Automated extraction of knowledge for model-based diagnostics
Gonzalez, Avelino J.; Myler, Harley R.; Towhidnejad, Massood; Mckenzie, Frederic D.; Kladke, Robin R.
1990-01-01
The concept of accessing computer aided design (CAD) design databases and extracting a process model automatically is investigated as a possible source for the generation of knowledge bases for model-based reasoning systems. The resulting system, referred to as automated knowledge generation (AKG), uses an object-oriented programming structure and constraint techniques as well as internal database of component descriptions to generate a frame-based structure that describes the model. The procedure has been designed to be general enough to be easily coupled to CAD systems that feature a database capable of providing label and connectivity data from the drawn system. The AKG system is capable of defining knowledge bases in formats required by various model-based reasoning tools.
Model-Based Information Extraction From Synthetic Aperture Radar Signals
Matzner, Shari A.
2011-07-01
Synthetic aperture radar (SAR) is a remote sensing technology for imaging areas of the earth's surface. SAR has been successfully used for monitoring characteristics of the natural environment such as land cover type and tree density. With the advent of higher resolution sensors, it is now theoretically possible to extract information about individual structures such as buildings from SAR imagery. This information could be used for disaster response and security-related intelligence. SAR has an advantage over other remote sensing technologies for these applications because SAR data can be collected during the night and in rainy or cloudy conditions. This research presents a model-based method for extracting information about a building -- its height and roof slope -- from a single SAR image. Other methods require multiple images or ancillary data from specialized sensors, making them less practical. The model-based method uses simulation to match a hypothesized building to an observed SAR image. The degree to which a simulation matches the observed data is measured by mutual information. The success of this method depends on the accuracy of the simulation and on the reliability of the mutual information similarity measure. Electromagnetic theory was applied to relate a building's physical characteristics to the features present in a SAR image. This understanding was used to quantify the precision of building information contained in SAR data, and to identify the inputs needed for accurate simulation. A new SAR simulation technique was developed to meet the accuracy and efficiency requirements of model-based information extraction. Mutual information, a concept from information theory, has become a standard for measuring the similarity between medical images. Its performance in the context of matching a simulation image to a SAR image was evaluated in this research, and it was found to perform well under certain conditions. The factors that affect its performance
Automating the Extraction of Model-Based Software Product Lines from Model Variants
Martinez, Jabier; Ziadi, Tewfik; Klein, Jacques; Le Traon, Yves
2015-01-01
International audience We address the problem of automating 1) the analysis of existing similar model variants and 2) migrating them into a software product line. Our approach, named MoVa2PL, considers the identification of variability and commonality in model variants, as well as the extraction of a CVL-compliant Model-based Software Product Line (MSPL) from the features identified on these variants. MoVa2PL builds on a generic representation of models making it suitable to any MOF-based ...
Auditory-model-based Feature Extraction Method for Mechanical Faults Diagnosis
LI Yungong; ZHANG Jinping; DAI Li; ZHANG Zhanyi; LIU Jie
2010-01-01
It is well known that the human auditory system possesses remarkable capabilities to analyze and identify signals. Therefore, it would be significant to build an auditory model based on the mechanism of human auditory systems, which may improve the effects of mechanical signal analysis and enrich the methods of mechanical faults features extraction. However the existing methods are all based on explicit senses of mathematics or physics, and have some shortages on distinguishing different faults, stability, and suppressing the disturbance noise, etc. For the purpose of improving the performances of the work of feature extraction, an auditory model, early auditory(EA) model, is introduced for the first time. This auditory model transforms time domain signal into auditory spectrum via bandpass filtering, nonlinear compressing, and lateral inhibiting by simulating the principle of the human auditory system. The EA model is developed with the Gammatone filterbank as the basilar membrane. According to the characteristics of vibration signals, a method is proposed for determining the parameter of inner hair cells model of EA model. The performance of EA model is evaluated through experiments on four rotor faults, including misalignment, rotor-to-stator rubbing, oil film whirl, and pedestal looseness. The results show that the auditory spectrum, output of EA model, can effectively distinguish different faults with satisfactory stability and has the ability to suppress the disturbance noise. Then, it is feasible to apply auditory model, as a new method, to the feature extraction for mechanical faults diagnosis with effect.
Akhbari, Mahsa; Shamsollahi, Mohammad,; Jutten, Christian
2013-01-01
International audience The automatic detection of Electrocardiogram (ECG) waves is important to cardiac disease diagnosis. A good perfor- mance of an automatic ECG analyzing system depends heavily upon the accurate and reliable detection of QRS complex, as well as P and T waves. In this paper, we propose an efficient method for extraction of characteristic points of ECG signal. The method is based on a nonlinear dynamic model, previously introduced for generation of synthetic ECG signals. ...
An Active Contour Model Based on Adaptive Threshold for Extraction of Cerebral Vascular Structures
Wang, Jiaxin; Zhao, Shifeng; Liu, Zifeng; Duan, Fuqing; Pan, Yutong
2016-01-01
Cerebral vessel segmentation is essential and helpful for the clinical diagnosis and the related research. However, automatic segmentation of brain vessels remains challenging because of the variable vessel shape and high complex of vessel geometry. This study proposes a new active contour model (ACM) implemented by the level-set method for segmenting vessels from TOF-MRA data. The energy function of the new model, combining both region intensity and boundary information, is composed of two region terms, one boundary term and one penalty term. The global threshold representing the lower gray boundary of the target object by maximum intensity projection (MIP) is defined in the first-region term, and it is used to guide the segmentation of the thick vessels. In the second term, a dynamic intensity threshold is employed to extract the tiny vessels. The boundary term is used to drive the contours to evolve towards the boundaries with high gradients. The penalty term is used to avoid reinitialization of the level-set function. Experimental results on 10 clinical brain data sets demonstrate that our method is not only able to achieve better Dice Similarity Coefficient than the global threshold based method and localized hybrid level-set method but also able to extract whole cerebral vessel trees, including the thin vessels. PMID:27597878
An Active Contour Model Based on Adaptive Threshold for Extraction of Cerebral Vascular Structures.
Wang, Jiaxin; Zhao, Shifeng; Liu, Zifeng; Tian, Yun; Duan, Fuqing; Pan, Yutong
2016-01-01
Cerebral vessel segmentation is essential and helpful for the clinical diagnosis and the related research. However, automatic segmentation of brain vessels remains challenging because of the variable vessel shape and high complex of vessel geometry. This study proposes a new active contour model (ACM) implemented by the level-set method for segmenting vessels from TOF-MRA data. The energy function of the new model, combining both region intensity and boundary information, is composed of two region terms, one boundary term and one penalty term. The global threshold representing the lower gray boundary of the target object by maximum intensity projection (MIP) is defined in the first-region term, and it is used to guide the segmentation of the thick vessels. In the second term, a dynamic intensity threshold is employed to extract the tiny vessels. The boundary term is used to drive the contours to evolve towards the boundaries with high gradients. The penalty term is used to avoid reinitialization of the level-set function. Experimental results on 10 clinical brain data sets demonstrate that our method is not only able to achieve better Dice Similarity Coefficient than the global threshold based method and localized hybrid level-set method but also able to extract whole cerebral vessel trees, including the thin vessels. PMID:27597878
Naulleau, Patrick P.; Cain, Jason P.
2007-06-01
As critical dimensions shrink, line edge and width roughness (LER and LWR) become of increasing concern. Crucial to the goal of reducing LER is its accurate characterization. LER has traditionally been represented as a single rms value. More recently the use of power spectral density (PSD), height-height correlation (HHCF), and {sigma} versus length plots has been proposed in order to extract the additional spatial descriptors of correlation length and roughness exponent. Here we perform a modeling-based noise-sensitivity study on the extraction of spatial descriptors from line-edge data as well as an experimental study of the robustness of these various descriptors using a large dataset of recent extreme-ultraviolet exposure data. The results show that in the presence of noise and in the large dataset limit, the PSD method provides higher accuracy in the extraction of the roughness exponent, whereas the HHCF method provides higher accuracy for the correlation length. On the other hand, when considering precision, the HHCF method is superior for both metrics.
ROI method used in Ga-68 EDTA PET dynamic study for quantitative determination of brain tumor BBB permeability assumes that the tumor is homogeneous in terms of Ga-68 EDTA kinetics, even though it is known to be highly heterogeneous. It is desirable to examine regions of different kinetics separately. In this study, we have developed an efficient and effective method to separate tissue regions of different Ga-68 EDTA kinetics. The method uses a two-compartment model to extract three principal component factors (vascular component, fast and slow components) from whole-tumor kinetics by model fitting, then each pixel kinetics in the tumor was expressed in terms of these factors by least-square regression to provide factor images. The whole tumor was separated into two regions - one with mainly fast kinetics and one with slow kinetics. The two regions have markedly different uptake and clearance rate. This method has combined the advantage of statistical factor analysis and modeling approach
Diggle, Peter J
2007-01-01
Model-based geostatistics refers to the application of general statistical principles of modeling and inference to geostatistical problems. This volume provides a treatment of model-based geostatistics and emphasizes on statistical methods and applications. It also features analyses of datasets from a range of scientific contexts.
Pafilis, Evangelos; Buttigieg, Pier Luigi; Ferrell, Barbra;
2016-01-01
The microbial and molecular ecology research communities have made substantial progress on developing standards for annotating samples with environment metadata. However, sample manual annotation is a highly labor intensive process and requires familiarity with the terminologies used. We have the...... and text-mining-assisted curation revealed that EXTRACT speeds up annotation by 15-25% and helps curators to detect terms that would otherwise have been missed.Database URL: https://extract.hcmr.gr/......., organism, tissue and disease terms. The evaluators in the BioCreative V Interactive Annotation Task found the system to be intuitive, useful, well documented and sufficiently accurate to be helpful in spotting relevant text passages and extracting organism and environment terms. Comparison of fully manual...
Heimann, Tobias; Delingette, Hervé
2011-01-01
This chapter starts with a brief introduction into model-based segmentation, explaining the basic concepts and different approaches. Subsequently, two segmentation approaches are presented in more detail: First, the method of deformable simplex meshes is described, explaining the special properties of the simplex mesh and the formulation of the internal forces. Common choices for image forces are presented, and how to evolve the mesh to adapt to certain structures. Second, the method of point...
Literature Survey on Model based Slicing
Sneh Krishna*,; Alekh Dwivedi
2014-01-01
Software testing is an activity which aims at evaluating an feature or capability of system and determining that whether it meets required expectations. One way to ease this program slicing technique is to break down the large programs into smaller ones and into other is model based slicing that break down the large software architecture model into smaller models at the early stage of SDLC (Software Development Life Cycle). This is the novel methodology to extract the sub mode...
Rowe, Sidney E.
2010-01-01
In September 2007, the Engineering Directorate at the Marshall Space Flight Center (MSFC) created the Design System Focus Team (DSFT). MSFC was responsible for the in-house design and development of the Ares 1 Upper Stage and the Engineering Directorate was preparing to deploy a new electronic Configuration Management and Data Management System with the Design Data Management System (DDMS) based upon a Commercial Off The Shelf (COTS) Product Data Management (PDM) System. The DSFT was to establish standardized CAD practices and a new data life cycle for design data. Of special interest here, the design teams were to implement Model Based Definition (MBD) in support of the Upper Stage manufacturing contract. It is noted that this MBD does use partially dimensioned drawings for auxiliary information to the model. The design data lifecycle implemented several new release states to be used prior to formal release that allowed the models to move through a flow of progressive maturity. The DSFT identified some 17 Lessons Learned as outcomes of the standards development, pathfinder deployments and initial application to the Upper Stage design completion. Some of the high value examples are reviewed.
Running a nuclear power plant involves monitoring data provided by the installation's sensors. Operators and computerized systems then use these data to establish a diagnostic of the plant. However, the instrumentation system is complex, and is not immune to faults and failures. This paper presents a system for detecting sensor failures using a topological description of the installation and a set of component models. This model of the plant implicitly contains relations between sensor data. These relations must always be checked if all the components are functioning correctly. The failure detection task thus consists of checking these constraints. The constraints are extracted in two stages. Firstly, a qualitative model of their existence is built using structural analysis. Secondly, the models are formally handled according to the results of the structural analysis, in order to establish the constraints on the sensor data. This work constitutes an initial step in extending model-based diagnosis, as the information on which it is based is suspect. This work will be followed by surveillance of the detection system. When the instrumentation is assumed to be sound, the unverified constraints indicate errors on the plant model. (authors). 8 refs., 4 figs
Principles of models based engineering
Dolin, R.M.; Hefele, J.
1996-11-01
This report describes a Models Based Engineering (MBE) philosophy and implementation strategy that has been developed at Los Alamos National Laboratory`s Center for Advanced Engineering Technology. A major theme in this discussion is that models based engineering is an information management technology enabling the development of information driven engineering. Unlike other information management technologies, models based engineering encompasses the breadth of engineering information, from design intent through product definition to consumer application.
Model-based Software Engineering
Kindler, Ekkart
2010-01-01
The vision of model-based software engineering is to make models the main focus of software development and to automatically generate software from these models. Part of that idea works already today. But, there are still difficulties when it comes to behaviour. Actually, there is no lack in models...
Yang, Zhihui; Zhao, Andong; Li, Zhongdong; Ge, Hua; Li, Tonghua; Zhang, Fucheng; Zhan, Hao; Wang, Jianchang
2016-06-01
Positive acceleration (+Gz) in the head-to-foot direction generated by modern high-performance fighter jets during flight maneuvers is characterized by high G values and a rapid rate of acceleration, and is often long in duration and a repeated occurrence. The acceleration overload far exceeds the pilot's physiological tolerance limits and causes considerable strain on several organ systems. Despite the importance of monitoring pathophysiological alterations related to +Gz exposure, we lack a complete explanation of the pathophysiology of +Gz exposure. Ginkgo biloba extract (GBE) is a classic traditional Chinese medicine (TCM) that might exert a protective effect against +Gz exposure. However, its mechanism remains unclear. Here, a metabolomics approach based on ultra high-performance liquid chromatography coupled with quadrupole time-of-flight mass spectrometry (UHPLC-Q-TOFMS) was used to characterize +Gz-induced metabolic fluctuations in a rat model and to evaluate the protective effect of GBE. Using partial least-squares discriminant analysis for the classification and selection of biomarkers, eighteen serum metabolites related to +Gz exposure were identified, and were found to primarily involve the fatty acid β-oxidation pathway, glycerophospholipid metabolism, phospholipid metabolism, bile acid metabolism, purine metabolism and lysine metabolism. Taking these potential biomarkers as screening indexes, we found that GBE could reverse the pathological process of +Gz exposure by partially regulating the perturbed fatty acid β-oxidation pathway, glycerophospholipid metabolism, purine metabolism and lysine metabolism. This indicates that UHPLC-Q-TOFMS-based metabolomics provides a powerful tool to reveal serum metabolic fluctuations in response to +Gz exposure and to study the mechanism underlying TCM. PMID:27010354
PV panel model based on datasheet values
Sera, Dezso; Teodorescu, Remus; Rodriguez, Pedro
This work presents the construction of a model for a PV panel using the single-diode five-parameters model, based exclusively on data-sheet parameters. The model takes into account the series and parallel (shunt) resistance of the panel. The equivalent circuit and the basic equations of the PV cell....../panel in Standard Test Conditions (STC) are shown, as well as the parameters extraction from the data-sheet values. The temperature dependence of the cell dark saturation current is expressed with an alternative formula, which gives better correlation with the datasheet values of the power temperature...... dependence. Based on these equations, a PV panel model, which is able to predict the panel behavior in different temperature and irradiance conditions, is built and tested....
Model-based tomographic reconstruction
Chambers, David H.; Lehman, Sean K.; Goodman, Dennis M.
2012-06-26
A model-based approach to estimating wall positions for a building is developed and tested using simulated data. It borrows two techniques from geophysical inversion problems, layer stripping and stacking, and combines them with a model-based estimation algorithm that minimizes the mean-square error between the predicted signal and the data. The technique is designed to process multiple looks from an ultra wideband radar array. The processed signal is time-gated and each section processed to detect the presence of a wall and estimate its position, thickness, and material parameters. The floor plan of a building is determined by moving the array around the outside of the building. In this paper we describe how the stacking and layer stripping algorithms are combined and show the results from a simple numerical example of three parallel walls.
Model-based requirements engineering
Holt, Jon
2012-01-01
This book provides a hands-on introduction to model-based requirementsengineering and management by describing a set of views that form the basisfor the approach. These views take into account each individual requirement interms of its description, but then also provide each requirement with meaning byputting it into the correct 'context'. A requirement that has been put into a contextis known as a 'use case' and may be based upon either stakeholders or levelsof hierarchy in a system. Each use case must then be analysed and validated bydefining a combination of scenarios and formal mathematica
Model-based target and background characterization
Mueller, Markus; Krueger, Wolfgang; Heinze, Norbert
2000-07-01
Up to now most approaches of target and background characterization (and exploitation) concentrate solely on the information given by pixels. In many cases this is a complex and unprofitable task. During the development of automatic exploitation algorithms the main goal is the optimization of certain performance parameters. These parameters are measured during test runs while applying one algorithm with one parameter set to images that constitute of image domains with very different domain characteristics (targets and various types of background clutter). Model based geocoding and registration approaches provide means for utilizing the information stored in GIS (Geographical Information Systems). The geographical information stored in the various GIS layers can define ROE (Regions of Expectations) and may allow for dedicated algorithm parametrization and development. ROI (Region of Interest) detection algorithms (in most cases MMO (Man- Made Object) detection) use implicit target and/or background models. The detection algorithms of ROIs utilize gradient direction models that have to be matched with transformed image domain data. In most cases simple threshold calculations on the match results discriminate target object signatures from the background. The geocoding approaches extract line-like structures (street signatures) from the image domain and match the graph constellation against a vector model extracted from a GIS (Geographical Information System) data base. Apart from geo-coding the algorithms can be also used for image-to-image registration (multi sensor and data fusion) and may be used for creation and validation of geographical maps.
Graph Model Based Indoor Tracking
Jensen, Christian Søndergaard; Lu, Hua; Yang, Bin
2009-01-01
The tracking of the locations of moving objects in large indoor spaces is important, as it enables a range of applications related to, e.g., security and indoor navigation and guidance. This paper presents a graph model based approach to indoor tracking that offers a uniform data management...... infrastructure for different symbolic positioning technologies, e.g., Bluetooth and RFID. More specifically, the paper proposes a model of indoor space that comprises a base graph and mappings that represent the topology of indoor space at different levels. The resulting model can be used for one or several...... indoor positioning technologies. Focusing on RFID-based positioning, an RFID specific reader deployment graph model is built from the base graph model. This model is then used in several algorithms for constructing and refining trajectories from raw RFID readings. Empirical studies with implementations...
A model-based display is identified, discussed, and illustrated. The model used in the display is based upon the Rankine Cycle, a heat engine cycle. Plant process data from the loss of main and auxiliary feedwater event at the Davis-Besse Plant on June 9, l985 is used to illustrate the display. The model used in the display fuses individual process variables into process functions. It also serves as a medium to communicate status of the process to human users. The human users may evaluate the goals of operation from the displayed process functions. Because of these display features, the user's cognitive workload is minimized. The opinions expressed herein are the author's personal ones and do not necessarily reflect criteria, requirements, and guidelines of the U.S. Nuclear Regulatory Commission
Model-Based Gait Enrolment in Real-World Imagery
Wagg, David K; Nixon, Mark S.
2003-01-01
We present a model-based approach to gait extraction that is capable of reliable operation on real-world imagery. Hierarchies of shape and motion are employed to yield relatively modest computational demands, avoiding the high-dimensional search spaces associated with complex models. Anatomical data is used to generate shape models consistent with normal human body proportions. Mean gait data is used to create prototype gait motion models, which are adapted to fit individual subjects. Accurac...
Hibbard, Bill
2012-05-01
Orseau and Ring, as well as Dewey, have recently described problems, including self-delusion, with the behavior of agents using various definitions of utility functions. An agent's utility function is defined in terms of the agent's history of interactions with its environment. This paper argues, via two examples, that the behavior problems can be avoided by formulating the utility function in two steps: 1) inferring a model of the environment from interactions, and 2) computing utility as a function of the environment model. Basing a utility function on a model that the agent must learn implies that the utility function must initially be expressed in terms of specifications to be matched to structures in the learned model. These specifications constitute prior assumptions about the environment so this approach will not work with arbitrary environments. But the approach should work for agents designed by humans to act in the physical world. The paper also addresses the issue of self-modifying agents and shows that if provided with the possibility to modify their utility functions agents will not choose to do so, under some usual assumptions.
Howard, Y; Gravell, A; Ferreira, C; Augusto, J C
2011-01-01
Trace analysis can be a useful way to discover problems in a program under test. Rather than writing a special purpose trace analysis tool, this paper proposes that traces can usefully be analysed by checking them against a formal model using a standard model-checker or else an animator for executable specifications. These techniques are illustrated using a Travel Agent case study implemented in J2EE. We added trace beans to this code that write trace information to a database. The traces are then extracted and converted into a form suitable for analysis by Spin, a popular model-checker, and Pro-B, a model-checker and animator for the B notation. This illustrates the technique, and also the fact that such a system can have a variety of models, in different notations, that capture different features. These experiments have demonstrated that model-based trace-checking is feasible. Future work is focussed on scaling up the approach to larger systems by increasing the level of automation.
Model-based phase-shifting interferometer
Liu, Dong; Zhang, Lei; Shi, Tu; Yang, Yongying; Chong, Shiyao; Miao, Liang; Huang, Wei; Shen, Yibing; Bai, Jian
2015-10-01
A model-based phase-shifting interferometer (MPI) is developed, in which a novel calculation technique is proposed instead of the traditional complicated system structure, to achieve versatile, high precision and quantitative surface tests. In the MPI, the partial null lens (PNL) is employed to implement the non-null test. With some alternative PNLs, similar as the transmission spheres in ZYGO interferometers, the MPI provides a flexible test for general spherical and aspherical surfaces. Based on modern computer modeling technique, a reverse iterative optimizing construction (ROR) method is employed for the retrace error correction of non-null test, as well as figure error reconstruction. A self-compiled ray-tracing program is set up for the accurate system modeling and reverse ray tracing. The surface figure error then can be easily extracted from the wavefront data in forms of Zernike polynomials by the ROR method. Experiments of the spherical and aspherical tests are presented to validate the flexibility and accuracy. The test results are compared with those of Zygo interferometer (null tests), which demonstrates the high accuracy of the MPI. With such accuracy and flexibility, the MPI would possess large potential in modern optical shop testing.
