establishment, verification and online adjustment. Both the Fluid Catalytic Cracking (FCC and the Residual Catalytic Cracking (RCC units are discussed. Catalytic cracking units involve complex interactive processes which are difficult to operate and control in an economically optimal way. The strong nonlinearities of the FCC process mean that the control calculation should be based on a nonlinear model with the relevant constraints included. However, the model can be simple compared to the complexity of the catalytic cracking plant. Model validity is ensured by a robust online model adjustment strategy. Model-predictive control schemes based on linear convolution models have been successfully applied to the supervisory dynamic control of catalytic cracking units, and the control can be further improved by the SSPC scheme.

Economic Model Predictive Control for Smart Energy Systems

DEFF Research Database (Denmark)

Halvgaard, Rasmus

Model Predictive Control (MPC) can be used to control the energy distribution in a Smart Grid with a high share of stochastic energy production from renewable energy sources like wind. Heat pumps for heating residential buildings can exploit the slow heat dynamics of a building to store heat and ...... and hereby shift the heat pump power consumption to periods with both low electricity prices and a high fraction of green energy in the grid.......Model Predictive Control (MPC) can be used to control the energy distribution in a Smart Grid with a high share of stochastic energy production from renewable energy sources like wind. Heat pumps for heating residential buildings can exploit the slow heat dynamics of a building to store heat...

Multimodel Predictive Control Approach for UAV Formation Flight

Directory of Open Access Journals (Sweden)

Chang-jian Ru

2014-01-01

Full Text Available Formation flight problem is the most important and interesting problem of multiple UAVs (unmanned aerial vehicles cooperative control. In this paper, a novel approach for UAV formation flight based on multimodel predictive control is designed. Firstly, the state equation of relative motion is obtained and then discretized. By the geometrical method, the characteristic points of state are determined. Afterwards, based on the linearization technique, the standard linear discrete model is obtained at each characteristic state point. Then, weighted model set is proposed using the idea of T-S (Takagi-Sugeno fuzzy control and the predictive control is carried out based on the multimodel method. Finally, to verify the performance of the proposed method, two different simulation scenarios are performed.

Planning Target Volume D95 and Mean Dose Should Be Considered for Optimal Local Control for Stereotactic Ablative Radiation Therapy

Energy Technology Data Exchange (ETDEWEB)

Zhao, Lina [Department of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, Texas (United States); Zhou, Shouhao [Department of Biostatistics, The University of Texas MD Anderson Cancer Center, Houston, Texas (United States); Balter, Peter [Department of Radiation Physics, The University of Texas MD Anderson Cancer Center, Houston, Texas (United States); Shen, Chan [Department of Health Service Research, The University of Texas MD Anderson Cancer Center, Houston, Texas (United States); Gomez, Daniel R.; Welsh, James D.; Lin, Steve H. [Department of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, Texas (United States); Chang, Joe Y., E-mail: jychang@mdanderson.org [Department of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, Texas (United States)

2016-07-15

Purpose: To identify the optimal dose parameters predictive for local/lobar control after stereotactic ablative radiation therapy (SABR) in early-stage non-small cell lung cancer (NSCLC). Methods and Materials: This study encompassed a total of 1092 patients (1200 lesions) with NSCLC of clinical stage T1-T2 N0M0 who were treated with SABR of 50 Gy in 4 fractions or 70 Gy in 10 fractions, depending on tumor location/size, using computed tomography-based heterogeneity corrections and a convolution superposition calculation algorithm. Patients were monitored by chest CT or positron emission tomography/CT and/or biopsy after SABR. Factors predicting local/lobar recurrence (LR) were determined by competing risk multivariate analysis. Continuous variables were divided into 2 subgroups at cutoff values identified by receiver operating characteristic curves. Results: At a median follow-up time of 31.7 months (interquartile range, 14.8-51.3 months), the 5-year time to local recurrence within the same lobe and overall survival rates were 93.8% and 44.8%, respectively. Total cumulative number of patients experiencing LR was 40 (3.7%), occurring at a median time of 14.4 months (range, 4.8-46 months). Using multivariate competing risk analysis, independent predictive factors for LR after SABR were minimum biologically effective dose (BED{sub 10}) to 95% of planning target volume (PTVD95 BED{sub 10}) ≤86 Gy (corresponding to PTV D95 physics dose of 42 Gy in 4 fractions or 55 Gy in 10 fractions) and gross tumor volume ≥8.3 cm{sup 3}. The PTVmean BED{sub 10} was highly correlated with PTVD95 BED{sub 10.} In univariate analysis, a cutoff of 130 Gy for PTVmean BED{sub 10} (corresponding to PTVmean physics dose of 55 Gy in 4 fractions or 75 Gy in 10 fractions) was also significantly associated with LR. Conclusions: In addition to gross tumor volume, higher radiation dose delivered to the PTV predicts for better local/lobar control. We recommend that both PTVD95 BED

Correlation of a hypoxia based tumor control model with observed local control rates in nasopharyngeal carcinoma treated with chemoradiotherapy

Energy Technology Data Exchange (ETDEWEB)

Avanzo, Michele; Stancanello, Joseph; Franchin, Giovanni; Sartor, Giovanna; Jena, Rajesh; Drigo, Annalisa; Dassie, Andrea; Gigante, Marco; Capra, Elvira [Department of Medical Physics, Centro di Riferimento Oncologico, Aviano 33081 (Italy); Research and Clinical Collaborations, Siemens Healthcare, Erlangen 91052 (Germany); Department of Radiation Oncology, Centro di Riferimento Oncologico, Aviano 33081 (Italy); Department of Medical Physics, Centro di Riferimento Oncologico, Aviano 33081 (Italy); Oncology Centre, Cambridge University Hospitals NHS Foundation Trust, Cambridge CB2 0QQ (United Kingdom); Department of Medical Physics, Centro di Riferimento Oncologico, Aviano 33081 (Italy); Department of Radiation Oncology, Centro di Riferimento Oncologico, Aviano 33081 (Italy); Department of Medical Physics, Centro di Riferimento Oncologico, Aviano 33081 (Italy)

2010-04-15

Purpose: To extend the application of current radiation therapy (RT) based tumor control probability (TCP) models of nasopharyngeal carcinoma (NPC) to include the effects of hypoxia and chemoradiotherapy (CRT). Methods: A TCP model is described based on the linear-quadratic model modified to account for repopulation, chemotherapy, heterogeneity of dose to the tumor, and hypoxia. Sensitivity analysis was performed to determine which parameters exert the greatest influence on the uncertainty of modeled TCP. On the basis of the sensitivity analysis, the values of specific radiobiological parameters were set to nominal values reported in the literature for NPC or head and neck tumors. The remaining radiobiological parameters were determined by fitting TCP to clinical local control data from published randomized studies using both RT and CRT. Validation of the model was performed by comparison of estimated TCP and average overall local control rate (LCR) for 45 patients treated at the institution with conventional linear-accelerator-based or helical tomotherapy based intensity-modulated RT and neoadjuvant chemotherapy. Results: Sensitivity analysis demonstrates that the model is most sensitive to the radiosensitivity term {alpha} and the dose per fraction. The estimated values of {alpha} and OER from data fitting were 0.396 Gy{sup -1} and 1.417. The model estimate of TCP (average 90.9%, range 26.9%-99.2%) showed good correlation with the LCR (86.7%). Conclusions: The model implemented in this work provides clinicians with a useful tool to predict the success rate of treatment, optimize treatment plans, and compare the effects of multimodality therapy.

Correlation of a hypoxia based tumor control model with observed local control rates in nasopharyngeal carcinoma treated with chemoradiotherapy

International Nuclear Information System (INIS)

Avanzo, Michele; Stancanello, Joseph; Franchin, Giovanni; Sartor, Giovanna; Jena, Rajesh; Drigo, Annalisa; Dassie, Andrea; Gigante, Marco; Capra, Elvira

2010-01-01

Purpose: To extend the application of current radiation therapy (RT) based tumor control probability (TCP) models of nasopharyngeal carcinoma (NPC) to include the effects of hypoxia and chemoradiotherapy (CRT). Methods: A TCP model is described based on the linear-quadratic model modified to account for repopulation, chemotherapy, heterogeneity of dose to the tumor, and hypoxia. Sensitivity analysis was performed to determine which parameters exert the greatest influence on the uncertainty of modeled TCP. On the basis of the sensitivity analysis, the values of specific radiobiological parameters were set to nominal values reported in the literature for NPC or head and neck tumors. The remaining radiobiological parameters were determined by fitting TCP to clinical local control data from published randomized studies using both RT and CRT. Validation of the model was performed by comparison of estimated TCP and average overall local control rate (LCR) for 45 patients treated at the institution with conventional linear-accelerator-based or helical tomotherapy based intensity-modulated RT and neoadjuvant chemotherapy. Results: Sensitivity analysis demonstrates that the model is most sensitive to the radiosensitivity term α and the dose per fraction. The estimated values of α and OER from data fitting were 0.396 Gy -1 and 1.417. The model estimate of TCP (average 90.9%, range 26.9%-99.2%) showed good correlation with the LCR (86.7%). Conclusions: The model implemented in this work provides clinicians with a useful tool to predict the success rate of treatment, optimize treatment plans, and compare the effects of multimodality therapy.

Can Image-Defined Risk Factors Predict Surgical Complications in Localized Neuroblastoma?

Science.gov (United States)

Yoneda, Akihiro; Nishikawa, Masanori; Uehara, Shuichiro; Oue, Takaharu; Usui, Noriaki; Inoue, Masami; Fukuzawa, Masahiro; Okuyama, Hiroomi

2016-02-01

Image-defined risk factors (IDRFs) have been propounded for predicting the surgical risks associated with localized neuroblastoma (NB) since 2009. In 2011, a new guideline (NG) for assessing IDRFs was published. According to the NG, the situation in which "the tumor is only in contact with renal vessels," should be considered to be "IDRF-present." Previously, this situation was diagnosed as "IDRF absent." In this study, we evaluated the IDRFs in localized NB patients to clarify the predictive capability of IDRFs for surgical complications, as well as the usefulness of the NG. Materials and A total of 107 localized patients with NB were included in this study. The enhanced computed tomography and magnetic resonance images from the time of their diagnoses were evaluated by a single radiologist. We also analyzed the association of clinical factors, including the IDRFs (before and after applying the NG), with surgical complications. Of the 107 patients, 33 and 74 patients were diagnosed as IDRF-present (OP group), and IDRF-absent (ON group) before the NG, respectively. According to the NG, there were 76 and 31 patients who were classified as IDRF-present (NP group) and IDRF absent (NN group), respectively. Thus, 43 (40%) patients in the ON group were reassigned to the NP group after the NG. Surgical complications were observed in 17 of 82 patients who underwent surgical resection. Of the patients who underwent secondary operations, surgical complication rates were 55% in the OP group and 44% in the NP group. According to a univariate analysis, non-INSS 1, IDRFs before and after the NG and secondary operations were significantly associated with surgical complications. In a multivariate analysis, non-INSS 1 status and IDRFs after the NG were significantly associated with surgical complications. Georg Thieme Verlag KG Stuttgart · New York.

Edge localized modes control: experiment and theory

International Nuclear Information System (INIS)

Bedoulet, M.; Huysmans, G.; Thomas, P.; Joffrin, E.; Rimini, F.; Monier-Garbet, P.; Grosman, A.; Ghendrih, P.; Parail, V.; Lomas, P.; Matthews, G.; Wilson, H.; Gryaznevich, M.; Gonsell, G.; Loarte, A.; Saibene, G.; Sartori, R.; Leonard, A.; Snyder, P.; Evans, T.; Gohil, P.; Burell, H.; Moyer, R.; Kamada, Y.; Oyama, N.; Hatae, T.; Degeling, A.; Martin, Y.; Lister, J.; Rapp, J.; Perez, C.; Lang, P.; Chankin, A.; Eich, T.; Sips, A.; Stober, J.; Horton, L.; Kallenbach, A.; Suttrop, W.; Saarelma, S.; Cowley, S.; Lonnroth, J.; Kamiya, K.; Shimada, M.; Polevoi, A.; Federici, G.

2004-01-01

The paper reviews recent theoretical and experimental results focusing on the identification of the key factors controlling ELM (energy localized mode) energy and particle losses both in natural ELMs and in the presence of external controlling mechanisms. The theoretical description of the most studied Type-I ELMs is progressing from linear MHD stability analysis for peeling and ballooning modes to the non-linear explosive models and transport codes. Present theories cannot predict the ELM size self-consistently, however they pointed out the benefit of the high plasma shaping, high q 95 and high pedestal density in reducing the ELM affected area. The experimental data also suggest that the conductive energy losses in Type-I ELM can be controlled by working in specific plasma conditions. In particular, the existence of purely convective small Type-I ELMs regimes at high q 95 (>4.5) with ΔW ELM /W ped <5% was demonstrated in high triangularity (δ ∼ 0.5) plasmas in JET. Small benign ELMs regimes in present machines (EDA, HRS, Type-II, grassy, QH, Type-III in impurity seeded discharges at high δ and their relevance for ITER parameters are reviewed briefly. The absence of already developed ITER relevant high confinement scenarios with acceptable ELMs has motivated recent intensive experimental and theoretical studies of active control of ELMs. The possibility of suppression of Type-I ELMs in H-mode scenarios at constant confinement was demonstrated in DIII-D experiments with a stochastic boundary created by external coils. It has been demonstrated in AUG that small pellets can trigger Type-I ELMs with a frequency imposed by the pellet injector. Pellet induced ELMs are similar to the intrinsic Type-I ELMs with the same frequency. At the same time the confinement degradation due to the fuelling can be minimized with pellets small as compared to the gas injection. Recent plasma current ramp experiments (JET, COMPASS-D) and modelling (JETTO) demonstrated that the edge

Edge localized modes control: experiment and theory

Energy Technology Data Exchange (ETDEWEB)

Bedoulet, M.; Huysmans, G.; Thomas, P.; Joffrin, E.; Rimini, F.; Monier-Garbet, P.; Grosman, A.; Ghendrih, P. [Association Euratom-CEA, Centre d' Etudes de Cadarache, 13 - Saint-Paul-lez-Durance (France). Dept. de Recherches sur la Fusion Controlee; Parail, V.; Lomas, P.; Matthews, G.; Wilson, H.; Gryaznevich, M.; Gonsell, G.; Loarte, A.; Saibene, G.; Sartori, R.; Leonard, A.; Snyder, P.; Evans, T.; Gohil, P.; Burell, H.; Moyer, R.; Kamada, Y.; Oyama, N.; Hatae, T.; Degeling, A.; Martin, Y.; Lister, J.; Rapp, J.; Perez, C.; Lang, P.; Chankin, A.; Eich, T.; Sips, A.; Stober, J.; Horton, L.; Kallenbach, A.; Suttrop, W.; Saarelma, S.; Cowley, S.; Lonnroth, J.; Kamiya, K.; Shimada, M.; Polevoi, A.; Federici, G

2004-07-01

The paper reviews recent theoretical and experimental results focusing on the identification of the key factors controlling ELM (energy localized mode) energy and particle losses both in natural ELMs and in the presence of external controlling mechanisms. The theoretical description of the most studied Type-I ELMs is progressing from linear MHD stability analysis for peeling and ballooning modes to the non-linear explosive models and transport codes. Present theories cannot predict the ELM size self-consistently, however they pointed out the benefit of the high plasma shaping, high q{sub 95} and high pedestal density in reducing the ELM affected area. The experimental data also suggest that the conductive energy losses in Type-I ELM can be controlled by working in specific plasma conditions. In particular, the existence of purely convective small Type-I ELMs regimes at high q{sub 95} (>4.5) with {delta}W{sub ELM}/W{sub ped}<5% was demonstrated in high triangularity ({delta} {approx} 0.5) plasmas in JET. Small benign ELMs regimes in present machines (EDA, HRS, Type-II, grassy, QH, Type-III in impurity seeded discharges at high {delta} and their relevance for ITER parameters are reviewed briefly. The absence of already developed ITER relevant high confinement scenarios with acceptable ELMs has motivated recent intensive experimental and theoretical studies of active control of ELMs. The possibility of suppression of Type-I ELMs in H-mode scenarios at constant confinement was demonstrated in DIII-D experiments with a stochastic boundary created by external coils. It has been demonstrated in AUG that small pellets can trigger Type-I ELMs with a frequency imposed by the pellet injector. Pellet induced ELMs are similar to the intrinsic Type-I ELMs with the same frequency. At the same time the confinement degradation due to the fuelling can be minimized with pellets small as compared to the gas injection. Recent plasma current ramp experiments (JET, COMPASS-D) and

Local control and survival in spinal cord compression from lymphoma and myeloma

International Nuclear Information System (INIS)

Wallington, M.; Mendis, S.; Premawardhana, U.; Sanders, P.; Shahsavar-Haghighi, K.