Probabilistic Model-Based Safety Analysis
Güdemann, Matthias; 10.4204/EPTCS.28.8
2010-01-01
Model-based safety analysis approaches aim at finding critical failure combinations by analysis of models of the whole system (i.e. software, hardware, failure modes and environment). The advantage of these methods compared to traditional approaches is that the analysis of the whole system gives more precise results. Only few model-based approaches have been applied to answer quantitative questions in safety analysis, often limited to analysis of specific failure propagation models, limited types of failure modes or without system dynamics and behavior, as direct quantitative analysis is uses large amounts of computing resources. New achievements in the domain of (probabilistic) model-checking now allow for overcoming this problem. This paper shows how functional models based on synchronous parallel semantics, which can be used for system design, implementation and qualitative safety analysis, can be directly re-used for (model-based) quantitative safety analysis. Accurate modeling of different types of proba...
Active Shape Model-Based Gait Recognition Using Infrared Images
Daehee Kim
2009-12-01
Full Text Available We present a gait recognition system using infra-red (IR images. Since an IR camera is not affected by the intensity of illumination, it is able to provide constant recognition performance regardless of the amount of illumination. Model-based object tracking algorithms enable robust tracking with partial occlusions or dynamic illumination. However, this algorithm often fails in tracking objects if strong edge exists near the object. Replacementof the input image by an IR image guarantees robust object region extraction because background edges do not affect the IR image. In conclusion, the proposed gait recognition algorithm improves accuracy in object extraction by using IR images and the improvementsfinally increase the recognition rate of gaits.
Traceability in Model-Based Testing
Mathew George
2012-11-01
Full Text Available The growing complexities of software and the demand for shorter time to market are two important challenges that face today’s IT industry. These challenges demand the increase of both productivity and quality of software. Model-based testing is a promising technique for meeting these challenges. Traceability modeling is a key issue and challenge in model-based testing. Relationships between the different models will help to navigate from one model to another, and trace back to the respective requirements and the design model when the test fails. In this paper, we present an approach for bridging the gaps between the different models in model-based testing. We propose relation definition markup language (RDML for defining the relationships between models.
Application software development via model based design
Haapala, O. (Olli)
2015-01-01
This thesis was set to study the utilization of the MathWorks’ Simulink® program in model based application software development and its compatibility with the Vacon 100 inverter. The target was to identify all the problems related to everyday usage of this method and create a white paper of how to execute a model based design to create a Vacon 100 compatible system software. Before this thesis was started, there was very little knowledge of the compatibility of this method. However durin...
Model-based internal wave processing
Candy, J.V.; Chambers, D.H.
1995-06-09
A model-based approach is proposed to solve the oceanic internal wave signal processing problem that is based on state-space representations of the normal-mode vertical velocity and plane wave horizontal velocity propagation models. It is shown that these representations can be utilized to spatially propagate the modal (dept) vertical velocity functions given the basic parameters (wave numbers, Brunt-Vaisala frequency profile etc.) developed from the solution of the associated boundary value problem as well as the horizontal velocity components. Based on this framework, investigations are made of model-based solutions to the signal enhancement problem for internal waves.
Model-based testing for embedded systems
Zander, Justyna; Mosterman, Pieter J
2011-01-01
What the experts have to say about Model-Based Testing for Embedded Systems: "This book is exactly what is needed at the exact right time in this fast-growing area. From its beginnings over 10 years ago of deriving tests from UML statecharts, model-based testing has matured into a topic with both breadth and depth. Testing embedded systems is a natural application of MBT, and this book hits the nail exactly on the head. Numerous topics are presented clearly, thoroughly, and concisely in this cutting-edge book. The authors are world-class leading experts in this area and teach us well-used
Model Based Control of Reefer Container Systems
Sørensen, Kresten Kjær
This thesis is concerned with the development of model based control for the Star Cool refrigerated container (reefer) with the objective of reducing energy consumption. This project has been carried out under the Danish Industrial PhD programme and has been financed by Lodam together with the...
What's Missing in Model-Based Teaching
Khan, Samia
2011-01-01
In this study, the author investigated how four science teachers employed model-based teaching (MBT) over a 1-year period. The purpose of the research was to develop a baseline of the fundamental and specific dimensions of MBT that are present and absent in science teaching. Teacher interviews, classroom observations, and pre and post-student…
An acoustical model based monitoring network
Wessels, P.W.; Basten, T.G.H.; Eerden, F.J.M. van der
2010-01-01
In this paper the approach for an acoustical model based monitoring network is demonstrated. This network is capable of reconstructing a noise map, based on the combination of measured sound levels and an acoustic model of the area. By pre-calculating the sound attenuation within the network the noi
Model-based failure detection for cylindrical shells from noisy vibration measurements.
Candy, J V; Fisher, K A; Guidry, B L; Chambers, D H
2014-12-01
Model-based processing is a theoretically sound methodology to address difficult objectives in complex physical problems involving multi-channel sensor measurement systems. It involves the incorporation of analytical models of both physical phenomenology (complex vibrating structures, noisy operating environment, etc.) and the measurement processes (sensor networks and including noise) into the processor to extract the desired information. In this paper, a model-based methodology is developed to accomplish the task of online failure monitoring of a vibrating cylindrical shell externally excited by controlled excitations. A model-based processor is formulated to monitor system performance and detect potential failure conditions. The objective of this paper is to develop a real-time, model-based monitoring scheme for online diagnostics in a representative structural vibrational system based on controlled experimental data. PMID:25480059
Model-based Processing of Microcantilever Sensor Arrays
Tringe, J W; Clague, D S; Candy, J V; Sinensky, A K; Lee, C L; Rudd, R E; Burnham, A K
2005-04-27
We have developed a model-based processor (MBP) for a microcantilever-array sensor to detect target species in solution. We perform a proof-of-concept experiment, fit model parameters to the measured data and use them to develop a Gauss-Markov simulation. We then investigate two cases of interest, averaged deflection data and multi-channel data. For this evaluation we extract model parameters via a model-based estimation, perform a Gauss-Markov simulation, design the optimal MBP and apply it to measured experimental data. The performance of the MBP in the multi-channel case is evaluated by comparison to a ''smoother'' (averager) typically used for microcantilever signal analysis. It is shown that the MBP not only provides a significant gain ({approx} 80dB) in signal-to-noise ratio (SNR), but also consistently outperforms the smoother by 40-60 dB. Finally, we apply the processor to the smoothed experimental data and demonstrate its capability for chemical detection. The MBP performs quite well, apart from a correctable systematic bias error.
Model-based clustered-dot screening
Kim, Sang Ho
2006-01-01
I propose a halftone screen design method based on a human visual system model and the characteristics of the electro-photographic (EP) printer engine. Generally, screen design methods based on human visual models produce dispersed-dot type screens while design methods considering EP printer characteristics generate clustered-dot type screens. In this paper, I propose a cost function balancing the conflicting characteristics of the human visual system and the printer. By minimizing the obtained cost function, I design a model-based clustered-dot screen using a modified direct binary search algorithm. Experimental results demonstrate the superior quality of the model-based clustered-dot screen compared to a conventional clustered-dot screen.
Model based Software Develeopment: Issues & Challenges
basha, N Md Jubair; Rizwanullah, Mohammed
2012-01-01
One of the goals of software design is to model a system in such a way that it is easily understandable. Nowadays the tendency for software development is changing from manual coding to automatic code generation; it is becoming model-based. This is a response to the software crisis, in which the cost of hardware has decreased and conversely the cost of software development has increased sharply. The methodologies that allowed this change are model-based, thus relieving the human from detailed coding. Still there is a long way to achieve this goal, but work is being done worldwide to achieve this objective. This paper presents the drastic changes related to modeling and important challenging issues and techniques that recur in MBSD.
Market Segmentation Using Bayesian Model Based Clustering
Van Hattum, P.
2009-01-01
This dissertation deals with two basic problems in marketing, that are market segmentation, which is the grouping of persons who share common aspects, and market targeting, which is focusing your marketing efforts on one or more attractive market segments. For the grouping of persons who share common aspects a Bayesian model based clustering approach is proposed such that it can be applied to data sets that are specifically used for market segmentation. The cluster algorithm can handle very l...
Memristor model based on fuzzy window function
Abdel-Kader, Rabab Farouk; Abuelenin, Sherif M.
2016-01-01
Memristor (memory-resistor) is the fourth passive circuit element. We introduce a memristor model based on a fuzzy logic window function. Fuzzy models are flexible, which enables the capture of the pinched hysteresis behavior of the memristor. The introduced fuzzy model avoids common problems associated with window-function based memristor models, such as the terminal state problem, and the symmetry issues. The model captures the memristor behavior with a simple rule-base which gives an insig...
Model-based Tomographic Reconstruction Literature Search
Chambers, D H; Lehman, S K
2005-11-30
In the process of preparing a proposal for internal research funding, a literature search was conducted on the subject of model-based tomographic reconstruction (MBTR). The purpose of the search was to ensure that the proposed research would not replicate any previous work. We found that the overwhelming majority of work on MBTR which used parameterized models of the object was theoretical in nature. Only three researchers had applied the technique to actual data. In this note, we summarize the findings of the literature search.
Model-based multiple patterning layout decomposition
Guo, Daifeng; Tian, Haitong; Du, Yuelin; Wong, Martin D. F.
2015-10-01
As one of the most promising next generation lithography technologies, multiple patterning lithography (MPL) plays an important role in the attempts to keep in pace with 10 nm technology node and beyond. With feature size keeps shrinking, it has become impossible to print dense layouts within one single exposure. As a result, MPL such as double patterning lithography (DPL) and triple patterning lithography (TPL) has been widely adopted. There is a large volume of literature on DPL/TPL layout decomposition, and the current approach is to formulate the problem as a classical graph-coloring problem: Layout features (polygons) are represented by vertices in a graph G and there is an edge between two vertices if and only if the distance between the two corresponding features are less than a minimum distance threshold value dmin. The problem is to color the vertices of G using k colors (k = 2 for DPL, k = 3 for TPL) such that no two vertices connected by an edge are given the same color. This is a rule-based approach, which impose a geometric distance as a minimum constraint to simply decompose polygons within the distance into different masks. It is not desired in practice because this criteria cannot completely capture the behavior of the optics. For example, it lacks of sufficient information such as the optical source characteristics and the effects between the polygons outside the minimum distance. To remedy the deficiency, a model-based layout decomposition approach to make the decomposition criteria base on simulation results was first introduced at SPIE 2013.1 However, the algorithm1 is based on simplified assumption on the optical simulation model and therefore its usage on real layouts is limited. Recently AMSL2 also proposed a model-based approach to layout decomposition by iteratively simulating the layout, which requires excessive computational resource and may lead to sub-optimal solutions. The approach2 also potentially generates too many stiches. In this
Model-Based Power Plant Master Control
Boman, Katarina; Thomas, Jean; Funkquist, Jonas
2010-08-15
The main goal of the project has been to evaluate the potential of a coordinated master control for a solid fuel power plant in terms of tracking capability, stability and robustness. The control strategy has been model-based predictive control (MPC) and the plant used in the case study has been the Vattenfall power plant Idbaecken in Nykoeping. A dynamic plant model based on nonlinear physical models was used to imitate the true plant in MATLAB/SIMULINK simulations. The basis for this model was already developed in previous Vattenfall internal projects, along with a simulation model of the existing control implementation with traditional PID controllers. The existing PID control is used as a reference performance, and it has been thoroughly studied and tuned in these previous Vattenfall internal projects. A turbine model was developed with characteristics based on the results of steady-state simulations of the plant using the software EBSILON. Using the derived model as a representative for the actual process, an MPC control strategy was developed using linearization and gain-scheduling. The control signal constraints (rate of change) and constraints on outputs were implemented to comply with plant constraints. After tuning the MPC control parameters, a number of simulation scenarios were performed to compare the MPC strategy with the existing PID control structure. The simulation scenarios also included cases highlighting the robustness properties of the MPC strategy. From the study, the main conclusions are: - The proposed Master MPC controller shows excellent set-point tracking performance even though the plant has strong interactions and non-linearity, and the controls and their rate of change are bounded. - The proposed Master MPC controller is robust, stable in the presence of disturbances and parameter variations. Even though the current study only considered a very small number of the possible disturbances and modelling errors, the considered cases are
Unifying Model-Based and Reactive Programming within a Model-Based Executive
Williams, Brian C.; Gupta, Vineet; Norvig, Peter (Technical Monitor)
1999-01-01
Real-time, model-based, deduction has recently emerged as a vital component in AI's tool box for developing highly autonomous reactive systems. Yet one of the current hurdles towards developing model-based reactive systems is the number of methods simultaneously employed, and their corresponding melange of programming and modeling languages. This paper offers an important step towards unification. We introduce RMPL, a rich modeling language that combines probabilistic, constraint-based modeling with reactive programming constructs, while offering a simple semantics in terms of hidden state Markov processes. We introduce probabilistic, hierarchical constraint automata (PHCA), which allow Markov processes to be expressed in a compact representation that preserves the modularity of RMPL programs. Finally, a model-based executive, called Reactive Burton is described that exploits this compact encoding to perform efficIent simulation, belief state update and control sequence generation.
Trip Generation Model Based on Destination Attractiveness
YAO Liya; GUAN Hongzhi; YAN Hai
2008-01-01
Traditional trip generation forecasting methods use unified average trip generation rates to determine trip generation volumes in various traffic zones without considering the individual characteristics of each traffic zone.Therefore,the results can have significant errors.To reduce the forecasting error produced by uniform trip generation rates for different traffic zones,the behavior of each traveler was studied instead of the characteristics of the traffic zone.This paper gives a method for calculating the trip efficiency and the effect of traffic zones combined with a destination selection model based on disaggregate theory for trip generation.Beijing data is used with the trip generation method to predict trip volumes.The results show that the disaggregate model in this paper is more accurate than the traditional method.An analysis of the factors influencing traveler behavior and destination selection shows that the attractiveness of the traffic zone strongly affects the trip generation volume.
Model Based Control of Refrigeration Systems
Larsen, Lars Finn Sloth
of the supermarket refrigeration systems therefore greatly relies on a human operator to detect and accommodate failures, and to optimize system performance under varying operational condition. Today these functions are maintained by monitoring centres located all over the world. Initiated by the growing need...... for automation of these procedures, that is to incorporate some "intelligence" in the control system, this project was started up. The main emphasis of this work has been on model based methods for system optimizing control in supermarket refrigeration systems. The idea of implementing a system optimizing...... optimizing the steady state operation "set-point optimizing control" and a part optimizing dynamic behaviour of the system "dynamical optimizing control". A novel approach for set-point optimization will be presented. The general idea is to use a prediction of the steady state, for computation of the cost...
Model-Based Clustering of Large Networks
Vu, Duy Quang; Schweinberger, Michael
2012-01-01
We describe a network clustering framework, based on finite mixture models, that can be applied to discrete-valued networks with hundreds of thousands of nodes and billions of edge variables. Relative to other recent model-based clustering work for networks, we introduce a more flexible modeling framework, improve the variational-approximation estimation algorithm, discuss and implement standard error estimation via a parametric bootstrap approach, and apply these methods to much larger datasets than those seen elsewhere in the literature. The more flexible modeling framework is achieved through introducing novel parameterizations of the model, giving varying degrees of parsimony, using exponential family models whose structure may be exploited in various theoretical and algorithmic ways. The algorithms, which we show how to adapt to the more complicated optimization requirements introduced by the constraints imposed by the novel parameterizations we propose, are based on variational generalized EM algorithms...
Internet Supported Model Based Condition Monitoring
A Lewlaski,
2010-04-01
Full Text Available The importance of condition monitoring for preventive and predictive maintenance has increased through the use of system modelling. This modelling is carried out using manufacturer(s information. Data collection using data acquisition cards provides raw data to support system monitoring, especially when used through internet and network facilities, which make it economically available for larger number of users. A model based condition monitoring system which utilises Internet is presented in this paper. The overall software/hardware for this system will be referred to as MBCM portable unit here. It contains a standalone model of system under consideration. The unit is capable of capturing signals directly from the system, savingthem and producing these data in different formats for further analysis. In order to monitor the performance of the investigated system, the MBCM contains an embedded web-server to enable different signals to be monitored and captured locally, over a network, and via internet connection.
Model-based control of networked systems
Garcia, Eloy; Montestruque, Luis A
2014-01-01
This monograph introduces a class of networked control systems (NCS) called model-based networked control systems (MB-NCS) and presents various architectures and control strategies designed to improve the performance of NCS. The overall performance of NCS considers the appropriate use of network resources, particularly network bandwidth, in conjunction with the desired response of the system being controlled. The book begins with a detailed description of the basic MB-NCS architecture that provides stability conditions in terms of state feedback updates . It also covers typical problems in NCS such as network delays, network scheduling, and data quantization, as well as more general control problems such as output feedback control, nonlinear systems stabilization, and tracking control. Key features and topics include: Time-triggered and event-triggered feedback updates Stabilization of uncertain systems subject to time delays, quantization, and extended absence of feedback Optimal control analysis and ...
Model-based vision for space applications
Chaconas, Karen; Nashman, Marilyn; Lumia, Ronald
1992-01-01
This paper describes a method for tracking moving image features by combining spatial and temporal edge information with model based feature information. The algorithm updates the two-dimensional position of object features by correlating predicted model features with current image data. The results of the correlation process are used to compute an updated model. The algorithm makes use of a high temporal sampling rate with respect to spatial changes of the image features and operates in a real-time multiprocessing environment. Preliminary results demonstrate successful tracking for image feature velocities between 1.1 and 4.5 pixels every image frame. This work has applications for docking, assembly, retrieval of floating objects and a host of other space-related tasks.
Sand-Dust Storm Ensemble Forecast Model Based on Rough Set
LU Zhiying; YANG Le; LI Yanying; ZHAO Zhichao
2007-01-01
To improve the accuracy of sand-dust storm forecast system, a sand-dust storm ensemble forecast model based on rough set (RS) is proposed. The feature data are extracted from the historical data sets using the self-organization map (SOM) clustering network and single fields forecast to form the feature values with low dimensions. Then, the unwanted attributes are reduced according to RS to discretize the continuous feature values. Lastly, the minimum decision rules are constructed according to the remainder attributes, namely sand-dust storm ensemble forecast model based on RS is constructed. Results comparison between the proposed model and the back propagation neural network model show that the sand-storm forecast model based on RS has better stability, faster running speed, and its forecasting accuracy ratio is increased from 17.1% to 86.21%.
Model based risk assessment - the CORAS framework
Gran, Bjoern Axel; Fredriksen, Rune; Thunem, Atoosa P-J.
2004-04-15
Traditional risk analysis and assessment is based on failure-oriented models of the system. In contrast to this, model-based risk assessment (MBRA) utilizes success-oriented models describing all intended system aspects, including functional, operational and organizational aspects of the target. The target models are then used as input sources for complementary risk analysis and assessment techniques, as well as a basis for the documentation of the assessment results. The EU-funded CORAS project developed a tool-supported methodology for the application of MBRA in security-critical systems. The methodology has been tested with successful outcome through a series of seven trial within the telemedicine and ecommerce areas. The CORAS project in general and the CORAS application of MBRA in particular have contributed positively to the visibility of model-based risk assessment and thus to the disclosure of several potentials for further exploitation of various aspects within this important research field. In that connection, the CORAS methodology's possibilities for further improvement towards utilization in more complex architectures and also in other application domains such as the nuclear field can be addressed. The latter calls for adapting the framework to address nuclear standards such as IEC 60880 and IEC 61513. For this development we recommend applying a trial driven approach within the nuclear field. The tool supported approach for combining risk analysis and system development also fits well with the HRP proposal for developing an Integrated Design Environment (IDE) providing efficient methods and tools to support control room systems design. (Author)
Active Appearance Model Based Hand Gesture Recognition
无
2005-01-01
This paper addresses the application of hand gesture recognition in monocular image sequences using Active Appearance Model (AAM). For this work, the proposed algorithm is conposed of constructing AAMs and fitting the models to the interest region. In training stage, according to the manual labeled feature points, the relative AAM is constructed and the corresponding average feature is obtained. In recognition stage, the interesting hand gesture region is firstly segmented by skin and movement cues.Secondly, the models are fitted to the image that includes the hand gesture, and the relative features are extracted.Thirdly, the classification is done by comparing the extracted features and average features. 30 different gestures of Chinese sign language are applied for testing the effectiveness of the method. The Experimental results are given indicating good performance of the algorithm.
Model based systems engineering for astronomical projects
Karban, R.; Andolfato, L.; Bristow, P.; Chiozzi, G.; Esselborn, M.; Schilling, M.; Schmid, C.; Sommer, H.; Zamparelli, M.
2014-08-01
Model Based Systems Engineering (MBSE) is an emerging field of systems engineering for which the System Modeling Language (SysML) is a key enabler for descriptive, prescriptive and predictive models. This paper surveys some of the capabilities, expectations and peculiarities of tools-assisted MBSE experienced in real-life astronomical projects. The examples range in depth and scope across a wide spectrum of applications (for example documentation, requirements, analysis, trade studies) and purposes (addressing a particular development need, or accompanying a project throughout many - if not all - its lifecycle phases, fostering reuse and minimizing ambiguity). From the beginnings of the Active Phasing Experiment, through VLT instrumentation, VLTI infrastructure, Telescope Control System for the E-ELT, until Wavefront Control for the E-ELT, we show how stepwise refinements of tools, processes and methods have provided tangible benefits to customary system engineering activities like requirement flow-down, design trade studies, interfaces definition, and validation, by means of a variety of approaches (like Model Checking, Simulation, Model Transformation) and methodologies (like OOSEM, State Analysis)
Model-Based Method for Sensor Validation
Vatan, Farrokh
2012-01-01
Fault detection, diagnosis, and prognosis are essential tasks in the operation of autonomous spacecraft, instruments, and in situ platforms. One of NASA s key mission requirements is robust state estimation. Sensing, using a wide range of sensors and sensor fusion approaches, plays a central role in robust state estimation, and there is a need to diagnose sensor failure as well as component failure. Sensor validation can be considered to be part of the larger effort of improving reliability and safety. The standard methods for solving the sensor validation problem are based on probabilistic analysis of the system, from which the method based on Bayesian networks is most popular. Therefore, these methods can only predict the most probable faulty sensors, which are subject to the initial probabilities defined for the failures. The method developed in this work is based on a model-based approach and provides the faulty sensors (if any), which can be logically inferred from the model of the system and the sensor readings (observations). The method is also more suitable for the systems when it is hard, or even impossible, to find the probability functions of the system. The method starts by a new mathematical description of the problem and develops a very efficient and systematic algorithm for its solution. The method builds on the concepts of analytical redundant relations (ARRs).
[Fast spectral modeling based on Voigt peaks].
Li, Jin-rong; Dai, Lian-kui
2012-03-01
Indirect hard modeling (IHM) is a recently introduced method for quantitative spectral analysis, which was applied to the analysis of nonlinear relation between mixture spectrum and component concentration. In addition, IHM is an effectual technology for the analysis of components of mixture with molecular interactions and strongly overlapping bands. Before the establishment of regression model, IHM needs to model the measured spectrum as a sum of Voigt peaks. The precision of the spectral model has immediate impact on the accuracy of the regression model. A spectrum often includes dozens or even hundreds of Voigt peaks, which mean that spectral modeling is a optimization problem with high dimensionality in fact. So, large operation overhead is needed and the solution would not be numerically unique due to the ill-condition of the optimization problem. An improved spectral modeling method is presented in the present paper, which reduces the dimensionality of optimization problem by determining the overlapped peaks in spectrum. Experimental results show that the spectral modeling based on the new method is more accurate and needs much shorter running time than conventional method. PMID:22582612
Advanced electron crystallography through model-based imaging.
Van Aert, Sandra; De Backer, Annick; Martinez, Gerardo T; den Dekker, Arnold J; Van Dyck, Dirk; Bals, Sara; Van Tendeloo, Gustaaf
2016-01-01
The increasing need for precise determination of the atomic arrangement of non-periodic structures in materials design and the control of nanostructures explains the growing interest in quantitative transmission electron microscopy. The aim is to extract precise and accurate numbers for unknown structure parameters including atomic positions, chemical concentrations and atomic numbers. For this purpose, statistical parameter estimation theory has been shown to provide reliable results. In this theory, observations are considered purely as data planes, from which structure parameters have to be determined using a parametric model describing the images. As such, the positions of atom columns can be measured with a precision of the order of a few picometres, even though the resolution of the electron microscope is still one or two orders of magnitude larger. Moreover, small differences in average atomic number, which cannot be distinguished visually, can be quantified using high-angle annular dark-field scanning transmission electron microscopy images. In addition, this theory allows one to measure compositional changes at interfaces, to count atoms with single-atom sensitivity, and to reconstruct atomic structures in three dimensions. This feature article brings the reader up to date, summarizing the underlying theory and highlighting some of the recent applications of quantitative model-based transmisson electron microscopy. PMID:26870383
Model based control of refrigeration systems
Sloth Larsen, L.F.
2005-11-15
The subject for this Ph.D. thesis is model based control of refrigeration systems. Model based control covers a variety of different types of controls, that incorporates mathematical models. In this thesis the main subject therefore has been restricted to deal with system optimizing control. The optimizing control is divided into two layers, where the system oriented top layers deals with set-point optimizing control and the lower layer deals with dynamical optimizing control in the subsystems. The thesis has two main contributions, i.e. a novel approach for set-point optimization and a novel approach for desynchronization based on dynamical optimization. The focus in the development of the proposed set-point optimizing control has been on deriving a simple and general method, that with ease can be applied on various compositions of the same class of systems, such as refrigeration systems. The method is based on a set of parameter depended static equations describing the considered process. By adapting the parameters to the given process, predict the steady state and computing a steady state gradient of the cost function, the process can be driven continuously towards zero gradient, i.e. the optimum (if the cost function is convex). The method furthermore deals with system constrains by introducing barrier functions, hereby the best possible performance taking the given constrains in to account can be obtained, e.g. under extreme operational conditions. The proposed method has been applied on a test refrigeration system, placed at Aalborg University, for minimization of the energy consumption. Here it was proved that by using general static parameter depended system equations it was possible drive the set-points close to the optimum and thus reduce the power consumption with up to 20%. In the dynamical optimizing layer the idea is to optimize the operation of the subsystem or the groupings of subsystems, that limits the obtainable system performance. In systems
Model-based vision for car following
Schneiderman, Henry; Nashman, Marilyn; Lumia, Ronald
1993-08-01
This paper describes a vision processing algorithm that supports autonomous car following. The algorithm visually tracks the position of a `lead vehicle' from the vantage of a pursuing `chase vehicle.' The algorithm requires a 2-D model of the back of the lead vehicle. This model is composed of line segments corresponding to features that give rise to strong edges. There are seven sequential stages of computation: (1) Extracting edge points; (2) Associating extracted edge points with the model features; (3) Determining the position of each model feature; (4) Determining the model position; (5) Updating the motion model of the object; (6) Predicting the position of the object in next image; (7) Predicting the location of all object features from prediction of object position. All processing is confined to the 2-D image plane. The 2-D model location computed in this processing is used to determine the position of the lead vehicle with respect to a 3-D coordinate frame affixed to the chase vehicle. This algorithm has been used as part of a complete system to drive an autonomous vehicle, a High Mobility Multipurpose Wheeled Vehicle (HMMWV) such that it follows a lead vehicle at speeds up to 35 km/hr. The algorithm runs at an update rate of 15 Hertz and has a worst case computational delay of 128 ms. The algorithm is implemented under the NASA/NBS Standard Reference Model for Telerobotic Control System Architecture (NASREM) and runs on a dedicated vision processing engine and a VME-based multiprocessor system.
Medical Device Integration Model Based on the Internet of Things.
Hao, Aiyu; Wang, Ling
2015-01-01
At present, hospitals in our country have basically established the HIS system, which manages registration, treatment, and charge, among many others, of patients. During treatment, patients need to use medical devices repeatedly to acquire all sorts of inspection data. Currently, the output data of the medical devices are often manually input into information system, which is easy to get wrong or easy to cause mismatches between inspection reports and patients. For some small hospitals of which information construction is still relatively weak, the information generated by the devices is still presented in the form of paper reports. When doctors or patients want to have access to the data at a given time again, they can only look at the paper files. Data integration between medical devices has long been a difficult problem for the medical information system, because the data from medical devices are lack of mandatory unified global standards and have outstanding heterogeneity of devices. In order to protect their own interests, manufacturers use special protocols, etc., thus causing medical decices to still be the "lonely island" of hospital information system. Besides, unfocused application of the data will lead to failure to achieve a reasonable distribution of medical resources. With the deepening of IT construction in hospitals, medical information systems will be bound to develop towards mobile applications, intelligent analysis, and interconnection and interworking, on the premise that there is an effective medical device integration (MDI) technology. To this end, this paper presents a MDI model based on the Internet of Things (IoT). Through abstract classification, this model is able to extract the common characteristics of the devices, resolve the heterogeneous differences between them, and employ a unified protocol to integrate data between devices. And by the IoT technology, it realizes interconnection network of devices and conducts associate matching
Model-based damage evaluation of layered CFRP structures
Munoz, Rafael; Bochud, Nicolas; Rus, Guillermo; Peralta, Laura; Melchor, Juan; Chiachío, Juan; Chiachío, Manuel; Bond, Leonard J.
2015-03-01
An ultrasonic evaluation technique for damage identification of layered CFRP structures is presented. This approach relies on a model-based estimation procedure that combines experimental data and simulation of ultrasonic damage-propagation interactions. The CFPR structure, a [0/90]4s lay-up, has been tested in an immersion through transmission experiment, where a scan has been performed on a damaged specimen. Most ultrasonic techniques in industrial practice consider only a few features of the received signals, namely, time of flight, amplitude, attenuation, frequency contents, and so forth. In this case, once signals are captured, an algorithm is used to reconstruct the complete signal waveform and extract the unknown damage parameters by means of modeling procedures. A linear version of the data processing has been performed, where only Young modulus has been monitored and, in a second nonlinear version, the first order nonlinear coefficient β was incorporated to test the possibility of detection of early damage. The aforementioned physical simulation models are solved by the Transfer Matrix formalism, which has been extended from linear to nonlinear harmonic generation technique. The damage parameter search strategy is based on minimizing the mismatch between the captured and simulated signals in the time domain in an automated way using Genetic Algorithms. Processing all scanned locations, a C-scan of the parameter of each layer can be reconstructed, obtaining the information describing the state of each layer and each interface. Damage can be located and quantified in terms of changes in the selected parameter with a measurable extension. In the case of the nonlinear coefficient of first order, evidence of higher sensitivity to damage than imaging the linearly estimated Young Modulus is provided.
The extractant for extraction and re-extraction of heavy metal ions has been worked out. The extractant consists of ferromagnetic particles suspended in liquid and covered by unsaturated fatty acids. The liquid, unsoluble in other liquids taken part in the process, contains also an organic derivative of phosphoric acid as a complexing agent
GLDAS Land Surface Models based Aridity Indices
Pande, S.; Ghazanfari, S.
2011-12-01
Identification of dryland areas is crucial to guide policy aimed at intervening in water stressed areas and addressing its perennial livelihood or food insecurity. Aridity indices based on spatially relative soil moisture conditions such as NCEP aridity index allow cross comparison of dry conditions between sites. NCEP aridity index is based on the ratio of annual precipitation (supply) to annual potential evaporation (demand). Such an index ignores subannual scale competition between evaporation and drainage functions well as rainfall and temperature regimes. This determines partitioning of annual supply of precipitation into two competing (but met) evaporation and runoff demands. We here introduce aridity indices based on these additional considerations by using soil moisture time series for the past 3 decades from three Land Surface Models (LSM) models and compare it with NCEP index. We analyze global monthly soil moisture time series (385 months) at 1 x 1 degree spatial resolution as modeled by three GLDAS LSMs - VIC, MOSAIC and NOAH. The first eigen vector from Empirical Orthogonal Function (EOF) analysis, as it is the most dominant spatial template of global soil moisture conditions, is extracted. Frequency of nonexceedences of this dominant soil moisture mode for a location by other locations is calculated and is used as our proposed aridity index. An area is indexed drier (relative to other areas in the world) if its frequency of nonexceedence is lower. The EOF analysis reveals that their first eigen vector explains approximately 32%, 43% and 47% of variance explained by first 385 eigen vectors for VIC, MOSAIC and NOAH respectively. The temporal coefficients associated with it for all three LSMS show seasonality with a jump in trend around the year 1999 for NOAH and MOSAIC. The VIC aridity index displays a pattern most closely resembling that of NCEP though all LSM based indices isolate dominant dryland areas. However, all three LSMs identify some parts of
Models-Based Practice: Great White Hope or White Elephant?
Casey, Ashley
2014-01-01
Background: Many critical curriculum theorists in physical education have advocated a model- or models-based approach to teaching in the subject. This paper explores the literature base around models-based practice (MBP) and asks if this multi-models approach to curriculum planning has the potential to be the great white hope of pedagogical change…
Trace-Based Code Generation for Model-Based Testing
Kanstrén, T.; Piel, E.; Gross, H.-G.
2009-01-01
Paper Submitted for review at the Eighth International Conference on Generative Programming and Component Engineering. Model-based testing can be a powerful means to generate test cases for the system under test. However, creating a useful model for model-based testing requires expertise in the (fo
Attenuating wind turbine loads through model based individual pitch control
Thomsen, Sven Creutz; Niemann, Hans Henrik; Poulsen, Niels Kjølstad
2009-01-01
In this paper we consider wind turbine load attenuation through model based control. Asymmetric loads caused by the wind field can be reduced by pitching the blades individually. To this end we investigate the use of stochastic models of the wind which can be included in a model based individual...
Mechanics and model-based control of advanced engineering systems
Irschik, Hans; Krommer, Michael
2014-01-01
Mechanics and Model-Based Control of Advanced Engineering Systems collects 32 contributions presented at the International Workshop on Advanced Dynamics and Model Based Control of Structures and Machines, which took place in St. Petersburg, Russia in July 2012. The workshop continued a series of international workshops, which started with a Japan-Austria Joint Workshop on Mechanics and Model Based Control of Smart Materials and Structures and a Russia-Austria Joint Workshop on Advanced Dynamics and Model Based Control of Structures and Machines. In the present volume, 10 full-length papers based on presentations from Russia, 9 from Austria, 8 from Japan, 3 from Italy, one from Germany and one from Taiwan are included, which represent the state of the art in the field of mechanics and model based control, with particular emphasis on the application of advanced structures and machines.
Model-based recognition of 3-D objects by geometric hashing technique
A model-based object recognition system is developed for recognition of polyhedral objects. The system consists of feature extraction, modelling and matching stages. Linear features are used for object descriptions. Lines are obtained from edges using rotation transform. For modelling and recognition process, geometric hashing method is utilized. Each object is modelled using 2-D views taken from the viewpoints on the viewing sphere. A hidden line elimination algorithm is used to find these views from the wire frame model of the objects. The recognition experiments yielded satisfactory results. (author). 8 refs, 5 figs
A tooth extraction is a procedure to remove a tooth from the gum socket. It is usually done by a general ... gum. If you need a more complex tooth extraction: You will be given sedation so you are ...
A Model-Based Prognostics Approach Applied to Pneumatic Valves
National Aeronautics and Space Administration — Within the area of systems health management, the task of prognostics centers on predicting when components will fail. Model-based prognostics exploits domain...
Multiple Damage Progression Paths in Model-based Prognostics
National Aeronautics and Space Administration — Model-based prognostics approaches employ do- main knowledge about a system, its components, and how they fail through the use of physics-based models. Compo- nent...
A Model-based Prognostics Approach Applied to Pneumatic Valves
National Aeronautics and Space Administration — Within the area of systems health management, the task of prognostics centers on predicting when components will fail. Model-based prognostics exploits domain...
Model-based Prognostics with Fixed-lag Particle Filters
National Aeronautics and Space Administration — Model-based prognostics exploits domain knowl- edge of the system, its components, and how they fail by casting the underlying physical phenom- ena in a...
A method to manage the model base in DSS
孙成双; 李桂君
2004-01-01
How to manage and use models in DSS is a most important subject. Generally, it costs a lot of money and time to develop the model base management system in the development of DSS and most are simple in function or cannot be used efficiently in practice. It is a very effective, applicable, and economical choice to make use of the interfaces of professional computer software to develop a model base management system. This paper presents the method of using MATLAB, a well-known statistics software, as the development platform of a model base management system. The main functional framework of a MATLAB-based model base managementsystem is discussed. Finally, in this paper, its feasible application is illustrated in the field of construction projects.
Probabilistic Model-Based Diagnosis for Electrical Power Systems
National Aeronautics and Space Administration — We present in this article a case study of the probabilistic approach to model-based diagnosis. Here, the diagnosed system is a real-world electrical power system,...
Model-based Prognostics with Concurrent Damage Progression Processes
National Aeronautics and Space Administration — Model-based prognostics approaches rely on physics-based models that describe the behavior of systems and their components. These models must account for the...
A Model-based Avionic Prognostic Reasoner (MAPR)
National Aeronautics and Space Administration — The Model-based Avionic Prognostic Reasoner (MAPR) presented in this paper is an innovative solution for non-intrusively monitoring the state of health (SoH) and...
Model-based design of integrated production systems: a review
Ould Sidi, Mohamed Mahmoud; Lescourret, Francoise
2011-01-01
Pest resistance and water pollution are major issues caused by the excessive use of pesticides in intensive agriculture. The concept of integrated production system (IPS) has been thus designed to solve those issues and also to meet the need for better food quality and production. Methodologies such as agronomic diagnosis-based design, prototyping, and model-based design have been developed. Here we review the model-based design of IPS. We identify tools for the development of comprehensive m...
Model-based clustering using copulas with applications
Kosmidis, Ioannis; Karlis, Dimitris
2014-01-01
The majority of model-based clustering techniques is based on multivariate Normal models and their variants. In this paper copulas are used for the construction of flexible families of models for clustering applications. The use of copulas in model-based clustering offers two direct advantages over current methods: i) the appropriate choice of copulas provides the ability to obtain a range of exotic shapes for the clusters, and ii) the explicit choice of marginal distributions for the cluster...
Model-Based Development of Control Systems for Forestry Cranes
Pedro La Hera; Daniel Ortíz Morales
2015-01-01
Model-based methods are used in industry for prototyping concepts based on mathematical models. With our forest industry partners, we have established a model-based workflow for rapid development of motion control systems for forestry cranes. Applying this working method, we can verify control algorithms, both theoretically and practically. This paper is an example of this workflow and presents four topics related to the application of nonlinear control theory. The first topic presents th...
Model Based Bootstrap Methods for Interval Censored Data
Sen, Bodhisattva; Xu, Gongjun
2013-01-01
We investigate the performance of model based bootstrap methods for constructing point-wise confidence intervals around the survival function with interval censored data. We show that bootstrapping from the nonparametric maximum likelihood estimator of the survival function is inconsistent for both the current status and case 2 interval censoring models. A model based smoothed bootstrap procedure is proposed and shown to be consistent. In addition, simulation studies are conducted to illustra...
Study of Teaching Model based on Cooperative Learning
Jing-qin SU; Fei-xue HUANG
2010-01-01
Cooperative learning is a popular teaching method now in the world. This paper first discusses the teaching model based on cooperative learning, then analyzes the advantages of cooperative learning and at last proposes the steps of carrying out cooperative learning. It is necessary to introduce the teaching model based on cooperative learning into the teaching for training software talents of China.
Key words: Cooperative Learning; Training Model; Teach...
Trace-Based Code Generation for Model-Based Testing
Kanstrén, T.; Piel, E.; Gross, H.-G.
2009-01-01
Paper Submitted for review at the Eighth International Conference on Generative Programming and Component Engineering. Model-based testing can be a powerful means to generate test cases for the system under test. However, creating a useful model for model-based testing requires expertise in the (formal) modeling language of the used tool and the general concept of modeling the system under test for effective test generation. A commonly used modeling notation is to describe the model through a...
Model Based Predictive Control of a Fully Parallel Robot
Vivas, Oscar Andrès; Poignet, Philippe
2003-01-01
This paper deals with an efficient application of a model based predictive control in parallel machines. A receding horizon control strategy based on a simplified dynamic model is implemented. Experimental results are shown for the H4 robot, a fully parallel structure providing 3 degrees of freedom (dof) in translation and 1 dof in rotation. The model based predictive control and the commonly used computed torque control strategies are compared. The tracking performances and the robustness wi...
Fuzzy model-based control of a nuclear reactor
The fuzzy model-based control of a nuclear power reactor is an emerging research topic world-wide. SCK-CEN is dealing with this research in a preliminary stage, including two aspects, namely fuzzy control and fuzzy modelling. The aim is to combine both methodologies in contrast to conventional model-based PID control techniques, and to state advantages of including fuzzy parameters as safety and operator feedback. This paper summarizes the general scheme of this new research project
TRAFFIC FLOW MODEL BASED ON CELLULAR AUTOMATION WITH ADAPTIVE DECELERATION
Shinkarev, A. A.
2016-01-01
This paper describes continuation of the authors’ work in the field of traffic flow mathematical models based on the cellular automata theory. The refactored representation of the multifactorial traffic flow model based on the cellular automata theory is used for a representation of an adaptive deceleration step implementation. The adaptive deceleration step in the case of a leader deceleration allows slowing down smoothly but not instantly. Concepts of the number of time steps without confli...
Model-based Extraction of Input and Organ Functions in Dynamic Medical Imaging
Tichý, Ondřej; Šmídl, Václav; Šámal, M.
Leiden: CRC Press/Balkema, 2013, s. 75-80. ISBN 978-1-138-00081-0. [IV ECCOMAS Thematic Conference on Computational Vision and Medical Image Processing . Funchal (PT), 14.10.2013-16.10.2013] R&D Projects: GA ČR GA13-29225S Institutional support: RVO:67985556 Keywords : dynamic medical imaging * compartment modeling * convolution * blind source separation Subject RIV: BB - Applied Statistics, Operational Research http://library.utia.cas.cz/separaty/2013/AS/tichy-0397761.pdf
Noninvasive fetal ECG (fECG) monitoring has potential applications in diagnosing congenital heart diseases in a timely manner and assisting clinicians to make more appropriate decisions during labor. However, despite advances in signal processing and machine learning techniques, the analysis of fECG signals has still remained in its preliminary stages. In this work, we describe an algorithm to automatically locate QRS complexes in noninvasive fECG signals obtained from a set of four electrodes placed on the mother’s abdomen. The algorithm is based on an iterative decomposition of the maternal and fetal subspaces and filtering of the maternal ECG (mECG) components from the fECG recordings. Once the maternal components are removed, a novel merging technique is applied to merge the signals and detect the fetal QRS (fQRS) complexes. The algorithm was trained and tested on the fECG datasets provided by the PhysioNet/CinC challenge 2013. The final results indicate that the algorithm is able to detect fetal peaks for a variety of signals with different morphologies and strength levels encountered in clinical practice. (paper)
Application of model based predictive control to a solvent extraction plant
British Nuclear Fuels plc. (BNFL) is the most experienced nuclear fuel company in the world, having supplied nuclear fuel cycle services in the UK and overseas for over forty years. BNFL is one of only two companies in the world that is able to offer nuclear fuel manufacture, enrichment, reprocessing and waste management services. In addition to its work for the UK Nuclear Power Programme, BNFL has developed a substantial export business with nuclear power plant operators in Western Europe, Japan and North America, which now accounts for 18% of the annual turnover. BNFL's plants re situated in North West England and Southern Scotland. Nuclear fuel and fuel products are manufactured at Springfields near Preston; uranium enrichment by the centrifuge process is carried out at Capenhurst, near Chester; reprocessing and waste management services are provided at Sellafield, West Cumbria. The Company's headquarters and engineering design facilities are based at Risley, near Warrington. BNFL also owns and operates two (MAGNOX) nuclear power stations-Calder Hall, on the Sellafield site, the Chapelcross, near Dumfries in Southern Scotland
Model-based extraction of input and organ functions in dynamic scintigraphic imaging
Tichý, Ondřej; Šmídl, Václav; Šámal, M.
2016-01-01
Roč. 4, 3-4 (2016), s. 135-145. ISSN 2168-1171 R&D Projects: GA ČR GA13-29225S Institutional support: RVO:67985556 Keywords : blind source separation * convolution * dynamic medical imaging * compartment modelling Subject RIV: BB - Applied Statistics, Operational Research http://library.utia.cas.cz/separaty/2014/AS/tichy-0428540.pdf
A process is described for extracting at least two desired constituents from a mineral, using a liquid reagent which produces the constituents, or compounds thereof, in separable form and independently extracting those constituents, or compounds. The process is especially valuable for the extraction of phosphoric acid and metal values from acidulated phosphate rock, the slurry being contacted with selective extractants for phosphoric acid and metal (e.g. uranium) values. In an example, uranium values are oxidized to uranyl form and extracted using an ion exchange resin. (U.K.)