1997-01-01

Background: Between 1979 and 1989, 48 cases of extradural spinal cord and cauda equina compression in patients with lymphoma (24) and myeloma (24) received local radiation therapy for control of cord compression. Twenty five (52%) of the cases were treated by surgical decompression prior to irradiation. Thirty five (73%) of the cases received chemotherapy following the diagnosis of spinal cord compression. Post-treatment outcome was assessed at a minimum follow-up of 24 months to determine the significant clinical and treatment factors following irradiation. Results: Seventeen (71%) of the lymphoma and 15 (63%) of the myeloma patients achieved local control, here defined as improvement to, or maintenance of ambulation with minimal or no assistance for 3 months from the start of radiotherapy. At a median follow-up of 30 (2-98) for the lymphoma and 10 (1-87) months for the myeloma patients, the results showed that survival following local radiation therapy for cord compression was independently influenced by the underlying disease type in favour of lymphoma compared to myeloma (P<0.01). The median duration of local control and survival figures were 23 and 48 months for the lymphomas compared to 4.5 and 10 months for the myeloma cases. Survival was also independently influenced by preservation of sphincter function at initial presentation (P<0.02) and the achievement of local control following treatment (P<0.01). Discussion: We conclude that while disease type independently impacts on outcome following treatment of spinal cord compression in lymphoma and myeloma, within both of these disease type the achievement of local control of spinal cord compression is an important management priority, for without local control survival may be adversely affected

Nonlinear model predictive control theory and algorithms

CERN Document Server

Grüne, Lars

2017-01-01

This book offers readers a thorough and rigorous introduction to nonlinear model predictive control (NMPC) for discrete-time and sampled-data systems. NMPC schemes with and without stabilizing terminal constraints are detailed, and intuitive examples illustrate the performance of different NMPC variants. NMPC is interpreted as an approximation of infinite-horizon optimal control so that important properties like closed-loop stability, inverse optimality and suboptimality can be derived in a uniform manner. These results are complemented by discussions of feasibility and robustness. An introduction to nonlinear optimal control algorithms yields essential insights into how the nonlinear optimization routine—the core of any nonlinear model predictive controller—works. Accompanying software in MATLAB® and C++ (downloadable from extras.springer.com/), together with an explanatory appendix in the book itself, enables readers to perform computer experiments exploring the possibilities and limitations of NMPC. T...

Model complexity control for hydrologic prediction

NARCIS (Netherlands)

Schoups, G.; Van de Giesen, N.C.; Savenije, H.H.G.

2008-01-01

A common concern in hydrologic modeling is overparameterization of complex models given limited and noisy data. This leads to problems of parameter nonuniqueness and equifinality, which may negatively affect prediction uncertainties. A systematic way of controlling model complexity is therefore

Nonparametric predictive inference in statistical process control

NARCIS (Netherlands)

Arts, G.R.J.; Coolen, F.P.A.; Laan, van der P.

2004-01-01

Statistical process control (SPC) is used to decide when to stop a process as confidence in the quality of the next item(s) is low. Information to specify a parametric model is not always available, and as SPC is of a predictive nature, we present a control chart developed using nonparametric

Comparisons of predicted steady-state levels in rooms with extended- and local-reaction bounding surfaces

Science.gov (United States)

Hodgson, Murray; Wareing, Andrew

2008-01-01

A combined beam-tracing and transfer-matrix model for predicting steady-state sound-pressure levels in rooms with multilayer bounding surfaces was used to compare the effect of extended- and local-reaction surfaces, and the accuracy of the local-reaction approximation. Three rooms—an office, a corridor and a workshop—with one or more multilayer test surfaces were considered. The test surfaces were a single-glass panel, a double-drywall panel, a carpeted floor, a suspended-acoustical ceiling, a double-steel panel, and glass fibre on a hard backing. Each test surface was modeled as of extended or of local reaction. Sound-pressure levels were predicted and compared to determine the significance of the surface-reaction assumption. The main conclusions were that the difference between modeling a room surface as of extended or of local reaction is not significant when the surface is a single plate or a single layer of material (solid or porous) with a hard backing. The difference is significant when the surface consists of multilayers of solid or porous material and includes a layer of fluid with a large thickness relative to the other layers. The results are partially explained by considering the surface-reflection coefficients at the first-reflection angles.

Rupture Predictions of Notched Ti-6Al-4V Using Local Approaches

Directory of Open Access Journals (Sweden)

Mirco Peron

2018-04-01

Full Text Available Ti-6Al-4V has been extensively used in structural applications in various engineering fields, from naval to automotive and from aerospace to biomedical. Structural applications are characterized by geometrical discontinuities such as notches, which are widely known to harmfully affect their tensile strength. In recent years, many attempts have been done to define solid criteria with which to reliably predict the tensile strength of materials. Among these criteria, two local approaches are worth mentioning due to the accuracy of their predictions, i.e., the strain energy density (SED approach and the theory of critical distance (TCD method. In this manuscript, the robustness of these two methods in predicting the tensile behavior of notched Ti-6Al-4V specimens has been compared. To this aim, two very dissimilar notch geometries have been tested, i.e., semi-circular and blunt V-notch with a notch root radius equal to 1 mm, and the experimental results have been compared with those predicted by the two models. The experimental values have been estimated with low discrepancies by either the SED approach and the TCD method, but the former results in better predictions. The deviations for the SED are in fact lower than 1.3%, while the TCD provides predictions with errors almost up to 8.5%. Finally, the weaknesses and the strengths of the two models have been reported.

The SubCons webserver: A user friendly web interface for state-of-the-art subcellular localization prediction.

Science.gov (United States)

Salvatore, M; Shu, N; Elofsson, A

2018-01-01

SubCons is a recently developed method that predicts the subcellular localization of a protein. It combines predictions from four predictors using a Random Forest classifier. Here, we present the user-friendly web-interface implementation of SubCons. Starting from a protein sequence, the server rapidly predicts the subcellular localizations of an individual protein. In addition, the server accepts the submission of sets of proteins either by uploading the files or programmatically by using command line WSDL API scripts. This makes SubCons ideal for proteome wide analyses allowing the user to scan a whole proteome in few days. From the web page, it is also possible to download precalculated predictions for several eukaryotic organisms. To evaluate the performance of SubCons we present a benchmark of LocTree3 and SubCons using two recent mass-spectrometry based datasets of mouse and drosophila proteins. The server is available at http://subcons.bioinfo.se/. © 2017 The Protein Society.

Generalized Predictive Control for Non-Stationary Systems

DEFF Research Database (Denmark)

Palsson, Olafur Petur; Madsen, Henrik; Søgaard, Henning Tangen

1994-01-01

This paper shows how the generalized predictive control (GPC) can be extended to non-stationary (time-varying) systems. If the time-variation is slow, then the classical GPC can be used in context with an adaptive estimation procedure of a time-invariant ARIMAX model. However, in this paper prior...... knowledge concerning the nature of the parameter variations is assumed available. The GPC is based on the assumption that the prediction of the system output can be expressed as a linear combination of present and future controls. Since the Diophantine equation cannot be used due to the time......-variation of the parameters, the optimal prediction is found as the general conditional expectation of the system output. The underlying model is of an ARMAX-type instead of an ARIMAX-type as in the original version of the GPC (Clarke, D. W., C. Mohtadi and P. S. Tuffs (1987). Automatica, 23, 137-148) and almost all later...

Finite Control Set Model Predictive Control for Multiple Distributed Generators Microgrids

Science.gov (United States)

Babqi, Abdulrahman Jamal

This dissertation proposes two control strategies for AC microgrids that consist of multiple distributed generators (DGs). The control strategies are valid for both grid-connected and islanded modes of operation. In general, microgrid can operate as a stand-alone system (i.e., islanded mode) or while it is connected to the utility grid (i.e., grid connected mode). To enhance the performance of a micrgorid, a sophisticated control scheme should be employed. The control strategies of microgrids can be divided into primary and secondary controls. The primary control regulates the output active and reactive powers of each DG in grid-connected mode as well as the output voltage and frequency of each DG in islanded mode. The secondary control is responsible for regulating the microgrid voltage and frequency in the islanded mode. Moreover, it provides power sharing schemes among the DGs. In other words, the secondary control specifies the set points (i.e. reference values) for the primary controllers. In this dissertation, Finite Control Set Model Predictive Control (FCS-MPC) was proposed for controlling microgrids. FCS-MPC was used as the primary controller to regulate the output power of each DG (in the grid-connected mode) or the voltage of the point of DG coupling (in the islanded mode of operation). In the grid-connected mode, Direct Power Model Predictive Control (DPMPC) was implemented to manage the power flow between each DG and the utility grid. In the islanded mode, Voltage Model Predictive Control (VMPC), as the primary control, and droop control, as the secondary control, were employed to control the output voltage of each DG and system frequency. The controller was equipped with a supplementary current limiting technique in order to limit the output current of each DG in abnormal incidents. The control approach also enabled smooth transition between the two modes. The performance of the control strategy was investigated and verified using PSCAD/EMTDC software

Distributed Model Predictive Control for Smart Energy Systems

DEFF Research Database (Denmark)

Halvgaard, Rasmus Fogtmann; Vandenberghe, Lieven; Poulsen, Niels Kjølstad

2016-01-01

Integration of a large number of flexible consumers in a smart grid requires a scalable power balancing strategy. We formulate the control problem as an optimization problem to be solved repeatedly by the aggregator in a model predictive control framework. To solve the large-scale control problem...

Offset-Free Direct Power Control of DFIG Under Continuous-Time Model Predictive Control

DEFF Research Database (Denmark)

Errouissi, Rachid; Al-Durra, Ahmed; Muyeen, S.M.

2017-01-01

This paper presents a robust continuous-time model predictive direct power control for doubly fed induction generator (DFIG). The proposed approach uses Taylor series expansion to predict the stator current in the synchronous reference frame over a finite time horizon. The predicted stator current...... is directly used to compute the required rotor voltage in order to minimize the difference between the actual stator currents and their references over the predictive time. However, as the proposed strategy is sensitive to parameter variations and external disturbances, a disturbance observer is embedded...... into the control loop to remove the steady-state error of the stator current. It turns out that the steady-state and the transient performances can be identified by simple design parameters. In this paper, the reference of the stator current is directly calculated from the desired stator active and reactive powers...

Local quantum control of Heisenberg spin chains

International Nuclear Information System (INIS)

Heule, Rahel; Bruder, C.; Stojanovic, Vladimir M.; Burgarth, Daniel

2010-01-01

Motivated by some recent results of quantum control theory, we discuss the feasibility of local operator control in arrays of interacting qubits modeled as isotropic Heisenberg spin chains. Acting on one of the end spins, we aim at finding piecewise-constant control pulses that lead to optimal fidelities for a chosen set of quantum gates. We analyze the robustness of the obtained results for the gate fidelities to random errors in the control fields, finding that with faster switching between piecewise-constant controls the system is less susceptible to these errors. The observed behavior falls into a generic class of physical phenomena that are related to a competition between resonance- and relaxation-type behavior, exemplified by motional narrowing in NMR experiments. Finally, we discuss how the obtained optimal gate fidelities are altered when the corresponding rapidly varying piecewise-constant control fields are smoothened through spectral filtering.

Quantized Predictive Control over Erasure Channels

DEFF Research Database (Denmark)

E. Quevedo, Daniel; Østergaard, Jan

2009-01-01

.i.d. dropouts, the controller transmits data packets containing quantized plant input predictions. These minimize a finite horizon cost function and are provided by an appropriate optimal entropy coded dithered lattice vector quantizer. Within this context, we derive an equivalent noise-shaping model...

Robust Predictive Functional Control for Flight Vehicles Based on Nonlinear Disturbance Observer

Directory of Open Access Journals (Sweden)

Yinhui Zhang

2015-01-01

Full Text Available A novel robust predictive functional control based on nonlinear disturbance observer is investigated in order to address the control system design for flight vehicles with significant uncertainties, external disturbances, and measurement noise. Firstly, the nonlinear longitudinal dynamics of the flight vehicle are transformed into linear-like state-space equations with state-dependent coefficient matrices. And then the lumped disturbances are considered in the linear structure predictive model of the predictive functional control to increase the precision of the predictive output and resolve the intractable mismatched disturbance problem. As the lumped disturbances cannot be derived or measured directly, the nonlinear disturbance observer is applied to estimate the lumped disturbances, which are then introduced to the predictive functional control to replace the unknown actual lumped disturbances. Consequently, the robust predictive functional control for the flight vehicle is proposed. Compared with the existing designs, the effectiveness and robustness of the proposed flight control are illustrated and validated in various simulation conditions.

Distributed illumination control with local sensing and actuation in networked lighting systems

NARCIS (Netherlands)

Caicedo Fernandez, D.R.; Pandharipande, A.