Reduced model-based decision-making in schizophrenia.
Culbreth, Adam J; Westbrook, Andrew; Daw, Nathaniel D; Botvinick, Matthew; Barch, Deanna M
2016-08-01
Individuals with schizophrenia have a diminished ability to use reward history to adaptively guide behavior. However, tasks traditionally used to assess such deficits often rely on multiple cognitive and neural processes, leaving etiology unresolved. In the current study, we adopted recent computational formalisms of reinforcement learning to distinguish between model-based and model-free decision-making in hopes of specifying mechanisms associated with reinforcement-learning dysfunction in schizophrenia. Under this framework, decision-making is model-free to the extent that it relies solely on prior reward history, and model-based if it relies on prospective information such as motivational state, future consequences, and the likelihood of obtaining various outcomes. Model-based and model-free decision-making was assessed in 33 schizophrenia patients and 30 controls using a 2-stage 2-alternative forced choice task previously demonstrated to discern individual differences in reliance on the 2 forms of reinforcement-learning. We show that, compared with controls, schizophrenia patients demonstrate decreased reliance on model-based decision-making. Further, parameter estimates of model-based behavior correlate positively with IQ and working memory measures, suggesting that model-based deficits seen in schizophrenia may be partially explained by higher-order cognitive deficits. These findings demonstrate specific reinforcement-learning and decision-making deficits and thereby provide valuable insights for understanding disordered behavior in schizophrenia. (PsycINFO Database Record PMID:27175984
Method to determine in rough set model based on connection degree
Li Huaxiong; Zhou Xianzhong; Huang Bing
2009-01-01
An improvement of tolerance relation is proposed in regard to rough set model based on connection degree by which reflexivity of relation can be assured without loss of information. Then, a method to determine optimal identity degree based on relative positive region is proposed so that the identity degree can be computed in an objective method without any preliminary or additional information about data, which is consistent with the notion of objectivity in rough set theory and data mining theory. Subsequently, an algorithm is proposed, and in two examples, the global optimum identity degree is found out. Finally, in regard to optimum connection degree, the method of rules extraction for connection degree rough set model baaed on generalization function is presented by which the rules extracted from a decision table are enumerated.
Image processor of model-based vision system for assembly robots
A special purpose image preprocessor for the visual system of assembly robots has been developed. The main function unit is composed of lookup tables to utilize the advantage of semiconductor memory for large scale integration, high speed and low price. More than one unit may be operated in parallel since it is designed on the standard IEEE 796 bus. The operation time of the preprocessor in line segment extraction is usually 200 ms per 500 segments, though it differs according to the complexity of scene image. The gray-scale visual system supported by the model-based analysis program using the extracted line segments recognizes partially visible or overlapping industrial workpieces, and detects these locations and orientations
Naser Samadi
2013-04-01
Full Text Available In traditional spectrophotometric determination of stability constants of complexation, it is necessary to find a wavelength at which only one of the components has absorbance without any spectroscopic interference of the other reaction components. In the present work, a simple multi-wavelength model-based method has been developed to determine stability constants for complexation reaction regardless of the spectra overlapping of components. Also, pure spectra and concentration profiles of all components are extracted using multi-wavelength model based method. In the present work spectrophotometric titration of several cationic metal ions with new synthetic ligand were studied in order to calculate the formation constant(s. In order to estimate the formation constants a chemometrics method, model based analysis was applied.
Distributed model-based nonlinear sensor fault diagnosis in wireless sensor networks
Lo, Chun; Lynch, Jerome P.; Liu, Mingyan
2016-01-01
Wireless sensors operating in harsh environments have the potential to be error-prone. This paper presents a distributive model-based diagnosis algorithm that identifies nonlinear sensor faults. The diagnosis algorithm has advantages over existing fault diagnosis methods such as centralized model-based and distributive model-free methods. An algorithm is presented for detecting common non-linearity faults without using reference sensors. The study introduces a model-based fault diagnosis framework that is implemented within a pair of wireless sensors. The detection of sensor nonlinearities is shown to be equivalent to solving the largest empty rectangle (LER) problem, given a set of features extracted from an analysis of sensor outputs. A low-complexity algorithm that gives an approximate solution to the LER problem is proposed for embedment in resource constrained wireless sensors. By solving the LER problem, sensors corrupted by non-linearity faults can be isolated and identified. Extensive analysis evaluates the performance of the proposed algorithm through simulation.
Modeling and Model-Based Control of a Three-Way Catalytic Converter
Balenovic, M.
2002-03-25
The subject of the research presented in this thesis was the development of new control strategies for automotive three-way catalytic converters in order to fulfill future ultra-low exhaust emission standards. The goal was to develop a model-based control strategy that can reduce the emissions under highly dynamic operation of the process, i.e.city driving. Also a possible improvement of the catalyst light-off (reduction of the temperature needed for the converter to become operational) has been studied. The main contribution of the thesis is the development of a model-based controller on the basis of information extracted from the first principle modeling of the converter. The three main parts of the research were: development of the rigorous first principle model of the catalytic converter; development of the control-oriented model of the catalytic converter and connecting it with the engine model; development and testing of the novel model-based controller by both simulations and experiments.
Candy, J V; Chambers, D H; Breitfeller, E F; Guidry, B L; Verbeke, J M; Axelrod, M A; Sale, K E; Meyer, A M
2010-03-02
The detection of radioactive contraband is a critical problem is maintaining national security for any country. Photon emissions from threat materials challenge both detection and measurement technologies especially when concealed by various types of shielding complicating the transport physics significantly. This problem becomes especially important when ships are intercepted by U.S. Coast Guard harbor patrols searching for contraband. The development of a sequential model-based processor that captures both the underlying transport physics of gamma-ray emissions including Compton scattering and the measurement of photon energies offers a physics-based approach to attack this challenging problem. The inclusion of a basic radionuclide representation of absorbed/scattered photons at a given energy along with interarrival times is used to extract the physics information available from the noisy measurements portable radiation detection systems used to interdict contraband. It is shown that this physics representation can incorporated scattering physics leading to an 'extended' model-based structure that can be used to develop an effective sequential detection technique. The resulting model-based processor is shown to perform quite well based on data obtained from a controlled experiment.
A Real-Time Model-Based Human Motion Tracking and Analysis for Human-Computer Interface Systems
Chung-Lin Huang
2004-09-01
Full Text Available This paper introduces a real-time model-based human motion tracking and analysis method for human computer interface (HCI. This method tracks and analyzes the human motion from two orthogonal views without using any markers. The motion parameters are estimated by pattern matching between the extracted human silhouette and the human model. First, the human silhouette is extracted and then the body definition parameters (BDPs can be obtained. Second, the body animation parameters (BAPs are estimated by a hierarchical tritree overlapping searching algorithm. To verify the performance of our method, we demonstrate different human posture sequences and use hidden Markov model (HMM for posture recognition testing.
Model-Based Reconstructive Elasticity Imaging Using Ultrasound
Salavat R. Aglyamov
2007-01-01
Full Text Available Elasticity imaging is a reconstructive imaging technique where tissue motion in response to mechanical excitation is measured using modern imaging systems, and the estimated displacements are then used to reconstruct the spatial distribution of Young's modulus. Here we present an ultrasound elasticity imaging method that utilizes the model-based technique for Young's modulus reconstruction. Based on the geometry of the imaged object, only one axial component of the strain tensor is used. The numerical implementation of the method is highly efficient because the reconstruction is based on an analytic solution of the forward elastic problem. The model-based approach is illustrated using two potential clinical applications: differentiation of liver hemangioma and staging of deep venous thrombosis. Overall, these studies demonstrate that model-based reconstructive elasticity imaging can be used in applications where the geometry of the object and the surrounding tissue is somewhat known and certain assumptions about the pathology can be made.
Model Based Mission Assurance: Emerging Opportunities for Robotic Systems
Evans, John W.; DiVenti, Tony
2016-01-01
The emergence of Model Based Systems Engineering (MBSE) in a Model Based Engineering framework has created new opportunities to improve effectiveness and efficiencies across the assurance functions. The MBSE environment supports not only system architecture development, but provides for support of Systems Safety, Reliability and Risk Analysis concurrently in the same framework. Linking to detailed design will further improve assurance capabilities to support failures avoidance and mitigation in flight systems. This also is leading new assurance functions including model assurance and management of uncertainty in the modeling environment. Further, the assurance cases, a structured hierarchal argument or model, are emerging as a basis for supporting a comprehensive viewpoint in which to support Model Based Mission Assurance (MBMA).
When Does Model-Based Control Pay Off?
Kool, Wouter; Cushman, Fiery A; Gershman, Samuel J
2016-08-01
Many accounts of decision making and reinforcement learning posit the existence of two distinct systems that control choice: a fast, automatic system and a slow, deliberative system. Recent research formalizes this distinction by mapping these systems to "model-free" and "model-based" strategies in reinforcement learning. Model-free strategies are computationally cheap, but sometimes inaccurate, because action values can be accessed by inspecting a look-up table constructed through trial-and-error. In contrast, model-based strategies compute action values through planning in a causal model of the environment, which is more accurate but also more cognitively demanding. It is assumed that this trade-off between accuracy and computational demand plays an important role in the arbitration between the two strategies, but we show that the hallmark task for dissociating model-free and model-based strategies, as well as several related variants, do not embody such a trade-off. We describe five factors that reduce the effectiveness of the model-based strategy on these tasks by reducing its accuracy in estimating reward outcomes and decreasing the importance of its choices. Based on these observations, we describe a version of the task that formally and empirically obtains an accuracy-demand trade-off between model-free and model-based strategies. Moreover, we show that human participants spontaneously increase their reliance on model-based control on this task, compared to the original paradigm. Our novel task and our computational analyses may prove important in subsequent empirical investigations of how humans balance accuracy and demand. PMID:27564094
Alarm coding of a model-based display
This paper discusses and illustrates alarm coding of a model based display. The model based display synthesizes the heat engine cycle within a light water reactor. A digital computer uses measured process variables to form an icon of the heat engine cycle. The Rankine Cycle, a heat engine cycle, serves to structure the data in terms of the temperature and entropy properties of water. The iconic display serves as a visual knowledge base of the plant process for the operator, thereby reducing the operator's mental workload in evaluating the process
Towards automatic model based controller design for reconfigurable plants
Michelsen, Axel Gottlieb; Stoustrup, Jakob; Izadi-Zamanabadi, Roozbeh
2008-01-01
This paper introduces model-based Plug and Play Process Control, a novel concept for process control, which allows a model-based control system to be reconfigured when a sensor or an actuator is plugged into a controlled process. The work reported in this paper focuses on composing a monolithic...... model from models of a process to be controlled and the actuators and sensors connected to the process, and propagation of tuning criteria from these sub-models, thereby accommodating automatic controller synthesis using existing methods. The developed method is successfully tested on an industrial case...
Verification and Validation of Model-Based Autonomous Systems
Pecheur, Charles; Koga, Dennis (Technical Monitor)
2001-01-01
This paper presents a three year project (FY99 to FY01) on the verification and validation of model based autonomous systems. The topics include: 1) Project Profile; 2) Model-Based Autonomy; 3) The Livingstone MIR; 4) MPL2SMV; 5) Livingstone to SMV Translation; 6) Symbolic Model Checking; 7) From Livingstone Models to SMV Models; 8) Application In-Situ Propellant Production; 9) Closed-Loop Verification Principle; 10) Livingstone PathFinder (LPF); 11) Publications and Presentations; and 12) Future Directions. This paper is presented in viewgraph form.
On grey relation projection model based on projection pursuit
Wang Shuo; Yang Shanlin; Ma Xijun
2008-01-01
Multidimensional grey relation projection value can be synthesized as one-dimensional projection value by u-sing projection pursuit model.The larger the projection value is,the better the model.Thus,according to the projection value,the best one can be chosen from the model aggregation.Because projection pursuit modeling based on accelera-ting genetic algorithm can simplify the implementation procedure of the projection pursuit technique and overcome its complex calculation as well as the difficulty in implementing its program,a new method can be obtained for choosing the best grey relation projection model based on the projection pursuit technique.
Model based process-product design and analysis
Gani, Rafiqul
This paper gives a perspective on modelling and the important role it has within product-process design and analysis. Different modelling issues related to development and application of systematic model-based solution approaches for product-process design is discussed and the need for a hybrid...... model-based framework is highlighted. This framework should be able to manage knowledge-data, models, and associated methods and tools integrated with design work-flows and data-flows for specific product-process design problems. In particular, the framework needs to manage models of different types...
Learning to Coordinate Efficiently: A Model-based Approach
Brafman, R I; 10.1613/jair.1154
2011-01-01
In common-interest stochastic games all players receive an identical payoff. Players participating in such games must learn to coordinate with each other in order to receive the highest-possible value. A number of reinforcement learning algorithms have been proposed for this problem, and some have been shown to converge to good solutions in the limit. In this paper we show that using very simple model-based algorithms, much better (i.e., polynomial) convergence rates can be attained. Moreover, our model-based algorithms are guaranteed to converge to the optimal value, unlike many of the existing algorithms.
Cognitive control predicts use of model-based reinforcement learning.
Otto, A Ross; Skatova, Anya; Madlon-Kay, Seth; Daw, Nathaniel D
2015-02-01
Accounts of decision-making and its neural substrates have long posited the operation of separate, competing valuation systems in the control of choice behavior. Recent theoretical and experimental work suggest that this classic distinction between behaviorally and neurally dissociable systems for habitual and goal-directed (or more generally, automatic and controlled) choice may arise from two computational strategies for reinforcement learning (RL), called model-free and model-based RL, but the cognitive or computational processes by which one system may dominate over the other in the control of behavior is a matter of ongoing investigation. To elucidate this question, we leverage the theoretical framework of cognitive control, demonstrating that individual differences in utilization of goal-related contextual information--in the service of overcoming habitual, stimulus-driven responses--in established cognitive control paradigms predict model-based behavior in a separate, sequential choice task. The behavioral correspondence between cognitive control and model-based RL compellingly suggests that a common set of processes may underpin the two behaviors. In particular, computational mechanisms originally proposed to underlie controlled behavior may be applicable to understanding the interactions between model-based and model-free choice behavior. PMID:25170791
Product Lifecycle Management Architecture: A Model Based Systems Engineering Analysis.
Noonan, Nicholas James [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)
2015-07-01
This report is an analysis of the Product Lifecycle Management (PLM) program. The analysis is centered on a need statement generated by a Nuclear Weapons (NW) customer. The need statement captured in this report creates an opportunity for the PLM to provide a robust service as a solution. Lifecycles for both the NW and PLM are analyzed using Model Based System Engineering (MBSE).
Nonlinear Model-Based Fault Detection for a Hydraulic Actuator
Van Eykeren, L.; Chu, Q.P.
2011-01-01
This paper presents a model-based fault detection algorithm for a specific fault scenario of the ADDSAFE project. The fault considered is the disconnection of a control surface from its hydraulic actuator. Detecting this type of fault as fast as possible helps to operate an aircraft more cost effect
Finite mixture models and model-based clustering
Volodymyr Melnykov
2010-01-01
Full Text Available Finite mixture models have a long history in statistics, having been used to model population heterogeneity, generalize distributional assumptions, and lately, for providing a convenient yet formal framework for clustering and classification. This paper provides a detailed review into mixture models and model-based clustering. Recent trends as well as open problems in the area are also discussed.
An Approach to Quality Estimation in Model-Based Development
Holmegaard, Jens Peter; Koch, Peter; Ravn, Anders Peter
2004-01-01
We present an approach to estimation of parameters for design space exploration in Model-Based Development, where synthesis of a system is done in two stages. Component qualities like space, execution time or power consumption are defined in a repository by platform dependent values. Connectors are...
A model-based evaluation system of enterprise
Yan Junwei; Ye Yang; Wang Jian
2005-01-01
This paper analyses the architecture of enterprise modeling, proposesindicator selection principles and indicator decomposition methods, examines the approaches to the evaluation of enterprise modeling and designs an evaluation model of AHP. Then a model-based evaluation system of enterprise is presented toeffectively evaluate the business model in the framework of enterprise modeling.
A Stock Pricing Model Based on Arithmetic Brown Motion
YAN Yong-xin; HAN Wen-xiu
2001-01-01
This paper presents a new stock pricing model based on arithmetic Brown motion. The model overcomes the shortcomings of Gordon model completely. With the model investors can estimate the stock value of surplus companies, deficit companies, zero increase companies and bankrupt companies in long term investment or in short term investment.
Impact of Model-Based Teaching on Argumentation Skills
Ogan-Bekiroglu, Feral; Belek, Deniz Eren
2014-01-01
The purpose of this study was to examine effects of model-based teaching on students' argumentation skills. Experimental design guided to the research. The participants of the study were pre-service physics teachers. The argumentative intervention lasted seven weeks. Data for this research were collected via video recordings and written…
Time series model based on global structure of complete genome
Yu, Z G; Anh, Vo
2001-01-01
A time series model based on the global structure of the complete genome is proposed. Three kinds of length sequences of the complete genome are considered. The correlation dimensions and Hurst exponents of the length sequences are calculated. Using these two exponents, some interesting results related to the problem of classification and evolution relationship of bacteria are obtained.
Statistical virtual eye model based on wavefront aberration
Wang, Jie-Mei; Liu, Chun-Ling; Luo, Yi-Ning; Liu, Yi-Guang; Hu, Bing-Jie
2012-01-01
Wavefront aberration affects the quality of retinal image directly. This paper reviews the representation and reconstruction of wavefront aberration, as well as the construction of virtual eye model based on Zernike polynomial coefficients. In addition, the promising prospect of virtual eye model is emphasized.
Dynamics of expert adjustment to model-based forecast
Ph.H.B.F. Franses (Philip Hans); R. Legerstee (Rianne)
2007-01-01
textabstractExperts often add domain knowledge to model-based forecasts while aiming to reduce forecast errors. Indeed, there is some empirical evidence that expert-adjusted forecasts improve forecast quality. However, surprisingly little is known about what experts actually do. Based on a large and
Model Based Fault Detection in a Centrifugal Pump Application
Kallesøe, Carsten; Cocquempot, Vincent; Izadi-Zamanabadi, Roozbeh
2006-01-01
A model based approach for fault detection in a centrifugal pump, driven by an induction motor, is proposed in this paper. The fault detection algorithm is derived using a combination of structural analysis, observer design and Analytical Redundancy Relation (ARR) design. Structural considerations...... the algorithm is capable of detecting four different faults in the mechanical and hydraulic parts of the pump....
Dynamic Chest Image Analysis: Model-Based Perfusion Analysis in Dynamic Pulmonary Imaging
Liang, Jianming; Järvi, Timo; Kiuru, Aaro; Kormano, Martti; Svedström, Erkki
2003-12-01
The "Dynamic Chest Image Analysis" project aims to develop model-based computer analysis and visualization methods for showing focal and general abnormalities of lung ventilation and perfusion based on a sequence of digital chest fluoroscopy frames collected with the dynamic pulmonary imaging technique. We have proposed and evaluated a multiresolutional method with an explicit ventilation model for ventilation analysis. This paper presents a new model-based method for pulmonary perfusion analysis. According to perfusion properties, we first devise a novel mathematical function to form a perfusion model. A simple yet accurate approach is further introduced to extract cardiac systolic and diastolic phases from the heart, so that this cardiac information may be utilized to accelerate the perfusion analysis and improve its sensitivity in detecting pulmonary perfusion abnormalities. This makes perfusion analysis not only fast but also robust in computation; consequently, perfusion analysis becomes computationally feasible without using contrast media. Our clinical case studies with 52 patients show that this technique is effective for pulmonary embolism even without using contrast media, demonstrating consistent correlations with computed tomography (CT) and nuclear medicine (NM) studies. This fluoroscopical examination takes only about 2 seconds for perfusion study with only low radiation dose to patient, involving no preparation, no radioactive isotopes, and no contrast media.
Dynamic Chest Image Analysis: Model-Based Perfusion Analysis in Dynamic Pulmonary Imaging
Kiuru Aaro
2003-01-01
Full Text Available The "Dynamic Chest Image Analysis" project aims to develop model-based computer analysis and visualization methods for showing focal and general abnormalities of lung ventilation and perfusion based on a sequence of digital chest fluoroscopy frames collected with the dynamic pulmonary imaging technique. We have proposed and evaluated a multiresolutional method with an explicit ventilation model for ventilation analysis. This paper presents a new model-based method for pulmonary perfusion analysis. According to perfusion properties, we first devise a novel mathematical function to form a perfusion model. A simple yet accurate approach is further introduced to extract cardiac systolic and diastolic phases from the heart, so that this cardiac information may be utilized to accelerate the perfusion analysis and improve its sensitivity in detecting pulmonary perfusion abnormalities. This makes perfusion analysis not only fast but also robust in computation; consequently, perfusion analysis becomes computationally feasible without using contrast media. Our clinical case studies with 52 patients show that this technique is effective for pulmonary embolism even without using contrast media, demonstrating consistent correlations with computed tomography (CT and nuclear medicine (NM studies. This fluoroscopical examination takes only about 2 seconds for perfusion study with only low radiation dose to patient, involving no preparation, no radioactive isotopes, and no contrast media.
Dynamic chest image analysis: model-based ventilation study with pyramid images
Liang, Jianming; Jaervi, Timo; Kiuru, Aaro J.; Kormano, Martti; Svedstrom, Erkki; Virkki, Raimo
1997-05-01
The aim of the study 'dynamic chest image analysis' is to develop computing analysis and visualization methods for showing focal and general abnormalities of lung ventilation and perfusion based on a sequence of digital chest fluoroscopy frames collected at different phases of the respiratory/cardiac cycles. A multiresolutional method for ventilation study with an explicit ventilation model based on pyramid images is proposed in this paper. The ventilation model is sophisticated enough in coverage of both inhalation and exhalation phases, but also remains simple enough in model realization. This model plays a critical role in extracting accurate, geographic ventilation parameters; while the pyramid helps in understanding ventilation at multiple resolutions and speeding up the convergence process in optimization. A number of patients have been studied with a research prototype produced in MATLAB. The prototype has proven to be useful aid in dynamic pulmonary ventilation study. However, for clinical use, further work must be done in the future.