2013-01-01

We consider the problem of illumination control in a networked lighting system wherein luminaires have local sensing and actuation capabilities. Each luminaire (i) consists of a light emitting diode (LED) based light source dimmable by a local controller, (ii) is actuated based on sensing

Fourier transform wavefront control with adaptive prediction of the atmosphere.

Science.gov (United States)

Poyneer, Lisa A; Macintosh, Bruce A; Véran, Jean-Pierre

2007-09-01

Predictive Fourier control is a temporal power spectral density-based adaptive method for adaptive optics that predicts the atmosphere under the assumption of frozen flow. The predictive controller is based on Kalman filtering and a Fourier decomposition of atmospheric turbulence using the Fourier transform reconstructor. It provides a stable way to compensate for arbitrary numbers of atmospheric layers. For each Fourier mode, efficient and accurate algorithms estimate the necessary atmospheric parameters from closed-loop telemetry and determine the predictive filter, adjusting as conditions change. This prediction improves atmospheric rejection, leading to significant improvements in system performance. For a 48x48 actuator system operating at 2 kHz, five-layer prediction for all modes is achievable in under 2x10(9) floating-point operations/s.

Modeling, robust and distributed model predictive control for freeway networks

NARCIS (Netherlands)

Liu, S.

2016-01-01

In Model Predictive Control (MPC) for traffic networks, traffic models are crucial since they are used as prediction models for determining the optimal control actions. In order to reduce the computational complexity of MPC for traffic networks, macroscopic traffic models are often used instead of

A Localization Method for Underwater Wireless Sensor Networks Based on Mobility Prediction and Particle Swarm Optimization Algorithms

Directory of Open Access Journals (Sweden)

Ying Zhang

2016-02-01

Full Text Available Due to their special environment, Underwater Wireless Sensor Networks (UWSNs are usually deployed over a large sea area and the nodes are usually floating. This results in a lower beacon node distribution density, a longer time for localization, and more energy consumption. Currently most of the localization algorithms in this field do not pay enough consideration on the mobility of the nodes. In this paper, by analyzing the mobility patterns of water near the seashore, a localization method for UWSNs based on a Mobility Prediction and a Particle Swarm Optimization algorithm (MP-PSO is proposed. In this method, the range-based PSO algorithm is used to locate the beacon nodes, and their velocities can be calculated. The velocity of an unknown node is calculated by using the spatial correlation of underwater object’s mobility, and then their locations can be predicted. The range-based PSO algorithm may cause considerable energy consumption and its computation complexity is a little bit high, nevertheless the number of beacon nodes is relatively smaller, so the calculation for the large number of unknown nodes is succinct, and this method can obviously decrease the energy consumption and time cost of localizing these mobile nodes. The simulation results indicate that this method has higher localization accuracy and better localization coverage rate compared with some other widely used localization methods in this field.

A Localization Method for Underwater Wireless Sensor Networks Based on Mobility Prediction and Particle Swarm Optimization Algorithms.

Science.gov (United States)

Zhang, Ying; Liang, Jixing; Jiang, Shengming; Chen, Wei

2016-02-06

Due to their special environment, Underwater Wireless Sensor Networks (UWSNs) are usually deployed over a large sea area and the nodes are usually floating. This results in a lower beacon node distribution density, a longer time for localization, and more energy consumption. Currently most of the localization algorithms in this field do not pay enough consideration on the mobility of the nodes. In this paper, by analyzing the mobility patterns of water near the seashore, a localization method for UWSNs based on a Mobility Prediction and a Particle Swarm Optimization algorithm (MP-PSO) is proposed. In this method, the range-based PSO algorithm is used to locate the beacon nodes, and their velocities can be calculated. The velocity of an unknown node is calculated by using the spatial correlation of underwater object's mobility, and then their locations can be predicted. The range-based PSO algorithm may cause considerable energy consumption and its computation complexity is a little bit high, nevertheless the number of beacon nodes is relatively smaller, so the calculation for the large number of unknown nodes is succinct, and this method can obviously decrease the energy consumption and time cost of localizing these mobile nodes. The simulation results indicate that this method has higher localization accuracy and better localization coverage rate compared with some other widely used localization methods in this field.

Gain-Scheduled Model Predictive Control of Wind Turbines using Laguerre Functions

DEFF Research Database (Denmark)

Adegas, Fabiano Daher; Wisniewski, Rafal; Larsen, Lars Finn Sloth

2014-01-01

This paper presents a systematic approach to design gain-scheduled predictive controllers for wind turbines. The predictive control law is based on Laguerre functions to parameterize control signals and a parameter-dependent cost function that is analytically determined from turbine data....... These properties facilitate the design of speed controllers by placement of the closed-loop poles (when constraints are not active) and systematic adaptation towards changes in the operating point. Vibration control of undamped modes is achieved by imposing a certain degree of stability to the closed-loop system....... The approach can be utilized to the design of new controllers and to represent existing gain-scheduled controllers as predictive controllers. The numerical example and simulations illustrate the design of a speed controller augmented with active damping of the tower fore-aft displacement....

Prediction based chaos control via a new neural network

International Nuclear Information System (INIS)

Shen Liqun; Wang Mao; Liu Wanyu; Sun Guanghui

2008-01-01

In this Letter, a new chaos control scheme based on chaos prediction is proposed. To perform chaos prediction, a new neural network architecture for complex nonlinear approximation is proposed. And the difficulty in building and training the neural network is also reduced. Simulation results of Logistic map and Lorenz system show the effectiveness of the proposed chaos control scheme and the proposed neural network

Fractional-Order Generalized Predictive Control: Application for Low-Speed Control of Gasoline-Propelled Cars

Directory of Open Access Journals (Sweden)

M. Romero

2013-01-01

Full Text Available There is an increasing interest in using fractional calculus applied to control theory generalizing classical control strategies as the PID controller and developing new ones with the intention of taking advantage of characteristics supplied by this mathematical tool for the controller definition. In this work, the fractional generalization of the successful and spread control strategy known as model predictive control is applied to drive autonomously a gasoline-propelled vehicle at low speeds. The vehicle is a Citroën C3 Pluriel that was modified to act over the throttle and brake pedals. Its highly nonlinear dynamics are an excellent test bed for applying beneficial characteristics of fractional predictive formulation to compensate unmodeled dynamics and external disturbances.

Including model uncertainty in the model predictive control with output feedback

Directory of Open Access Journals (Sweden)

Rodrigues M.A.

2002-01-01

Full Text Available This paper addresses the development of an efficient numerical output feedback robust model predictive controller for open-loop stable systems. Stability of the closed loop is guaranteed by using an infinite horizon predictive controller and a stable state observer. The performance and the computational burden of this approach are compared to a robust predictive controller from the literature. The case used for this study is based on an industrial gasoline debutanizer column.

Numerical prediction of local transitional features of turbulent forced gas flows in circular tubes with strong heating

International Nuclear Information System (INIS)

Ezato, Koichiro; Kunugi, Tomoaki; Shehata, A.M.; McEligot, D.M.

1997-03-01

Previous numerical simulation for the laminarization due to heating of the turbulent flow in pipe were assessed by comparison with only macroscopic characteristics such as heat transfer coefficient and pressure drop, since no experimental data on the local distributions of the velocity and temperature in such flow situation was available. Recently, Shehata and McEligot reported the first measurements of local distributions of velocity and temperature for turbulent forced air flow in a vertical circular tube with strongly heating. They carried out the experiments in three situations from turbulent flow to laminarizing flow according to the heating rate. In the present study, we analyzed numerically the local transitional features of turbulent flow evolving laminarizing due to strong heating in their experiments by using the advanced low-Re two-equation turbulence model. As the result, we successfully predicted the local distributions of velocity and temperature as well as macroscopic characteristics in three turbulent flow conditions. By the present study, a numerical procedure has been established to predict the local characteristics such as velocity distribution of the turbulent flow with large thermal-property variation and laminarizing flow due to strong heating with enough accuracy. (author). 60 refs

Skill prediction of local weather forecasts based on the ECMWF ensemble

Directory of Open Access Journals (Sweden)

C. Ziehmann

2001-01-01

Full Text Available Ensemble Prediction has become an essential part of numerical weather forecasting. In this paper we investigate the ability of ensemble forecasts to provide an a priori estimate of the expected forecast skill. Several quantities derived from the local ensemble distribution are investigated for a two year data set of European Centre for Medium-Range Weather Forecasts (ECMWF temperature and wind speed ensemble forecasts at 30 German stations. The results indicate that the population of the ensemble mode provides useful information for the uncertainty in temperature forecasts. The ensemble entropy is a similar good measure. This is not true for the spread if it is simply calculated as the variance of the ensemble members with respect to the ensemble mean. The number of clusters in the C regions is almost unrelated to the local skill. For wind forecasts, the results are less promising.

Selection of References in Wind Turbine Model Predictive Control Design

DEFF Research Database (Denmark)

Odgaard, Peter Fogh; Hovgaard, Tobias

2015-01-01

a model predictive controller for a wind turbine. One of the important aspects for a tracking control problem is how to setup the optimal reference tracking problem, as it might be relevant to track, e.g., the three concurrent references: optimal pitch angle, optimal rotational speed, and optimal power......Lowering the cost of energy is one of the major focus areas in the wind turbine industry. Recent research has indicated that wind turbine controllers based on model predictive control methods can be useful in obtaining this objective. A number of design considerations have to be made when designing....... The importance if the individual references differ depending in particular on the wind speed. In this paper we investigate the performance of a reference tracking model predictive controller with two different setups of the used optimal reference signals. The controllers are evaluated using an industrial high...

Tuberculosis control: decentralization, local planning and management specificities.

Science.gov (United States)

Trigueiro, Janaína Von Söhsten; Nogueira, Jordana de Almeida; de Sá, Lenilde Duarte; Palha, Pedro Fredemir; Villa, Tereza Cristina Scatena; Trigueiro, Débora Raquel Soares Guedes

2011-01-01

The goal was to analyze, according to the perception of health managers, the practices that guide tuberculosis control actions in cities in the metropolitan region of João Pessoa - PB, Brazil. This qualitative study involved eight professionals in management functions. Testimonies were collected through semi-structured interviews between May and June 2009 and organized through content analysis. Despite the acknowledged benefits of tuberculosis control action decentralization, local planning indicates the predominance of a bureaucratic model that is restricted to negotiation and supplies. Local programming is centered on the coordinator, which shows a command line and vertical management that lead to the fragmentation of the work process. Management action should follow an innovative and transformative route that surpasses bureaucratic barriers and faces the biggest challenge it is proposed: to balance professional interrelations with a view to improving health work performance.

Neural Network Predictive Control for Vanadium Redox Flow Battery

Directory of Open Access Journals (Sweden)

Hai-Feng Shen

2013-01-01

Full Text Available The vanadium redox flow battery (VRB is a nonlinear system with unknown dynamics and disturbances. The flowrate of the electrolyte is an important control mechanism in the operation of a VRB system. Too low or too high flowrate is unfavorable for the safety and performance of VRB. This paper presents a neural network predictive control scheme to enhance the overall performance of the battery. A radial basis function (RBF network is employed to approximate the dynamics of the VRB system. The genetic algorithm (GA is used to obtain the optimum initial values of the RBF network parameters. The gradient descent algorithm is used to optimize the objective function of the predictive controller. Compared with the constant flowrate, the simulation results show that the flowrate optimized by neural network predictive controller can increase the power delivered by the battery during the discharge and decrease the power consumed during the charge.

Simulation research on multivariable fuzzy model predictive control of nuclear power plant

International Nuclear Information System (INIS)

Su Jie

2012-01-01

To improve the dynamic control capabilities of the nuclear power plant, the algorithm of the multivariable nonlinear predictive control based on the fuzzy model was applied in the main parameters control of the nuclear power plant, including control structure and the design of controller in the base of expounding the math model of the turbine and the once-through steam generator. The simulation results show that the respond of the change of the gas turbine speed and the steam pressure under the algorithm of multivariable fuzzy model predictive control is faster than that under the PID control algorithm, and the output value of the gas turbine speed and the steam pressure under the PID control algorithm is 3%-5% more than that under the algorithm of multi-variable fuzzy model predictive control. So it shows that the algorithm of multi-variable fuzzy model predictive control can control the output of the main parameters of the nuclear power plant well and get better control effect. (author)

Model Predictive Control of Mineral Column Flotation Process

Directory of Open Access Journals (Sweden)

Yahui Tian

2018-06-01

Full Text Available Column flotation is an efficient method commonly used in the mineral industry to separate useful minerals from ores of low grade and complex mineral composition. Its main purpose is to achieve maximum recovery while ensuring desired product grade. This work addresses a model predictive control design for a mineral column flotation process modeled by a set of nonlinear coupled heterodirectional hyperbolic partial differential equations (PDEs and ordinary differential equations (ODEs, which accounts for the interconnection of well-stirred regions represented by continuous stirred tank reactors (CSTRs and transport systems given by heterodirectional hyperbolic PDEs, with these two regions combined through the PDEs’ boundaries. The model predictive control considers both optimality of the process operations and naturally present input and state/output constraints. For the discrete controller design, spatially varying steady-state profiles are obtained by linearizing the coupled ODE–PDE model, and then the discrete system is obtained by using the Cayley–Tustin time discretization transformation without any spatial discretization and/or without model reduction. The model predictive controller is designed by solving an optimization problem with input and state/output constraints as well as input disturbance to minimize the objective function, which leads to an online-solvable finite constrained quadratic regulator problem. Finally, the controller performance to keep the output at the steady state within the constraint range is demonstrated by simulation studies, and it is concluded that the optimal control scheme presented in this work makes this flotation process more efficient.

Model Predictive Control Algorithms for Pen and Pump Insulin Administration

DEFF Research Database (Denmark)

Boiroux, Dimitri

at mealtime, and the case where the insulin sensitivity increases during the night. This thesis consists of a summary report, glucose and insulin proles of the clinical studies and research papers submitted, peer-reviewed and/or published in the period September 2009 - September 2012....... of current closed-loop controllers. In this thesis, we present different control strategies based on Model Predictive Control (MPC) for an artificial pancreas. We use Nonlinear Model Predictive Control (NMPC) in order to determine the optimal insulin and blood glucose profiles. The optimal control problem...

Local system for control by console-mobile crane for russian depository of fissionable materials

International Nuclear Information System (INIS)

Troshchenko, V.G.; Kapustin, V.N.; Zinina, N.V.; Derbyshev, S.A.

2005-01-01

Description of crane of console-mobile type used for transportation of fissionable materials in depository with local control system is represented. Local control system realizes program control in real time [ru

Efficient predictive model-based and fuzzy control for green urban mobility

NARCIS (Netherlands)

Jamshidnejad, A.