Dynamic chest image analysis: model-based pulmonary perfusion analysis with pyramid images
Liang, Jianming; Haapanen, Arto; Jaervi, Timo; Kiuru, Aaro J.; Kormano, Martti; Svedstrom, Erkki; Virkki, Raimo
1998-07-01
The aim of the study 'Dynamic Chest Image Analysis' is to develop computer analysis and visualization methods for showing focal and general abnormalities of lung ventilation and perfusion based on a sequence of digital chest fluoroscopy frames collected at different phases of the respiratory/cardiac cycles in a short period of time. We have proposed a framework for ventilation study with an explicit ventilation model based on pyramid images. In this paper, we extend the framework to pulmonary perfusion study. A perfusion model and the truncated pyramid are introduced. The perfusion model aims at extracting accurate, geographic perfusion parameters, and the truncated pyramid helps in understanding perfusion at multiple resolutions and speeding up the convergence process in optimization. Three cases are included to illustrate the experimental results.
A Modified Active Appearance Model Based on an Adaptive Artificial Bee Colony
Mohammed Hasan Abdulameer
2014-01-01
Full Text Available Active appearance model (AAM is one of the most popular model-based approaches that have been extensively used to extract features by highly accurate modeling of human faces under various physical and environmental circumstances. However, in such active appearance model, fitting the model with original image is a challenging task. State of the art shows that optimization method is applicable to resolve this problem. However, another common problem is applying optimization. Hence, in this paper we propose an AAM based face recognition technique, which is capable of resolving the fitting problem of AAM by introducing a new adaptive ABC algorithm. The adaptation increases the efficiency of fitting as against the conventional ABC algorithm. We have used three datasets: CASIA dataset, property 2.5D face dataset, and UBIRIS v1 images dataset in our experiments. The results have revealed that the proposed face recognition technique has performed effectively, in terms of accuracy of face recognition.
Object Detection using a Novel YIQ Model based Image Fusion for UAV Aerial Surveillance
Thillainayagi.R
2014-07-01
Full Text Available Multi-sensor image fusion is an important precondition of realizing target perception for unmanned aerial vehicles (UAVs, and then UAV can execute various given missions. Imaging devices on UAV are used to capture visual scenes of the ground and they are fused to extract the information. Both the imaging devices setup in the UAV and the target in the ground are in dynamic environment. Due to the imperfection of imaging device and instability of the observed scene, captured images often blurred and exhibit unsatisfactory spatial resolution. Hence single sensor does not fulfil the visual surveillance need in daytime. This paper propose the concept of fusing multi sensor aerial images captured by UAV using YIQ colour model based on Laplacian pyramid transform with Principal component analysis technique. The performance of the proposed image fusion scheme is analyzed using the evaluation metrics of Entropy, Mean Square Error (MSE and Peak Signal to Noise Ratio (PSNR with the existing techniques.
Research on the Prediction of VNN Neural Network Traffic Flow Model Based on Chaotic Algorithm
Yin Lisheng
2013-06-01
Full Text Available This paperresearches on the prediction of traffic flow chaotic time series based on VNNTF neural network. First, the traffic flow time series chaotic feature is extracted by chaos theory. Pretreatment for traffic flow time series and the VNNTP neural networks model was build by this. Second, principles of neural network learning algorithm VNNTF is described. Based on chaotic learning algorithm, the neural network traffic Volterra learning algorithm isdesigned for fast learning algorithm. Last, a single-step prediction of traffic flow chaotic time series is researched by VNNTF network model based on chaotic algorithm. The results showed that the VNNTF network model predictive performance is better than the Volterra prediction filter and the BP neural network by the simulation results and root-mean-square value.
Model-Based Development of Control Systems for Forestry Cranes
Pedro La Hera
2015-01-01
Full Text Available Model-based methods are used in industry for prototyping concepts based on mathematical models. With our forest industry partners, we have established a model-based workflow for rapid development of motion control systems for forestry cranes. Applying this working method, we can verify control algorithms, both theoretically and practically. This paper is an example of this workflow and presents four topics related to the application of nonlinear control theory. The first topic presents the system of differential equations describing the motion dynamics. The second topic presents nonlinear control laws formulated according to sliding mode control theory. The third topic presents a procedure for model calibration and control tuning that are a prerequisite to realize experimental tests. The fourth topic presents the results of tests performed on an experimental crane specifically equipped for these tasks. Results of these studies show the advantages and disadvantages of these control algorithms, and they highlight their performance in terms of robustness and smoothness.
Bond graph model-based fault diagnosis of hybrid systems
Borutzky, Wolfgang
2015-01-01
This book presents a bond graph model-based approach to fault diagnosis in mechatronic systems appropriately represented by a hybrid model. The book begins by giving a survey of the fundamentals of fault diagnosis and failure prognosis, then recalls state-of-art developments referring to latest publications, and goes on to discuss various bond graph representations of hybrid system models, equations formulation for switched systems, and simulation of their dynamic behavior. The structured text: • focuses on bond graph model-based fault detection and isolation in hybrid systems; • addresses isolation of multiple parametric faults in hybrid systems; • considers system mode identification; • provides a number of elaborated case studies that consider fault scenarios for switched power electronic systems commonly used in a variety of applications; and • indicates that bond graph modelling can also be used for failure prognosis. In order to facilitate the understanding of fault diagnosis and the presented...
Design Intelligent Model base Online Tuning Methodology for Nonlinear System
Ali Roshanzamir
2014-04-01
Full Text Available In various dynamic parameters systems that need to be training on-line adaptive control methodology is used. In this paper fuzzy model-base adaptive methodology is used to tune the linear Proportional Integral Derivative (PID controller. The main objectives in any systems are; stability, robust and reliability. However PID controller is used in many applications but it has many challenges to control of continuum robot. To solve these problems nonlinear adaptive methodology based on model base fuzzy logic is used. This research is used to reduce or eliminate the PID controller problems based on model reference fuzzy logic theory to control of flexible robot manipulator system and testing of the quality of process control in the simulation environment of MATLAB/SIMULINK Simulator.
3-D model-based tracking for UAV indoor localization.
Teulière, Céline; Marchand, Eric; Eck, Laurent
2015-05-01
This paper proposes a novel model-based tracking approach for 3-D localization. One main difficulty of standard model-based approach lies in the presence of low-level ambiguities between different edges. In this paper, given a 3-D model of the edges of the environment, we derive a multiple hypotheses tracker which retrieves the potential poses of the camera from the observations in the image. We also show how these candidate poses can be integrated into a particle filtering framework to guide the particle set toward the peaks of the distribution. Motivated by the UAV indoor localization problem where GPS signal is not available, we validate the algorithm on real image sequences from UAV flights. PMID:25099967
Model-based decision support in diabetes care.
Salzsieder, E; Vogt, L; Kohnert, K-D; Heinke, P; Augstein, P
2011-05-01
The model-based Karlsburg Diabetes Management System (KADIS®) has been developed as a patient-focused decision-support tool to provide evidence-based advice for physicians in their daily efforts to optimize metabolic control in diabetes care of their patients on an individualized basis. For this purpose, KADIS® was established in terms of a personalized, interactive in silico simulation procedure, implemented into a problem-related diabetes health care network and evaluated under different conditions by conducting open-label mono- and polycentric trials, and a case-control study, and last but not least, by application in routine diabetes outpatient care. The trial outcomes clearly show that the recommendations provided to the physicians by KADIS® lead to significant improvement of metabolic control. This model-based decision-support system provides an excellent tool to effectively guide physicians in personalized decision-making to achieve optimal metabolic control for their patients. PMID:20621384
Fusing Quantitative Requirements Analysis with Model-based Systems Engineering
Cornford, Steven L.; Feather, Martin S.; Heron, Vance A.; Jenkins, J. Steven
2006-01-01
A vision is presented for fusing quantitative requirements analysis with model-based systems engineering. This vision draws upon and combines emergent themes in the engineering milieu. "Requirements engineering" provides means to explicitly represent requirements (both functional and non-functional) as constraints and preferences on acceptable solutions, and emphasizes early-lifecycle review, analysis and verification of design and development plans. "Design by shopping" emphasizes revealing the space of options available from which to choose (without presuming that all selection criteria have previously been elicited), and provides means to make understandable the range of choices and their ramifications. "Model-based engineering" emphasizes the goal of utilizing a formal representation of all aspects of system design, from development through operations, and provides powerful tool suites that support the practical application of these principles. A first step prototype towards this vision is described, embodying the key capabilities. Illustrations, implications, further challenges and opportunities are outlined.
Model-based objects recognition in man-made environments
Martí Bonmatí, Joan; Casals, Alícia
1996-01-01
We describe a model-based objects recognition system which is part of an image interpretation system intended to assist autonomous vehicles navigation. The system is intended to operate in man-made environments. Behavior-based navigation of autonomous vehicles involves the recognition of navigable areas and the potential obstacles. The recognition system integrates color, shape and texture information together with the location of the vanishing point. The recognition process starts from some ...
Multimedia Data Modeling Based on Temporal Logic and XYZ System
MA Huadong; LIU Shenquan
1999-01-01
This paper proposes a new approach to modeling multimedia data. The newapproach is the multimedia data model based on temporal logic and XYZSystem. It supports the formal specifications in a multimedia system.Using this model, we can not only specify information unitsbut also design and script a multimedia title in an unified framework.Based on this model, an interactive multimedia authoring environment hasbeen developed.
Mechatronic Model Based Computed Torque Control of a Parallel Manipulator
Zhiyong Yang; Jiang Wu; Jiangping Mei; Jian Gao; Tian Huang
2008-01-01
With high speed and accuracy the parallel manipulators have wide application in the industry, but there still exist many difficulties in the actual control process because of the time-varying and coupling. Unfortunately, the present-day commercial controlles cannot provide satisfying performance for its single axis linear control only. Therefore, aimed at a novel 2-DOF (Degree of Freedom) parallel manipulator called Diamond 600, a motor-mechanism coupling dynamic model based control scheme em...
Model-based clustering of array CGH data
Shah, Sohrab P.; Cheung, K-John; Johnson, Nathalie A.; Alain, Guillaume; Gascoyne, Randy D.; Horsman, Douglas E.; Ng, Raymond T.; Murphy, Kevin P.
2009-01-01
Motivation: Analysis of array comparative genomic hybridization (aCGH) data for recurrent DNA copy number alterations from a cohort of patients can yield distinct sets of molecular signatures or profiles. This can be due to the presence of heterogeneous cancer subtypes within a supposedly homogeneous population. Results: We propose a novel statistical method for automatically detecting such subtypes or clusters. Our approach is model based: each cluster is defined in terms of a sparse profile...
GENI: A graphical environment for model-based control
A new method to operate machine and beam simulation programs for accelerator control has been developed. Existing methods, although cumbersome, have been used in control systems for commissioning and operation of many machines. We developed GENI, a generalized graphical interface to these programs for model-based control. This ''object-oriented''-like environment is described and some typical applications are presented. 4 refs., 5 figs
Model based traffic congestion detection in optical remote sensing imagery
Palubinskas, Gintautas; Kurz, Franz; Reinartz, Peter
2010-01-01
Purpose A new model based approach for the traffic congestion detection in time series of airborne optical digital camera images is proposed. Methods It is based on the estimation of the average vehicle speed on road segments. The method puts various techniques together: the vehicle detection on road segments by change detection between two images with a short time lag, the usage of a priori information such as road data base, vehicle sizes and road parameters and a si...
SELFORGANIZING ASSEMBLY MODELING BASED ON RELATIONAL CONSTRAINTS
无
2000-01-01
On the research of assembly modeling of mechanical products, current CAD systems can only support the design process of componettoassembly. It is difficult to realize the design process of assemblyto component. The theory of selforganizing assembly modeling based on relational constraints is proposed, which implements the product design of assembly to component commencing with conceptual design and supporting abstract design and sepnice refinement design.
Towards model-based control of Parkinson's disease
Schiff, Steven J.
2010-01-01
Modern model-based control theory has led to transformative improvements in our ability to track the nonlinear dynamics of systems that we observe, and to engineer control systems of unprecedented efficacy. In parallel with these developments, our ability to build computational models to embody our expanding knowledge of the biophysics of neurons and their networks is maturing at a rapid rate. In the treatment of human dynamical disease, our employment of deep brain stimulators for the treatm...
MODEL-BASED MR PARAMETER MAPPING WITH SPARSITY CONSTRAINT
Zhao, Bo; Lam, Fan; Lu, Wenmiao; Liang, Zhi-Pei
2013-01-01
MR parameter mapping (e.g., T1 mapping, T2 mapping, or T2* mapping) is a valuable tool for tissue characterization. However, its practical utility has been limited due to long data acquisition time. This paper addresses this problem with a new model-based parameter mapping method, which utilizes an explicit signal model and imposes a sparsity constraint on the parameter values. The proposed method enables direct estimation of the parameters of interest from highly undersampl...
Normal Cloud Model Based Reputation Quantification in Trusted Networks
Yang Zhi-xiao; Fan Yan-feng
2013-01-01
In order to quantify node reputation in trusted networks, while considering fuzziness and randomness of the concept and adapting to network changes, a Normal Cloud Model based (NCM) approach is proposed. Node reputation cloud is constructed through inverse cloud generator from Service Satisfaction Degrees (SSDs) in a big window N. With cloud generator of the cloud, certainty degree of each SSD in reputation computation window H is generated. It is random but with stable tendency. SSD’s weight...
Model-based testing design for embedded automotive software
Mjeda, Anila; McElligott, Pat; Ryan, Kevin; Thiel, Steffen
2009-01-01
peer-reviewed The ever increasing complexity of embedded automotive software is not matched by the current development and test processes of automotive embedded software and the latter have become the limiting factor. A model-based software development and testing approach has the potential to reduce software development times, to produce executable specifications very early in the process as well as facilitate automatic code generation. Not surprisingly, the above are regarded as hi...
Multiple input support in a model-based interaction framework
Chatty, Stéphane; Lemort, Alexandre; Valès, Stéphane
2007-01-01
Developing for tabletops puts special requirements on interface programming frameworks: managing parallel input, device discovery, device equivalence, and describing combined interactions. We analyse these issues and describe the solutions that were used in IntuiKit, a model- based framework aimed at making the design and development of post-WIMP user interfaces more accessible. Some solutions are simple consequences of the support of multi- modality, while others are more specific to multipl...
Detecting influential observations in a model-based cluster analysis
Bruckers, L.; Molenberghs, G; Verbeke, G; Geys, H.
2016-01-01
Finite mixture models have been used to model population heterogeneity and to relax distributional assumptions. These models are also convenient tools for clustering and classification of complex data such as, for example, repeated-measurements data. The performance of model-based clustering algorithms is sensitive to influential and outlying observations. Methods for identifying outliers in a finite mixture model have been described in the literature. Approaches to identify influential obser...
Model based wind vector field reconstruction from lidar data
Schlipf, David; Rettenmeier, Andreas; Haizmann, Florian; Hofsäß, Martin; Courtney, Mike; Cheng, Po Wen
2012-01-01
In recent years lidar technology found its way into wind energy for resource assessment and control. For both fields of application it is crucial to reconstruct the wind field from the limited information provided by a lidar system. For lidar assisted wind turbine control model based wind field reconstruction is used to obtain signals from wind characteristics such as wind speed, direction and shears in a high temporal resolution. This work shows how these methods can be used for lidar based ...
A NEW DYNAMIC DEFENSE MODEL BASED ON ACTIVE DECEPTION
Gong Jing; Sun Zhixin; Gu Qiang
2009-01-01
Aiming at the traditional passive deception models, this paper constructs a Decoy Platform based on Intelligent Agent (DPIA) to realize dynamic defense. The paper explores a new dynamic defense model based on active deception, introduces its architecture, and expatiates on communication methods and security guarantee in information transference. Simulation results show that the DPIA can attract hacker agility and activity, lead abnormal traffic into it, distribute a large number of attack data, and ensure real network security.
A Multicore Load Balancing Model Based on Java NIO
Yang Wang; Guofeng Qin
2012-01-01
First this paper points out two common problems of utilizing processors under multicore architecture, namely processors waiting for IO operation to finish and load balancing among cores. Then it makes an analysis of the reasons for them. In order to fully exploit multicore processors, this paper proposes a multicore load balancing model based on the Java NIO framework which offers a solution to above problems. This model mainly illustrates a task scheduling algorithm which uses a parallel com...
Tools for model-based security engineering: models vs. code
Jürjens, Jan; Yu, Yijun
2007-01-01
We present tools to support model-based security engineering on both the model and the code level. In the approach supported by these tools, one firstly specifies the security-critical part of the system (e.g. a crypto protocol) using the UML security extension UMLsec. The models are automatically verified for security properties using automated theorem provers. These are implemented within a framework that supports implementing verification routines, based on XMI output of the diagrams from ...
Adaptive model based control for wastewater treatment plants
Niet, de, A.; Vrugt, van de, Noëlle Maria; Korving, Hans; Boucherie, Richard J.; Savic, D.A.; Kapelan, Z.; Butler, D.
2011-01-01
In biological wastewater treatment, nitrogen and phosphorous are removed by activated sludge. The process requires oxygen input via aeration of the activated sludge tank. Aeration is responsible for about 60% of the energy consumption of a treatment plant. Hence optimization of aeration can contribute considerably to the increase of energy-efficiency in wastewater treatment. To this end, we introduce an adaptive model based control strategy for aeration called adaptive WOMBAT. The strategy is...
Current Practices on Model-based Context-aware Adaptation
Genaro Motti, Vivian; Raggett, Dave; Vanderdonckt, Jean; Workshop on Context-Aware Adaptation of Service Front-Ends 2013 CASFE'2013
2013-01-01
The scientific community has already investigated in depth the benefits of combining model-based approaches for implementing context-aware adaptation. As benefits, it can be highlighted: lower development costs, faster time to market, higher usability levels, optimal usage of the resources available and a better user interaction. Although these benefits are claimed, for practitioners it may be not always evident that they actually compensate for the costs of incorporating such practices into ...
Pervasive Computing Location-aware Model Based on Ontology
PU Fang; CAI Hai-bin; CAO Qi-ying; SUN Dao-qing; LI Tong
2008-01-01
In order to integrate heterogeneous location-aware systems into pervasive computing environment, a novel pervasive computing location-aware model based on ontology is presented. A location-aware model ontology (LMO) is constructed. The location-aware model has the capabilities of sharing knowledge, reasoning and adjusting the usage policies of services dynamically through a unified semantic location manner. At last, the work process of our proposed location-aware model is explained by an application scenario.
Variable selection in model-based discriminant analysis
Maugis, Cathy; Celeux, Gilles; Martin-Magniette, Marie-Laure
2010-01-01
A general methodology for selecting predictors for Gaussian generative classification models is presented. The problem is regarded as a model selection problem. Three different roles for each possible predictor are considered: a variable can be a relevant classification predictor or not, and the irrelevant classification variables can be linearly dependent on a part of the relevant predictors or independent variables. This variable selection model was inspired by the model-based clustering mo...
European Climate - Energy Security Nexus. A model based scenario analysis
In this research, we have provided an overview of the climate-security nexus in the European sector through a model based scenario analysis with POLES model. The analysis underline that under stringent climate policies, Europe take advantage of a double dividend in its capacity to develop a new cleaner energy model and in lower vulnerability to potential shocks on the international energy markets. (authors)
A contextual modeling approach for model-based recommender systems
Fernández-Tobías, Ignacio; Campos Soto, Pedro G.; Cantador, Iván; Díez, Fernando
2013-01-01
The final publication is available at Springer via http://dx.doi.org/10.1007/978-3-642-40643-0_5 Proceedings of 15th Conference of the Spanish Association for Artificial Intelligence, CAEPIA 2013, Madrid, Spain, September 17-20, 2013. In this paper we present a contextual modeling approach for model-based recommender systems that integrates and exploits both user preferences and contextual signals in a common vector space. Differently to previous work, we conduct a user study acquiring ...
The Modelery: a model-based software development repository
Couto, Rui; Ribeiro, António Nestor; Campos, J. Creissac
2015-01-01
Purpose – This paper aims to present the Modelery, a platform for collaborative repository to support model-based software development. The Modelery is a Web platform, composed both by a Web page and Web services for interoperability. Design/methodology/approach – By performing a study in the existing platforms, it was possible to achieve a set of issues to tackle. The issues enabled the possibility to define a set of requirements that allowed the authors to design a new platform, a...
Integrating Design Decision Management with Model-based Software Development
Könemann, Patrick; Kindler, Ekkart
2011-01-01
Design decisions are continuously made during the development of software systems and are important artifacts for design documentation. Dedicated decision management systems are often used to capture such design knowledge. Most such systems are, however, separated from the design artifacts of the system. In model-based software development, where design models are used to develop a software system, outcomes of many design decisions have big impact on design models. The realization of design d...
Network Proactive Defense Model Based on Immune Danger Theory
Zhenxing Wang; Liancheng Zhang; Yazhou Kong; Yu Wang
2016-01-01
Recent investigations into proactive network defense have not produced a systematic methodology and structure; in addition, issues including multi-source information fusion and attacking behavior analysis have not been resolved. Borrowing ideas of danger sensing and immune response from danger theory, a proactive network defense model based on danger theory is proposed. This paper defines the signals and antigens in the network environment as well as attacking behavior analysis algorithm, pro...
Model based control of dynamic atomic force microscope
A model-based robust control approach is proposed that significantly improves imaging bandwidth for the dynamic mode atomic force microscopy. A model for cantilever oscillation amplitude and phase dynamics is derived and used for the control design. In particular, the control design is based on a linearized model and robust H∞ control theory. This design yields a significant improvement when compared to the conventional proportional-integral designs and verified by experiments
A cloud model-based approach for water quality assessment.
Wang, Dong; Liu, Dengfeng; Ding, Hao; Singh, Vijay P; Wang, Yuankun; Zeng, Xiankui; Wu, Jichun; Wang, Lachun
2016-07-01
Water quality assessment entails essentially a multi-criteria decision-making process accounting for qualitative and quantitative uncertainties and their transformation. Considering uncertainties of randomness and fuzziness in water quality evaluation, a cloud model-based assessment approach is proposed. The cognitive cloud model, derived from information science, can realize the transformation between qualitative concept and quantitative data, based on probability and statistics and fuzzy set theory. When applying the cloud model to practical assessment, three technical issues are considered before the development of a complete cloud model-based approach: (1) bilateral boundary formula with nonlinear boundary regression for parameter estimation, (2) hybrid entropy-analytic hierarchy process technique for calculation of weights, and (3) mean of repeated simulations for determining the degree of final certainty. The cloud model-based approach is tested by evaluating the eutrophication status of 12 typical lakes and reservoirs in China and comparing with other four methods, which are Scoring Index method, Variable Fuzzy Sets method, Hybrid Fuzzy and Optimal model, and Neural Networks method. The proposed approach yields information concerning membership for each water quality status which leads to the final status. The approach is found to be representative of other alternative methods and accurate. PMID:26995351
A Model-Based Expert System For Digital Systems Design
Wu, J. G.; Ho, W. P. C.; Hu, Y. H.; Yun, D. Y. Y.; Parng, T. M.
1987-05-01
In this paper, we present a model-based expert system for automatic digital systems design. The goal of digital systems design is to generate a workable and efficient design from high level specifications. The formalization of the design process is a necessity for building an efficient automatic CAD system. Our approach combines model-based, heuristic best-first search, and meta-planning techniques from AI to facilitate the design process. The design process is decomposed into three subprocesses. First, the high-level behavioral specifications are translated into sequences of primitive behavioral operations. Next, primitive operations are grouped to form intermediate-level behavioral functions. Finally, structural function modules are selected to implement these functions. Using model-based reasoning on the primitive behavioral operations level extends the solution space considered in design and provides more opportunity for minimization. Heuristic best-first search and meta-planning tech-niques control the decision-making in the latter two subprocesses to optimize the final design. They also facilitate system maintenance by separating design strategy from design knowledge.
Proceedings 7th Workshop on Model-Based Testing
Petrenko, Alexander K; 10.4204/EPTCS.80
2012-01-01
This volume contains the proceedings of the Seventh Workshop on Model-Based Testing (MBT 2012), which was held on 25 March, 2012 in Tallinn, Estonia, as a satellite event of the European Joint Conferences on Theory and Practice of Software, ETAPS 2012. The workshop is devoted to model-based testing of both software and hardware. Model-based testing uses models describing the required behavior of the system under consideration to guide such efforts as test selection and test results evaluation. Testing validates the real system behavior against models and checks that the implementation conforms to them, but is capable also to find errors in the models themselves. The first MBT workshop was held in 2004, in Barcelona. At that time MBT already had become a hot topic, but the MBT workshop was the first event devoted mostly to this topic. Since that time the area has generated enormous scientific interest, and today there are several specialized workshops and more broad conferences on software and hardware design ...
GPU-accelerated 3-D model-based tracking
Model-based approaches to tracking the pose of a 3-D object in video are effective but computationally demanding. While statistical estimation techniques, such as the particle filter, are often employed to minimize the search space, real-time performance remains unachievable on current generation CPUs. Recent advances in graphics processing units (GPUs) have brought massively parallel computational power to the desktop environment and powerful developer tools, such as NVIDIA Compute Unified Device Architecture (CUDA), have provided programmers with a mechanism to exploit it. NVIDIA GPUs' single-instruction multiple-thread (SIMT) programming model is well-suited to many computer vision tasks, particularly model-based tracking, which requires several hundred 3-D model poses to be dynamically configured, rendered, and evaluated against each frame in the video sequence. Using 6 degree-of-freedom (DOF) rigid hand tracking as an example application, this work harnesses consumer-grade GPUs to achieve real-time, 3-D model-based, markerless object tracking in monocular video.
Maagaard, Mathilde; Oestergaard, Jeanett; Johansen, Marianne;
2012-01-01
physicians with daily work in the obstetric field were tested. Methods. The Delphi method was used for development of the scale. In a simulated vacuum extraction scenario, first-year residents and obstetric chief physicians were rated using the developed OSATS scale for vacuum extraction to test construct...... validity of the scale. Main outcome measures. Consensus for the content of the scale. To test the scale of Cronbach's alpha, interclass correlation and differential item function was calculated in the prospective study. Results. 89% completed the first and 61% completed the second Delphi round. Hereafter...
Effective model based on QCD with gluon condensate
Kohyama, Hiroaki
2016-01-01
We construct the effective model based on QCD with gluon condensate. Under the assumption that the gluons are condensed with the sharp momentum peak in the momentum space, we formulate the effective field theory incorporating both the gluon condensate and the chiral condensate, then study the phase transition on temperature and chemical potential plane with respect to two condensates. We find that the condensates decrease with increasing temperature, which is reliable tendency on the condensate being consistent with the argument of the asymptotic behavior.
Method for Real-Time Model Based Structural Anomaly Detection
Smith, Timothy A. (Inventor); Urnes, James M., Sr. (Inventor); Reichenbach, Eric Y. (Inventor)
2015-01-01
A system and methods for real-time model based vehicle structural anomaly detection are disclosed. A real-time measurement corresponding to a location on a vehicle structure during an operation of the vehicle is received, and the real-time measurement is compared to expected operation data for the location to provide a modeling error signal. A statistical significance of the modeling error signal to provide an error significance is calculated, and a persistence of the error significance is determined. A structural anomaly is indicated, if the persistence exceeds a persistence threshold value.
Non-frontal model based approach to forensic face recognition
Dutta, Abhishek; Veldhuis, Raymond; Spreeuwers, Luuk
2012-01-01
In this paper, we propose a non-frontal model based approach which ensures that a face recognition system always gets to compare images having similar view (or pose). This requires a virtual suspect reference set that consists of non-frontal suspect images having pose similar to the surveillance view trace image. We apply the 3D model reconstruction followed by image synthesis approach to the frontal view mug shot images in the suspect reference set in order to create such a virtual suspect r...
Model-based control versus classical control for parallel robots
Belda, Květoslav
Praha : ÚTIA AV ČR, 2004 - ( And rýsek, J.; Kárný, M.; Kracík, J.), s. 1-9 [Computer-Intensive Methods in Control and Data Processing. CMP'04: Towards Electronic Democracy. Praha (CZ), 12.05.2004-14.05.2004] R&D Projects: GA ČR GA101/03/0620 Institutional research plan: CEZ:AV0Z1075907 Keywords : model based control * classical PSD control * global and local levels of control Subject RIV: BC - Control Systems Theory http://library.utia.cas.cz/separaty/historie/belda-0106263.pdf
Monocular model-based 3D tracking of rigid objects
Lepetit, Vincent
2014-01-01
Many applications require tracking complex 3D objects. These include visual serving of robotic arms on specific target objects, Augmented Reality systems that require real time registration of the object to be augmented, and head tracking systems that sophisticated interfaces can use. Computer vision offers solutions that are cheap, practical and non-invasive. ""Monocular Model-Based 3D Tracking of Rigid Objects"" reviews the different techniques and approaches that have been developed by industry and research. First, important mathematical tools are introduced: camera representation, robust e
Logistics Enterprise Evaluation Model Based On Fuzzy Clustering Analysis
Fu, Pei-hua; Yin, Hong-bo
In this thesis, we introduced an evaluation model based on fuzzy cluster algorithm of logistics enterprises. First of all,we present the evaluation index system which contains basic information, management level, technical strength, transport capacity,informatization level, market competition and customer service. We decided the index weight according to the grades, and evaluated integrate ability of the logistics enterprises using fuzzy cluster analysis method. In this thesis, we introduced the system evaluation module and cluster analysis module in detail and described how we achieved these two modules. At last, we gave the result of the system.
Model-Based Integration and Interpretation of Data
Petersen, Johannes
2004-01-01
Data integration and interpretation plays a crucial role in supervisory control. The paper defines a set of generic inference steps for the data integration and interpretation process based on a three-layer model of system representations. The three-layer model is used to clarify the combination...... of constraint and object-centered representations of the work domain throwing new light on the basic principles underlying the data integration and interpretation process of Rasmussen's abstraction hierarchy as well as other model-based approaches combining constraint and object-centered representations. Based...
Model-based analysis and simulation of regenerative heat wheel
Wu, Zhuang; Melnik, Roderick V. N.; Borup, F.
2006-01-01
The rotary regenerator (also called the heat wheel) is an important component of energy intensive sectors, which is used in many heat recovery systems. In this paper, a model-based analysis of a rotary regenerator is carried out with a major emphasis given to the development and implementation of...... mathematical models for the thermal analysis of the fluid and wheel matrix. The effect of heat conduction in the direction of the fluid flow is taken into account and the influence of variations in rotating speed of the wheel as well as other characteristics (ambient temperature, airflow and geometric size) on...
Model-Based GUI Testing Using Uppaal at Novo Nordisk
H. Hjort, Ulrik; Rasmussen, Jacob Illum; Larsen, Kim Guldstrand;
2009-01-01
test suite satisfying some testing criterion, such as edge or state coverage, and converts the individual test case into a scripting language that can be automatically executed against the target. The tool has significantly reduced the time required for test construction and generation, and reduced the......This paper details a collaboration between Aalborg University and Novo Nordiskin developing an automatic model-based test generation tool for system testing of the graphical user interface of a medical device on an embedded platform. The tool takes as input an UML Statemachine model and generates a...... number of test scripts while increasing the coverage....
Model-based acoustic remote sensing of seafloor characteristics
De, Ch.; Chakraborty, B.
spectrum strength w 2 are different at 33 and 210 kHz. Because the interface roughness is modeled (based on the assumption of isotropic Gaussian distribution of surface relief) by a single power law relief energy, the values of the roughness spectrum... characterized by coarse sediments has less-steep decay (i.e., lower value of γ 2 ) in the power–law relationship [25]. One of the possibilities for a power spectrum to have less-steep decay (i.e., less-steep slope of the regression line) is that the intercept...
A model-based multisensor data fusion knowledge management approach
Straub, Jeremy
2014-06-01
A variety of approaches exist for combining data from multiple sensors. The model-based approach combines data based on its support for or refutation of elements of the model which in turn can be used to evaluate an experimental thesis. This paper presents a collection of algorithms for mapping various types of sensor data onto a thesis-based model and evaluating the truth or falsity of the thesis, based on the model. The use of this approach for autonomously arriving at findings and for prioritizing data are considered. Techniques for updating the model (instead of arriving at a true/false assertion) are also discussed.
Line impedance estimation using model based identification technique
Ciobotaru, Mihai; Agelidis, Vassilios; Teodorescu, Remus
into the operation of the grid-connected power converters. This paper describes a quasi passive method for estimating the line impedance of the distribution electricity network. The method uses the model based identification technique to obtain the resistive and inductive parts of the line impedance....... The quasi-passive behaviour of the proposed method comes from the combination of the non intrusive behaviour of the passive methods with a better accuracy of the active methods. The simulation results reveal the good accuracy of the proposed method....
Model-based automated testing of critical PLC programs.
Fernández Adiego, B; Tournier, J-C; González Suárez, V M; Bliudze, S
2014-01-01
Testing of critical PLC (Programmable Logic Controller) programs remains a challenging task for control system engineers as it can rarely be automated. This paper proposes a model based approach which uses the BIP (Behavior, Interactions and Priorities) framework to perform automated testing of PLC programs developed with the UNICOS (UNified Industrial COntrol System) framework. This paper defines the translation procedure and rules from UNICOS to BIP which can be fully automated in order to hide the complexity of the underlying model from the control engineers. The approach is illustrated and validated through the study of a water treatment process.
Model-Based Thermal Management Functions for Aircraft Systems
Schlabe, Daniel; Lienig, Jens
2014-01-01
This paper describes a novel Thermal Management Function (TMF) and its design process developed in the framework of the Clean Sky project. This TMF is capable of calculating optimized control signals in real-time for thermal management systems by using model-based system knowledge. This can be either a physical model of the system or a data record generated from this model. The TMF provides control signals to the air and vapor cycle which are possible sources of cooling power, as well as load...
A Multiple Model Approach to Modeling Based on LPF Algorithm
无
2001-01-01
Input-output data fitting methods are often used for unknown-structure nonlinear system modeling. Based on model-on-demand tactics, a multiple model approach to modeling for nonlinear systems is presented. The basic idea is to find out, from vast historical system input-output data sets, some data sets matching with the current working point, then to develop a local model using Local Polynomial Fitting (LPF) algorithm. With the change of working points, multiple local models are built, which realize the exact modeling for the global system. By comparing to other methods, the simulation results show good performance for its simple, effective and reliable estimation.``
An Industrial Model Based Disturbance Feedback Control Scheme
Kawai, Fukiko; Nakazawa, Chikashi; Vinther, Kasper;
2014-01-01
This paper presents a model based disturbance feedback control scheme. Industrial process systems have been traditionally controlled by using relay and PID controller. However these controllers are affected by disturbances and model errors and these effects degrade control performance. The authors...... propose a new control method that can decrease the negative impact of disturbance and model errors. The control method is motivated by industrial practice by Fuji Electric. Simulation tests are examined with a conventional PID controller and the disturbance feedback control. The simulation results...
Construct Method of Predicting Satisfaction Model Based on Technical Characteristics
YANG Xiao-an; DENG Qian; SUN Guan-long; ZHANG Wei-she
2011-01-01
In order to construct objective relatively mapping relationship model between customer requirements and product technical characteristics, a novel approach based on customer satisfactions information digging from case products and satisfaction information of expert technical characteristics was put forward in this paper. Technical characteristics evaluation values were expressed by rough number, and technical characteristics target sequence was determined on the basis of efficiency, cost type and middle type in this method. Use each calculated satisfactions of customers and technical characteristics as input and output elements to construct BP network model. And we use MATLAB software to simulate this BP network model based on the case of electric bicycles.
Model-based Control of a Bottom Fired Marine Boiler
Solberg, Brian; Karstensen, Claus M. S.; Andersen, Palle;
This paper focuses on applying model based MIMO control to minimize variations in water level for a specific boiler type. A first principles model is put up. The model is linearized and an LQG controller is designed. Furthermore the benefit of using a steam °ow measurement is compared to a strategy...... relying on estimates of the disturbance. Preliminary tests at the boiler system show that the designed controller is able to control the boiler process. Furthermore it can be concluded that relying on estimates of the steam flow in the control strategy does not decrease the controller performance...
Model-based Control of a Bottom Fired Marine Boiler
Solberg, Brian; Karstensen, Claus M. S.; Andersen, Palle;
2005-01-01
This paper focuses on applying model based MIMO control to minimize variations in water level for a specific boiler type. A first principles model is put up. The model is linearized and an LQG controller is designed. Furthermore the benefit of using a steam °ow measurement is compared to a strategy...... relying on estimates of the disturbance. Preliminary tests at the boiler system show that the designed controller is able to control the boiler process. Furthermore it can be concluded that relying on estimates of the steam flow in the control strategy does not decrease the controller performance...
Collaborative work model based on peer-to-peer network
JIANG Jian-zhong; FU Li; ZHANG Xuan-peng; XU Chuan-yun
2007-01-01
In this paper, we incorporated peer-to-peer (P2P) concept with agent technology and put forward a collaborative work model based on peer-to-peer network (P2PCWM) after investigating into business demands of modern enterprises and problems prevailing in mainstream collaborative work systems based on central server. Theoretically, the P2PCWM can effectively overcome the problems in a conventional system with a central server and meet the practical demands of modern businesses. It is distinguished from other systems by its features of equality, openness, promptness, fairness, expandability and convenience.
Model-based Control of a Bottom Fired Marine Boiler
Solberg, Brian; Karstensen, Claus M. S.; Andersen, Palle; Pedersen, Tom Søndergård; Hvistendahl, Poul U.
2005-01-01
This paper focuses on applying model based MIMO control to minimize variations in water level for a specific boiler type. A first principles model is put up. The model is linearized and an LQG controller is designed. Furthermore the benefit of using a steam °ow measurement is compared to a strategy relying on estimates of the disturbance. Preliminary tests at the boiler system show that the designed controller is able to control the boiler process. Furthermore it can be concluded that relying...
Model-based engineering for medical-device software.
Ray, Arnab; Jetley, Raoul; Jones, Paul L; Zhang, Yi
2010-01-01
This paper demonstrates the benefits of adopting model-based design techniques for engineering medical device software. By using a patient-controlled analgesic (PCA) infusion pump as a candidate medical device, the authors show how using models to capture design information allows for i) fast and efficient construction of executable device prototypes ii) creation of a standard, reusable baseline software architecture for a particular device family, iii) formal verification of the design against safety requirements, and iv) creation of a safety framework that reduces verification costs for future versions of the device software. 1. PMID:21142522
Numerical Analysis of Modeling Based on Improved Elman Neural Network
Shao Jie; Wang Li; Zhao WeiSong; Zhong YaQin; Reza Malekian
2014-01-01
A modeling based on the improved Elman neural network (IENN) is proposed to analyze the nonlinear circuits with the memory effect. The hidden layer neurons are activated by a group of Chebyshev orthogonal basis functions instead of sigmoid functions in this model. The error curves of the sum of squared error (SSE) varying with the number of hidden neurons and the iteration step are studied to determine the number of the hidden layer neurons. Simulation results of the half-bridge class-D power...
Adaptive continuous hierarchical model-based decision making
Dedecius, Kamil; Ettler, P.
Portugalsko: SciTePress – Science and Technology Publications, 2011, s. 284-289. ISBN 978-989-8425-74-4. [8th International Conference on Informatics in Control, Automation and Robotics (ICINCO). Noordwijkerhout (NL), 27.07.2011-31.07.2011] R&D Projects: GA MŠk(CZ) 7D09008; GA MŠk 1M0572 Institutional research plan: CEZ:AV0Z10750506 Keywords : Bayesian modelling * Hierarchical model * Parameter estimation Subject RIV: BB - Applied Statistics, Operational Research http://library.utia.cas.cz/separaty/2011/AS/dedecius-adaptive continuous hierarchical model-based decision making.pdf
Structured model-based control of redundant parallel robot kinematics
Belda, Květoslav; Píša, P.; Böhm, Josef; Valášek, M.
Chemnitz: Verlag Wissenschaftliche Scripten, 2004 - (Neugebauer, R.), s. 701-705 ISBN 3-937524-05-3. [Chemnitz Parallel Kinematics Seminar /4./. Chemnitz (DE), 20.04.2004-21.04.2004] R&D Projects: GA ČR GA101/03/0620; GA ČR GA102/02/0204 Institutional research plan: CEZ:AV0Z1075907 Keywords : structuring of model-based control * genetic distance * reduntancy Subject RIV: BC - Control Systems Theory http://library.utia.cas.cz/separaty/historie/belda-0106228.pdf
Model-Based Building Detection from Low-Cost Optical Sensors Onboard Unmanned Aerial Vehicles
Karantzalos, K.; Koutsourakis, P.; Kalisperakis, I.; Grammatikopoulos, L.
2015-08-01
The automated and cost-effective building detection in ultra high spatial resolution is of major importance for various engineering and smart city applications. To this end, in this paper, a model-based building detection technique has been developed able to extract and reconstruct buildings from UAV aerial imagery and low-cost imaging sensors. In particular, the developed approach through advanced structure from motion, bundle adjustment and dense image matching computes a DSM and a true orthomosaic from the numerous GoPro images which are characterised by important geometric distortions and fish-eye effect. An unsupervised multi-region, graphcut segmentation and a rule-based classification is responsible for delivering the initial multi-class classification map. The DTM is then calculated based on inpaininting and mathematical morphology process. A data fusion process between the detected building from the DSM/DTM and the classification map feeds a grammar-based building reconstruction and scene building are extracted and reconstructed. Preliminary experimental results appear quite promising with the quantitative evaluation indicating detection rates at object level of 88% regarding the correctness and above 75% regarding the detection completeness.
Saura Barreda, Juan J.; Habib, Kudama A.; Ferrer, C.; Damra, M. S.; Cervera González, Iván; Giménez Torres, Enrique; Cabedo Mas, Luis
2008-01-01
En este trabajo se ha estudiado, las fases, las propiedades mecánicas y la resistencia al desgaste abrasivo de recubrimientos cerámicos alumina/titania proyectados por el proceso de oxifuel (spray llama). La proporción de titania tiene una fuerte influencia sobre la porosidad de los recubrimientos, habiéndose observado una disminución casi-lineal de la porosidad con el incremento de titania. Las fases cristalinas que resultan después de la proyección han variado según la naturaleza del polvo ...
Lin, Y; Al-Zuhairy, S.; Pronk, M.; M. C. M. van Loosdrecht
2015-01-01
In a prior art reactor set up dense aggregates of microorganisms are formed, typically in or embedded in an extracellular matrix. Such may relate to granules, to sphere like entities having a higher viscosity than water, globules, a biofilm, etc. The dense aggregates comprise extracellular polymeric substances, or biopolymers, in particular linear polysaccharides, The present invention is in the field of extraction of a biopolymer from a granular sludge, a biopolymer obtained by said method, ...
A probabilistic graphical model based stochastic input model construction
Model reduction techniques have been widely used in modeling of high-dimensional stochastic input in uncertainty quantification tasks. However, the probabilistic modeling of random variables projected into reduced-order spaces presents a number of computational challenges. Due to the curse of dimensionality, the underlying dependence relationships between these random variables are difficult to capture. In this work, a probabilistic graphical model based approach is employed to learn the dependence by running a number of conditional independence tests using observation data. Thus a probabilistic model of the joint PDF is obtained and the PDF is factorized into a set of conditional distributions based on the dependence structure of the variables. The estimation of the joint PDF from data is then transformed to estimating conditional distributions under reduced dimensions. To improve the computational efficiency, a polynomial chaos expansion is further applied to represent the random field in terms of a set of standard random variables. This technique is combined with both linear and nonlinear model reduction methods. Numerical examples are presented to demonstrate the accuracy and efficiency of the probabilistic graphical model based stochastic input models. - Highlights: • Data-driven stochastic input models without the assumption of independence of the reduced random variables. • The problem is transformed to a Bayesian network structure learning problem. • Examples are given in flows in random media
Formal model based methodology for developing software for nuclear applications
The approach used in model based design is to build the model of the system in graphical/textual language. In older model based design approach, the correctness of the model is usually established by simulation. Simulation which is analogous to testing, cannot guarantee that the design meets the system requirements under all possible scenarios. This is however possible if the modeling language is based on formal semantics so that the developed model can be subjected to formal verification of properties based on specification. The verified model can then be translated into an implementation through reliable/verified code generator thereby reducing the necessity of low level testing. Such a methodology is admissible as per guidelines of IEC60880 standard applicable to software used in computer based systems performing category A functions in nuclear power plant and would also be acceptable for category B functions. In this article, the experience in implementation and formal verification of important controllers used in the process control system of a nuclear reactor. We have used The SCADE (Safety Critical System Analysis and Design Environment) environment to model the controllers. The modeling language used in SCADE is based on the synchronous dataflow model of computation. A set of safety properties has been verified using formal verification technique
Model-Based Testing: The New Revolution in Software Testing
Hitesh KUMAR SHARMA
2014-05-01
Full Text Available The efforts spent on testing are enormous due to the continuing quest for better software quality, and the ever growing complexity of software systems. The situation is aggravated by the fact that the complexity of testing tends to grow faster than the complexity of the systems being tested, in the worst case even exponentially. Whereas development and construction methods for software allow the building of ever larger and more complex systems, there is a real danger that testing methods cannot keep pace with construction, hence these new systems cannot be sufficiently fast and thoroughly be tested. This may seriously hamper the development of future generations of software systems. One of the new technologies to meet the challenges imposed on software testing is model-based testing. Models can be utilized in many ways throughout the product life-cycle, including: improved quality of specifications, code generation, reliability analysis, and test generation. This paper will focus on the testing benefits from MBT methods and review some of the historical challenges that prevented model based testing and we also try to present the solutions that can overcome these challenges.