2017-01-01

In this thesis, we develop efficient predictive model-based control approaches, including model-predictive control (MPC) andmodel-based fuzzy control, for application in urban traffic networks with the aim of reducing a combination of the total time spent by the vehicles within the network and the

Local control of striatal dopamine release

Directory of Open Access Journals (Sweden)

Roger eCachope

2014-05-01

Full Text Available The mesolimbic and nigrostriatal dopamine (DA systems play a key role in the physiology of reward seeking, motivation and motor control. Importantly, they are also involved in the pathophysiology of Parkinson’s and Huntington’s disease, schizophrenia and addiction. Control of DA release in the striatum is tightly linked to firing of DA neurons in the ventral tegmental area (VTA and the substantia nigra (SN. However, local influences in the striatum affect release by exerting their action directly on axon terminals. For example, endogenous glutamatergic and cholinergic activity is sufficient to trigger striatal DA release independently of cell body firing. Recent developments involving genetic manipulation, pharmacological selectivity or selective stimulation have allowed for better characterization of these phenomena. Such termino-terminal forms of control of DA release transform considerably our understanding of the mesolimbic and nigrostriatal systems, and have strong implications as potential mechanisms to modify impaired control of DA release in the diseased brain. Here, we review these and related mechanisms and their implications in the physiology of ascending DA systems.

Participatory health impact assessment for the development of local government regulation on hazard control

International Nuclear Information System (INIS)

Inmuong, Uraiwan; Rithmak, Panee; Srisookwatana, Soomol; Traithin, Nathathai; Maisuporn, Pornpun

2011-01-01

The Thai Public Health Act 1992 required the Thai local governments to issue respective regulations to take control of any possible health-hazard related activities, both from commercial and noncommercial sources. Since 1999, there has been centrally decentralized of power to a new form of local government establishment, namely Sub-district Administrative Organization (SAO). The SAO is asmall-scale local governing structure while its legitimate function is for community services, including control of health impact related activities. Most elected SAO administrators and officers are new and less experience with any of public health code of practice, particularly on health-hazard control. This action research attempted to introduce and apply a participatory health impact assessment (HIA) tool for the development of SAO health-hazard control regulation. The study sites were at Ban Meang and Kok See SAOs, Khon Kaen Province, Thailand, while all intervention activities conducted during May 2005-April 2006. A set of cooperative activities between researchers and community representatives were planned and organized by; surveying and identifying place and service base locally causing local environmental health problems, organizing community participatory workshops for drafting and proposing the health-hazard control regulation, and appropriate practices for health-hazard controlling measures. This action research eventually could successfully enable the SAO administrators and officers understanding of local environmental-related health problem, as well as development of imposed health-hazard control regulation for local community.

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....

Role of blood tumor markers in predicting metastasis and local recurrence after curative resection of colon cancer

Science.gov (United States)

Peng, Yifan; Zhai, Zhiwei; Li, Zhongmin; Wang, Lin; Gu, Jin

2015-01-01

Aim: To investigate the prognostic value of carcinoembryonic antigen (CEA), CA199, CA724 and CA242 in peripheral blood and local draining venous blood in colon cancer patients after curative resection. Methods: 92 colon cancer patients who received curative resection were retrospectively analyzed. The CEA, CA199, CA724 and CA242 were detected in peripheral blood and local draining venous blood. Results: Metastasis or local recurrence was found in 29 (29/92, 31.5%) patients during follow-up period. 92 patients were divided into two groups: metastasis/local recurrence group (n = 29) and non-metastasis/local recurrence group (n = 63). Peripheral venous CEA, CA199, CA724 and CA242 (p-CEA, p-CA199, p-CA724 and p-CA242) were comparable between two groups (P > 0.05). The median draining venous CEA (d-CEA) in metastases/local recurrence group (23.7 ± 6.9 ng/ml) was significantly higher than that in non-metastases/local recurrence group (18.1 ± 6.3 ng/ml; P 0.05). The optimal cut-off value of d-CEA was 2.76 ng/ml, with the sensitivity and specificity of 90% and 40% in the prediction of metastasis or local recurrence, respectively. d-CEA correlated with tumor differentiation, T stage, TNM stage, metastasis and local recurrence. Subgroup analysis showed that, of 41 patients with stage II colon cancer, the optimal cut-off value of d-CEA was 8.78 ng/mL, and the sensitivity and specificity were 87.5% and 69.7% in the prediction of metastasis or local recurrence, respectively. Conclusion: d-CEA may be a prognostic factor for stage II colon cancer patients. PMID:25785084

Evaluating local and overall thermal comfort in buildings using thermal manikins

Energy Technology Data Exchange (ETDEWEB)

Foda, E.

2012-07-01

Evaluation methods of human thermal comfort that are based on whole-body heat balance with its surroundings may not be adequate for evaluations in non-uniform thermal conditions. Under these conditions, the human body's segments may experience a wide range of room physical parameters and the evaluation of the local (segmental) thermal comfort becomes necessary. In this work, subjective measurements of skin temperature were carried out to investigate the human body's local responses due to a step change in the room temperature; and the variability in the body's local temperatures under different indoor conditions and exposures as well as the physiological steady state local temperatures. Then, a multi-segmental model of human thermoregulation was developed based on these findings to predict the local skin temperatures of individuals' body segments with a good accuracy. The model predictability of skin temperature was verified for steady state and dynamic conditions using measured data at uniform neutral, cold and warm as well as different asymmetric thermal conditions. The model showed very good predictability with average absolute deviation ranged from 0.3-0.8 K. The model was then implemented onto the control system of the thermal manikin 'THERMINATOR' to adjust the segmental skin temperature set-points based on the indoor conditions. This new control for the manikin was experimentally validated for the prediction of local and overall thermal comfort using the equivalent temperature measure. THERMINATOR with the new control mode was then employed in the evaluation of localized floor-heating system variants towards maximum energy efficiency. This aimed at illustrating a design strategy using the thermal manikin to find the optimum geometry and surface area of a floor-heater for a single seated person. Furthermore, a psychological comfort model that is based on local skin temperature was adapted for the use with the model of human

Wind farms production: Control and prediction

Science.gov (United States)

El-Fouly, Tarek Hussein Mostafa

Wind energy resources, unlike dispatchable central station generation, produce power dependable on external irregular source and that is the incident wind speed which does not always blow when electricity is needed. This results in the variability, unpredictability, and uncertainty of wind resources. Therefore, the integration of wind facilities to utility electrical grid presents a major challenge to power system operator. Such integration has significant impact on the optimum power flow, transmission congestion, power quality issues, system stability, load dispatch, and economic analysis. Due to the irregular nature of wind power production, accurate prediction represents the major challenge to power system operators. Therefore, in this thesis two novel models are proposed for wind speed and wind power prediction. One proposed model is dedicated to short-term prediction (one-hour ahead) and the other involves medium term prediction (one-day ahead). The accuracy of the proposed models is revealed by comparing their results with the corresponding values of a reference prediction model referred to as the persistent model. Utility grid operation is not only impacted by the uncertainty of the future production of wind farms, but also by the variability of their current production and how the active and reactive power exchange with the grid is controlled. To address this particular task, a control technique for wind turbines, driven by doubly-fed induction generators (DFIGs), is developed to regulate the terminal voltage by equally sharing the generated/absorbed reactive power between the rotor-side and the gridside converters. To highlight the impact of the new developed technique in reducing the power loss in the generator set, an economic analysis is carried out. Moreover, a new aggregated model for wind farms is proposed that accounts for the irregularity of the incident wind distribution throughout the farm layout. Specifically, this model includes the wake effect

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

Science.gov (United States)

Shadmand, Mohammad Bagher

transmission loss if not controlled appropriately. Inductive loads which operate with lagging power factor consume VARs, thus load compensation techniques by capacitor bank employment locally supply VARs needed by the load. Capacitors are highly unreliable components due to their failure modes and aging inherent. Approximately 60% of power electronic devices failure such as voltage-source inverter based static synchronous compensator (STATCOM) is due to the use of aluminum electrolytic DC capacitors. Therefore, a capacitor-less VAR compensation is desired. This dissertation also investigates a STATCOM capacitor-less reactive power compensation that uses only inductors combined with predictive controlled matrix converter.

Prediction of active control of subsonic centrifugal compressor rotating stall

Science.gov (United States)

Lawless, Patrick B.; Fleeter, Sanford

1993-01-01

A mathematical model is developed to predict the suppression of rotating stall in a centrifugal compressor with a vaned diffuser. This model is based on the employment of a control vortical waveform generated upstream of the impeller inlet to damp weak potential disturbances that are the early stages of rotating stall. The control system is analyzed by matching the perturbation pressure in the compressor inlet and exit flow fields with a model for the unsteady behavior of the compressor. The model was effective at predicting the stalling behavior of the Purdue Low Speed Centrifugal Compressor for two distinctly different stall patterns. Predictions made for the effect of a controlled inlet vorticity wave on the stability of the compressor show that for minimum control wave magnitudes, on the order of the total inlet disturbance magnitude, significant damping of the instability can be achieved. For control waves of sufficient amplitude, the control phase angle appears to be the most important factor in maintaining a stable condition in the compressor.

Stability of the spreading in small-world network with predictive controller

International Nuclear Information System (INIS)

Bao, Z.J.; Jiang, Q.Y.; Yan, W.J.; Cao, Y.J.

2010-01-01

In this Letter, we apply the predictive control strategy to suppress the propagation of diseases or viruses in small-world network. The stability of small-world spreading model with predictive controller is investigated. The sufficient and necessary stability condition is given, which is closely related to the controller parameters and small-world rewiring probability p. Our simulations discover a phenomenon that, with the fixed predictive controller parameters, the spreading dynamics become more and more stable when p decreases from a larger value to a smaller one, and the suitable controller parameters can effectively suppress the spreading behaviors even when p varies within the whole spectrum, and the unsuitable controller parameters can lead to oscillation when p lies within a certain range.

Local topographic wetness indices predict household malaria risk better than land-use and land-cover in the western Kenya highlands.

Science.gov (United States)

Cohen, Justin M; Ernst, Kacey C; Lindblade, Kim A; Vulule, John M; John, Chandy C; Wilson, Mark L

2010-11-16

household malaria. However, these land-cover/land-use variables failed to produce unambiguous improvements in statistical predictive models controlling for important topographic factors, with none improving prediction of household-level malaria more than 75% of the time. Topographic wetness values in this region of highly varied terrain more accurately predicted houses at greater risk of malaria than did consideration of land-cover/land-use characteristics. As such, those planning control or local elimination strategies in similar highland regions may use topographic and geographic characteristics to effectively identify high-receptivity regions that may require enhanced vigilance.

Local topographic wetness indices predict household malaria risk better than land-use and land-cover in the western Kenya highlands

Directory of Open Access Journals (Sweden)

Vulule John M

2010-11-01

environment also demonstrated clear associations with household malaria. However, these land-cover/land-use variables failed to produce unambiguous improvements in statistical predictive models controlling for important topographic factors, with none improving prediction of household-level malaria more than 75% of the time. Conclusions Topographic wetness values in this region of highly varied terrain more accurately predicted houses at greater risk of malaria than did consideration of land-cover/land-use characteristics. As such, those planning control or local elimination strategies in similar highland regions may use topographic and geographic characteristics to effectively identify high-receptivity regions that may require enhanced vigilance.

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

Science.gov (United States)

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

2017-07-01

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

A LIDAR-assisted model predictive controller added on a traditional wind turbine controller

DEFF Research Database (Denmark)

Mirzaei, Mahmood; Hansen, Morten Hartvig

2016-01-01

control and opens the market of retrofitting existing wind turbines with the new technology. In this paper, we suggest a model predictive controller (MPC) that is added to the basic gain scheduled PI controller of a WT to enhance the performance of the closed loop system using LIDAR measurements...

Predicting local dengue transmission in Guangzhou, China, through the influence of imported cases, mosquito density and climate variability.

Directory of Open Access Journals (Sweden)

Shaowei Sang

Full Text Available Each year there are approximately 390 million dengue infections worldwide. Weather variables have a significant impact on the transmission of Dengue Fever (DF, a mosquito borne viral disease. DF in mainland China is characterized as an imported disease. Hence it is necessary to explore the roles of imported cases, mosquito density and climate variability in dengue transmission in China. The study was to identify the relationship between dengue occurrence and possible risk factors and to develop a predicting model for dengue's control and prevention purpose.Three traditional suburbs and one district with an international airport in Guangzhou city were selected as the study areas. Autocorrelation and cross-correlation analysis were used to perform univariate analysis to identify possible risk factors, with relevant lagged effects, associated with local dengue cases. Principal component analysis (PCA was applied to extract principal components and PCA score was used to represent the original variables to reduce multi-collinearity. Combining the univariate analysis and prior knowledge, time-series Poisson regression analysis was conducted to quantify the relationship between weather variables, Breteau Index, imported DF cases and the local dengue transmission in Guangzhou, China. The goodness-of-fit of the constructed model was determined by pseudo-R2, Akaike information criterion (AIC and residual test. There were a total of 707 notified local DF cases from March 2006 to December 2012, with a seasonal distribution from August to November. There were a total of 65 notified imported DF cases from 20 countries, with forty-six cases (70.8% imported from Southeast Asia. The model showed that local DF cases were positively associated with mosquito density, imported cases, temperature, precipitation, vapour pressure and minimum relative humidity, whilst being negatively associated with air pressure, with different time lags.Imported DF cases and mosquito

Predictive Function Control for Communication-Based Train Control (CBTC Systems

Directory of Open Access Journals (Sweden)

Bing Bu

2013-01-01

Full Text Available In Communication-Based Train Control (CBTC systems, random transmission delays and packet drops are inevitable in the wireless networks, which could result in unnecessary traction, brakes or even emergency brakes of trains, losses of line capacity and passenger dissatisfaction. This paper applies predictive function control technology with a mixed H2/∞ control approach to improve the control performances. The controller is in the state feedback form and satisfies the requirement of quadratic input and state constraints. A linear matrix inequality (LMI approach is developed to solve the control problem. The proposed method attenuates disturbances by incorporating H2/∞ into the control scheme. The control command from the automatic train operation (ATO is included in the reward function to optimize the train's running profile. The influence of transmission delays and packet drops is alleviated through improving the performances of the controller. Simulation results show that the method is effective to improve the performances and robustness of CBTC systems.

Driving-behavior-aware stochastic model predictive control for plug-in hybrid electric buses

International Nuclear Information System (INIS)

Li, Liang; You, Sixiong; Yang, Chao; Yan, Bingjie; Song, Jian; Chen, Zheng

2016-01-01

Highlights: • The novel approximated global optimal energy management strategy has been proposed for hybrid powertrains. • Eight typical driving behaviors have been classified with K-means to deal with the multiplicative traffic conditions. • The stochastic driver models of different driving behaviors were established based on the Markov chains. • ECMS was used to modify the SMPC-based energy management strategy to improve its fuel economy. • The approximated global optimal energy management strategy for plug-in hybrid electric buses has been verified and analyzed. - Abstract: Driving cycles of a city bus is statistically characterized by some repetitive features, which makes the predictive energy management strategy very desirable to obtain approximate optimal fuel economy of a plug-in hybrid electric bus. But dealing with the complicated traffic conditions and finding an approximated global optimal strategy which is applicable to the plug-in hybrid electric bus still remains a challenging technique. To solve this problem, a novel driving-behavior-aware modified stochastic model predictive control method is proposed for the plug-in hybrid electric bus. Firstly, the K-means is employed to classify driving behaviors, and the driver models based on Markov chains is obtained under different kinds of driving behaviors. While the obtained driver behaviors are regarded as stochastic disturbance inputs, the local minimum fuel consumption might be obtained with a traditional stochastic model predictive control at each step, taking tracking the reference battery state of charge trajectory into consideration in the finite predictive horizons. However, this technique is still accompanied by some working points with reduced/worsened fuel economy. Thus, the stochastic model predictive control is modified with the equivalent consumption minimization strategy to eliminate these undesirable working points. The results in real-world city bus routines show that the

Stability of a neural predictive controller scheme on a neural model

DEFF Research Database (Denmark)

Luther, Jim Benjamin; Sørensen, Paul Haase

2009-01-01

In previous works presenting various forms of neural-network-based predictive controllers, the main emphasis has been on the implementation aspects, i.e. the development of a robust optimization algorithm for the controller, which will be able to perform in real time. However, the stability issue....... The resulting controller is tested on a nonlinear pneumatic servo system.......In previous works presenting various forms of neural-network-based predictive controllers, the main emphasis has been on the implementation aspects, i.e. the development of a robust optimization algorithm for the controller, which will be able to perform in real time. However, the stability issue...... has not been addressed specifically for these controllers. On the other hand a number of results concerning the stability of receding horizon controllers on a nonlinear system exist. In this paper we present a proof of stability for a predictive controller controlling a neural network model...

Modeling, Prediction, and Control of Heating Temperature for Tube Billet

Directory of Open Access Journals (Sweden)

Yachun Mao

2015-01-01

Full Text Available Annular furnaces have multivariate, nonlinear, large time lag, and cross coupling characteristics. The prediction and control of the exit temperature of a tube billet are important but difficult. We establish a prediction model for the final temperature of a tube billet through OS-ELM-DRPLS method. We address the complex production characteristics, integrate the advantages of PLS and ELM algorithms in establishing linear and nonlinear models, and consider model update and data lag. Based on the proposed model, we design a prediction control algorithm for tube billet temperature. The algorithm is validated using the practical production data of Baosteel Co., Ltd. Results show that the model achieves the precision required in industrial applications. The temperature of the tube billet can be controlled within the required temperature range through compensation control method.

Two stage neural network modelling for robust model predictive control.

Science.gov (United States)

Patan, Krzysztof

2018-01-01

The paper proposes a novel robust model predictive control scheme realized by means of artificial neural networks. The neural networks are used twofold: to design the so-called fundamental model of a plant and to catch uncertainty associated with the plant model. In order to simplify the optimization process carried out within the framework of predictive control an instantaneous linearization is applied which renders it possible to define the optimization problem in the form of constrained quadratic programming. Stability of the proposed control system is also investigated by showing that a cost function is monotonically decreasing with respect to time. Derived robust model predictive control is tested and validated on the example of a pneumatic servomechanism working at different operating regimes. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.

Hybrid model predictive control applied to switching control of burner load for a compact marine boiler design

DEFF Research Database (Denmark)

Solberg, Brian; Andersen, Palle; Maciejowski, Jan

2008-01-01

This paper discusses the application of hybrid model predictive control to control switching between different burner modes in a novel compact marine boiler design. A further purpose of the present work is to point out problems with finite horizon model predictive control applied to systems for w...

Transforming local government by project portfolio management: Identifying and overcoming control problems

DEFF Research Database (Denmark)

Hansen, Lars Kristian

2013-01-01

Purpose – As public organizations strive for higher e-government maturity, information technology (IT) Project Portfolio Management (IT PPM) has become a high priority issue. Assuming control is central in IT PPM, the purpose of this paper is to investigate how a Danish local government conducts...... workshop, and analyses of documents. Findings – It is found that the local government relies vastly on informal control mechanisms and five control problems are identified: weak accountability processes between the political and administrative level; weak accountability between the director level...... the identified control problems. Research limitations/implications – As a single qualitative case study, the results are limited to one organization and subject. Practical implications – The paper has implications for IT PPM in Danish local governments and similar organizations in other countries. The paper...

Range-Space Predictive Control for Optimal Robot Motion

Czech Academy of Sciences Publication Activity Database

Belda, Květoslav; Böhm, Josef

2008-01-01

Roč. 1, č. 1 (2008), s. 1-7 ISSN 1998-0140 R&D Projects: GA ČR GP102/06/P275 Institutional research plan: CEZ:AV0Z10750506 Keywords : Accurate manipulation * Industrial robotics * Predictive control * Range-space control Subject RIV: BC - Control Systems Theory http://library.utia.cas.cz/separaty/historie/belda-0305644.pdf

Predicting worsening asthma control following the common cold

NARCIS (Netherlands)

Walter, M. J.; Castro, M.; Kunselman, S. J.; Chinchilli, V. M.; Reno, M.; Ramkumar, T. P.; Avila, P. C.; Boushey, H. A.; Ameredes, B. T.; Bleecker, E. R.; Calhoun, W. J.; Cherniack, R. M.; Craig, T. J.; Denlinger, L. C.; Israel, E.; Fahy, J. V.; Jarjour, N. N.; Kraft, M.; Lazarus, S. C.; Lemanske, R. F.; Martin, R. J.; Peters, S. P.; Ramsdell, J. W.; Sorkness, C. A.; Sutherland, E. R.; Szefler, S. J.; Wasserman, S. I.; Wechsler, M. E.

2008-01-01

The asthmatic response to the common cold is highly variable, and early characteristics that predict worsening of asthma control following a cold have not been identified. In this prospective multicentric cohort study of 413 adult subjects with asthma, the mini-Asthma Control Questionnaire

ClubSub-P: Cluster-Based Subcellular Localization Prediction for Gram-Negative Bacteria and Archaea

Science.gov (United States)

Paramasivam, Nagarajan; Linke, Dirk

2011-01-01

The subcellular localization (SCL) of proteins provides important clues to their function in a cell. In our efforts to predict useful vaccine targets against Gram-negative bacteria, we noticed that misannotated start codons frequently lead to wrongly assigned SCLs. This and other problems in SCL prediction, such as the relatively high false-positive and false-negative rates of some tools, can be avoided by applying multiple prediction tools to groups of homologous proteins. Here we present ClubSub-P, an online database that combines existing SCL prediction tools into a consensus pipeline from more than 600 proteomes of fully sequenced microorganisms. On top of the consensus prediction at the level of single sequences, the tool uses clusters of homologous proteins from Gram-negative bacteria and from Archaea to eliminate false-positive and false-negative predictions. ClubSub-P can assign the SCL of proteins from Gram-negative bacteria and Archaea with high precision. The database is searchable, and can easily be expanded using either new bacterial genomes or new prediction tools as they become available. This will further improve the performance of the SCL prediction, as well as the detection of misannotated start codons and other annotation errors. ClubSub-P is available online at http://toolkit.tuebingen.mpg.de/clubsubp/ PMID:22073040

Prediction Governors for Input-Affine Nonlinear Systems and Application to Automatic Driving Control

Directory of Open Access Journals (Sweden)

Yuki Minami

2018-04-01

Full Text Available In recent years, automatic driving control has attracted attention. To achieve a satisfactory driving control performance, the prediction accuracy of the traveling route is important. If a highly accurate prediction method can be used, an accurate traveling route can be obtained. Despite the considerable efforts that have been invested in improving prediction methods, prediction errors do occur in general. Thus, a method to minimize the influence of prediction errors on automatic driving control systems is required. This need motivated us to focus on the design of a mechanism for shaping prediction signals, which is called a prediction governor. In this study, we first extended our previous study to the input-affine nonlinear system case. Then, we analytically derived a solution to an optimal design problem of prediction governors. Finally, we applied the solution to an automatic driving control system, and demonstrated its usefulness through a numerical example and an experiment using a radio controlled car.

Modeling Local Control After Hypofractionated Stereotactic Body Radiation Therapy for Stage I Non-Small Cell Lung Cancer: A Report From the Elekta Collaborative Lung Research Group

International Nuclear Information System (INIS)

Ohri, Nitin; Werner-Wasik, Maria; Grills, Inga S.; Belderbos, José; Hope, Andrew; Yan Di; Kestin, Larry L.; Guckenberger, Matthias; Sonke, Jan-Jakob; Bissonnette, Jean-Pierre; Xiao, Ying

2012-01-01

Purpose: Hypofractionated stereotactic body radiation therapy (SBRT) has emerged as an effective treatment option for early-stage non-small cell lung cancer (NSCLC). Using data collected by the Elekta Lung Research Group, we generated a tumor control probability (TCP) model that predicts 2-year local control after SBRT as a function of biologically effective dose (BED) and tumor size. Methods and Materials: We formulated our TCP model as follows: TCP = e [BED10−c∗L−TCD50]/k ÷ (1 + e [BED10−c∗L−TCD50]/k ), where BED10 is the biologically effective SBRT dose, c is a constant, L is the maximal tumor diameter, and TCD50 and k are parameters that define the shape of the TCP curve. Least-squares optimization with a bootstrap resampling approach was used to identify the values of c, TCD50, and k that provided the best fit with observed actuarial 2-year local control rates. Results: Data from 504 NSCLC tumors treated with a variety of SBRT schedules were available. The mean follow-up time was 18.4 months, and 26 local recurrences were observed. The optimal values for c, TCD50, and k were 10 Gy/cm, 0 Gy, and 31 Gy, respectively. Thus, size-adjusted BED (sBED) may be defined as BED minus 10 times the tumor diameter (in centimeters). Our TCP model indicates that sBED values of 44 Gy, 69 Gy, and 93 Gy provide 80%, 90%, and 95% chances of tumor control at 2 years, respectively. When patients were grouped by sBED, the model accurately characterized the relationship between sBED and actuarial 2-year local control (r=0.847, P=.008). Conclusion: We have developed a TCP model that predicts 2-year local control rate after hypofractionated SBRT for early-stage NSCLC as a function of biologically effective dose and tumor diameter. Further testing of this model with additional datasets is warranted.

Modeling Local Control After Hypofractionated Stereotactic Body Radiation Therapy for Stage I Non-Small Cell Lung Cancer: A Report From the Elekta Collaborative Lung Research Group

Energy Technology Data Exchange (ETDEWEB)

Ohri, Nitin, E-mail: ohri.nitin@gmail.com [Department of Radiation Oncology, Jefferson Medical College of Thomas Jefferson University, Philadelphia, Pennsylvania (United States); Werner-Wasik, Maria [Department of Radiation Oncology, Jefferson Medical College of Thomas Jefferson University, Philadelphia, Pennsylvania (United States); Grills, Inga S. [Department of Radiation Oncology, William Beaumont Hospital, Royal Oak, Michigan (United States); Belderbos, Jose [Department of Radiation Oncology, The Netherlands Cancer Institute, Amsterdam (Netherlands); Hope, Andrew [Department of Radiation Oncology, Princess Margaret Hospital and University of Toronto, Toronto, ON (Canada); Yan Di; Kestin, Larry L. [Department of Radiation Oncology, William Beaumont Hospital, Royal Oak, Michigan (United States); Guckenberger, Matthias [Department of Radiation Oncology, University of Wuerzburg, Wuerzburg (Germany); Sonke, Jan-Jakob [Department of Radiation Oncology, The Netherlands Cancer Institute, Amsterdam (Netherlands); Bissonnette, Jean-Pierre [Department of Radiation Oncology, Princess Margaret Hospital and University of Toronto, Toronto, ON (Canada); Xiao, Ying [Department of Radiation Oncology, Jefferson Medical College of Thomas Jefferson University, Philadelphia, Pennsylvania (United States)

2012-11-01

Purpose: Hypofractionated stereotactic body radiation therapy (SBRT) has emerged as an effective treatment option for early-stage non-small cell lung cancer (NSCLC). Using data collected by the Elekta Lung Research Group, we generated a tumor control probability (TCP) model that predicts 2-year local control after SBRT as a function of biologically effective dose (BED) and tumor size. Methods and Materials: We formulated our TCP model as follows: TCP = e{sup [BED10-c Asterisk-Operator L-TCD50]/k} Division-Sign (1 + e{sup [BED10-c Asterisk-Operator L-TCD50]/k}), where BED10 is the biologically effective SBRT dose, c is a constant, L is the maximal tumor diameter, and TCD50 and k are parameters that define the shape of the TCP curve. Least-squares optimization with a bootstrap resampling approach was used to identify the values of c, TCD50, and k that provided the best fit with observed actuarial 2-year local control rates. Results: Data from 504 NSCLC tumors treated with a variety of SBRT schedules were available. The mean follow-up time was 18.4 months, and 26 local recurrences were observed. The optimal values for c, TCD50, and k were 10 Gy/cm, 0 Gy, and 31 Gy, respectively. Thus, size-adjusted BED (sBED) may be defined as BED minus 10 times the tumor diameter (in centimeters). Our TCP model indicates that sBED values of 44 Gy, 69 Gy, and 93 Gy provide 80%, 90%, and 95% chances of tumor control at 2 years, respectively. When patients were grouped by sBED, the model accurately characterized the relationship between sBED and actuarial 2-year local control (r=0.847, P=.008). Conclusion: We have developed a TCP model that predicts 2-year local control rate after hypofractionated SBRT for early-stage NSCLC as a function of biologically effective dose and tumor diameter. Further testing of this model with additional datasets is warranted.

One-Step-Ahead Predictive Control for Hydroturbine Governor

Directory of Open Access Journals (Sweden)

Zhihuai Xiao

2015-01-01

Full Text Available The hydroturbine generator regulating system can be considered as one system synthetically integrating water, machine, and electricity. It is a complex and nonlinear system, and its configuration and parameters are time-dependent. A one-step-ahead predictive control based on on-line trained neural networks (NNs for hydroturbine governor with variation in gate position is described in this paper. The proposed control algorithm consists of a one-step-ahead neuropredictor that tracks the dynamic characteristics of the plant and predicts its output and a neurocontroller to generate the optimal control signal. The weights of two NNs, initially trained off-line, are updated on-line according to the scalar error. The proposed controller can thus track operating conditions in real-time and produce the optimal control signal over the wide operating range. Only the inputs and outputs of the generator are measured and there is no need to determine the other states of the generator. Simulations have been performed with varying operating conditions and different disturbances to compare the performance of the proposed controller with that of a conventional PID controller and validate the feasibility of the proposed approach.