Model-based design of adaptive embedded systems
Hamberg, Roelof; Reckers, Frans; Verriet, Jacques
2013-01-01
Today’s embedded systems have to operate in a wide variety of dynamically changing environmental circumstances. Adaptivity, the ability of a system to autonomously adapt itself, is a means to optimise a system’s behaviour to accommodate changes in its environment. It involves making in-product trade-offs between system qualities at system level. The main challenge in the development of adaptive systems is keeping control of the intrinsic complexity of such systems while working with multi-disciplinary teams to create different parts of the system. Model-Based Development of Adaptive Embedded Systems focuses on the development of adaptive embedded systems both from an architectural and methodological point of view. It describes architectural solution patterns for adaptive systems and state-of-the-art model-based methods and techniques to support adaptive system development. In particular, the book describes the outcome of the Octopus project, a cooperation of a multi-disciplinary team of academic and indus...
Sequential Bayesian Detection: A Model-Based Approach
Candy, J V
2008-12-08
Sequential detection theory has been known for a long time evolving in the late 1940's by Wald and followed by Middleton's classic exposition in the 1960's coupled with the concurrent enabling technology of digital computer systems and the development of sequential processors. Its development, when coupled to modern sequential model-based processors, offers a reasonable way to attack physics-based problems. In this chapter, the fundamentals of the sequential detection are reviewed from the Neyman-Pearson theoretical perspective and formulated for both linear and nonlinear (approximate) Gauss-Markov, state-space representations. We review the development of modern sequential detectors and incorporate the sequential model-based processors as an integral part of their solution. Motivated by a wealth of physics-based detection problems, we show how both linear and nonlinear processors can seamlessly be embedded into the sequential detection framework to provide a powerful approach to solving non-stationary detection problems.
Qualitative-Modeling-Based Silicon Neurons and Their Networks
Kohno, Takashi; Sekikawa, Munehisa; Li, Jing; Nanami, Takuya; Aihara, Kazuyuki
2016-01-01
The ionic conductance models of neuronal cells can finely reproduce a wide variety of complex neuronal activities. However, the complexity of these models has prompted the development of qualitative neuron models. They are described by differential equations with a reduced number of variables and their low-dimensional polynomials, which retain the core mathematical structures. Such simple models form the foundation of a bottom-up approach in computational and theoretical neuroscience. We proposed a qualitative-modeling-based approach for designing silicon neuron circuits, in which the mathematical structures in the polynomial-based qualitative models are reproduced by differential equations with silicon-native expressions. This approach can realize low-power-consuming circuits that can be configured to realize various classes of neuronal cells. In this article, our qualitative-modeling-based silicon neuron circuits for analog and digital implementations are quickly reviewed. One of our CMOS analog silicon neuron circuits can realize a variety of neuronal activities with a power consumption less than 72 nW. The square-wave bursting mode of this circuit is explained. Another circuit can realize Class I and II neuronal activities with about 3 nW. Our digital silicon neuron circuit can also realize these classes. An auto-associative memory realized on an all-to-all connected network of these silicon neurons is also reviewed, in which the neuron class plays important roles in its performance. PMID:27378842
Discrete Surface Modeling Based on Google Earth: A Case Study
Mei, Gang; Tipper, John C.; Xu, Nengxiong
2012-01-01
Google Earth (GE) has become a powerful tool for geological, geophysical and geographical modeling; yet GE can be accepted to acquire elevation data of terrain. In this paper, we present a real study case of building the discrete surface model (DSM) at Haut-Barr Castle in France based on the elevation data of terrain points extracted from GE using the COM API. We first locate the position of Haut-Barr Castle and determine the region of the study area, then extract elevation data of terrain at...
Model-based robustness testing for avionics-embedded software
Yang Shunkun; Liu Bin; Wang Shihai; Lu Minyan
2013-01-01
Robustness testing for safety-critical embedded software is still a challenge in its nascent stages.In this paper,we propose a practical methodology and implement an environment by employing model-based robustness testing for embedded software systems.It is a system-level black-box testing approach in which the fault behaviors of embedded software is triggered with the aid of modelbased fault injection by the support of an executable model-driven hardware-in-loop (HIL) testing environment.The prototype implementation of the robustness testing environment based on the proposed approach is experimentally discussed and illustrated by industrial case studies based on several avionics-embedded software systems.The results show that our proposed and implemented robustness testing method and environment are effective to find more bugs,and reduce burdens of testing engineers to enhance efficiency of testing tasks,especially for testing complex embedded systems.
Model based methods and tools for process systems engineering
Gani, Rafiqul
Process systems engineering (PSE) provides means to solve a wide range of problems in a systematic and efficient manner. This presentation will give a perspective on model based methods and tools needed to solve a wide range of problems in product-process synthesis-design. These methods and tools...... need to be integrated with work-flows and data-flows for specific product-process synthesis-design problems within a computer-aided framework. The framework therefore should be able to manage knowledge-data, models and the associated methods and tools needed by specific synthesis-design work-flows and...... data-flows. In particular, the framework needs to manage models of different types, forms and complexity, together with their associated parameters. The application range of the framework depends very much on the application range of the associated models. Therefore, a modelling tool-box is also a part...
Multi-Task Collaboration CPS Modeling Based on Immune Feedback
Haiying Li
2013-09-01
Full Text Available In this paper, a dynamic multi-task collaboration CPS control model based on the self-adaptive immune feedback is proposed and implemented in the smart home environment. First, the internal relations between CPS and the biological immune system are explored via their basic theories. Second, CPS control mechanism is elaborated through the analysis of CPS control structure. Finally, a comprehensive strategy for support is introduced into multi-task collaboration to improve the dynamic cognitive ability. At the same time, the performance of parameters is correspondingly increased by the operator of the antibody concentration and the selective pressure. Furthermore, the model has been put into service in the smart home laboratory. The experimental results show that this model can integrate user’s needs into the environment for properly regulating the home environment.
Product Modeling Based on Knowledge Fusion in Virtual Environment
邹湘军; 孙健; 何汉武
2004-01-01
Following researches on the knowledge-based product design, product modeling based on knowledge fusion is studied in a virtual environment. Knowledge fusion is the energy sources of product innovation designs. Because a knowledge representation method is the main content of knowledge fusion, production rule way, semantic network, predicate, object-oriented and case-based representations are discussed. Using agents with object-oriented method, the knowledge can be represented as a set. The product knowledge set is divided into two subset: text knowledge and knowledge of engineering graphics that is a different form. Manipulation of the subset knowledge and fusion method is described. The paper also describes a six-tuple function in an agent data structure. A virtual environment computation model is proposed, and a practical example given.
Education Knowledge System Combination Model Based on the Components
CHEN Lei; LI Dehua; LI Xiaojian; WU Chunxiang
2007-01-01
Resources are the base and core of education information, but current web education resources have no structure and it is still difficult to reuse them and make them can be self assembled and developed continually. According to the knowledge structure of course and text, the relation among knowledge points, knowledge units from three levels of media material, we can build education resource components, and build TKCM (Teaching Knowledge Combination Model) based on resource components. Builders can build and assemble knowledge system structure and make knowledge units can be self assembled, thus we can develop and consummate them continually. Users can make knowledge units can be self assembled and renewed, and build education knowledge system to satisfy users' demand under the form of education knowledge system.
Model based IVHM system for the solid rocket booster
Luchinsky, D G; Smelyanskiy, V N; Timucin, D A; Uckun, S
2008-01-01
We report progress in the development of a model-based hybrid probabilistic approach to an on-board IVHM for solid rocket boosters (SRBs) that can accommodate the abrupt changes of the model parameters in various nonlinear dynamical off-nominal regimes. The work is related to the ORION mission program. Specifically, a case breach fault for SRBs is considered that takes into account burning a hole through the rocket case, as well as ablation of the nozzle throat under the action of hot gas flow. A high-fidelity model (HFM) of the fault is developed in FLUENT in cylindrical symmetry. The results of the FLUENT simulations are shown to be in good agreement with quasi-stationary approximation and analytical solution of a system of one-dimensional partial differential equations (PDEs) for the gas flow in the combustion chamber and in the hole through the rocket case.
Numeral eddy current sensor modelling based on genetic neural network
This paper presents a method used to the numeral eddy current sensor modelling based on the genetic neural network to settle its nonlinear problem. The principle and algorithms of genetic neural network are introduced. In this method, the nonlinear model parameters of the numeral eddy current sensor are optimized by genetic neural network (GNN) according to measurement data. So the method remains both the global searching ability of genetic algorithm and the good local searching ability of neural network. The nonlinear model has the advantages of strong robustness, on-line modelling and high precision. The maximum nonlinearity error can be reduced to 0.037% by using GNN. However, the maximum nonlinearity error is 0.075% using the least square method
An Emotional Agent Model Based on Granular Computing
Jun Hu
2012-01-01
Full Text Available Affective computing has a very important significance for fulfilling intelligent information processing and harmonious communication between human being and computers. A new model for emotional agent is proposed in this paper to make agent have the ability of handling emotions, based on the granular computing theory and the traditional BDI agent model. Firstly, a new emotion knowledge base based on granular computing for emotion expression is presented in the model. Secondly, a new emotional reasoning algorithm based on granular computing is proposed. Thirdly, a new emotional agent model based on granular computing is presented. Finally, based on the model, an emotional agent for patient assistant in hospital is realized, experiment results show that it is efficient to handle simple emotions.
Integrating Design Decision Management with Model-based Software Development
Könemann, Patrick
Design decisions are continuously made during the development of software systems and are important artifacts for design documentation. Dedicated decision management systems are often used to capture such design knowledge. Most such systems are, however, separated from the design artifacts of the...... system. In model-based software development, where design models are used to develop a software system, outcomes of many design decisions have big impact on design models. The realization of design decisions is often manual and tedious work on design models. Moreover, keeping design models consistent...... binding, or by ignoring the causes. This substitutes manual reviews to some extent. The concepts, implemented in a tool, have been validated with design patterns, refactorings, and domain level tests that comprise a replay of a real project. This proves the applicability of the solution to realistic...
Model-based condition monitoring for lithium-ion batteries
Kim, Taesic; Wang, Yebin; Fang, Huazhen; Sahinoglu, Zafer; Wada, Toshihiro; Hara, Satoshi; Qiao, Wei
2015-11-01
Condition monitoring for batteries involves tracking changes in physical parameters and operational states such as state of health (SOH) and state of charge (SOC), and is fundamentally important for building high-performance and safety-critical battery systems. A model-based condition monitoring strategy is developed in this paper for Lithium-ion batteries on the basis of an electrical circuit model incorporating hysteresis effect. It systematically integrates 1) a fast upper-triangular and diagonal recursive least squares algorithm for parameter identification of the battery model, 2) a smooth variable structure filter for the SOC estimation, and 3) a recursive total least squares algorithm for estimating the maximum capacity, which indicates the SOH. The proposed solution enjoys advantages including high accuracy, low computational cost, and simple implementation, and therefore is suitable for deployment and use in real-time embedded battery management systems (BMSs). Simulations and experiments validate effectiveness of the proposed strategy.
Optimal pricing decision model based on activity-based costing
王福胜; 常庆芳
2003-01-01
In order to find out the applicability of the optimal pricing decision model based on conventional costbehavior model after activity-based costing has given strong shock to the conventional cost behavior model andits assumptions, detailed analyses have been made using the activity-based cost behavior and cost-volume-profitanalysis model, and it is concluded from these analyses that the theory behind the construction of optimal pri-cing decision model is still tenable under activity-based costing, but the conventional optimal pricing decisionmodel must be modified as appropriate to the activity-based costing based cost behavior model and cost-volume-profit analysis model, and an optimal pricing decision model is really a product pricing decision model construc-ted by following the economic principle of maximizing profit.
CONCEPTUAL MODELING BASED ON LOGICAL EXPRESSION AND EVOLVEMENT
Yl Guodong; ZHANG Shuyou; TAN Jianrong; JI Yangjian
2007-01-01
Aiming at the problem of abstract and polytype information modeling in product conceptual design, a method of conceptual modeling based on logical expression and evolvement is presented. Based on the logic expressions of the product conceptual design information, a function/logic/structure mapping model is set up. First, the function semantics is transformed into logical expressions through function/logic mapping. Second, the methods of logical evolvement are utilized to describe the function analysis, function/structure mapping and structure combination. Last, the logical structure scheme is transformed into geometrical sketch through logic/structure mapping. The conceptual design information and modeling process are described uniformly with logical methods in the model, and an effective method for computer aided conceptual design based on the model is implemented.
Mechatronic Model Based Computed Torque Control of a Parallel Manipulator
Zhiyong Yang
2008-11-01
Full Text Available With high speed and accuracy the parallel manipulators have wide application in the industry, but there still exist many difficulties in the actual control process because of the time-varying and coupling. Unfortunately, the present-day commercial controlles cannot provide satisfying performance for its single axis linear control only. Therefore, aimed at a novel 2-DOF (Degree of Freedom parallel manipulator called Diamond 600, a motor-mechanism coupling dynamic model based control scheme employing the computed torque control algorithm are presented in this paper. First, the integrated dynamic coupling model is deduced, according to equivalent torques between the mechanical structure and the PM (Permanent Magnetism servomotor. Second, computed torque controller is described in detail for the above proposed model. At last, a series of numerical simulations and experiments are carried out to test the effectiveness of the system, and the results verify the favourable tracking ability and robustness.
Model based active power control of a wind turbine
Mirzaei, Mahmood; Soltani, Mohsen; Poulsen, Niels Kjølstad;
2014-01-01
In recent decades there has been increasing interest in green energies, of which wind energy is one of the most important. Wind turbines are the most common wind energy conversion systems and are hoped to be able to compete with traditional power plants in near future. This demands better...... technology to increase competitiveness of the wind power plants. One way to increase competitiveness of wind power plants is to offer grid services (also called ancillary services) that are normally offered by traditional power plants. One of the ancillary services is called reserve power. There are instants...... in the electricity market that selling the reserve power is more profitable than producing with the full capacity. Therefore wind turbines can be down-regulated and sell the differential capacity as the reserve power. In this paper we suggest a model based approach to control wind turbines for active...
Model-based reasoning and large-knowledge bases
In such engineering fields as nuclear power plant engineering, technical information expressed in the form of schematics is frequently used. A new paradigm for model-based reasoning (MBR) and an AI tool called PLEXSYS (plant expert system) using this paradigm has been developed. PLEXSYS and the underlying paradigm are specifically designed to handle schematic drawings, by expressing drawings as models and supporting various sophisticated searches on these models. Two application systems have been constructed with PLEXSYS: one generates PLEXSYS models from existing CAD data files, and the other provides functions for nuclear power plant design support. Since the models can be generated from existing data resources, the design support system automatically has full access to a large-scale model or knowledge base representing actual nuclear power plants. (author)
Cosmological Model Based on Gauge Theory of Gravity
WU Ning
2005-01-01
A cosmological model based on gauge theory of gravity is proposed in this paper. Combining cosmological principle and field equation of gravitational gauge field, dynamical equations of the scale factor R(t) of our universe can be obtained. This set of equations has three different solutions. A prediction of the present model is that, if the energy density of the universe is not zero and the universe is expanding, the universe must be space-flat, the total energy density must be the critical density ρc of the universe. For space-flat case, this model gives the same solution as that of the Friedmann model. In other words, though they have different dynamics of gravitational interactions, general relativity and gauge theory of gravity give the same cosmological model.
Automated Decomposition of Model-based Learning Problems
Williams, Brian C.; Millar, Bill
1996-01-01
A new generation of sensor rich, massively distributed autonomous systems is being developed that has the potential for unprecedented performance, such as smart buildings, reconfigurable factories, adaptive traffic systems and remote earth ecosystem monitoring. To achieve high performance these massive systems will need to accurately model themselves and their environment from sensor information. Accomplishing this on a grand scale requires automating the art of large-scale modeling. This paper presents a formalization of [\\em decompositional model-based learning (DML)], a method developed by observing a modeler's expertise at decomposing large scale model estimation tasks. The method exploits a striking analogy between learning and consistency-based diagnosis. Moriarty, an implementation of DML, has been applied to thermal modeling of a smart building, demonstrating a significant improvement in learning rate.
Yang–Baxter sigma models based on the CYBE
It is known that Yang–Baxter sigma models provide a systematic way to study integrable deformations of both principal chiral models and symmetric coset sigma models. In the original proposal and its subsequent development, the deformations have been characterized by classical r-matrices satisfying the modified classical Yang–Baxter equation (mCYBE). In this article, we propose the Yang–Baxter sigma models based on the classical Yang–Baxter equations (CYBE) rather than the mCYBE. This generalization enables us to utilize various kinds of solutions of the CYBE to classify integrable deformations. In particular, it is straightforward to realize partial deformations of the target space without loss of the integrability of the parent theory
Model-based fault diagnosis in PEM fuel cell systems
Escobet, T.; de Lira, S.; Puig, V.; Quevedo, J. [Automatic Control Department (ESAII), Universitat Politecnica de Catalunya (UPC), Rambla Sant Nebridi 10, 08222 Terrassa (Spain); Feroldi, D.; Riera, J.; Serra, M. [Institut de Robotica i Informatica Industrial (IRI), Consejo Superior de Investigaciones Cientificas (CSIC), Universitat Politecnica de Catalunya (UPC) Parc Tecnologic de Barcelona, Edifici U, Carrer Llorens i Artigas, 4-6, Planta 2, 08028 Barcelona (Spain)
2009-07-01
In this work, a model-based fault diagnosis methodology for PEM fuel cell systems is presented. The methodology is based on computing residuals, indicators that are obtained comparing measured inputs and outputs with analytical relationships, which are obtained by system modelling. The innovation of this methodology is based on the characterization of the relative residual fault sensitivity. To illustrate the results, a non-linear fuel cell simulator proposed in the literature is used, with modifications, to include a set of fault scenarios proposed in this work. Finally, it is presented the diagnosis results corresponding to these fault scenarios. It is remarkable that with this methodology it is possible to diagnose and isolate all the faults in the proposed set in contrast with other well known methodologies which use the binary signature matrix of analytical residuals and faults. (author)
A Multicore Load Balancing Model Based on Java NIO
Yang Wang
2012-10-01
Full Text Available First this paper points out two common problems of utilizing processors under multicore architecture, namely processors waiting for IO operation to finish and load balancing among cores. Then it makes an analysis of the reasons for them. In order to fully exploit multicore processors, this paper proposes a multicore load balancing model based on the Java NIO framework which offers a solution to above problems. This model mainly illustrates a task scheduling algorithm which uses a parallel computing framework, Java Fork/Join. At last, experiments and performance analysis prove the effectiveness of this model in utilizing the multicore processors. Although the model is constructed under the architecture of Java language, it can be extended to other languages without much being changed.
Constructive Alignment for Teaching Model-Based Design for Concurrency
Brabrand, Claus
2007-01-01
"How can we make sure our students learn what we want them to?" is the number one question in teaching. This paper is intended to provide the reader with: i) a general answer to this question based on the theory of constructive alignment by John Biggs; ii) relevant insights for bringing this answ...... from theory to practice; and iii) specific insights and experiences from using constructive alignment in teaching model-based design for concurrency (as a case study in implementing alignment)......."How can we make sure our students learn what we want them to?" is the number one question in teaching. This paper is intended to provide the reader with: i) a general answer to this question based on the theory of constructive alignment by John Biggs; ii) relevant insights for bringing this answer...
Embedded Control System Design A Model Based Approach
Forrai, Alexandru
2013-01-01
Control system design is a challenging task for practicing engineers. It requires knowledge of different engineering fields, a good understanding of technical specifications and good communication skills. The current book introduces the reader into practical control system design, bridging the gap between theory and practice. The control design techniques presented in the book are all model based., considering the needs and possibilities of practicing engineers. Classical control design techniques are reviewed and methods are presented how to verify the robustness of the design. It is how the designed control algorithm can be implemented in real-time and tested, fulfilling different safety requirements. Good design practices and the systematic software development process are emphasized in the book according to the generic standard IEC61508. The book is mainly addressed to practicing control and embedded software engineers - working in research and development – as well as graduate students who are face...
Yang–Baxter sigma models based on the CYBE
Matsumoto, Takuya, E-mail: takuya.matsumoto@math.nagoya-u.ac.jp [Institute for Advanced Research and Department of Mathematics, Nagoya University, Nagoya 464-8602 (Japan); Yoshida, Kentaroh, E-mail: kyoshida@gauge.scphys.kyoto-u.ac.jp [Department of Physics, Kyoto University, Kyoto 606-8502 (Japan)
2015-04-15
It is known that Yang–Baxter sigma models provide a systematic way to study integrable deformations of both principal chiral models and symmetric coset sigma models. In the original proposal and its subsequent development, the deformations have been characterized by classical r-matrices satisfying the modified classical Yang–Baxter equation (mCYBE). In this article, we propose the Yang–Baxter sigma models based on the classical Yang–Baxter equations (CYBE) rather than the mCYBE. This generalization enables us to utilize various kinds of solutions of the CYBE to classify integrable deformations. In particular, it is straightforward to realize partial deformations of the target space without loss of the integrability of the parent theory.
Intelligent Transportation and Evacuation Planning A Modeling-Based Approach
Naser, Arab
2012-01-01
Intelligent Transportation and Evacuation Planning: A Modeling-Based Approach provides a new paradigm for evacuation planning strategies and techniques. Recently, evacuation planning and modeling have increasingly attracted interest among researchers as well as government officials. This interest stems from the recent catastrophic hurricanes and weather-related events that occurred in the southeastern United States (Hurricane Katrina and Rita). The evacuation methods that were in place before and during the hurricanes did not work well and resulted in thousands of deaths. This book offers insights into the methods and techniques that allow for implementing mathematical-based, simulation-based, and integrated optimization and simulation-based engineering approaches for evacuation planning. This book also: Comprehensively discusses the application of mathematical models for evacuation and intelligent transportation modeling Covers advanced methodologies in evacuation modeling and planning Discusses principles a...