Distributed model predictive control made easy

CERN Document Server

Negenborn, Rudy

2014-01-01

The rapid evolution of computer science, communication, and information technology has enabled the application of control techniques to systems beyond the possibilities of control theory just a decade ago. Critical infrastructures such as electricity, water, traffic and intermodal transport networks are now in the scope of control engineers. The sheer size of such large-scale systems requires the adoption of advanced distributed control approaches. Distributed model predictive control (MPC) is one of the promising control methodologies for control of such systems.   This book provides a state-of-the-art overview of distributed MPC approaches, while at the same time making clear directions of research that deserve more attention. The core and rationale of 35 approaches are carefully explained. Moreover, detailed step-by-step algorithmic descriptions of each approach are provided. These features make the book a comprehensive guide both for those seeking an introduction to distributed MPC as well as for those ...

Distributed Model Predictive Control over Multiple Groups of Vehicles in Highway Intelligent Space for Large Scale System

Directory of Open Access Journals (Sweden)

Tang Xiaofeng

2014-01-01

Full Text Available The paper presents the three time warning distances for solving the large scale system of multiple groups of vehicles safety driving characteristics towards highway tunnel environment based on distributed model prediction control approach. Generally speaking, the system includes two parts. First, multiple vehicles are divided into multiple groups. Meanwhile, the distributed model predictive control approach is proposed to calculate the information framework of each group. Each group of optimization performance considers the local optimization and the neighboring subgroup of optimization characteristics, which could ensure the global optimization performance. Second, the three time warning distances are studied based on the basic principles used for highway intelligent space (HIS and the information framework concept is proposed according to the multiple groups of vehicles. The math model is built to avoid the chain avoidance of vehicles. The results demonstrate that the proposed highway intelligent space method could effectively ensure driving safety of multiple groups of vehicles under the environment of fog, rain, or snow.

Robust Output Model Predictive Control of an Unstable Rijke Tube

Directory of Open Access Journals (Sweden)

Fabian Jarmolowitz

2012-01-01

Full Text Available This work investigates the active control of an unstable Rijke tube using robust output model predictive control (RMPC. As internal model a polytopic linear system with constraints is assumed to account for uncertainties. For guaranteed stability, a linear state feedback controller is designed using linear matrix inequalities and used within a feedback formulation of the model predictive controller. For state estimation a robust gain-scheduled observer is developed. It is shown that the proposed RMPC ensures robust stability under constraints over the considered operating range.

Sparsely-Packetized Predictive Control by Orthogonal Matching Pursuit

DEFF Research Database (Denmark)

Nagahara, Masaaki; Quevedo, Daniel; Østergaard, Jan

2012-01-01

We study packetized predictive control, known to be robust against packet dropouts in networked systems. To obtain sparse packets for rate-limited networks, we design control packets via an ℓ0 optimization, which can be eectively solved by orthogonal matching pursuit. Our formulation ensures...

Fatigue life prediction method for contact wire using maximum local stress

Energy Technology Data Exchange (ETDEWEB)

Kim, Yong Seok; Haochuang, Li; Seok, Chang Sung; Koo, Jae Mean [Sungkyunkwan University, Suwon (Korea, Republic of); Lee, Ki Won; Kwon, Sam Young; Cho, Yong Hyeon [Korea Railroad Research Institute, Uiwang (Korea, Republic of)

2015-01-15

Railway contact wires supplying electricity to trains are exposed to repeated mechanical strain and stress caused by their own weight and discontinuous contact with a pantograph during train operation. Since the speed of railway transportation has increased continuously, railway industries have recently reported a number of contact wire failures caused by mechanical fatigue fractures instead of normal wear, which has been a more common failure mechanism. To secure the safety and durability of contact wires in environments with increased train speeds, a bending fatigue test on contact wire has been performed. The test equipment is too complicated to evaluate the fatigue characteristics of contact wire. Thus, the axial tension fatigue test was performed for a standard specimen, and the bending fatigue life for the contact wire structure was then predicted using the maximum local stress occurring at the top of the contact wire. Lastly, the tested bending fatigue life of the structure was compared with the fatigue life predicted by the axial tension fatigue test for verification.

Fatigue life prediction method for contact wire using maximum local stress

International Nuclear Information System (INIS)

Kim, Yong Seok; Haochuang, Li; Seok, Chang Sung; Koo, Jae Mean; Lee, Ki Won; Kwon, Sam Young; Cho, Yong Hyeon

2015-01-01

Railway contact wires supplying electricity to trains are exposed to repeated mechanical strain and stress caused by their own weight and discontinuous contact with a pantograph during train operation. Since the speed of railway transportation has increased continuously, railway industries have recently reported a number of contact wire failures caused by mechanical fatigue fractures instead of normal wear, which has been a more common failure mechanism. To secure the safety and durability of contact wires in environments with increased train speeds, a bending fatigue test on contact wire has been performed. The test equipment is too complicated to evaluate the fatigue characteristics of contact wire. Thus, the axial tension fatigue test was performed for a standard specimen, and the bending fatigue life for the contact wire structure was then predicted using the maximum local stress occurring at the top of the contact wire. Lastly, the tested bending fatigue life of the structure was compared with the fatigue life predicted by the axial tension fatigue test for verification.

Repetitive model predictive approach to individual pitch control of wind turbines

DEFF Research Database (Denmark)

Adegas, Fabiano Daher; Stoustrup, Jakob; Odgaard, Peter Fogh

2011-01-01

prediction. As a consequence, individual pitch feed-forward control action is generated by the controller, taking ”future” wind disturbance into account. Information about the estimated wind spatial distribution one blade experience can be used in the prediction model to better control the next passing blade......Wind turbines are inherently exposed to nonuniform wind fields with of wind shear, tower shadow, and possible wake contributions. Asymmetrical aerodynamic rotor loads are a consequence of such periodic, repetitive wind disturbances experienced by the blades. A controller may estimate and use...... this peculiar disturbance pattern to better attenuate loads and regulate power by controlling the blade pitch angles individually. A novel model predictive (MPC) approach for individual pitch control of wind turbines is proposed in this paper. A repetitive wind disturbance model is incorporated into the MPC...

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

Science.gov (United States)

Mcvey, Eugene S.; Taylor, Lynore Denise

1992-01-01

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

Differing Air Traffic Controller Responses to Similar Trajectory Prediction Errors

Science.gov (United States)

Mercer, Joey; Hunt-Espinosa, Sarah; Bienert, Nancy; Laraway, Sean

2016-01-01

A Human-In-The-Loop simulation was conducted in January of 2013 in the Airspace Operations Laboratory at NASA's Ames Research Center. The simulation airspace included two en route sectors feeding the northwest corner of Atlanta's Terminal Radar Approach Control. The focus of this paper is on how uncertainties in the study's trajectory predictions impacted the controllers ability to perform their duties. Of particular interest is how the controllers interacted with the delay information displayed in the meter list and data block while managing the arrival flows. Due to wind forecasts with 30-knot over-predictions and 30-knot under-predictions, delay value computations included errors of similar magnitude, albeit in opposite directions. However, when performing their duties in the presence of these errors, did the controllers issue clearances of similar magnitude, albeit in opposite directions?

Local control after brachytherapy for localized prostatic carcinomas

International Nuclear Information System (INIS)

Wachter, T.; Peneau, M.; Sabattier, R.; Breteau, N.

1996-01-01

From 1991 to 1995; 31 patients (mid-age: 70 years) underwent prostatic brachytherapy for localized prostate cancers using Iridium 192 transperineal percutaneous interstitial implantation guided by transrectal ultrasonography. Initial staging included among other evaluations a bilateral staging, iliac and obturator lymph nodes dissection. Classification according to stage was : T1b=16%, T1c=36%, T2a=19%, T2b=13%, T2c=13%, T3a=3%. All patients were N (-). Gleason score was 5 for 55%. 77% of the initial PSA was < 25μg/l. Follow-up included one clinical control and psa determination at 1-3-6-12 and 18 months, bone scanning at 12 months and prostate biopsy guided by transrectal ultrasonography at 18, 24, 30 months. Up to now, mean follow-up is 32 months. At one month, psa was normal (< 2,5μg/l) in 21% of the patients, at 12 months 60% and 67% two years after brachytherapy. Biopsies at 18 months were negative for 60% of the patients and 63% at 24 months. 3 patients were metastased after 3 years. 4 patients had severe complications with colostomy and/or urinary derivation. This technic seems to be interesting for localized prostate cancers T1 and T2 with initial psa < 25μg/l. Two third of the patients had normal psa and negative biopsies after 2 years. The rate of ano-rectal and urinary morbidity is high but is explained by the technic used at the beginning of this study

Improving local clustering based top-L link prediction methods via asymmetric link clustering information

Science.gov (United States)

Wu, Zhihao; Lin, Youfang; Zhao, Yiji; Yan, Hongyan

2018-02-01

Networks can represent a wide range of complex systems, such as social, biological and technological systems. Link prediction is one of the most important problems in network analysis, and has attracted much research interest recently. Many link prediction methods have been proposed to solve this problem with various techniques. We can note that clustering information plays an important role in solving the link prediction problem. In previous literatures, we find node clustering coefficient appears frequently in many link prediction methods. However, node clustering coefficient is limited to describe the role of a common-neighbor in different local networks, because it cannot distinguish different clustering abilities of a node to different node pairs. In this paper, we shift our focus from nodes to links, and propose the concept of asymmetric link clustering (ALC) coefficient. Further, we improve three node clustering based link prediction methods via the concept of ALC. The experimental results demonstrate that ALC-based methods outperform node clustering based methods, especially achieving remarkable improvements on food web, hamster friendship and Internet networks. Besides, comparing with other methods, the performance of ALC-based methods are very stable in both globalized and personalized top-L link prediction tasks.

Model Predictive Control for Connected Hybrid Electric Vehicles

Directory of Open Access Journals (Sweden)

Kaijiang Yu

2015-01-01

Full Text Available This paper presents a new model predictive control system for connected hybrid electric vehicles to improve fuel economy. The new features of this study are as follows. First, the battery charge and discharge profile and the driving velocity profile are simultaneously optimized. One is energy management for HEV for Pbatt; the other is for the energy consumption minimizing problem of acc control of two vehicles. Second, a system for connected hybrid electric vehicles has been developed considering varying drag coefficients and the road gradients. Third, the fuel model of a typical hybrid electric vehicle is developed using the maps of the engine efficiency characteristics. Fourth, simulations and analysis (under different parameters, i.e., road conditions, vehicle state of charge, etc. are conducted to verify the effectiveness of the method to achieve higher fuel efficiency. The model predictive control problem is solved using numerical computation method: continuation and generalized minimum residual method. Computer simulation results reveal improvements in fuel economy using the proposed control method.

Ensemble Linear Neighborhood Propagation for Predicting Subchloroplast Localization of Multi-Location Proteins.

Science.gov (United States)

Wan, Shibiao; Mak, Man-Wai; Kung, Sun-Yuan

2016-12-02

In the postgenomic era, the number of unreviewed protein sequences is remarkably larger and grows tremendously faster than that of reviewed ones. However, existing methods for protein subchloroplast localization often ignore the information from these unlabeled proteins. This paper proposes a multi-label predictor based on ensemble linear neighborhood propagation (LNP), namely, LNP-Chlo, which leverages hybrid sequence-based feature information from both labeled and unlabeled proteins for predicting localization of both single- and multi-label chloroplast proteins. Experimental results on a stringent benchmark dataset and a novel independent dataset suggest that LNP-Chlo performs at least 6% (absolute) better than state-of-the-art predictors. This paper also demonstrates that ensemble LNP significantly outperforms LNP based on individual features. For readers' convenience, the online Web server LNP-Chlo is freely available at http://bioinfo.eie.polyu.edu.hk/LNPChloServer/ .

NLStradamus: a simple Hidden Markov Model for nuclear localization signal prediction

Directory of Open Access Journals (Sweden)

Provart Nicholas

2009-06-01

Full Text Available Abstract Background Nuclear localization signals (NLSs are stretches of residues within a protein that are important for the regulated nuclear import of the protein. Of the many import pathways that exist in yeast, the best characterized is termed the 'classical' NLS pathway. The classical NLS contains specific patterns of basic residues and computational methods have been designed to predict the location of these motifs on proteins. The consensus sequences, or patterns, for the other import pathways are less well-understood. Results In this paper, we present an analysis of characterized NLSs in yeast, and find, despite the large number of nuclear import pathways, that NLSs seem to show similar patterns of amino acid residues. We test current prediction methods and observe a low true positive rate. We therefore suggest an approach using hidden Markov models (HMMs to predict novel NLSs in proteins. We show that our method is able to consistently find 37% of the NLSs with a low false positive rate and that our method retains its true positive rate outside of the yeast data set used for the training parameters. Conclusion Our implementation of this model, NLStradamus, is made available at: http://www.moseslab.csb.utoronto.ca/NLStradamus/

Combining local and global optimisation for virtual camera control

OpenAIRE

Burelli, Paolo; Yannakakis, Georgios N.; 2010 IEEE Symposium on Computational Intelligence and Games

2010-01-01

Controlling a virtual camera in 3D computer games is a complex task. The camera is required to react to dynamically changing environments and produce high quality visual results and smooth animations. This paper proposes an approach that combines local and global search to solve the virtual camera control problem. The automatic camera control problem is described and it is decomposed into sub-problems; then a hierarchical architecture that solves each sub-problem using the most appropriate op...

Model Predictive Control based on Finite Impulse Response Models

DEFF Research Database (Denmark)

Prasath, Guru; Jørgensen, John Bagterp

2008-01-01

We develop a regularized l2 finite impulse response (FIR) predictive controller with input and input-rate constraints. Feedback is based on a simple constant output disturbance filter. The performance of the predictive controller in the face of plant-model mismatch is investigated by simulations...... and related to the uncertainty of the impulse response coefficients. The simulations can be used to benchmark l2 MPC against FIR based robust MPC as well as to estimate the maximum performance improvements by robust MPC....

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

Science.gov (United States)

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

2016-07-01

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

Traditional methods of social control in Afikpo north local ...

African Journals Online (AJOL)

Traditional methods of social control in Afikpo north local government area, Ebonyi state south eastern Nigeria. ... Journal of Religion and Human Relations ... simple percentage was used in presenting and interpreting the quantitative data.

Localization and prediction of malignant potential in recurrent pheochromocytoma/paraganglioma (PCC/PGL) using 18F-FDG PET/CT.