Numeral eddy current sensor modelling based on genetic neural network
Yu A-Long
2008-01-01
This paper presents a method used to the numeral eddy current sensor modelling based on the genetic neural network to settle its nonlinear problem. The principle and algorithms of genetic neural network are introduced. In this method, the nonlinear model parameters of the numeral eddy current sensor are optimized by genetic neural network (GNN) according to measurement data. So the method remains both the global searching ability of genetic algorithm and the good local searching ability of neural network. The nonlinear model has the advantages of strong robustness,on-line modelling and high precision.The maximum nonlinearity error can be reduced to 0.037% by using GNN.However, the maximum nonlinearity error is 0.075% using the least square method.
Spatio-temporal GIS Data Model Based on Event Semantics
XU Zhihong; BIAN Fuling
2003-01-01
There are mainly four kinds of models to record and deal with historical information. By taking them as reference, the spatio-temporal model based on event semantics is proposed. In this model, according to the way for describing an event, all the information are divided into five domains. This paper describes the model by using the land parcel change in the cadastral information system, and expounds the model by using five tables corresponding to the five domains.With the aid of this model, seven examples are given on historical query,trace back and recurrence. This model can be implemented either in the extended relational database or in the object-oriented database.
GENERALISED MODEL BASED CONFIDENCE INTERVALS IN TWO STAGE CLUSTER SAMPLING
Christopher Ouma Onyango
2010-09-01
Full Text Available Chambers and Dorfman (2002 constructed bootstrap confidence intervals in model based estimation for finite population totals assuming that auxiliary values are available throughout a target population and that the auxiliary values are independent. They also assumed that the cluster sizes are known throughout the target population. We now extend to two stage sampling in which the cluster sizes are known only for the sampled clusters, and we therefore predict the unobserved part of the population total. Jan and Elinor (2008 have done similar work, but unlike them, we use a general model, in which the auxiliary values are not necessarily independent. We demonstrate that the asymptotic properties of our proposed estimator and its coverage rates are better than those constructed under the model assisted local polynomial regression model.
Numerical Analysis of Modeling Based on Improved Elman Neural Network
Shao Jie
2014-01-01
Full Text Available A modeling based on the improved Elman neural network (IENN is proposed to analyze the nonlinear circuits with the memory effect. The hidden layer neurons are activated by a group of Chebyshev orthogonal basis functions instead of sigmoid functions in this model. The error curves of the sum of squared error (SSE varying with the number of hidden neurons and the iteration step are studied to determine the number of the hidden layer neurons. Simulation results of the half-bridge class-D power amplifier (CDPA with two-tone signal and broadband signals as input have shown that the proposed behavioral modeling can reconstruct the system of CDPAs accurately and depict the memory effect of CDPAs well. Compared with Volterra-Laguerre (VL model, Chebyshev neural network (CNN model, and basic Elman neural network (BENN model, the proposed model has better performance.
Numerical analysis of modeling based on improved Elman neural network.
Jie, Shao; Li, Wang; WeiSong, Zhao; YaQin, Zhong; Malekian, Reza
2014-01-01
A modeling based on the improved Elman neural network (IENN) is proposed to analyze the nonlinear circuits with the memory effect. The hidden layer neurons are activated by a group of Chebyshev orthogonal basis functions instead of sigmoid functions in this model. The error curves of the sum of squared error (SSE) varying with the number of hidden neurons and the iteration step are studied to determine the number of the hidden layer neurons. Simulation results of the half-bridge class-D power amplifier (CDPA) with two-tone signal and broadband signals as input have shown that the proposed behavioral modeling can reconstruct the system of CDPAs accurately and depict the memory effect of CDPAs well. Compared with Volterra-Laguerre (VL) model, Chebyshev neural network (CNN) model, and basic Elman neural network (BENN) model, the proposed model has better performance. PMID:25054172
Optimal Model-Based Control in HVAC Systems
Komareji, Mohammad; Stoustrup, Jakob; Rasmussen, Henrik; Bidstrup, Niels; Svendsen, Peter; Nielsen, Finn
developed. Then the optimal control structure is designed and implemented. The HVAC system is splitted into two subsystems. By selecting the right set-points and appropriate cost functions for each subsystem controller the optimal control strategy is respected to gaurantee the minimum thermal and electrical......This paper presents optimal model-based control of a heating, ventilating, and air-conditioning (HVAC) system. This HVAC system is made of two heat exchangers: an air-to-air heat exchanger (a rotary wheel heat recovery) and a water-to- air heat exchanger. First dynamic model of the HVAC system is...... energy consumption. Finally, the controller is applied to control the mentioned HVAC system and the results show that the expected goals are fulfilled....
A social discounting model based on Tsallis’ statistics
Takahashi, Taiki
2010-09-01
Social decision making (e.g. social discounting and social preferences) has been attracting attention in economics, econophysics, social physics, behavioral psychology, and neuroeconomics. This paper proposes a novel social discounting model based on the deformed algebra developed in the Tsallis’ non-extensive thermostatistics. Furthermore, it is suggested that this model can be utilized to quantify the degree of consistency in social discounting in humans and analyze the relationships between behavioral tendencies in social discounting and other-regarding economic decision making under game-theoretic conditions. Future directions in the application of the model to studies in econophysics, neuroeconomics, and social physics, as well as real-world problems such as the supply of live organ donations, are discussed.
A Model Based on Cocitation for Web Information Retrieval
Yue Xie
2014-01-01
Full Text Available According to the relationship between authority and cocitation in HITS, we propose a new hyperlink weighting scheme to describe the strength of the relevancy between any two webpages. Then we combine hyperlink weight normalization and random surfing schemes as used in PageRank to justify the new model. In the new model based on cocitation (MBCC, the pages with stronger relevancy are assigned higher values, not just depending on the outlinks. This model combines both features of HITS and PageRank. Finally, we present the results of some numerical experiments, showing that the MBCC ranking agrees with the HITS ranking, especially in top 10. Meanwhile, MBCC keeps the superiority of PageRank, that is, existence and uniqueness of ranking vectors.
Accurate Load Modeling Based on Analytic Hierarchy Process
Zhenshu Wang
2016-01-01
Full Text Available Establishing an accurate load model is a critical problem in power system modeling. That has significant meaning in power system digital simulation and dynamic security analysis. The synthesis load model (SLM considers the impact of power distribution network and compensation capacitor, while randomness of power load is more precisely described by traction power system load model (TPSLM. On the basis of these two load models, a load modeling method that combines synthesis load with traction power load is proposed in this paper. This method uses analytic hierarchy process (AHP to interact with two load models. Weight coefficients of two models can be calculated after formulating criteria and judgment matrixes and then establishing a synthesis model by weight coefficients. The effectiveness of the proposed method was examined through simulation. The results show that accurate load modeling based on AHP can effectively improve the accuracy of load model and prove the validity of this method.
Web Pre-fetching Model Based on Concept Association Network
XUHuanqing; WANGYongcheng
2004-01-01
With the enormous growth of information on the web, Internet has become one of the most important information sources. However, limited by the network bandwidth, users always suffer from long time waiting. Web pre-fetching is one of the most popular strategies,which are proposed for reducing the perceived access delay and improving the service quality of web server. This paper presents a pre-fetching model based on concept as sociation network, which mines concept association relationships that are implied in user access patterns and employs online learning and oitiine mining algorithm to construct the user-oriented concept association network. Using concept association network, pre-fetching model makes semantics-based pre-fetching decisions in the client side.This model implements the concept-based analysis on user access patterns and improves the prediction accuracy. Experimental results show that the proposed pre-fetching model has better general performance.
Model-based approach for elevator performance estimation
Esteban, E.; Salgado, O.; Iturrospe, A.; Isasa, I.
2016-02-01
In this paper, a dynamic model for an elevator installation is presented in the state space domain. The model comprises both the mechanical and the electrical subsystems, including the electrical machine and a closed-loop field oriented control. The proposed model is employed for monitoring the condition of the elevator installation. The adopted model-based approach for monitoring employs the Kalman filter as an observer. A Kalman observer estimates the elevator car acceleration, which determines the elevator ride quality, based solely on the machine control signature and the encoder signal. Finally, five elevator key performance indicators are calculated based on the estimated car acceleration. The proposed procedure is experimentally evaluated, by comparing the key performance indicators calculated based on the estimated car acceleration and the values obtained from actual acceleration measurements in a test bench. Finally, the proposed procedure is compared with the sliding mode observer.
THE HYPERMEDIA DATA MODEL BASED ON THE INFINITY IMAGE
无
2000-01-01
This paper presents the hypermedia data model based on the infinity RS image information system we have developed.The hypermedia data model consists of different semantic units called nodes,and the associations between nodes are called links.This paper proposes three kinds of nodes (interior node,physical node and complex node) and two kinds of links (plane network structure link,hyper-cube network structure links).The hypermedia information system,based on the model and the basic data layer (the infiniy RS image),represents a digital globe.An approach to the "Getting Lost in the Hyper-space" problem is presented.The approach using the hypermedia data model is an efficient way of handling a large number of RS images in various geographical information systems.
Model-Based Engineering and Manufacturing CAD/CAM Benchmark.
Domm, T.C.; Underwood, R.S.
1999-10-13
The Benchmark Project was created from a desire to identify best practices and improve the overall efficiency and performance of the Y-12 Plant's systems and personnel supporting the manufacturing mission. The mission of the benchmark team was to search out industry leaders in manufacturing and evaluate their engineering practices and processes to determine direction and focus for Y-12 modernization efforts. The companies visited included several large established companies and a new, small, high-tech machining firm. As a result of this effort, changes are recommended that will enable Y-12 to become a more modern, responsive, cost-effective manufacturing facility capable of supporting the needs of the Nuclear Weapons Complex (NWC) into the 21st century. The benchmark team identified key areas of interest, both focused and general. The focus areas included Human Resources, Information Management, Manufacturing Software Tools, and Standards/Policies and Practices. Areas of general interest included Infrastructure, Computer Platforms and Networking, and Organizational Structure. The results of this benchmark showed that all companies are moving in the direction of model-based engineering and manufacturing. There was evidence that many companies are trying to grasp how to manage current and legacy data. In terms of engineering design software tools, the companies contacted were somewhere between 3-D solid modeling and surfaced wire-frame models. The manufacturing computer tools were varied, with most companies using more than one software product to generate machining data and none currently performing model-based manufacturing (MBM) from a common model. The majority of companies were closer to identifying or using a single computer-aided design (CAD) system than a single computer-aided manufacturing (CAM) system. The Internet was a technology that all companies were looking to either transport information more easily throughout the corporation or as a conduit for
Object feature extraction and recognition model
The characteristics of objects, especially flying objects, are analyzed, which include characteristics of spectrum, image and motion. Feature extraction is also achieved. To improve the speed of object recognition, a feature database is used to simplify the data in the source database. The feature vs. object relationship maps are stored in the feature database. An object recognition model based on the feature database is presented, and the way to achieve object recognition is also explained
A Comparison of Filter-based Approaches for Model-based Prognostics
National Aeronautics and Space Administration — Model-based prognostics approaches use domain knowledge about a system and its failure modes through the use of physics-based models. Model-based prognosis is...
A model-based approach to human identification using ECG
Homer, Mark; Irvine, John M.; Wendelken, Suzanne
2009-05-01
Biometrics, such as fingerprint, iris scan, and face recognition, offer methods for identifying individuals based on a unique physiological measurement. Recent studies indicate that a person's electrocardiogram (ECG) may also provide a unique biometric signature. Current techniques for identification using ECG rely on empirical methods for extracting features from the ECG signal. This paper presents an alternative approach based on a time-domain model of the ECG trace. Because Auto-Regressive Integrated Moving Average (ARIMA) models form a rich class of descriptors for representing the structure of periodic time series data, they are well-suited to characterizing the ECG signal. We present a method for modeling the ECG, extracting features from the model representation, and identifying individuals using these features.
Discrete Surface Modeling Based on Google Earth: A Case Study
Mei, Gang; Xu, Nengxiong
2012-01-01
Google Earth (GE) has become a powerful tool for geological, geophysical and geographical modeling; yet GE can be accepted to acquire elevation data of terrain. In this paper, we present a real study case of building the discrete surface model (DSM) at Haut-Barr Castle in France based on the elevation data of terrain points extracted from GE using the COM API. We first locate the position of Haut-Barr Castle and determine the region of the study area, then extract elevation data of terrain at Haut-Barr, and thirdly create a planar triangular mesh that covers the study area and finally generate the desired DSM by calculating the elevation of vertices in the planar mesh via interpolating with Universal Kriging (UK) and Inverse Distance Weighting (IDW). The generated DSM can reflect the features of the ground surface at Haut-Barr well, and can be used for constructingthe Sealed Engineering Geological Model (SEGM) in further step.
Applications Of Algebraic Image Operators To Model-Based Vision
Lerner, Bao-Ting; Morelli, Michael V.; Thomas, Hans J.
1989-03-01
This paper extends our previous research on a highly structured and compact algebraic representation of grey-level images. Addition and multiplication are defined for the set of all grey-level images, which can then be described as polynomials of two variables. Utilizing this new algebraic structure, we have devised an innovative, efficient edge detection scheme.We have developed a robust method for linear feature extraction by combining the techniques of a Hough transform and a line follower with this new edge detection scheme. The major advantage of this feature extractor is its general, object-independent nature. Target attributes, such as line segment lengths, intersections, angles of intersection, and endpoints are derived by the feature extraction algorithm and employed during model matching. The feature extractor and model matcher are being incorporated into a distributed robot control system. Model matching is accomplished using both top-down and bottom-up processing: a priori sensor and world model information are used to constrain the search of the image space for features, while extracted image information is used to update the model.
Model-based reasoning and the control of process plants
In addition to feedback control, safe and economic operation of industrial process plants requires discrete-event type logic control like for example automatic control sequences, interlocks, etc. A lot of complex routine reasoning is involved in the design and verification and validation (VandV) of such automatics. Similar reasoning tasks are encountered during plant operation in action planning and fault diagnosis. The low-level part of the required problem solving is so straightforward that it could be accomplished by a computer if only there were plant models which allow versatile mechanised reasoning. Such plant models and corresponding inference algorithms are the main subject of this report. Deep knowledge and qualitative modelling play an essential role in this work. Deep knowledge refers to mechanised reasoning based on the first principles of the phenomena in the problem domain. Qualitative modelling refers to knowledge representation formalism and related reasoning methods which allow solving problems on an abstraction level higher than for example traditional simulation and optimisation. Prolog is a commonly used platform for artificial intelligence (Al) applications. Constraint logic languages like CLP(R) and Prolog-III extend the scope of logic programming to numeric problem solving. In addition they allow a programming style which often reduces the computational complexity significantly. An approach to model-based reasoning implemented in constraint logic programming language CLP(R) is presented. The approach is based on some of the principles of QSIM, an algorithm for qualitative simulation. It is discussed how model-based reasoning can be applied in the design and VandV of plant automatics and in action planning during plant operation. A prototype tool called ISIR is discussed and some initial results obtained during the development of the tool are presented. The results presented originate from preliminary test results of the prototype obtained
Model-based cartilage thickness measurement in the submillimeter range
Current methods of image-based thickness measurement in thin sheet structures utilize second derivative zero crossings to locate the layer boundaries. It is generally acknowledged that the nonzero width of the point spread function (PSF) limits the accuracy of this measurement procedure. We propose a model-based method that strongly reduces PSF-induced bias by incorporating the PSF into the thickness estimation method. We estimated the bias in thickness measurements in simulated thin sheet images as obtained from second derivative zero crossings. To gain insight into the range of sheet thickness where our method is expected to yield improved results, sheet thickness was varied between 0.15 and 1.2 mm with an assumed PSF as present in the high-resolution modes of current computed tomography (CT) scanners [full width at half maximum (FWHM) 0.5-0.8 mm]. Our model-based method was evaluated in practice by measuring layer thickness from CT images of a phantom mimicking two parallel cartilage layers in an arthrography procedure. CT arthrography images of cadaver wrists were also evaluated, and thickness estimates were compared to those obtained from high-resolution anatomical sections that served as a reference. The thickness estimates from the simulated images reveal that the method based on second derivative zero crossings shows considerable bias for layers in the submillimeter range. This bias is negligible for sheet thickness larger than 1 mm, where the size of the sheet is more than twice the FWHM of the PSF but can be as large as 0.2 mm for a 0.5 mm sheet. The results of the phantom experiments show that the bias is effectively reduced by our method. The deviations from the true thickness, due to random fluctuations induced by quantum noise in the CT images, are of the order of 3% for a standard wrist imaging protocol. In the wrist the submillimeter thickness estimates from the CT arthrography images correspond within 10% to those estimated from the anatomical
Biased Randomized Algorithm for Fast Model-Based Diagnosis
Williams, Colin; Vartan, Farrokh
2005-01-01
A biased randomized algorithm has been developed to enable the rapid computational solution of a propositional- satisfiability (SAT) problem equivalent to a diagnosis problem. The closest competing methods of automated diagnosis are described in the preceding article "Fast Algorithms for Model-Based Diagnosis" and "Two Methods of Efficient Solution of the Hitting-Set Problem" (NPO-30584), which appears elsewhere in this issue. It is necessary to recapitulate some of the information from the cited articles as a prerequisite to a description of the present method. As used here, "diagnosis" signifies, more precisely, a type of model-based diagnosis in which one explores any logical inconsistencies between the observed and expected behaviors of an engineering system. The function of each component and the interconnections among all the components of the engineering system are represented as a logical system. Hence, the expected behavior of the engineering system is represented as a set of logical consequences. Faulty components lead to inconsistency between the observed and expected behaviors of the system, represented by logical inconsistencies. Diagnosis - the task of finding the faulty components - reduces to finding the components, the abnormalities of which could explain all the logical inconsistencies. One seeks a minimal set of faulty components (denoted a minimal diagnosis), because the trivial solution, in which all components are deemed to be faulty, always explains all inconsistencies. In the methods of the cited articles, the minimal-diagnosis problem is treated as equivalent to a minimal-hitting-set problem, which is translated from a combinatorial to a computational problem by mapping it onto the Boolean-satisfiability and integer-programming problems. The integer-programming approach taken in one of the prior methods is complete (in the sense that it is guaranteed to find a solution if one exists) and slow and yields a lower bound on the size of the
杨永霞; 王琳琳; 郑凌云; 王淑美; 黄榕波; 张磊; 黄耀庭
2014-01-01
With the application of 1H nuclear magnetic resonance(1 H NMR) spectroscopy, we studied the effect of Huanglian Jiedu decoction( HJD) on the metabonomics of brown adipose tissue extracts in high fruc-tose-induced insulin resistance model. 32 Wistar rats were divided into four groups, i. e. , controls, model group, positive drug group and HJD treated group, 8 in each group. The last three groups were given 100 g/L fructose water for 28 d to establish insulin resistance model, normal control group was given the equal volume of pure water at the same time. After 28 d, four groups of rats were given 100 g/L fructose water continuously. Rats in positive drug group were administered orally atorvastain at a dose of 10 mg/( kg·d) , and rats in HJD treated group were given by gavage with HJD water. The control and model groups were given by gavage with a certain volume of saline solution, and the experiment lasted 56 d. Brown adipose tissues were obtained and 1 H NMR spectra of each sample was performed and analyzed by principal component analysis( PCA) method. Compared with the control group, lactate, alanine, choline, phosphocholine/glycerol phosphocholine ( PC/GPC) , creatine/creatinine, taurine and inosine increased in the model and lipid decreased. In comparison with model group, the myo-inositol was increased in HJD group, and HJD had reversed the metabolites in the model group. HJD can regulate the body’ s energy metabolism and reduce the damaged cell membrances and the injury of liver and kidney. Therefore, this study elucidates the metabolic mechanism of HJD on insulin re-sistance( IR) .%采用基于核磁共振氢谱(1 H NMR)的代谢组学方法,研究了黄连解毒汤( HJD)对高果糖诱导胰岛素抵抗大鼠模型棕色脂肪代谢组的影响.选取Wistar大鼠32只,适应7 d后随机分为正常对照组、模型组、阳性药物对照组和黄连解毒汤组,每组8只.正常对照组给予纯净水喂养,其它3组给予100 g/L的果糖水喂饲.28
杨永霞; 王琳琳; 郑凌云; 王淑美; 黄榕波; 张磊; 黄耀庭
2014-01-01
With the application of 1H nuclear magnetic resonance(1 H NMR) spectroscopy, we studied the effect of Huanglian Jiedu decoction( HJD) on the metabonomics of brown adipose tissue extracts in high fruc-tose-induced insulin resistance model. 32 Wistar rats were divided into four groups, i. e. , controls, model group, positive drug group and HJD treated group, 8 in each group. The last three groups were given 100 g/L fructose water for 28 d to establish insulin resistance model, normal control group was given the equal volume of pure water at the same time. After 28 d, four groups of rats were given 100 g/L fructose water continuously. Rats in positive drug group were administered orally atorvastain at a dose of 10 mg/( kg·d) , and rats in HJD treated group were given by gavage with HJD water. The control and model groups were given by gavage with a certain volume of saline solution, and the experiment lasted 56 d. Brown adipose tissues were obtained and 1 H NMR spectra of each sample was performed and analyzed by principal component analysis( PCA) method. Compared with the control group, lactate, alanine, choline, phosphocholine/glycerol phosphocholine ( PC/GPC) , creatine/creatinine, taurine and inosine increased in the model and lipid decreased. In comparison with model group, the myo-inositol was increased in HJD group, and HJD had reversed the metabolites in the model group. HJD can regulate the body’ s energy metabolism and reduce the damaged cell membrances and the injury of liver and kidney. Therefore, this study elucidates the metabolic mechanism of HJD on insulin re-sistance( IR) .%采用基于核磁共振氢谱(1 H NMR)的代谢组学方法,研究了黄连解毒汤( HJD)对高果糖诱导胰岛素抵抗大鼠模型棕色脂肪代谢组的影响.选取Wistar大鼠32只,适应7 d后随机分为正常对照组、模型组、阳性药物对照组和黄连解毒汤组,每组8只.正常对照组给予纯净水喂养,其它3组给予100 g/L的果糖水喂饲.28