Science.gov (United States)

Fikri, Ahmad Saad Fathinul; Kroiss, A; Ahmad, A Z F; Zanariah, H; Lau, W F E; Uprimny, C; Donnemiller, E; Kendler, D; Nordin, A J; Virgolini, I J

2014-06-01

To our knowledge, data are lacking on the role of 18F-FDG PET/CT in the localization and prediction of neuroendocrine tumors, in particular the pheochromocytoma/paraganglioma (PCC/PGL) group. To evaluate the role of 18F-FDG PET/CT in localizing and predicting the malignant potential of PCC/PGL. Twenty-three consecutive patients with a history of PCC/PGL, presenting with symptoms related to catecholamine excess, underwent 18F-FDG PET/CT. Final confirmation of the diagnosis was made using the composite references. PET/CT findings were analyzed on a per-lesion basis and a per-patient basis. Tumor SUVmax was analyzed to predict the dichotomization of patient endpoints for the local disease and metastatic groups. We investigated 23 patients (10 men, 13 women) with a mean age of 46.43 ± 3.70 years. Serum catecholamine levels were elevated in 82.60% of these patients. There were 136 sites (mean SUVmax: 16.39 ± 3.47) of validated disease recurrence. The overall sensitivities for diagnostic CT, FDG PET, and FDG PET/CT were 86.02%, 87.50%, and 98.59%, respectively. Based on the composite references, 39.10% of patients had local disease. There were significant differences in the SUVmax distribution between the local disease and metastatic groups; a significant correlation was noted when a SUVmax cut-off was set at 9.2 (Plocalization of recurrent tumors. Tumor SUVmax is a potentially useful predictor of malignant tumor potential. © The Foundation Acta Radiologica 2013 Reprints and permissions: sagepub.co.uk/journalsPermissions.nav.

Predicting habitat suitability for rare plants at local spatial scales using a species distribution model.

Science.gov (United States)

Gogol-Prokurat, Melanie

2011-01-01

If species distribution models (SDMs) can rank habitat suitability at a local scale, they may be a valuable conservation planning tool for rare, patchily distributed species. This study assessed the ability of Maxent, an SDM reported to be appropriate for modeling rare species, to rank habitat suitability at a local scale for four edaphic endemic rare plants of gabbroic soils in El Dorado County, California, and examined the effects of grain size, spatial extent, and fine-grain environmental predictors on local-scale model accuracy. Models were developed using species occurrence data mapped on public lands and were evaluated using an independent data set of presence and absence locations on surrounding lands, mimicking a typical conservation-planning scenario that prioritizes potential habitat on unsurveyed lands surrounding known occurrences. Maxent produced models that were successful at discriminating between suitable and unsuitable habitat at the local scale for all four species, and predicted habitat suitability values were proportional to likelihood of occurrence or population abundance for three of four species. Unfortunately, models with the best discrimination (i.e., AUC) were not always the most useful for ranking habitat suitability. The use of independent test data showed metrics that were valuable for evaluating which variables and model choices (e.g., grain, extent) to use in guiding habitat prioritization for conservation of these species. A goodness-of-fit test was used to determine whether habitat suitability values ranked habitat suitability on a continuous scale. If they did not, a minimum acceptable error predicted area criterion was used to determine the threshold for classifying habitat as suitable or unsuitable. I found a trade-off between model extent and the use of fine-grain environmental variables: goodness of fit was improved at larger extents, and fine-grain environmental variables improved local-scale accuracy, but fine-grain variables

Signal peptides and protein localization prediction

DEFF Research Database (Denmark)

Nielsen, Henrik

2005-01-01

In 1999, the Nobel prize in Physiology or Medicine was awarded to Gunther Blobel “for the discovery that proteins have intrinsic signals that govern their transport and localization in the cell”. Since the subcellular localization of a protein is an important clue to its function, the characteriz...

Model predictive controller design of hydrocracker reactors

OpenAIRE

GÖKÇE, Dila

2011-01-01

This study summarizes the design of a Model Predictive Controller (MPC) in Tüpraş, İzmit Refinery Hydrocracker Unit Reactors. Hydrocracking process, in which heavy vacuum gasoil is converted into lighter and valuable products at high temperature and pressure is described briefly. Controller design description, identification and modeling studies are examined and the model variables are presented. WABT (Weighted Average Bed Temperature) equalization and conversion increase are simulate...

Epileptogenic zone localization using magnetoencephalography predicts seizure freedom in epilepsy surgery

Science.gov (United States)

Englot, Dario J.; Nagarajan, Srikantan S.; Imber, Brandon S.; Raygor, Kunal P.; Honma, Susanne M.; Mizuiri, Danielle; Mantle, Mary; Knowlton, Robert C.; Kirsch, Heidi E.; Chang, Edward F.

2015-01-01

Objective The efficacy of epilepsy surgery depends critically upon successful localization of the epileptogenic zone. Magnetoencephalography (MEG) enables non-invasive detection of interictal spike activity in epilepsy, which can then be localized in three dimensions using magnetic source imaging (MSI) techniques. However, the clinical value of MEG in the pre-surgical epilepsy evaluation is not fully understood, as studies to date are limited by either a lack of long-term seizure outcomes or small sample size. Methods We performed a retrospective cohort study of focal epilepsy patients who received MEG for interictal spike mapping followed by surgical resection at our institution. Results We studied 132 surgical patients, with mean post-operative follow-up of 3.6 years (minimum 1 year). Dipole source modelling was successful in 103 (78%) patients, while no interictal spikes were seen in others. Among patients with successful dipole modelling, MEG findings were concordant with and specific to: i) the region of resection in 66% of patients, ii) invasive electrocorticography (ECoG) findings in 67% of individuals, and iii) the MRI abnormality in 74% of cases. MEG showed discordant lateralization in ~5% of cases. After surgery, 70% of all patients achieved seizure-freedom (Engel class I outcome). Whereas 85% of patients with concordant and specific MEG findings became seizure-free, this outcome was achieved by only 37% of individuals with MEG findings that were non-specific or discordant with the region of resection (χ2 = 26.4, p < 0.001). MEG reliability was comparable in patients with or without localized scalp EEG, and overall, localizing MEG findings predicted seizure freedom with an odds ratio of 5.11 (2.23–11.8, 95% CI). Significance MEG is a valuable tool for non-invasive interictal spike mapping in epilepsy surgery, including patients with non-localized findings on long-term EEG monitoring, and localization of the epileptogenic zone using MEG is associated

A novel representation for apoptosis protein subcellular localization prediction using support vector machine.

Science.gov (United States)

Zhang, Li; Liao, Bo; Li, Dachao; Zhu, Wen

2009-07-21

Apoptosis, or programmed cell death, plays an important role in development of an organism. Obtaining information on subcellular location of apoptosis proteins is very helpful to understand the apoptosis mechanism. In this paper, based on the concept that the position distribution information of amino acids is closely related with the structure and function of proteins, we introduce the concept of distance frequency [Matsuda, S., Vert, J.P., Ueda, N., Toh, H., Akutsu, T., 2005. A novel representation of protein sequences for prediction of subcellular location using support vector machines. Protein Sci. 14, 2804-2813] and propose a novel way to calculate distance frequencies. In order to calculate the local features, each protein sequence is separated into p parts with the same length in our paper. Then we use the novel representation of protein sequences and adopt support vector machine to predict subcellular location. The overall prediction accuracy is significantly improved by jackknife test.

Robust Model Predictive Control of a Wind Turbine

DEFF Research Database (Denmark)

Mirzaei, Mahmood; Poulsen, Niels Kjølstad; Niemann, Hans Henrik

2012-01-01

In this work the problem of robust model predictive control (robust MPC) of a wind turbine in the full load region is considered. A minimax robust MPC approach is used to tackle the problem. Nonlinear dynamics of the wind turbine are derived by combining blade element momentum (BEM) theory...... of the uncertain system is employed and a norm-bounded uncertainty model is used to formulate a minimax model predictive control. The resulting optimization problem is simplified by semidefinite relaxation and the controller obtained is applied on a full complexity, high fidelity wind turbine model. Finally...... and first principle modeling of the turbine flexible structure. Thereafter the nonlinear model is linearized using Taylor series expansion around system operating points. Operating points are determined by effective wind speed and an extended Kalman filter (EKF) is employed to estimate this. In addition...

Optimal control in a micro gas grid of prosumers using Model Predictive Control

NARCIS (Netherlands)

Alkano, Desti; Nefkens, W.J.; Scherpen, Jacqueline M.A.; Volkerts, M.

This paper studies the optimal control of a micro grid of biogas prosumers equipped with local storage devices. Excess biogas can be upgraded and injected into the low- pressure gas grid or, alternatively, shipped per lorry to be used elsewhere in an effort to create revenue. The aim of the control

Local hierarchical control for industrial microgrids with improved frequency regulation

DEFF Research Database (Denmark)

Rey, Juan M.; Vergara, Pedro P.; Castilla, Miguel

2018-01-01

Local control strategies that operate without relying on communication systems enhance flexibility and reliability of AC industrial microgrids. Based on a previous work in which a secondary switched control was proposed, this paper presents a complementary strategy to improve the frequency......-use of communications. Experimental results obtained on a laboratory microgrid are presented to validate the performance of the proposed complementary control strategy....

A mobile console for local access to accelerator control systems.

CERN Multimedia

1981-01-01

Microprocessors were installed as auxiliary crate controllers (ACCs) in the CAMAC interface of control systems for various accelerators. The same ACC was also at the hearth of a stand-alone system in the form of a mobile console. This was also used for local access to the control systems for tests and development work (Annual Report 1981, p. 80, Fig. 10).

Enhanced Voltage Control of VSC-HVDC Connected Offshore Wind Farms Based on Model Predictive Control

DEFF Research Database (Denmark)

Guo, Yifei; Gao, Houlei; Wu, Qiuwei

2018-01-01

This paper proposes an enhanced voltage control strategy (EVCS) based on model predictive control (MPC) for voltage source converter based high voltage direct current (VSCHVDC) connected offshore wind farms (OWFs). In the proposed MPC based EVCS, all wind turbine generators (WTGs) as well...... as the wind farm side VSC are optimally coordinated to keep voltages within the feasible range and reduce system power losses. Considering the high ratio of the OWF collector system, the effects of active power outputs of WTGs on voltage control are also taken into consideration. The predictive model of VSC...

Nonlinear Predictive Sliding Mode Control for Active Suspension System

Directory of Open Access Journals (Sweden)

Dazhuang Wang

2018-01-01

Full Text Available An active suspension system is important in meeting the requirements of the ride comfort and handling stability for vehicles. In this work, a nonlinear model of active suspension system and a corresponding nonlinear robust predictive sliding mode control are established for the control problem of active suspension. Firstly, a seven-degree-of-freedom active suspension model is established considering the nonlinear effects of springs and dampers; and secondly, the dynamic model is expanded in the time domain, and the corresponding predictive sliding mode control is established. The uncertainties in the controller are approximated by the fuzzy logic system, and the adaptive controller reduces the approximation error to increase the robustness of the control system. Finally, the simulation results show that the ride comfort and handling stability performance of the active suspension system is better than that of the passive suspension system and the Skyhook active suspension. Thus, the system can obviously improve the shock absorption performance of vehicles.

Generic Model Predictive Control Framework for Advanced Driver Assistance Systems

NARCIS (Netherlands)

Wang, M.

2014-01-01

This thesis deals with a model predictive control framework for control design of Advanced Driver Assistance Systems, where car-following tasks are under control. The framework is applied to design several autonomous and cooperative controllers and to examine the controller properties at the

Predicted Mobility Edges in One-Dimensional Incommensurate Optical Lattices: An Exactly Solvable Model of Anderson Localization

International Nuclear Information System (INIS)

Biddle, J.; Das Sarma, S.

2010-01-01

Localization properties of noninteracting quantum particles in one-dimensional incommensurate lattices are investigated with an exponential short-range hopping that is beyond the minimal nearest-neighbor tight-binding model. Energy dependent mobility edges are analytically predicted in this model and verified with numerical calculations. The results are then mapped to the continuum Schroedinger equation, and an approximate analytical expression for the localization phase diagram and the energy dependent mobility edges in the ground band is obtained.

Localized and Energy-Efficient Topology Control in Wireless Sensor Networks Using Fuzzy-Logic Control Approaches

Directory of Open Access Journals (Sweden)

Yuanjiang Huang

2014-01-01

Full Text Available The sensor nodes in the Wireless Sensor Networks (WSNs are prone to failures due to many reasons, for example, running out of battery or harsh environment deployment; therefore, the WSNs are expected to be able to maintain network connectivity and tolerate certain amount of node failures. By applying fuzzy-logic approach to control the network topology, this paper aims at improving the network connectivity and fault-tolerant capability in response to node failures, while taking into account that the control approach has to be localized and energy efficient. Two fuzzy controllers are proposed in this paper: one is Learning-based Fuzzy-logic Topology Control (LFTC, of which the fuzzy controller is learnt from a training data set; another one is Rules-based Fuzzy-logic Topology Control (RFTC, of which the fuzzy controller is obtained through designing if-then rules and membership functions. Both LFTC and RFTC do not rely on location information, and they are localized. Comparing them with other three representative algorithms (LTRT, List-based, and NONE through extensive simulations, our two proposed fuzzy controllers have been proved to be very energy efficient to achieve desired node degree and improve the network connectivity when sensor nodes run out of battery or are subject to random attacks.

Streamlining Local Behaviour Through Communication, Incentives and Control: A Case Study of Local Environmental Policies in China

Directory of Open Access Journals (Sweden)

Thomas Heberer

2011-01-01

Full Text Available This article describes how China uses evaluation ratings and monitoring as incentives in order to foster the implementation of environmental policies at the local level. It is argued that decentralisation in China leaves room for actors at the local levels to manoeuver and bargain with those on higher levels for flexible adjustment of implementation policies according to local conditions. However, decentralisation is accompanied by significant institutional changes in the structure of intergovernmental communication, incentives and control. Accordingly, decentralisation in China exhibits a specific design which leaves space for divergent local environmental policies while also engendering “grass-roots mechanisms”. On the whole, this new institutional setting benefits the implementation of environmental policies.

Offset Free Tracking Predictive Control Based on Dynamic PLS Framework

Directory of Open Access Journals (Sweden)

Jin Xin

2017-10-01

Full Text Available This paper develops an offset free tracking model predictive control based on a dynamic partial least square (PLS framework. First, state space model is used as the inner model of PLS to describe the dynamic system, where subspace identification method is used to identify the inner model. Based on the obtained model, multiple independent model predictive control (MPC controllers are designed. Due to the decoupling character of PLS, these controllers are running separately, which is suitable for distributed control framework. In addition, the increment of inner model output is considered in the cost function of MPC, which involves integral action in the controller. Hence, the offset free tracking performance is guaranteed. The results of an industry background simulation demonstrate the effectiveness of proposed method.

An estimator-based distributed voltage-predictive control strategy for ac islanded microgrids

DEFF Research Database (Denmark)

Wang, Yanbo; Chen, Zhe; Wang, Xiongfei

2015-01-01

This paper presents an estimator-based voltage predictive control strategy for AC islanded microgrids, which is able to perform voltage control without any communication facilities. The proposed control strategy is composed of a network voltage estimator and a voltage predictive controller for each...... and has a good capability to reject uncertain perturbations of islanded microgrids....

The Comparison Study of Short-Term Prediction Methods to Enhance the Model Predictive Controller Applied to Microgrid Energy Management

Directory of Open Access Journals (Sweden)

César Hernández-Hernández

2017-06-01

Full Text Available Electricity load forecasting, optimal power system operation and energy management play key roles that can bring significant operational advantages to microgrids. This paper studies how methods based on time series and neural networks can be used to predict energy demand and production, allowing them to be combined with model predictive control. Comparisons of different prediction methods and different optimum energy distribution scenarios are provided, permitting us to determine when short-term energy prediction models should be used. The proposed prediction models in addition to the model predictive control strategy appear as a promising solution to energy management in microgrids. The controller has the task of performing the management of electricity purchase and sale to the power grid, maximizing the use of renewable energy sources and managing the use of the energy storage system. Simulations were performed with different weather conditions of solar irradiation. The obtained results are encouraging for future practical implementation.

Association between obesity and local control of advanced rectal cancer after combined surgery and radiotherapy

Energy Technology Data Exchange (ETDEWEB)

Choi, Yun Seon; Park, Sung Kwang; Cho, Heung Lae; Ahn, Ki Jung [Dept. of Radiation Oncology, (Korea, Republic of); Lee, Yun Han [Dept. of Molecular Medicine, Keimyung University School of Medicine, Daegu (Korea, Republic of)

2016-06-15

The association between metabolism and cancer has been recently emphasized. This study aimed to find the prognostic significance of obesity in advanced stage rectal cancer patients treated with surgery and radiotherapy (RT). We retrospectively reviewed the medical records of 111 patients who were treated with combined surgery and RT for clinical stage 2–3 (T3 or N+) rectal cancer between 2008 and 2014. The prognostic significance of obesity (body mass index [BMI] ≥25 kg/m{sup 2}) in local control was evaluated. The median follow-up was 31.2 months (range, 4.1 to 85.7 months). Twenty-five patients (22.5%) were classified as obese. Treatment failure occurred in 33 patients (29.7%), including local failures in 13 patients (11.7%), regional lymph node failures in 5, and distant metastases in 24. The 3-year local control, recurrence-free survival, and overall survival rates were 88.7%, 73.6%, and 87.7%, respectively. Obesity (n = 25) significantly reduced the local control rate (p = 0.045; 3-year local control, 76.2%), especially in women (n = 37, p = 0.021). Segregation of local control was best achieved by BMI of 25.6 kg/m{sup 2} as a cutoff value. Obese rectal cancer patients showed poor local control after combined surgery and RT. More effective local treatment strategies for obese patients are warranted.

Association between obesity and local control of advanced rectal cancer after combined surgery and radiotherapy

International Nuclear Information System (INIS)

Choi, Yun Seon; Park, Sung Kwang; Cho, Heung Lae; Ahn, Ki Jung; Lee, Yun Han

2016-01-01

The association between metabolism and cancer has been recently emphasized. This study aimed to find the prognostic significance of obesity in advanced stage rectal cancer patients treated with surgery and radiotherapy (RT). We retrospectively reviewed the medical records of 111 patients who were treated with combined surgery and RT for clinical stage 2–3 (T3 or N+) rectal cancer between 2008 and 2014. The prognostic significance of obesity (body mass index [BMI] ≥25 kg/m 2 ) in local control was evaluated. The median follow-up was 31.2 months (range, 4.1 to 85.7 months). Twenty-five patients (22.5%) were classified as obese. Treatment failure occurred in 33 patients (29.7%), including local failures in 13 patients (11.7%), regional lymph node failures in 5, and distant metastases in 24. The 3-year local control, recurrence-free survival, and overall survival rates were 88.7%, 73.6%, and 87.7%, respectively. Obesity (n = 25) significantly reduced the local control rate (p = 0.045; 3-year local control, 76.2%), especially in women (n = 37, p = 0.021). Segregation of local control was best achieved by BMI of 25.6 kg/m 2 as a cutoff value. Obese rectal cancer patients showed poor local control after combined surgery and RT. More effective local treatment strategies for obese patients are warranted

Predictive control of irrigation canals – robust design and real-time implementation

NARCIS (Netherlands)

Aguilar, José V.; Langarita, Pedro; Rodellar, José; Linares, Lorenzo; Horváth, K.

2016-01-01

Predictive control is one of the most commonly used control methods in a variety of application areas, including hydraulic processes such as water distribution canals for irrigation. This article presents the design and application of predictive control for the water discharge entering into an

Enhanced pid vs model predictive control applied to bldc motor

Science.gov (United States)

Gaya, M. S.; Muhammad, Auwal; Aliyu Abdulkadir, Rabiu; Salim, S. N. S.; Madugu, I. S.; Tijjani, Aminu; Aminu Yusuf, Lukman; Dauda Umar, Ibrahim; Khairi, M. T. M.

2018-01-01

BrushLess Direct Current (BLDC) motor is a multivariable and highly complex nonlinear system. Variation of internal parameter values with environment or reference signal increases the difficulty in controlling the BLDC effectively. Advanced control strategies (like model predictive control) often have to be integrated to satisfy the control desires. Enhancing or proper tuning of a conventional algorithm results in achieving the desired performance. This paper presents a performance comparison of Enhanced PID and Model Predictive Control (MPC) applied to brushless direct current motor. The simulation results demonstrated that the PSO-PID is slightly better than the PID and MPC in tracking the trajectory of the reference signal. The proposed scheme could be useful algorithms for the system.

Nonlinear Economic Model Predictive Control Strategy for Active Smart Buildings

DEFF Research Database (Denmark)

Santos, Rui Mirra; Zong, Yi; Sousa, Joao M. C.

2016-01-01

Nowadays, the development of advanced and innovative intelligent control techniques for energy management in buildings is a key issue within the smart grid topic. A nonlinear economic model predictive control (EMPC) scheme, based on the branch-and-bound tree search used as optimization algorithm ...... controller is shown very reliable keeping the comfort levels in the two considered seasons and shifting the load away from peak hours in order to achieve the desired flexible electricity consumption.......Nowadays, the development of advanced and innovative intelligent control techniques for energy management in buildings is a key issue within the smart grid topic. A nonlinear economic model predictive control (EMPC) scheme, based on the branch-and-bound tree search used as optimization algorithm...

Robust multi-model predictive control of multi-zone thermal plate system

Directory of Open Access Journals (Sweden)

Poom Jatunitanon

2018-02-01

Full Text Available A modern controller was designed by using the mathematical model of a multi–zone thermal plate system. An important requirement for this type of controller is that it must be able to keep the temperature set-point of each thermal zone. The mathematical model used in the design was determined through a system identification process. The results showed that when the operating condition is changed, the performance of the controller may be reduced as a result of the system parameter uncertainties. This paper proposes a weighting technique of combining the robust model predictive controller for each operating condition into a single robust multi-model predictive control. Simulation and experimental results showed that the proposed method performed better than the conventional multi-model predictive control in rise time of transient response, when used in a system designed to work over a wide range of operating conditions.

Network control principles predict neuron function in the Caenorhabditis elegans connectome

Science.gov (United States)

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

2017-10-01

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

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

Science.gov (United States)

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

2017-10-26

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

State and local safety program

Energy Technology Data Exchange (ETDEWEB)

Carlyle Thompson, G D [Utah State Division of Health, Salt Lake City, UT (United States)

1969-07-01

This paper will give emphasis to the need for an increasing role of the states, along with the Federal agencies, in the Plowshare Program in order to assure state and local confidence with respect to the safety of their residents as the Federal government seeks new methods to benefit society. First will be stressed the age-old principle of control at the source. Other factors to be discussed are monitoring; standards and their use; control action; public relations; predictions and the need to have certain advance knowledge of tests - even if security clearance is necessary for appropriate state representatives; the state and local government responsibility to their citizens; the isolation of national decision making from state and local concern and responsibility; cost assessments and their responsibility; and research as it relates to the ecological system as well a the direct short- or long-term effects of radioactivity on man. (author)

State and local safety program

International Nuclear Information System (INIS)

Carlyle Thompson, G.D.

1969-01-01

This paper will give emphasis to the need for an increasing role of the states, along with the Federal agencies, in the Plowshare Program in order to assure state and local confidence with respect to the safety of their residents as the Federal government seeks new methods to benefit society. First will be stressed the age-old principle of control at the source. Other factors to be discussed are monitoring; standards and their use; control action; public relations; predictions and the need to have certain advance knowledge of tests - even if security clearance is necessary for appropriate state representatives; the state and local government responsibility to their citizens; the isolation of national decision making from state and local concern and responsibility; cost assessments and their responsibility; and research as it relates to the ecological system as well a the direct short- or long-term effects of radioactivity on man. (author)

Control System Design for Cylindrical Tank Process Using Neural Model Predictive Control Technique

Directory of Open Access Journals (Sweden)

M. Sridevi

2010-10-01

Full Text Available Chemical manufacturing and process industry requires innovative technologies for process identification. This paper deals with model identification and control of cylindrical process. Model identification of the process was done using ARMAX technique. A neural model predictive controller was designed for the identified model. The performance of the controllers was evaluated using MATLAB software. The performance of NMPC controller was compared with Smith Predictor controller and IMC controller based on rise time, settling time, overshoot and ISE and it was found that the NMPC controller is better suited for this process.

Prediction of welding residual distortions of large structures using a local/global approach

International Nuclear Information System (INIS)

Duan, Y. G.; Bergheau, J. M.; Vincent, Y.; Boitour, F.; Leblond, J. B.

2007-01-01

Prediction of welding residual distortions is more difficult than that of the microstructure and residual stresses. On the one hand, a fine mesh (often 3D) has to be used in the heat affected zone for the sake of the sharp variations of thermal, metallurgical and mechanical fields in this region. On the other hand, the whole structure is required to be meshed for the calculation of residual distortions. But for large structures, a 3D mesh is inconceivable caused by the costs of the calculation. Numerous methods have been developed to reduce the size of models. A local/global approach has been proposed to determine the welding residual distortions of large structures. The plastic strains and the microstructure due to welding are supposed can be determined from a local 3D model which concerns only the weld and its vicinity. They are projected as initial strains into a global 3D model which consists of the whole structure and obviously much less fine in the welded zone than the local model. The residual distortions are then calculated using a simple elastic analysis, which makes this method particularly effective in an industrial context. The aim of this article is to present the principle of the local/global approach then show the capacity of this method in an industrial context and finally study the definition of the local model

Volumetric PET/CT parameters predict local response of head and neck squamous cell carcinoma to chemoradiotherapy

International Nuclear Information System (INIS)

Hanamoto, Atsushi; Tatsumi, Mitsuaki; Takenaka, Yukinori; Hamasaki, Toshimitsu; Yasui, Toshimichi; Nakahara, Susumu; Yamamoto, Yoshifumi; Seo, Yuji; Isohashi, Fumiaki; Ogawa, Kazuhiko; Hatazawa, Jun; Inohara, Hidenori

2014-01-01

It is not well established whether pretreatment 18 F-FDG PET/CT can predict local response of head and neck squamous cell carcinoma (HNSCC) to chemoradiotherapy (CRT). We examined 118 patients: 11 with nasopharyngeal cancer (NPC), 30 with oropharyngeal cancer (OPC), and 77 with laryngohypopharyngeal cancer (LHC) who had completed CRT. PET/CT parameters of primary tumor, including metabolic tumor volume (MTV), total lesion glycolysis (TLG), and maximum and mean standardized uptake value (SUV max and SUV mean ), were correlated with local response, according to primary site and human papillomavirus (HPV) status. Receiver-operating characteristic analyses were made to access predictive values of the PET/CT parameters, while logistic regression analyses were used to identify independent predictors. Area under the curve (AUC) of the PET/CT parameters ranged from 0.53 to 0.63 in NPC and from 0.50 to 0.54 in OPC. HPV-negative OPC showed AUC ranging from 0.51 to 0.58, while all of HPV-positive OPCs showed complete response. In contrast, AUC ranged from 0.71 to 0.90 in LHC. Moreover, AUCs of MTV and TLG were significantly higher than those of SUV max and SUV mean (P < 0.01). After multivariate analysis, high MTV >25.0 mL and high TLG >144.8 g remained as independent, significant predictors of incomplete response compared with low MTV (odds ratio [OR], 13.4; 95% confidence interval [CI], 2.5–72.9; P = 0.003) and low TLG (OR, 12.8; 95% CI, 2.4–67.9; P = 0.003), respectively. In conclusion, predictive efficacy of pretreatment 18 F-FDG PET/CT varies with different primary sites and chosen parameters. Local response of LHC is highly predictable by volume-based PET/CT parameters

Preschool Inhibitory Control Predicts ADHD Group Status and Inhibitory Weakness in School.

Science.gov (United States)

Jacobson, Lisa A; Schneider, Heather; Mahone, E Mark

2017-12-26

Discriminative utility of performance measures of inhibitory control was examined in preschool children with and without ADHD to determine whether performance measures added to diagnostic prediction and to prediction of informant-rated day-to-day executive function. Children ages 4-5 years (N = 105, 61% boys; 54 ADHD, medication-naïve) were assessed using performance measures (Auditory Continuous Performance Test for Preschoolers-Commission errors, Conflicting Motor Response Test, NEPSY Statue) and caregiver (parent, teacher) ratings of inhibition (Behavior Rating Inventory of Executive Function-Preschool version). Performance measures and parent and teacher reports of inhibitory control significantly and uniquely predicted ADHD group status; however, performance measures did not add to prediction of group status beyond parent reports. Performance measures did significantly predict classroom inhibitory control (teacher ratings), over and above parent reports of inhibitory control. Performance measures of inhibitory control may be adequate predictors of ADHD status and good predictors of young children's classroom inhibitory control, demonstrating utility as components of clinical assessments. © The Author(s) 2017. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Automatic Power Control for Daily Load-following Operation using Model Predictive Control Method

Energy Technology Data Exchange (ETDEWEB)

Yu, Keuk Jong; Kim, Han Gon [KH, Daejeon (Korea, Republic of)

2009-10-15

Under the circumstances that nuclear power occupies more than 50%, nuclear power plants are required to be operated on load-following operation in order to make the effective management of electric grid system and enhanced responsiveness to rapid changes in power demand. Conventional reactors such as the OPR1000 and APR1400 have a regulating system that controls the average temperature of the reactor core relation to the reference temperature. This conventional method has the advantages of proven technology and ease of implementation. However, this method is unsuitable for controlling the axial power shape, particularly the load following operation. Accordingly, this paper reports on the development of a model predictive control method which is able to control the reactor power and the axial shape index. The purpose of this study is to analyze the behavior of nuclear reactor power and the axial power shape by using a model predictive control method when the power is increased and decreased for a daily load following operation. The study confirms that deviations in the axial shape index (ASI) are within the operating limit.

Multi-region fuzzy logic controller with local PID controllers for U-tube steam generator in nuclear power plant

Directory of Open Access Journals (Sweden)